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Author SHA1 Message Date
ethernet 4312a9cc4e test ci 2026-06-12 15:02:05 -04:00
4325 changed files with 89214 additions and 741444 deletions
+4 -5
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@@ -66,12 +66,8 @@ runtime/
# ---------- Not needed inside the Docker image ----------
# Desktop app source (Tauri/Electron); never installed in the container.
# apps/shared is the dashboard↔desktop websocket helper and is linked from
# web/package.json as a file: workspace dep — keep it in the build context.
# Desktop app source (Tauri/Electron); never installed in the container
apps/
!apps/shared/
!apps/shared/**
# Test suite — not shipped in production images
tests/
@@ -106,3 +102,6 @@ acp_registry/
.gitattributes
.hadolint.yaml
.mailmap
# Top-level LICENSE (not matched by *.md); not needed inside the container
LICENSE
-24
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@@ -1,13 +1,6 @@
# Hermes Agent Environment Configuration
# Copy this file to .env and fill in your API keys
# =============================================================================
# LLM PROVIDER (Fireworks AI)
# =============================================================================
# Get your key at: https://app.fireworks.ai/settings/users/api-keys
# Address models directly by catalog ID, e.g.
# accounts/fireworks/models/kimi-k2p6, accounts/fireworks/models/glm-5p2
# FIREWORKS_API_KEY=
# =============================================================================
# LLM PROVIDER (OpenRouter)
# =============================================================================
@@ -112,13 +105,8 @@
# Get your token at: https://huggingface.co/settings/tokens
# Required permission: "Make calls to Inference Providers"
# HF_TOKEN=
# HF_BASE_URL=https://router.huggingface.co/v1 # Override default base URL
# OPENCODE_GO_BASE_URL=https://opencode.ai/zen/go/v1 # Override default base URL
# DeepInfra — 100+ top open models, pay-per-use.
# Get your key at: https://deepinfra.com/dash/api_keys
# DEEPINFRA_API_KEY=
# =============================================================================
# LLM PROVIDER (Qwen OAuth)
# =============================================================================
@@ -136,15 +124,6 @@
# Optional base URL override:
# XIAOMI_BASE_URL=https://api.xiaomimimo.com/v1
# =============================================================================
# LLM PROVIDER (Upstage Solar)
# =============================================================================
# Upstage provides access to Upstage Solar models.
# Get your key at: https://console.upstage.ai/api-keys
# UPSTAGE_API_KEY=your_key_here
# Optional base URL override:
# UPSTAGE_BASE_URL=https://api.upstage.ai/v1
# =============================================================================
# TOOL API KEYS
# =============================================================================
@@ -432,9 +411,6 @@ IMAGE_TOOLS_DEBUG=false
# Groq API key (free tier — used for Whisper STT in voice mode)
# GROQ_API_KEY=
# ElevenLabs API key (cloud STT/TTS — Scribe transcription)
# ELEVENLABS_API_KEY=
# =============================================================================
# STT PROVIDER SELECTION
# =============================================================================
+2 -2
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@@ -1,5 +1,5 @@
watch_file pyproject.toml uv.lock hermes
watch_file pyproject.toml uv.lock
watch_file package-lock.json package.json web/package.json ui-tui/package.json website/package.json apps/shared/package.json apps/desktop/package.json ui-tui/packages/hermes-ink/package.json
watch_file flake.nix flake.lock nix/devShell.nix nix/tui.nix nix/package.nix nix/python.nix nix/hermes-agent.nix nix/desktop.nix
watch_file flake.nix flake.lock nix/devShell.nix nix/tui.nix nix/package.nix nix/python.nix
use flake
-102
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@@ -1,102 +0,0 @@
name: Detect affected areas
description: >-
Classify a PR's changed files into CI work lanes (python, frontend, site,
scan, deps, mcp_catalog) so the orchestrator can conditionally call only
the sub-workflows a PR can affect. Outputs are always "true" on push/dispatch
events and fail open (everything "true") when the diff cannot be computed.
inputs:
github-token:
description: Token for the GitHub API (gh CLI). Pass steps.app-token.outputs.token from the calling workflow.
required: false
default: ${{ github.token }}
outputs:
python:
description: Run Python tests / ruff / ty / windows-footguns.
value: ${{ steps.classify.outputs.python }}
frontend:
description: Run the TypeScript testing matrix + desktop build.
value: ${{ steps.classify.outputs.frontend }}
docker_meta:
description: Docker setup and meta files have changed.
value: ${{ steps.classify.outputs.docker_meta }}
site:
description: Build the Docusaurus docs site.
value: ${{ steps.classify.outputs.site }}
scan:
description: Run the supply-chain critical-pattern scanner.
value: ${{ steps.classify.outputs.scan }}
deps:
description: Check pyproject.toml dependency upper bounds.
value: ${{ steps.classify.outputs.deps }}
npm_lock:
description: Post/update the semantic package-lock.json diff PR comment.
value: ${{ steps.classify.outputs.npm_lock }}
mcp_catalog:
description: Require MCP catalog security review label.
value: ${{ steps.classify.outputs.mcp_catalog }}
ci_review:
description: Require CI-sensitive file review label.
value: ${{ steps.classify.outputs.ci_review }}
runs:
using: composite
steps:
- name: Classify changed files
id: classify
shell: bash
env:
# Fall back to the built-in read-only token when the caller passes an
# empty value. Fork PRs get no repo secrets, so AUTOFIX_BOT_PAT is ""
# there, and an input `default:` only applies when the input is omitted,
# not when it's passed empty. Without this fallback the compare API
# fails on forks and the classifier fails open (every lane forced on).
GH_TOKEN: ${{ inputs.github-token || github.token }}
REPO: ${{ github.repository }}
EVENT_NAME: ${{ github.event_name }}
BASE_SHA: ${{ github.event.pull_request.base.sha }}
HEAD_SHA: ${{ github.event.pull_request.head.sha }}
run: |
set -euo pipefail
# Only pull_request events are gated. Other events (push, release,
# dispatch) leave CHANGED empty, so the classifier fails open and every
# lane runs. Post-merge / on-demand validation is never weakened.
if [ "$EVENT_NAME" = "pull_request" ]; then
# Use the compare endpoint with the pinned base/head SHAs from the
# event payload instead of the "current PR files" endpoint. The SHAs
# are frozen at trigger time, so the file list is deterministic even
# if the PR receives a new push between trigger and detect.
#
# Retried: a rate-limit blip or eventual-consistency 404 on a
# freshly-pushed HEAD would otherwise silently fall open (all lanes
# run — safe, but wasteful and it masks the API failure).
#
# `.files[]?` (null-safe): with --paginate, a PR more than 100
# commits ahead of its merge-base paginates the compare, and pages
# after the first carry `files: null` — bare `.files[]` makes jq
# die with "cannot iterate over: null", which fails every retry
# and forces the fail-open path (seen on stacked PRs). The full
# file list (up to the API's 300-file cap) is on page one.
CHANGED=""
for i in 1 2 3; do
if CHANGED="$(gh api \
--paginate \
"repos/${REPO}/compare/${BASE_SHA}...${HEAD_SHA}" \
--jq '.files[]?.filename')"; then
break
fi
if [ "$i" = 3 ]; then
echo "::warning::compare API failed after 3 attempts — failing open (all lanes run)"
CHANGED=""
break
fi
echo "::warning::compare API failed (attempt $i); retrying in 10s"
sleep 10
done
fi
echo "Changed files:"
printf '%s\n' "${CHANGED:-(none)}"
printf '%s\n' "${CHANGED:-}" | python3 scripts/ci/classify_changes.py
-59
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@@ -1,59 +0,0 @@
name: Get GitHub App Token
description: >-
Mint a short-lived (1-hour) installation access token from the repo's
GitHub App, replacing the long-lived AUTOFIX_BOT_PAT. App tokens get
5,000 req/hr per installation (vs 1,000 for the default GITHUB_TOKEN)
and are scoped to the App's installation permissions, not a user account.
Falls back to the built-in GITHUB_TOKEN when APP_CLIENT_ID is not set —
this happens on fork PRs where repo secrets are unavailable. The fallback
ensures classification, timings, and review comments still work on
forks (with the lower GITHUB_TOKEN rate limit).
Composite actions cannot access the secrets context directly, so the
calling workflow must pass secrets.APP_CLIENT_ID and secrets.APP_PRIVATE_KEY
as inputs. When both are empty (fork PRs), the fallback fires.
inputs:
client-id:
description: GitHub App Client ID. Pass secrets.APP_CLIENT_ID from the calling workflow.
required: false
default: ''
private-key:
description: GitHub App private key PEM. Pass secrets.APP_PRIVATE_KEY from the calling workflow.
required: false
default: ''
outputs:
token:
description: A GitHub App installation access token (1-hour TTL), or GITHUB_TOKEN on forks.
value: ${{ steps.app-token.outputs.token || steps.fallback.outputs.token }}
runs:
using: composite
steps:
- name: Check if App credentials exist
id: check
shell: bash
env:
CLIENT_ID: ${{ inputs.client-id }}
run: |
if [ -n "$CLIENT_ID" ]; then
echo "has_app=true" >> "$GITHUB_OUTPUT"
else
echo "has_app=false" >> "$GITHUB_OUTPUT"
fi
- name: Create GitHub App token
id: app-token
if: steps.check.outputs.has_app == 'true'
uses: actions/create-github-app-token@bcd2ba49218906704ab6c1aa796996da409d3eb1 # v3.2.0
with:
client-id: ${{ inputs.client-id }}
private-key: ${{ inputs.private-key }}
- name: Fall back to GITHUB_TOKEN
id: fallback
if: steps.check.outputs.has_app != 'true'
shell: bash
run: echo "token=${{ github.token }}" >> "$GITHUB_OUTPUT"
@@ -0,0 +1,50 @@
name: Hermes smoke test
description: >
Run the image's built-in entrypoint against `--help` and `dashboard --help`
to catch basic runtime regressions before publishing. Requires the image
to already be loaded into the local Docker daemon under `image`.
Works identically on amd64 and arm64 runners.
inputs:
image:
description: Fully-qualified image tag (e.g. nousresearch/hermes-agent:test)
required: true
runs:
using: composite
steps:
- name: Ensure /tmp/hermes-test is hermes-writable
shell: bash
run: |
# The image runs as the hermes user (UID 10000). GitHub Actions
# creates /tmp/hermes-test root-owned by default, which hermes
# can't write to — chown it to match the in-container UID before
# bind-mounting. Real users doing `docker run -v ~/.hermes:...`
# with their own UID hit the same issue and have their own
# remediations (HERMES_UID env var, or chown locally).
mkdir -p /tmp/hermes-test
sudo chown -R 10000:10000 /tmp/hermes-test
- name: hermes --help
shell: bash
run: |
# Use the image's real ENTRYPOINT (/init + main-wrapper.sh) so
# this exercises the actual production startup path. PR #30136
# review caught that an --entrypoint override here had been
# silently neutered by the s6-overlay migration — stage2-hook
# ignores its CMD args, so the smoke test was a no-op.
docker run --rm \
-v /tmp/hermes-test:/opt/data \
"${{ inputs.image }}" --help
- name: hermes dashboard --help
shell: bash
run: |
# Regression guard for #9153: dashboard was present in source but
# missing from the published image. If this fails, something in
# the Dockerfile is excluding the dashboard subcommand from the
# installed package.
docker run --rm \
-v /tmp/hermes-test:/opt/data \
"${{ inputs.image }}" dashboard --help
-70
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@@ -1,70 +0,0 @@
name: Retry a flaky command
description: >-
Run a shell command, retrying on non-zero exit. For dependency installs
(npm ci, uv sync) whose only failures are transient network/toolchain
flakes — a node-gyp header fetch, a registry blip — so CI self-heals
instead of needing a manual re-run. Can also capture stdout as a step
output for commands whose result must be consumed by later steps.
inputs:
command:
description: Shell command to run (and retry).
required: true
attempts:
description: Max attempts before giving up.
default: "3"
delay:
description: Seconds to wait between attempts.
default: "10"
working-directory:
description: Directory to run in.
default: "."
outputs:
stdout:
description: Captured stdout from the successful attempt (empty if not needed).
value: ${{ steps.retry.outputs.stdout }}
runs:
using: composite
steps:
- id: retry
shell: bash
working-directory: ${{ inputs.working-directory }}
# command goes through env, never interpolated into the script body, so
# a command with quotes/specials can't break or inject into the runner.
env:
_CMD: ${{ inputs.command }}
_ATTEMPTS: ${{ inputs.attempts }}
_DELAY: ${{ inputs.delay }}
run: |
set -uo pipefail
_OUTFILE="$(mktemp)"
trap 'rm -f "$_OUTFILE"' EXIT
n=0
while :; do
n=$((n + 1))
echo "::group::attempt $n/$_ATTEMPTS: $_CMD"
# Run the command, capturing stdout to a temp file while still
# streaming to the log. We redirect first, then tee the file to
# stdout — this avoids pipefail + tee exit-code interactions that
# can cause the if-branch to be skipped under set -e.
if bash -c "$_CMD" > "$_OUTFILE"; then
cat "$_OUTFILE"
echo "::endgroup::"
# Preserve newlines in the output via heredoc delimiter.
{
echo 'stdout<<__RETRY_STDOUT_EOF__'
cat "$_OUTFILE"
echo '__RETRY_STDOUT_EOF__'
} >> "$GITHUB_OUTPUT"
exit 0
fi
echo "::endgroup::"
if [ "$n" -ge "$_ATTEMPTS" ]; then
echo "::error::failed after $n attempts: $_CMD"
exit 1
fi
echo "::warning::attempt $n failed; retrying in ${_DELAY}s: $_CMD"
sleep "$_DELAY"
done
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@@ -0,0 +1,100 @@
name: Build Windows Installer
on:
workflow_dispatch:
permissions:
contents: read
jobs:
# Gate: workflow_dispatch is already restricted to users with write access,
# but we want ADMIN-only. Explicitly check the triggering actor's repo
# permission via the API and fail fast for anyone below admin.
authorize:
name: Authorize (admins only)
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- name: Check actor is a repo admin
env:
GH_TOKEN: ${{ github.token }}
ACTOR: ${{ github.actor }}
run: |
set -euo pipefail
perm=$(gh api \
"repos/${{ github.repository }}/collaborators/${ACTOR}/permission" \
--jq '.permission')
echo "Actor '${ACTOR}' has permission: ${perm}"
if [ "${perm}" != "admin" ]; then
echo "::error::'${ACTOR}' is not a repo admin (permission=${perm}). Refusing to build/sign."
exit 1
fi
echo "Authorized: '${ACTOR}' is an admin."
build:
name: Hermes-Setup.exe
needs: authorize
runs-on: windows-latest
timeout-minutes: 30
permissions:
contents: read
# Required for OIDC auth to Azure (azure/login federated credentials).
id-token: write
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Setup Node.js
uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
- name: Install npm dependencies
run: npm ci
- name: Setup Rust
uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable
- name: Cache Rust targets
uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
with:
workspaces: apps/bootstrap-installer/src-tauri
- name: Build installer
run: npm run tauri:build
working-directory: apps/bootstrap-installer
- name: Azure login (OIDC)
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Sign Hermes-Setup.exe with Azure Artifact Signing
uses: azure/artifact-signing-action@c7ab2a863ab5f9a846ddb8265964877ef296ee82 # v2
with:
endpoint: ${{ vars.AZURE_SIGNING_ENDPOINT }}
signing-account-name: ${{ vars.AZURE_SIGNING_ACCOUNT_NAME }}
certificate-profile-name: ${{ vars.AZURE_SIGNING_CERTIFICATE_PROFILE }}
# Sign both the raw exe and the bundled NSIS installer.
files-folder: ${{ github.workspace }}\apps\bootstrap-installer\src-tauri\target\release
files-folder-filter: exe
files-folder-recurse: true
file-digest: SHA256
timestamp-rfc3161: http://timestamp.acs.microsoft.com
timestamp-digest: SHA256
- name: Upload NSIS installer
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: Hermes-Setup-installer
path: apps/bootstrap-installer/src-tauri/target/release/bundle/nsis/*.exe
- name: Upload raw exe
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: Hermes-Setup-exe
path: apps/bootstrap-installer/src-tauri/target/release/Hermes-Setup.exe
-399
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@@ -1,399 +0,0 @@
name: CI
# Orchestrator workflow. Runs ``detect-changes`` once, then conditionally
# calls the sub-workflows that a PR can actually affect. A final
# ``all-checks-pass`` gate job aggregates results so branch protection only
# needs to require a single check.
#
# Sub-workflows are triggered via ``workflow_call`` and keep their own job
# definitions, matrices, and concurrency settings. They no longer have
# ``push:`` / ``pull_request:`` triggers of their own — everything flows
# through this file.
on:
pull_request:
push:
branches: [main]
permissions:
contents: read
pull-requests: write # needed by lint (PR comment) + supply-chain review_status
actions: read # needed by osv-scanner (SARIF upload)
security-events: write # needed by osv-scanner (SARIF upload)
packages: write # needed by docker build
concurrency:
group: ci-${{ github.ref }}
cancel-in-progress: ${{ github.event_name == 'pull_request' }}
jobs:
# ─────────────────────────────────────────────────────────────────────
# detect: run the classifier once. Every downstream job reads its outputs
# to decide whether to run. On push/dispatch the classifier fails open
# (all lanes true) so post-merge validation is never weakened.
# ─────────────────────────────────────────────────────────────────────
detect:
name: Detect affected areas
runs-on: ubuntu-latest
timeout-minutes: 10
outputs:
python: ${{ steps.classify.outputs.python }}
frontend: ${{ steps.classify.outputs.frontend }}
site: ${{ steps.classify.outputs.site }}
scan: ${{ steps.classify.outputs.scan }}
deps: ${{ steps.classify.outputs.deps }}
npm_lock: ${{ steps.classify.outputs.npm_lock }}
docker_meta: ${{ steps.classify.outputs.docker_meta }}
mcp_catalog: ${{ steps.classify.outputs.mcp_catalog }}
ci_review: ${{ steps.classify.outputs.ci_review }}
event_name: ${{ github.event_name }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- name: Detect affected areas
id: classify
uses: ./.github/actions/detect-changes
with:
# The get-app-token composite action falls back to GITHUB_TOKEN
# on fork PRs where APP_ID is unavailable.
github-token: ${{ steps.app-token.outputs.token }}
# ─────────────────────────────────────────────────────────────────────
# Lane-gated sub-workflows. Each runs in parallel after detect finishes.
# Skipped workflows (if condition is false) don't spin up runners.
# ─────────────────────────────────────────────────────────────────────
tests:
name: Python tests
needs: detect
if: needs.detect.outputs.python == 'true'
uses: ./.github/workflows/tests.yml
with:
slice_count: 8
secrets: inherit
lint:
name: Python lints
needs: detect
if: needs.detect.outputs.python == 'true'
uses: ./.github/workflows/lint.yml
with:
event_name: ${{ needs.detect.outputs.event_name }}
secrets: inherit
js-tests:
name: JS & TS checks
needs: detect
if: needs.detect.outputs.frontend == 'true'
uses: ./.github/workflows/js-tests.yml
secrets: inherit
e2e-desktop:
name: Desktop E2E
needs: detect
if: needs.detect.outputs.python == 'true' || needs.detect.outputs.frontend == 'true'
uses: ./.github/workflows/e2e-desktop.yml
docs-site:
name: Docs Site
needs: detect
if: needs.detect.outputs.site == 'true'
uses: ./.github/workflows/docs-site-checks.yml
secrets: inherit
history-check:
name: Deny unrelated histories
needs: detect
if: needs.detect.outputs.event_name == 'pull_request'
uses: ./.github/workflows/history-check.yml
secrets: inherit
contributor-check:
name: Check contributors
needs: detect
if: needs.detect.outputs.python == 'true'
uses: ./.github/workflows/contributor-check.yml
secrets: inherit
uv-lockfile:
name: Check uv.lock
needs: detect
uses: ./.github/workflows/uv-lockfile-check.yml
secrets: inherit
lockfile-diff:
name: package-lock.json diff
needs: detect
if: needs.detect.outputs.event_name == 'pull_request' && needs.detect.outputs.npm_lock == 'true'
uses: ./.github/workflows/lockfile-diff.yml
secrets: inherit
docker-lint:
name: Lint Docker scripts
needs: detect
if: needs.detect.outputs.docker_meta == 'true'
uses: ./.github/workflows/docker-lint.yml
secrets: inherit
docker:
name: Build&Test Docker image
needs: detect
if: needs.detect.outputs.python == 'true' || needs.detect.outputs.frontend == 'true' || needs.detect.outputs.docker_meta == 'true'
uses: ./.github/workflows/docker.yml
secrets: inherit
supply-chain:
name: Supply-chain scan
needs: detect
if: needs.detect.outputs.event_name == 'pull_request' && (needs.detect.outputs.scan == 'true' || needs.detect.outputs.deps == 'true')
uses: ./.github/workflows/supply-chain-audit.yml
with:
event_name: ${{ needs.detect.outputs.event_name }}
scan: ${{ needs.detect.outputs.scan == 'true' }}
deps: ${{ needs.detect.outputs.deps == 'true' }}
review-labels:
name: Review label gate
needs: [detect, supply-chain]
if: always() && needs.detect.outputs.event_name == 'pull_request' && (needs.detect.outputs.ci_review == 'true' || needs.detect.outputs.mcp_catalog == 'true' || needs.supply-chain.outputs.critical_findings == 'true')
uses: ./.github/workflows/review-labels.yml
with:
ci_review: ${{ needs.detect.outputs.ci_review == 'true' }}
mcp_catalog: ${{ needs.detect.outputs.mcp_catalog == 'true' }}
supply_chain: ${{ needs.supply-chain.outputs.critical_findings == 'true' }}
secrets: inherit
osv-scanner:
name: OSV scan
uses: ./.github/workflows/osv-scanner.yml
secrets: inherit
# ─────────────────────────────────────────────────────────────────────
# Live-updating PR review comment.
#
# A single ``comment-live`` job polls the GitHub Actions API every 15s
# for job statuses in this run, re-assembles the review comment from
# whatever results are available, and upserts it via the
# ``<!-- hermes-ci-review-bot -->`` marker.
#
# The poller exits when all non-infra jobs are completed (or on
# timeout). ci-timings' review_status is picked up automatically when
# its artifact becomes available — the poller downloads and merges it.
# ─────────────────────────────────────────────────────────────────────
comment-live:
name: CI review comment (live)
needs: [detect, review-labels, lockfile-diff, supply-chain, osv-scanner, uv-lockfile, history-check, contributor-check]
if: always() && github.event_name == 'pull_request' && github.event.pull_request.head.repo.fork != true
runs-on: ubuntu-latest
timeout-minutes: 40
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Run live comment poller
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITHUB_REPOSITORY: ${{ github.repository }}
GITHUB_RUN_ID: ${{ github.run_id }}
PR_NUMBER: ${{ github.event.pull_request.number }}
RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
# Commit info for the review comment header.
COMMIT_SHA: ${{ github.event.pull_request.head.sha }}
COMMIT_MESSAGE: ${{ github.event.pull_request.head.commit.message }}
COMMIT_URL: ${{ github.server_url }}/${{ github.repository }}/pull/${{ github.event.pull_request.number }}/commits/${{ github.event.pull_request.head.sha }}
# Structured review statuses from workflow_call jobs.
# Each job outputs a JSON array of {source, results: [...]} objects
# that the assembler renders directly — no hardcoded job-name
# matching. We merge all available outputs into one array.
REVIEW_STATUSES: ${{ toJSON(needs.*.outputs.review_status) }}
run: |
set -uo pipefail
# REVIEW_STATUSES is a JSON array of strings (some may be empty
# when a job was skipped). Parse each string and merge into one
# flat array for the assembler.
python3 - <<'PYEOF'
import json, os, sys
raw = os.environ.get("REVIEW_STATUSES", "")
merged = []
if raw:
try:
arr = json.loads(raw)
except (json.JSONDecodeError, TypeError):
arr = []
for item in arr:
if not item:
continue
try:
statuses = json.loads(item)
except (json.JSONDecodeError, TypeError):
continue
if isinstance(statuses, list):
merged.extend(statuses)
# Write merged array to a temp file the poller reads.
with open("/tmp/review_statuses.json", "w") as f:
json.dump(merged, f)
print(f"Merged {len(merged)} review status entries")
PYEOF
python3 scripts/ci/live_comment.py \
--interval 15 \
--timeout 2100 \
--review-statuses-file /tmp/review_statuses.json
# ─────────────────────────────────────────────────────────────────────
# Gate: runs after everything. ``if: always()`` ensures it reports a
# status even when some deps were skipped. Only actual ``failure``
# results cause it to fail; ``skipped`` is treated as success.
#
# Branch protection should require ONLY this check.
#
# Outputs ``needs-json`` — a compact ``{job_name: result}`` dict — so
# the live comment poller can list failed jobs in the PR comment.
# ─────────────────────────────────────────────────────────────────────
all-checks-pass:
name: All required checks pass
needs:
- detect
- tests
- lint
- js-tests
- e2e-desktop
- docs-site
- history-check
- contributor-check
- uv-lockfile
- lockfile-diff
- docker-lint
- supply-chain
- review-labels
- osv-scanner
# comment-live is a polling job — it doesn't block the gate.
# we don't require docker to pass rn because it's so slow lol
# - docker
if: always()
runs-on: ubuntu-latest
timeout-minutes: 10
outputs:
needs-json: ${{ steps.evaluate.outputs.needs-json }}
steps:
- name: Evaluate job results
id: evaluate
env:
NEEDS: ${{ toJSON(needs) }}
run: |
echo "$NEEDS" | python3 -c "
import json, sys
needs = json.load(sys.stdin)
# Emit compact {job_name: result} for the comment assembler.
compact = {name: info['result'] for name, info in needs.items()}
print(f'needs-json={json.dumps(compact)}')
with open('$GITHUB_OUTPUT', 'a') as f:
f.write(f'needs-json={json.dumps(compact)}\n')
failed = [name for name, info in needs.items() if info['result'] == 'failure']
for name, info in sorted(needs.items()):
result = info['result']
icon = '✅' if result in ('success', 'skipped') else '❌'
print(f'{icon} {name}: {result}')
if failed:
print(f'::error::{len(failed)} job(s) failed: {\", \".join(failed)}')
sys.exit(1)
print('All checks passed (or were skipped)')
"
# ─────────────────────────────────────────────────────────────────────
# CI timing report: collect per-job/step durations from the GitHub API,
# cache them on main (as a baseline), and on PRs generate an HTML diff
# report with a gantt chart + per-step breakdown. The report is uploaded
# as an artifact and a markdown summary is written to $GITHUB_STEP_SUMMARY.
#
# The live comment poller picks up ci-timings' completion automatically —
# it reads review-status.json from the artifact when the job finishes.
# ─────────────────────────────────────────────────────────────────────
ci-timings:
name: CI timing report
needs: [all-checks-pass, docker]
if: always()
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- name: Restore baseline cache (PR only)
if: github.event_name == 'pull_request'
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: ci-timings-baseline.json
# Prefix-match: exact key will never hit (run_id differs), so
# restore-keys finds the most recent baseline from main.
key: ci-timings-baseline-never-exact
restore-keys: |
ci-timings-baseline-
- name: Collect timings and generate report
env:
# Forks get no repo secrets (AUTOFIX_BOT_PAT is empty); fall back to
# the built-in read-only token so the timings API read still works
# there instead of hard-failing this advisory job on every fork PR.
# The get-app-token composite action falls back to GITHUB_TOKEN
# on fork PRs where APP_ID is unavailable.
GITHUB_TOKEN: ${{ steps.app-token.outputs.token }}
run: |
python3 scripts/ci/timings_report.py \
--baseline ci-timings-baseline.json \
--output ci-timings-report.html \
--json-out ci-timings.json \
--summary-out ci-timings-summary.md \
--review-status-out review-status.json
- name: Upload HTML report + review status
# Advisory report — artifact-service blips must not fail the job.
continue-on-error: true
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
id: ci-timings-artifact
with:
name: ci-timings-report
path: |
ci-timings-report.html
review-status.json
retention-days: 14
- name: Output summary
env:
REPORT_URL: ${{ steps.ci-timings-artifact.outputs.artifact-url}}
run: |
echo "# CI Timing report" >> "$GITHUB_STEP_SUMMARY"
echo "[View the full interactive report]($REPORT_URL)" >> "$GITHUB_STEP_SUMMARY"
cat ci-timings-summary.md >> "$GITHUB_STEP_SUMMARY"
- name: Save baseline cache (main only)
if: github.event_name == 'push' && github.ref == 'refs/heads/main'
run: |
# Degraded runs (API rate-limited) produce no ci-timings.json —
# skip rather than fail, and never cache an empty baseline.
if [ -f ci-timings.json ]; then
cp ci-timings.json ci-timings-baseline.json
else
echo "No timings JSON this run — skipping baseline update"
fi
- name: Upload baseline to cache (main only)
if: github.event_name == 'push' && github.ref == 'refs/heads/main' && hashFiles('ci-timings-baseline.json') != ''
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: ci-timings-baseline.json
key: ci-timings-baseline-${{ github.run_id }}
+26 -32
View File
@@ -1,11 +1,11 @@
name: Contributor Attribution Check
on:
workflow_call:
outputs:
review_status:
description: "JSON array of review status objects"
value: ${{ jobs.check-attribution.outputs.review_status }}
pull_request:
branches: [main]
# No paths filter — the job must always run so the required check
# reports a status (path-gated workflows leave checks "pending" forever
# when no matching files change, which blocks merge).
permissions:
contents: read
@@ -13,16 +13,26 @@ permissions:
jobs:
check-attribution:
runs-on: ubuntu-latest
timeout-minutes: 10
outputs:
review_status: ${{ steps.check-emails.outputs.review_status }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
fetch-depth: 0 # Full history needed for git log
- name: Check if relevant files changed
id: filter
run: |
BASE="${{ github.event.pull_request.base.sha }}"
HEAD="${{ github.event.pull_request.head.sha }}"
CHANGED=$(git diff --name-only "$BASE"..."$HEAD" -- '*.py' '**/*.py' '.github/workflows/contributor-check.yml' || true)
if [ -n "$CHANGED" ]; then
echo "run=true" >> "$GITHUB_OUTPUT"
else
echo "run=false" >> "$GITHUB_OUTPUT"
echo "No Python files changed, skipping attribution check."
fi
- name: Check for unmapped contributor emails
id: check-emails
if: steps.filter.outputs.run == 'true'
run: |
# Get the merge base between this PR and main
MERGE_BASE=$(git merge-base origin/main HEAD)
@@ -32,13 +42,10 @@ jobs:
if [ -z "$NEW_EMAILS" ]; then
echo "No new commits to check."
echo "review_status=[]" >> "$GITHUB_OUTPUT"
exit 0
fi
# An email is mapped if it has a file in contributors/emails/
# (one file per email — conflict-free) or an entry in the frozen
# legacy AUTHOR_MAP in scripts/release.py.
# Check each email against AUTHOR_MAP in release.py
MISSING=""
while IFS= read -r email; do
# Skip teknium and bot emails
@@ -47,12 +54,9 @@ jobs:
continue ;;
esac
# Check if email is in AUTHOR_MAP (either as a key or matches noreply pattern)
if echo "$email" | grep -qP '\+.*@users\.noreply\.github\.com'; then
continue # GitHub id+login noreply emails auto-resolve
fi
if [ -f "contributors/emails/${email}" ]; then
continue # mapped via the contributors directory
continue # GitHub noreply emails auto-resolve
fi
if ! grep -qF "\"${email}\"" scripts/release.py 2>/dev/null; then
@@ -63,29 +67,19 @@ jobs:
if [ -n "$MISSING" ]; then
echo ""
echo "⚠️ New contributor email(s) without a mapping:"
echo "⚠️ New contributor email(s) not in AUTHOR_MAP:"
echo -e "$MISSING"
echo ""
echo "Add a mapping file (do NOT edit AUTHOR_MAP in release.py):"
echo "Please add mappings to scripts/release.py AUTHOR_MAP:"
echo -e "$MISSING" | while read -r line; do
email=$(echo "$line" | sed 's/^ *//' | cut -d' ' -f1)
[ -z "$email" ] && continue
echo " python3 scripts/add_contributor.py ${email} <github-username>"
echo " \"${email}\": \"<github-username>\","
done
echo ""
echo "To find the GitHub username for an email:"
echo " gh api 'search/users?q=EMAIL+in:email' --jq '.items[0].login'"
# Emit review_status for unmapped emails
DETAIL=$(echo -e "$MISSING" | sed '/^$/d; s/^ //')
HOW_TO_FIX=$'Add mappings to scripts/release.py AUTHOR_MAP:\n```\n"<email>": "<github-username>",\n```\nTo find the GitHub username for an email:\n```\ngh api \'search/users?q=EMAIL+in:email\' --jq \'.items[0].login\'\n```\n'
REVIEW_STATUS=$(jq -nc \
--arg detail "$DETAIL" \
--arg how_to_fix "$HOW_TO_FIX" \
'[{"source":"contributor attribution","results":[{"kind":"action_required","title":"Unmapped contributor email(s)","summary":"New contributor email(s) are not in AUTHOR_MAP.","detail":$detail,"how_to_fix":$how_to_fix}]}]')
echo "review_status=$REVIEW_STATUS" >> "$GITHUB_OUTPUT"
exit 1
else
echo "✅ All contributor emails are mapped."
echo "✅ All contributor emails are mapped in AUTHOR_MAP."
fi
+20 -100
View File
@@ -11,20 +11,8 @@ on:
- 'optional-skills/**'
- '.github/workflows/deploy-site.yml'
workflow_dispatch:
inputs:
skills_index_run_id:
description: 'Optional Build Skills Index run ID whose skills-index artifact should be deployed'
required: false
type: string
rebuild_skills_index:
description: 'Force a fresh multi-source crawl instead of reusing the latest healthy index'
required: false
default: false
type: boolean
permissions:
contents: read
actions: read
pages: write
id-token: write
@@ -41,28 +29,19 @@ jobs:
# doesn't auto-deploy via the deploy-docs path.
if: github.event_name == 'release' || github.event_name == 'workflow_dispatch'
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- name: Trigger Vercel Deploy
run: curl -fsS --retry 3 --retry-delay 10 -X POST "${{ secrets.VERCEL_DEPLOY_HOOK }}"
run: curl -X POST "${{ secrets.VERCEL_DEPLOY_HOOK }}"
deploy-docs:
if: github.repository == 'NousResearch/hermes-agent'
runs-on: ubuntu-latest
timeout-minutes: 30
environment:
name: github-pages
url: ${{ steps.deploy.outputs.page_url }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
@@ -74,85 +53,28 @@ jobs:
python-version: '3.11'
- name: Install PyYAML for skill extraction
uses: ./.github/actions/retry
with:
command: pip install pyyaml==6.0.2 httpx==0.28.1
run: pip install pyyaml==6.0.2 httpx==0.28.1
- name: Prepare skills index (unified multi-source catalog)
- name: Build skills index (unified multi-source catalog)
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
GITHUB_TOKEN: ${{ steps.app-token.outputs.token }}
SKILLS_INDEX_RUN_ID: ${{ github.event.inputs.skills_index_run_id || '' }}
REBUILD_SKILLS_INDEX: ${{ github.event.inputs.rebuild_skills_index || 'false' }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
# The unified external catalog is expensive to crawl and can burn
# through the repository installation's GitHub API quota when several
# docs deploys land close together. Normal docs deploys therefore
# reuse the latest healthy catalog: first the artifact from a
# scheduled skills-index run, then the currently live index. Only a
# manual force rebuild does a fresh crawl here.
# Rebuild the unified catalog. The file is gitignored, so a fresh
# checkout starts without it and we want the freshest crawl in
# every deploy.
#
# If we do crawl, the build remains fatal. build_skills_index.py runs
# the health check BEFORE writing and exits non-zero on source
# collapse, keeping the last good Pages deployment live instead of
# publishing a degenerate catalog.
set -euo pipefail
INDEX_PATH="website/static/api/skills-index.json"
mkdir -p "$(dirname "$INDEX_PATH")"
validate_index() {
python3 - "$INDEX_PATH" <<'PY'
import json
import sys
from pathlib import Path
path = Path(sys.argv[1])
try:
data = json.loads(path.read_text(encoding="utf-8"))
except Exception as exc:
print(f"invalid skills index JSON: {exc}", file=sys.stderr)
sys.exit(1)
skills = data.get("skills")
if not isinstance(skills, list) or len(skills) < 1500:
count = len(skills) if isinstance(skills, list) else "missing"
print(f"skills index too small: {count}", file=sys.stderr)
sys.exit(1)
print(f"skills index ready: {len(skills)} skills")
PY
}
if [ "$REBUILD_SKILLS_INDEX" = "true" ]; then
python3 scripts/build_skills_index.py
validate_index
exit 0
fi
if [ -n "$SKILLS_INDEX_RUN_ID" ]; then
tmpdir="$(mktemp -d)"
echo "Downloading skills-index artifact from run $SKILLS_INDEX_RUN_ID"
if gh run download "$SKILLS_INDEX_RUN_ID" --name skills-index --dir "$tmpdir"; then
candidate="$(find "$tmpdir" -name skills-index.json -type f | head -n 1 || true)"
if [ -n "$candidate" ]; then
cp "$candidate" "$INDEX_PATH"
if validate_index; then
exit 0
fi
fi
fi
echo "::warning::Could not use skills-index artifact from run $SKILLS_INDEX_RUN_ID; trying live index"
fi
echo "Downloading currently live skills index"
if curl -fsSL --retry 3 --retry-delay 5 \
"https://hermes-agent.nousresearch.com/docs/api/skills-index.json" \
-o "$INDEX_PATH" && validate_index; then
exit 0
fi
echo "::warning::Live skills index unavailable or unhealthy; falling back to a fresh crawl"
rm -f "$INDEX_PATH"
# This MUST be fatal. build_skills_index.py runs a health check and
# exits non-zero WITHOUT writing the output file when a source
# collapses (e.g. a GitHub API rate limit zeroes the github /
# claude-marketplace / well-known taps all at once). Letting the
# deploy continue would either (a) ship a degenerate index missing
# whole hubs — the June 2026 regression where OpenAI/Anthropic/
# HuggingFace/NVIDIA tabs vanished — or (b) fall through to a
# local-only catalog. Failing here keeps the last good deployment
# live (GitHub Pages serves the previous build) instead of
# publishing a broken catalog. Re-run the workflow once the
# transient rate limit clears.
python3 scripts/build_skills_index.py
validate_index
- name: Extract skill metadata for dashboard
run: python3 website/scripts/extract-skills.py
@@ -161,10 +83,8 @@ jobs:
run: python3 website/scripts/generate-skill-docs.py
- name: Install dependencies
uses: ./.github/actions/retry
with:
command: npm ci
working-directory: website
run: npm ci
working-directory: website
- name: Build Docusaurus
run: npm run build
+15 -2
View File
@@ -2,7 +2,7 @@ name: Docker / shell lint
# Lints the container build inputs: Dockerfile (via hadolint) and any shell
# scripts under docker/ (via shellcheck). These catch the class of regression
# the behavioral docker smoke test can't — unquoted variable
# the behavioral docker-publish smoke test can't — unquoted variable
# expansions, silently-failing RUN commands, etc.
#
# Rules and ignores are documented in .hadolint.yaml at the repo root.
@@ -11,7 +11,20 @@ name: Docker / shell lint
# activate script doesn't exist at lint time.
on:
workflow_call:
push:
branches: [main]
paths:
- Dockerfile
- docker/**
- .hadolint.yaml
- .github/workflows/docker-lint.yml
pull_request:
branches: [main]
paths:
- Dockerfile
- docker/**
- .hadolint.yaml
- .github/workflows/docker-lint.yml
permissions:
contents: read
+360
View File
@@ -0,0 +1,360 @@
name: Docker Build and Publish
on:
push:
branches: [main]
paths:
- '**/*.py'
- 'pyproject.toml'
- 'uv.lock'
- 'Dockerfile'
- 'docker/**'
- '.github/workflows/docker-publish.yml'
- '.github/actions/hermes-smoke-test/**'
pull_request:
branches: [main]
paths:
- '**/*.py'
- 'pyproject.toml'
- 'uv.lock'
- 'Dockerfile'
- 'docker/**'
- '.github/workflows/docker-publish.yml'
- '.github/actions/hermes-smoke-test/**'
release:
types: [published]
permissions:
contents: read
# Needed so the arm64 job can push/pull its registry-backed build cache
# to ghcr.io (cache-to/cache-from type=registry). See the build-arm64
# job for why registry cache replaced the gha cache on that arch.
packages: write
# Concurrency: push/release runs are NEVER cancelled so every merge gets
# its own image. PR runs reuse a PR-scoped group with
# cancel-in-progress: true so rapid pushes to the same PR collapse to the
# latest commit.
concurrency:
group: docker-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: ${{ github.event_name == 'pull_request' }}
env:
IMAGE_NAME: nousresearch/hermes-agent
jobs:
# ---------------------------------------------------------------------------
# Build amd64 natively. This job also runs the smoke tests (basic --help
# and the dashboard subcommand regression guard from #9153), because amd64
# is the only arch we can `load` into the local daemon on an amd64 runner.
# ---------------------------------------------------------------------------
build-amd64:
# Only run on the upstream repository, not on forks
if: github.repository == 'NousResearch/hermes-agent'
runs-on: ubuntu-latest
timeout-minutes: 45
outputs:
digest: ${{ steps.push.outputs.digest }}
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@8d2750c68a42422c14e847fe6c8ac0403b4cbd6f # v3
# Build once, load into the local daemon for smoke testing. Cached
# to gha with a per-arch scope; the push step below reuses every
# layer from this build.
- name: Build image (amd64, smoke test)
uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
with:
context: .
file: Dockerfile
load: true
platforms: linux/amd64
tags: ${{ env.IMAGE_NAME }}:test
build-args: |
HERMES_GIT_SHA=${{ github.sha }}
cache-from: type=gha,scope=docker-amd64
cache-to: type=gha,mode=max,scope=docker-amd64
- name: Smoke test image
uses: ./.github/actions/hermes-smoke-test
with:
image: ${{ env.IMAGE_NAME }}:test
# ---------------------------------------------------------------------
# Run the docker-integration test suite against the freshly-built
# image already loaded into the local daemon (`:test`). These tests
# are excluded from the sharded `tests.yml :: test` matrix on purpose
# (see `_SKIP_PARTS` in scripts/run_tests_parallel.py) because each
# shard would otherwise reach the session-scoped ``built_image``
# fixture in ``tests/docker/conftest.py`` and start a 3-7min
# ``docker build`` under a 180s pytest-timeout cap — guaranteed to
# die in fixture setup.
#
# Piggybacking here avoids a second image build: the smoke test
# already proved the image loads + runs, so the daemon has it under
# `${IMAGE_NAME}:test` and we just point ``HERMES_TEST_IMAGE`` at
# that. The fixture's ``HERMES_TEST_IMAGE`` branch (see
# tests/docker/conftest.py:62-63) short-circuits the rebuild.
#
# Why this job and not a standalone one: the image is 5GB+; passing
# it between jobs via ``docker save``/``upload-artifact`` is slower
# than the build itself. Reusing the existing daemon state is the
# cheapest path to coverage on every PR that touches docker code.
# ---------------------------------------------------------------------
- name: Install uv (for docker tests)
uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5
- name: Set up Python 3.11 (for docker tests)
run: uv python install 3.11
- name: Install Python dependencies (for docker tests)
run: |
uv venv .venv --python 3.11
source .venv/bin/activate
# ``dev`` extra pulls in pytest, pytest-asyncio, pytest-timeout —
# everything tests/docker/ needs. We deliberately avoid ``all``
# here because the docker tests only drive the container via
# subprocess and don't import hermes_agent's optional deps.
uv pip install -e ".[dev]"
- name: Run docker integration tests
env:
# Skip rebuild; use the image already loaded by the build step.
HERMES_TEST_IMAGE: ${{ env.IMAGE_NAME }}:test
# Match the policy in tests.yml :: test job — no accidental
# real-API calls from inside the harness.
OPENROUTER_API_KEY: ""
OPENAI_API_KEY: ""
NOUS_API_KEY: ""
run: |
source .venv/bin/activate
python -m pytest tests/docker/ -v --tb=short
- name: Log in to Docker Hub
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
# Push amd64 by digest only (no tag). The merge job assembles the
# tagged manifest list. `push-by-digest=true` is docker's recommended
# pattern for multi-runner multi-platform builds.
- name: Push amd64 by digest
id: push
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
with:
context: .
file: Dockerfile
platforms: linux/amd64
labels: |
org.opencontainers.image.revision=${{ github.sha }}
build-args: |
HERMES_GIT_SHA=${{ github.sha }}
outputs: type=image,name=${{ env.IMAGE_NAME }},push-by-digest=true,name-canonical=true,push=true
cache-from: type=gha,scope=docker-amd64
cache-to: type=gha,mode=max,scope=docker-amd64
# Write the digest to a file and upload it as an artifact so the
# merge job can stitch both per-arch digests into a manifest list.
- name: Export digest
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
run: |
mkdir -p /tmp/digests
digest="${{ steps.push.outputs.digest }}"
touch "/tmp/digests/${digest#sha256:}"
- name: Upload digest artifact
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4
with:
name: digest-amd64
path: /tmp/digests/*
if-no-files-found: error
retention-days: 1
# ---------------------------------------------------------------------------
# Build arm64 natively on GitHub's free arm64 runner. This replaces the
# previous QEMU-emulated arm64 build, which was ~5-10x slower and shared
# a cache scope with amd64. Matches the amd64 job's shape: build+load,
# smoke test, then on push/release push by digest.
# ---------------------------------------------------------------------------
build-arm64:
if: github.repository == 'NousResearch/hermes-agent'
runs-on: ubuntu-24.04-arm
timeout-minutes: 45
outputs:
digest: ${{ steps.push.outputs.digest }}
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@8d2750c68a42422c14e847fe6c8ac0403b4cbd6f # v3
# Log in to ghcr.io so the registry-backed build cache below can be
# read (cache-from) on every event and written (cache-to) on
# push/release. Uses the workflow's GITHUB_TOKEN, which is valid for
# the whole job — unlike the gha cache backend's short-lived Azure SAS
# token, which expired mid-build on slow cold-cache arm64 runs and
# crashed the build before the smoke test (the reason the gha cache
# was removed from arm64 PRs in the first place).
- name: Log in to ghcr.io (build cache)
uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
# Build once, load into the local daemon for smoke testing.
#
# PR builds use the registry-backed cache READ-ONLY (cache-from only):
# they pull warm layers pushed by the most recent main build but never
# write, so rapid PR pushes don't race on cache writes or pollute the
# cache ref. This restores warm-cache speed to arm64 PR builds (which
# were running fully uncached and were ~45% slower than amd64, making
# them the job most often cancelled on supersede).
#
# Registry cache (type=registry on ghcr.io) is used instead of the gha
# cache that previously broke here: its credential is the job-lifetime
# GITHUB_TOKEN, not a short-lived SAS token, so the cold-build-outlives-
# token failure mode cannot recur.
- name: Build image (arm64, smoke test, cache read-only PR)
if: github.event_name == 'pull_request'
uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
with:
context: .
file: Dockerfile
load: true
platforms: linux/arm64
tags: ${{ env.IMAGE_NAME }}:test
build-args: |
HERMES_GIT_SHA=${{ github.sha }}
cache-from: type=registry,ref=ghcr.io/nousresearch/hermes-agent:buildcache-arm64
# Main/release builds read AND write the registry cache so the digest
# push below reuses layers from this smoke-test build, and so the next
# PR/main build starts warm.
- name: Build image (arm64, smoke test, cached publish)
if: github.event_name != 'pull_request'
uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
with:
context: .
file: Dockerfile
load: true
platforms: linux/arm64
tags: ${{ env.IMAGE_NAME }}:test
build-args: |
HERMES_GIT_SHA=${{ github.sha }}
cache-from: type=registry,ref=ghcr.io/nousresearch/hermes-agent:buildcache-arm64
cache-to: type=registry,ref=ghcr.io/nousresearch/hermes-agent:buildcache-arm64,mode=max
- name: Smoke test image
uses: ./.github/actions/hermes-smoke-test
with:
image: ${{ env.IMAGE_NAME }}:test
- name: Log in to Docker Hub
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Push arm64 by digest
id: push
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
with:
context: .
file: Dockerfile
platforms: linux/arm64
labels: |
org.opencontainers.image.revision=${{ github.sha }}
build-args: |
HERMES_GIT_SHA=${{ github.sha }}
outputs: type=image,name=${{ env.IMAGE_NAME }},push-by-digest=true,name-canonical=true,push=true
cache-from: type=registry,ref=ghcr.io/nousresearch/hermes-agent:buildcache-arm64
cache-to: type=registry,ref=ghcr.io/nousresearch/hermes-agent:buildcache-arm64,mode=max
- name: Export digest
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
run: |
mkdir -p /tmp/digests
digest="${{ steps.push.outputs.digest }}"
touch "/tmp/digests/${digest#sha256:}"
- name: Upload digest artifact
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4
with:
name: digest-arm64
path: /tmp/digests/*
if-no-files-found: error
retention-days: 1
# ---------------------------------------------------------------------------
# Stitch both per-arch digests into a single tagged multi-arch manifest.
# This is a registry-side operation — no building, no layer re-push —
# so it runs in ~30 seconds.
#
# On main pushes: tags both :main and :latest.
# On releases: tags :<release_tag_name>.
# ---------------------------------------------------------------------------
merge:
if: github.repository == 'NousResearch/hermes-agent' && (github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release')
runs-on: ubuntu-latest
needs: [build-amd64, build-arm64]
timeout-minutes: 10
steps:
- name: Download digests
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
with:
path: /tmp/digests
pattern: digest-*
merge-multiple: true
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@8d2750c68a42422c14e847fe6c8ac0403b4cbd6f # v3
- name: Log in to Docker Hub
uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Create manifest list and push
working-directory: /tmp/digests
run: |
set -euo pipefail
args=()
for digest_file in *; do
args+=("${IMAGE_NAME}@sha256:${digest_file}")
done
if [ "${{ github.event_name }}" = "release" ]; then
TAG="${{ github.event.release.tag_name }}"
docker buildx imagetools create \
-t "${IMAGE_NAME}:${TAG}" \
"${args[@]}"
else
docker buildx imagetools create \
-t "${IMAGE_NAME}:main" \
-t "${IMAGE_NAME}:latest" \
"${args[@]}"
fi
env:
IMAGE_NAME: ${{ env.IMAGE_NAME }}
- name: Inspect image
run: |
if [ "${{ github.event_name }}" = "release" ]; then
docker buildx imagetools inspect "${IMAGE_NAME}:${{ github.event.release.tag_name }}"
else
docker buildx imagetools inspect "${IMAGE_NAME}:main"
fi
env:
IMAGE_NAME: ${{ env.IMAGE_NAME }}
-219
View File
@@ -1,219 +0,0 @@
name: Docker Build, Test, and Publish
on:
release:
types: [published]
workflow_call:
permissions:
contents: read
# Concurrency: push/release runs are NEVER cancelled so every merge gets
# its own image. PR runs reuse a PR-scoped group with
# cancel-in-progress: true so rapid pushes to the same PR collapse to
# the latest commit.
concurrency:
group: docker-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: ${{ github.event_name == 'pull_request' }}
env:
IMAGE_NAME: nousresearch/hermes-agent
jobs:
# Build, test, and optionally push the image for each architecture.
build:
if: github.repository == 'NousResearch/hermes-agent'
strategy:
fail-fast: false
matrix:
include:
- arch: amd64
runner: ubuntu-latest
platform: linux/amd64
cache-from: type=gha,scope=docker-amd64
cache-to: type=gha,mode=max,scope=docker-amd64
- arch: arm64
runner: ubuntu-24.04-arm
platform: linux/arm64
cache-from: type=gha,scope=docker-arm64
cache-to: type=gha,mode=max,scope=docker-arm64
runs-on: ${{ matrix.runner }}
timeout-minutes: 45
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@8d2750c68a42422c14e847fe6c8ac0403b4cbd6f # v3
# Build once, load into the local daemon for testing. Cached
# per-arch; the push step below reuses every layer from this build.
- name: Build image (${{ matrix.arch }})
uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
with:
context: .
file: Dockerfile
load: true
platforms: ${{ matrix.platform }}
tags: ${{ env.IMAGE_NAME }}:test
build-args: |
HERMES_GIT_SHA=${{ github.sha }}
cache-from: ${{ matrix.cache-from }}
cache-to: ${{ (github.event_name != 'pull_request') && matrix.cache-to || '' }}
- name: Log in to Docker Hub
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
# Push by digest only (no tag). The merge job assembles the
# tagged manifest list. `push-by-digest=true` is docker's recommended
# pattern for multi-runner multi-platform builds.
- name: Push ${{ matrix.arch }} by digest
id: push
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
with:
context: .
file: Dockerfile
platforms: ${{ matrix.platform }}
labels: |
org.opencontainers.image.revision=${{ github.sha }}
build-args: |
HERMES_GIT_SHA=${{ github.sha }}
outputs: type=image,name=${{ env.IMAGE_NAME }},push-by-digest=true,name-canonical=true,push=true
cache-from: ${{ matrix.cache-from }}
cache-to: ${{ matrix.cache-to }}
# Write the digest to a file and upload it as an artifact so the
# merge job can stitch both per-arch digests into a manifest list.
- name: Export digest
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
run: |
mkdir -p /tmp/digests
digest="${{ steps.push.outputs.digest }}"
touch "/tmp/digests/${digest#sha256:}"
- name: Upload digest artifact
if: github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release'
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: digest-${{ matrix.arch }}
path: /tmp/digests/*
if-no-files-found: error
retention-days: 1
# Run the docker-integration test suite against the freshly-built
# image already loaded into the local daemon (`:test`).
#
# Piggybacking here avoids a second image build: the build step
# already loaded the image into the daemon under
# `${IMAGE_NAME}:test`, so we just point ``HERMES_TEST_IMAGE`` at
# that. The fixture's ``HERMES_TEST_IMAGE`` branch (see
# tests/docker/conftest.py:62-63) short-circuits the rebuild.
#
# Why this job and not a standalone one: the image is 5GB+; passing
# it between jobs via ``docker save``/``upload-artifact`` is slower
# than the build itself. Reusing the existing daemon state is the
# cheapest path to coverage on every PR that touches docker code.
# ---------------------------------------------------------------------
- name: Install uv (for docker tests)
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
- name: Set up Python 3.11 (for docker tests)
run: uv python install 3.11
- name: Install Python dependencies (for docker tests)
# ``dev`` extra pulls in pytest, pytest-asyncio —
# everything tests/docker/ needs. We deliberately avoid ``all``
# here because the docker tests only drive the container via
# subprocess and don't import hermes_agent's optional deps.
uses: ./.github/actions/retry
with:
command: uv sync --locked --python 3.11 --extra dev
- name: Run docker integration tests
env:
# Skip rebuild; use the image already loaded by the build step.
HERMES_TEST_IMAGE: ${{ env.IMAGE_NAME }}:test
# Match the policy in tests.yml :: test job — no accidental
# real-API calls from inside the harness.
OPENROUTER_API_KEY: ""
OPENAI_API_KEY: ""
NOUS_API_KEY: ""
run: |
scripts/run_tests.sh tests/docker/ --file-timeout 600
# ---------------------------------------------------------------------------
# Stitch both per-arch digests into a single tagged multi-arch manifest.
# This is a registry-side operation — no building, no layer re-push —
# so it runs in ~30 seconds.
#
# On main pushes: tags both :main and :latest.
# On releases: tags :<release_tag_name>.
# ---------------------------------------------------------------------------
merge:
if: github.repository == 'NousResearch/hermes-agent' && (github.event_name == 'push' && github.ref == 'refs/heads/main' || github.event_name == 'release')
runs-on: ubuntu-latest
needs: [build]
timeout-minutes: 10
steps:
- name: Download digests
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
with:
path: /tmp/digests
pattern: digest-*
merge-multiple: true
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@8d2750c68a42422c14e847fe6c8ac0403b4cbd6f # v3
- name: Log in to Docker Hub
uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Create manifest list and push
working-directory: /tmp/digests
env:
IMAGE_NAME: ${{ env.IMAGE_NAME }}
RELEASE_TAG: ${{ github.event.release.tag_name }}
run: |
set -euo pipefail
args=()
for digest_file in *; do
args+=("${IMAGE_NAME}@sha256:${digest_file}")
done
if [ "${{ github.event_name }}" = "release" ]; then
tags=(-t "${IMAGE_NAME}:${RELEASE_TAG}")
else
tags=(-t "${IMAGE_NAME}:main" -t "${IMAGE_NAME}:latest")
fi
# Retry: Docker Hub API + just-pushed digest eventual consistency
# can transiently fail the create; the operation is idempotent.
for i in 1 2 3; do
if docker buildx imagetools create "${tags[@]}" "${args[@]}"; then
break
fi
if [ "$i" = 3 ]; then
echo "::error::imagetools create failed after 3 attempts"
exit 1
fi
echo "::warning::imagetools create failed (attempt $i); retrying in 20s"
sleep 20
done
- name: Inspect image
env:
IMAGE_NAME: ${{ env.IMAGE_NAME }}
RELEASE_TAG: ${{ github.event.release.tag_name }}
run: |
if [ "${{ github.event_name }}" = "release" ]; then
docker buildx imagetools inspect "${IMAGE_NAME}:${RELEASE_TAG}"
else
docker buildx imagetools inspect "${IMAGE_NAME}:main"
fi
+12 -13
View File
@@ -1,7 +1,11 @@
name: Docs Site Checks
on:
workflow_call:
pull_request:
paths:
- 'website/**'
- '.github/workflows/docs-site-checks.yml'
workflow_dispatch:
permissions:
contents: read
@@ -9,30 +13,25 @@ permissions:
jobs:
docs-site-checks:
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
cache-dependency-path: website/package-lock.json
- name: Install website dependencies
uses: ./.github/actions/retry
with:
command: npm ci
working-directory: website
run: npm ci
working-directory: website
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: "3.11"
python-version: '3.11'
- name: Install ascii-guard
uses: ./.github/actions/retry
with:
command: python -m pip install ascii-guard==2.3.0 pyyaml==6.0.3
run: python -m pip install ascii-guard==2.3.0 pyyaml==6.0.3
- name: Extract skill metadata for dashboard
run: python3 website/scripts/extract-skills.py
+49
View File
@@ -0,0 +1,49 @@
name: E2E CLI Tests
on:
push:
branches:
- "**"
permissions:
contents: read
jobs:
e2e-tui-test:
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Checkout code
uses: actions/checkout@v4
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
- run: npm ci
- run: cd e2e && CI=true npm run test
env:
# Ensure tests don't accidentally call real APIs
OPENROUTER_API_KEY: ""
OPENAI_API_KEY: ""
NOUS_API_KEY: ""
- name: Bundle TUI traces into self-contained replay HTML
if: always()
run: node e2e/scripts/bundle-replay-html.mjs
- name: Upload TUI replay viewer
uses: actions/upload-artifact@v4
if: always()
with:
name: tui-replay-viewer
path: tui-replay-viewer/
retention-days: 7
- name: Upload raw TUI test traces
uses: actions/upload-artifact@v4
if: always()
with:
name: tui-test-traces
path: e2e/tui-traces/
retention-days: 7
-212
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@@ -1,212 +0,0 @@
name: E2E Desktop
on:
workflow_call:
permissions:
contents: read
concurrency:
group: e2e-desktop-${{ github.ref }}
cancel-in-progress: true
jobs:
e2e:
name: Playwright E2E (Linux)
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
# ── System deps for Electron on headless Ubuntu ───────────────────
# Electron needs GTK, NSS,atk, etc. even under xvfb. Playwright's
# install-deps covers browsers; for Electron we install the apt
# packages directly.
- name: Install system dependencies for Electron
run: |
sudo apt-get update -qq
sudo apt-get install -y -qq \
xvfb \
libgtk-3-0 libnotify4 libnss3 libxss1 libxtst6 \
xdg-utils libatspi2.0-0 libdrm2 libgbm1 libasound2t64
# ── Node ───────────────────────────────────────────────────────────
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
# Full npm ci (not --ignore-scripts): electron's postinstall
# downloads the binary we launch, and node-pty's native build is
# needed for the terminal pane.
- uses: ./.github/actions/retry
with:
command: npm ci
# ── Python (for the hermes serve backend) ──────────────────────────
- name: Install uv
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
with:
enable-cache: true
cache-dependency-glob: |
pyproject.toml
uv.lock
- name: Set up Python 3.11
run: uv python install 3.11
- name: Install Python dependencies
uses: ./.github/actions/retry
with:
command: uv sync --locked --python 3.11 --extra all --extra dev
# ── Build desktop app ─────────────────────────────────────────────
- run: npm run --prefix apps/desktop build
# ── Restore visual baseline screenshots from main ──────────────────
# Baselines are generated on main (via --update-snapshots) and cached.
# On PRs, we restore them so toHaveScreenshot has something to compare
# against. The cache key is keyed on the desktop source files so a
# UI change naturally invalidates it — but we fall back to the main
# cache to avoid cold starts on unrelated PRs.
- name: Restore visual baseline screenshots
id: restore-baselines
uses: actions/cache@0400d5f644dc74513175e3cd8d07132dd4860809 # v4.2.4
with:
path: apps/desktop/e2e/*-snapshots
key: visual-baselines-${{ github.ref_name }}
restore-keys: |
visual-baselines-main
# ── Run Playwright E2E under xvfb ─────────────────────────────────
# xvfb runs at a fixed 1280x1024 screen so the 1220x800 Electron
# window always has a consistent viewport for screenshot comparison.
# On main, we run with --update-snapshots to generate baselines.
- name: Run Playwright E2E tests
working-directory: apps/desktop
run: |
if [ "${{ github.ref_name }}" = "main" ]; then
echo "On main — generating/updating baseline screenshots"
xvfb-run -a --server-args="-screen 0 1280x1024x24" \
npx playwright test --reporter=list --update-snapshots
else
echo "On PR — comparing against cached baselines"
xvfb-run -a --server-args="-screen 0 1280x1024x24" \
npx playwright test --reporter=list
fi
env:
CI: "true"
# Ensure no real API keys leak into the test env.
OPENROUTER_API_KEY: ""
OPENAI_API_KEY: ""
NOUS_API_KEY: ""
# ── Save updated baselines to cache (main only) ───────────────────
- name: Save updated baselines to cache
if: github.ref_name == 'main' && always()
uses: actions/cache/save@0400d5f644dc74513175e3cd8d07132dd4860809 # v4.2.4
with:
path: apps/desktop/e2e/*-snapshots
key: visual-baselines-main
# ── Upload Playwright report (HTML + traces) ──────────────────────
- name: Upload Playwright report
id: upload-report
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: playwright-report-${{ github.sha }}
path: apps/desktop/playwright-report
retention-days: 14
overwrite: true
# ── Upload test results (screenshots, traces, diffs) ───────────────
- name: Upload test results
id: upload-results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: playwright-test-results-${{ github.sha }}
path: apps/desktop/test-results
retention-days: 14
overwrite: true
# ── Upload just the visual diffs (small, fast to review) ──────────
- name: Upload visual diffs
id: upload-diffs
if: always() && github.ref_name != 'main'
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: visual-diffs-${{ github.sha }}
path: |
apps/desktop/test-results/**/*-diff.png
apps/desktop/test-results/**/*-actual.png
apps/desktop/test-results/**/*-expected.png
retention-days: 14
overwrite: true
if-no-files-found: ignore
# ── Generate step summary with visual diff info ───────────────────
# Parse the JSON report + scan for diff images, then post a summary
# to the GitHub Actions step output so reviewers can see what changed
# without downloading artifacts. Runs AFTER uploads so it can link
# the artifact download URLs from their step outputs.
- name: Generate visual diff summary
if: always()
working-directory: apps/desktop
env:
REPORT_URL: ${{ steps.upload-report.outputs.artifact-url }}
RESULTS_URL: ${{ steps.upload-results.outputs.artifact-url }}
DIFFS_URL: ${{ steps.upload-diffs.outputs.artifact-url }}
run: |
echo "## Desktop E2E — Visual Diff Report" >> "$GITHUB_STEP_SUMMARY"
echo "" >> "$GITHUB_STEP_SUMMARY"
# Count diff images (playwright writes *-diff.png on mismatch)
DIFF_COUNT=$(find test-results -name '*-diff.png' 2>/dev/null | wc -l)
ACTUAL_COUNT=$(find test-results -name '*-actual.png' 2>/dev/null | wc -l)
if [ "$DIFF_COUNT" -eq 0 ]; then
echo "✅ All $ACTUAL_COUNT screenshot(s) matched their baselines (or no baselines existed yet)." >> "$GITHUB_STEP_SUMMARY"
else
echo "📸 **$DIFF_COUNT of $ACTUAL_COUNT screenshot(s) differ from baseline:**" >> "$GITHUB_STEP_SUMMARY"
echo "" >> "$GITHUB_STEP_SUMMARY"
echo "| Test | Diff | Actual | Expected |" >> "$GITHUB_STEP_SUMMARY"
echo "|------|------|--------|----------|" >> "$GITHUB_STEP_SUMMARY"
# List each diff image with a link to the artifact
for diff in $(find test-results -name '*-diff.png' 2>/dev/null | sort); do
base=$(echo "$diff" | sed 's/-diff\.png$//')
test_name=$(basename "$base")
echo "| $test_name | [diff]($diff) | [actual](${base}-actual.png) | [expected](${base}-expected.png) |" >> "$GITHUB_STEP_SUMMARY"
done
fi
echo "" >> "$GITHUB_STEP_SUMMARY"
echo "📥 **Artifacts:**" >> "$GITHUB_STEP_SUMMARY"
echo "" >> "$GITHUB_STEP_SUMMARY"
if [ -n "$RESULTS_URL" ]; then
echo "- [playwright-test-results]($RESULTS_URL) — all screenshots (actual + expected + diff) + traces" >> "$GITHUB_STEP_SUMMARY"
fi
if [ -n "$REPORT_URL" ]; then
echo "- [playwright-report]($REPORT_URL) — interactive HTML report" >> "$GITHUB_STEP_SUMMARY"
fi
if [ -n "$DIFFS_URL" ]; then
echo "- [visual-diffs]($DIFFS_URL) — just the diffed screenshots (small, fast to review)" >> "$GITHUB_STEP_SUMMARY"
fi
echo "" >> "$GITHUB_STEP_SUMMARY"
echo "**To update baselines:** merge to main (baselines auto-update on main runs) or run \`npx playwright test --update-snapshots\` locally." >> "$GITHUB_STEP_SUMMARY"
# Also parse the JSON report for pass/fail counts
if [ -f playwright-report/results.json ]; then
echo "" >> "$GITHUB_STEP_SUMMARY"
echo "### Test Results" >> "$GITHUB_STEP_SUMMARY"
echo "" >> "$GITHUB_STEP_SUMMARY"
node -e "
const r = require('./playwright-report/results.json');
const stats = r.stats || {};
console.log('| Status | Count |');
console.log('|--------|-------|');
console.log('| ✅ Passed | ' + (stats.expected || 0) + ' |');
console.log('| ❌ Failed | ' + (stats.unexpected || 0) + ' |');
console.log('| ⏭️ Skipped | ' + (stats.skipped || 0) + ' |');
console.log('| 🔄 Flaky | ' + (stats.flaky || 0) + ' |');
" >> "$GITHUB_STEP_SUMMARY" 2>/dev/null || true
fi
+5 -15
View File
@@ -14,11 +14,8 @@ name: History Check
# the PR head and main to be non-empty.
on:
workflow_call:
outputs:
review_status:
description: "JSON array of review_status objects for the synthesizer."
value: ${{ jobs.check-common-ancestor.outputs.review_status }}
pull_request:
branches: [main]
permissions:
contents: read
@@ -26,24 +23,18 @@ permissions:
jobs:
check-common-ancestor:
runs-on: ubuntu-latest
timeout-minutes: 10
outputs:
review_status: ${{ steps.merge-base-check.outputs.review_status }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
fetch-depth: 0 # full history both sides for merge-base
fetch-depth: 0 # full history both sides for merge-base
- id: merge-base-check
name: Reject PRs with no common ancestor on main
- name: Reject PRs with no common ancestor on main
run: |
# `git merge-base` exits non-zero AND prints nothing when the two
# commits share no ancestor. We check both conditions explicitly
# so the failure message is clear regardless of which signal fires
# first.
if ! BASE=$(git merge-base origin/main HEAD 2>/dev/null) || [ -z "$BASE" ]; then
STATUS='[{"source":"unrelated histories","results":[{"kind":"action_required","title":"Unrelated histories","summary":"This PR has no common ancestor with main.","detail":"","how_to_fix":"Rebase your changes onto current main:\n```\ngit fetch origin main\ngit checkout -b fix-branch origin/main\n# re-apply your changes (cherry-pick, copy files, etc.)\ngit push -f origin fix-branch\n```\n"}]}]'
echo "review_status=${STATUS}" >> "$GITHUB_OUTPUT"
echo ""
echo "::error::This PR has no common ancestor with main."
echo ""
@@ -65,4 +56,3 @@ jobs:
exit 1
fi
echo "::notice::Common ancestor with main: $BASE"
echo "review_status=[]" >> "$GITHUB_OUTPUT"
-258
View File
@@ -1,258 +0,0 @@
name: auto-fix lint issues & formatting
# On push to main (or manual trigger), run `npm run fix` on each workspace
# package and apply any changes via a PR.
#
# Fixable lint issues (import sorting, unused imports, curly braces, etc.) are
# auto-corrected on merge so PRs aren't blocked by them. The PR-time eslint
# check in typecheck.yml fails only when un-fixable errors remain.
#
# NOTE: App token pushes DO trigger further workflow runs (unlike
# secrets.GITHUB_TOKEN). The concurrency group (ts-autofix-${{ github.ref }})
# with cancel-in-progress: true prevents an infinite loop — a re-triggered
# run cancels the in-flight one, and since the second run finds no new fixes
# (the first run already applied them), it exits with an empty patch.
#
# ── Security model: two-job split ───────────────────────────────────────────
#
# The eslint process executes repo code (eslint.config.mjs, package.json
# scripts, installed plugins). To prevent a malicious PR from getting arbitrary
# code execution on a runner with push access, the work is split:
#
# 1. generate-patch (unprivileged, contents: read only)
# Checks out, installs deps, runs eslint --fix, produces a .patch artifact.
# Worst case: malicious code runs here on an ephemeral runner with zero
# push permissions.
#
# 2. apply-patch (privileged, contents: write + pull-requests: write)
# Checks out, downloads the patch artifact, applies it, pushes to the
# bot/js-autofix branch, creates/updates a PR, and enables auto-merge.
# This job never runs npm, never installs anything, never executes any
# repo code. The only input it trusts is the patch artifact.
# Skipped entirely when generate-patch reports no fixes (has-fixes != true).
# The PR auto-merges (squash) once CI passes. If CI fails or main moves,
# the PR is auto-closed and the branch deleted — the next run re-applies
# on the current state.
on:
push:
branches: [main]
paths:
- '**/*.js'
- '**/*.cjs'
- '**/*.mjs'
- '**/*.ts'
- '**/*.tsx'
- 'package.json'
- 'package-lock.json'
workflow_dispatch:
permissions:
contents: read # default; apply-patch job overrides to write
concurrency:
group: ts-autofix-${{ github.ref }}
cancel-in-progress: true
jobs:
generate-patch:
name: Generate eslint --fix patch
runs-on: ubuntu-latest
timeout-minutes: 5
outputs:
has-fixes: ${{ steps.produce-patch.outputs.has-fixes }}
# No permissions override → inherits workflow-level contents: read.
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
# --ignore-scripts: eslint only needs TS sources + eslint packages.
- uses: ./.github/actions/retry
with:
command: npm ci --ignore-scripts
- name: npm run fix in all workspaces
# continue-on-error: if un-fixable errors exist on main, we still want
# to commit whatever fixes were applied. The PR-time check in
# typecheck.yml is what blocks un-fixable errors from landing.
continue-on-error: true
run: npm run fix
- name: Produce patch
id: produce-patch
run: |
if git diff --quiet; then
echo "No fixes needed."
echo "has-fixes=false" >> "$GITHUB_OUTPUT"
# Empty patch signals "nothing to do" to apply-patch.
: > js-fix.patch
else
git diff > js-fix.patch
echo "has-fixes=true" >> "$GITHUB_OUTPUT"
echo "Patch size: $(wc -c < js-fix.patch) bytes"
# Reject patches that touch anything outside JS/TS/JSON sources.
# `npm run fix` should only ever modify those; anything else means
# eslint/prettier or a plugin went rogue and we refuse to ship it.
BAD=$(git diff --name-only | grep -vE '\.(js|cjs|mjs|ts|tsx|json)$' || true)
if [ -n "$BAD" ]; then
echo "::error::Refusing to upload patch — touches disallowed files:"
echo "$BAD"
exit 1
fi
fi
- name: Upload patch artifact
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4
with:
name: js-fix-patch
path: js-fix.patch
retention-days: 1
include-hidden-files: true
apply-patch:
name: Apply patch
needs: generate-patch
# Skip entirely when generate-patch found no fixes — saves a runner,
# avoids a redundant checkout/download, and keeps the job graph honest.
if: needs.generate-patch.outputs.has-fixes == 'true'
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
contents: write # needed to push to bot/js-autofix
pull-requests: write # needed for PR creation + auto-merge
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- name: Download patch
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
with:
name: js-fix-patch
# ${{ runner.temp }} expands in with: params (shell-style $VAR does not).
# download-artifact's path is a *directory* — the artifact's js-fix.patch
# file lands inside it, so $RUNNER_TEMP/js-fix.patch resolves correctly
# in the run step below.
path: ${{ runner.temp }}
- name: Apply patch and push to bot branch
env:
BOT_BRANCH: bot/js-autofix
run: |
set -euo pipefail
# Empty patch = nothing to do.
if [ ! -s "$RUNNER_TEMP/js-fix.patch" ]; then
echo "Patch is empty. No fixes to apply."
exit 0
fi
# Apply the patch produced by the unprivileged job.
git apply --check "$RUNNER_TEMP/js-fix.patch" || {
echo "::error::Patch does not apply cleanly. Branch may have moved."
exit 1
}
git apply "$RUNNER_TEMP/js-fix.patch"
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
git add -A
git commit -m "fmt(js): \`npm run fix\` on merge"
# Push to the dedicated bot branch. Force-push is safe here:
# bot/js-autofix is a bot-only branch that gets rewritten each run.
# If the branch was deleted after a previous PR merge, this
# recreates it.
git push --force origin HEAD:"$BOT_BRANCH"
- name: Create/update PR and enable auto-merge
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
BOT_BRANCH: bot/js-autofix
run: |
set -euo pipefail
# Create PR if one doesn't exist. If it already exists, the
# force-push above already updated it with the latest fixes.
PR_NUM=$(gh pr list --head "$BOT_BRANCH" --state open --json number --jq '.[0].number' 2>/dev/null || true)
if [ -z "$PR_NUM" ]; then
# gh pr create prints the PR URL. Extract the number from it
# (https://github.com/<org>/<repo>/pull/<number>).
PR_URL=$(gh pr create \
--head "$BOT_BRANCH" --base main \
--title 'fmt(js): `npm run fix` auto-fix' \
--body 'Auto-generated by the `auto-fix lint issues & formatting` workflow. Auto-merges (squash) once CI passes. If CI fails or `main` moves, the PR is auto-closed and the branch deleted — the next run re-applies on the current state.')
PR_NUM=$(echo "$PR_URL" | grep -oE '[0-9]+$')
fi
# Enable auto-merge (squash). If already enabled, this is a no-op.
gh pr merge "$PR_NUM" --auto --squash || true
- name: Wait for merge, auto-close on failure or stale
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
START_SHA: ${{ github.sha }}
run: |
set -euo pipefail
PR_NUM=$(gh pr list --head bot/js-autofix --state open --json number --jq '.[0].number' 2>/dev/null || true)
if [ -z "$PR_NUM" ]; then
echo "No open PR. Nothing to wait for."
exit 0
fi
echo "Waiting for PR #$PR_NUM to merge..."
# Poll every 15s for up to ~10 minutes. Auto-merge will handle the
# PR even if this job times out — the polling is for cleanup only
# (auto-close on CI failure, conflicts, or main moving).
for i in $(seq 1 40); do
sleep 15
STATE=$(gh pr view "$PR_NUM" --json state --jq '.state')
if [ "$STATE" = "MERGED" ] || [ "$STATE" = "CLOSED" ]; then
echo "PR #$PR_NUM is $STATE."
exit 0
fi
# If main moved, the PR may have already merged (which moves
# main) or another commit landed. Re-check state first.
CURRENT_SHA=$(gh api "repos/${{ github.repository }}/branches/main" --jq '.commit.sha')
if [ "$CURRENT_SHA" != "$START_SHA" ]; then
STATE=$(gh pr view "$PR_NUM" --json state --jq '.state')
if [ "$STATE" = "MERGED" ]; then
echo "PR #$PR_NUM merged (main moved to $CURRENT_SHA)."
exit 0
fi
echo "Main moved ($START_SHA → $CURRENT_SHA). Closing stale PR."
gh pr close "$PR_NUM" --delete-branch || true
exit 0
fi
# If CI checks failed, close + delete the branch.
if gh pr checks "$PR_NUM" 2>/dev/null | grep -qi "fail"; then
echo "CI failed on PR #$PR_NUM. Closing + deleting branch."
gh pr close "$PR_NUM" --delete-branch
exit 0
fi
# If PR is conflicted, close + delete the branch.
MERGEABLE=$(gh pr view "$PR_NUM" --json mergeable --jq '.mergeable')
if [ "$MERGEABLE" = "CONFLICTING" ]; then
echo "PR #$PR_NUM is conflicted. Closing + deleting branch."
gh pr close "$PR_NUM" --delete-branch
exit 0
fi
done
echo "Timeout reached. Auto-merge will handle PR #$PR_NUM if CI passes."
-51
View File
@@ -1,51 +0,0 @@
# .github/workflows/js-tests.yml
name: JS Tests
on:
workflow_call:
jobs:
workspaces:
name: List npm workspaces
runs-on: ubuntu-latest
timeout-minutes: 20
outputs:
packages: ${{ steps.set-matrix.outputs.packages }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
- uses: ./.github/actions/retry
with:
command: npm ci --ignore-scripts
- id: set-matrix
run: |
PACKAGES=$(npm query .workspace | jq -c '[.[].location]')
if [ "$PACKAGES" = "[]" ] || [ -z "$PACKAGES" ]; then
echo "::error::Workspace discovery produced an empty package list — refusing to emit a zero-length matrix (would skip all JS/TS checks silently)."
exit 1
fi
echo "packages=$PACKAGES" >> "$GITHUB_OUTPUT"
check:
name: Typecheck & Test
needs: workspaces
runs-on: ubuntu-latest
timeout-minutes: 20
strategy:
matrix:
package: ${{ fromJson(needs.workspaces.outputs.packages) }}
fail-fast: false # report all failures, not just the first one
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
- uses: ./.github/actions/retry
with:
command: npm ci
- run: npm run --prefix ${{ matrix.package }} check
- run: npm run --prefix ${{ matrix.package }} fix
-81
View File
@@ -1,81 +0,0 @@
name: Label rerun
# When the ``ci-reviewed`` label is added to a PR, rerun all failed jobs in
# the latest CI run. This re-evaluates ``review-labels`` (which now sees the
# label) and GitHub automatically reruns dependent jobs (``comment-live``,
# ``all-checks-pass``) — so the review comment gets updated too.
#
# If the CI run is still in progress when the label is added, we wait for it
# to finish before rerunning (``gh run rerun`` only works on completed runs).
# The wait can be long (20+ min for a full CI run), but it's better than
# silently failing and leaving the reviewer stuck.
on:
pull_request:
types: [labeled]
permissions:
actions: write
pull-requests: read
concurrency:
group: label-rerun-${{ github.event.pull_request.number }}
cancel-in-progress: true
jobs:
rerun-review-labels:
name: Rerun review-labels job
if: github.event.label.name == 'ci-reviewed'
runs-on: ubuntu-latest
timeout-minutes: 40
steps:
- name: Wait for CI run to finish, then rerun failed jobs
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
REPO: ${{ github.repository }}
HEAD_SHA: ${{ github.event.pull_request.head.sha }}
run: |
set -uo pipefail
# Find the latest CI run for this PR's head SHA.
RUN_ID=$(gh run list \
--repo "$REPO" \
--commit "$HEAD_SHA" \
--workflow ci.yml \
--limit 1 \
--json databaseId,status \
--jq '.[0] | "\(.databaseId) \(.status)"' 2>/dev/null || true)
if [ -z "$RUN_ID" ]; then
echo "No CI run found for this PR — nothing to rerun."
exit 0
fi
# Split "RUN_ID STATUS" into two vars.
RUN_ID="${RUN_ID%% *}"
STATUS="${RUN_ID##* }"
echo "Latest CI run: $RUN_ID (status: $STATUS)"
# If the run is still in progress, wait for it to finish.
# gh run rerun only works on completed runs — if we try while it's
# running, GitHub rejects with "cannot be rerun; This workflow is
# already running".
if [ "$STATUS" != "completed" ]; then
echo "Run is $STATUS — waiting for completion (this may take a while)..."
# gh run watch --exit-status exits non-zero if the run fails,
# which is expected (the label gate fails). Don't let that kill
# the workflow — we WANT to rerun failed jobs.
timeout 2100 gh run watch "$RUN_ID" --repo "$REPO" --interval 15 || true
# Verify it's actually completed now.
STATUS=$(gh run view "$RUN_ID" --repo "$REPO" --json status --jq '.status' 2>/dev/null || echo "unknown")
if [ "$STATUS" != "completed" ]; then
echo "Run is still $STATUS after wait — giving up."
exit 0
fi
fi
echo "Run completed. Rerunning all failed jobs..."
gh run rerun "$RUN_ID" --repo "$REPO" --failed || true
echo "Done. GitHub will rerun review-labels and all dependent jobs."
+65 -25
View File
@@ -2,25 +2,29 @@ name: Lint (ruff + ty)
# Two things here:
# 1. Advisory diff — ruff + ty diagnostics as a diff vs the target branch.
# Writes a Markdown summary to the run page. Exit zero always.
# Posts a Markdown summary and a PR comment. Exit zero always.
# 2. Blocking ``ruff check .`` — enforces the explicit rules in
# ``[tool.ruff.lint.select]`` (currently PLW1514). Failure blocks merge.
# Separate job so the advisory diff still runs even when enforcement
# fails.
#
# CI-sensitive file review was previously here as a ``ci-review`` job but
# has moved to ``review-labels.yml`` so it can be rerun independently.
# Separate job so the advisory diff still runs and posts even when
# enforcement fails.
on:
workflow_call:
inputs:
event_name:
description: The event name from the calling orchestrator (pull_request or push).
type: string
required: true
push:
branches: [main]
paths-ignore:
- "**/*.md"
- "docs/**"
- "website/**"
pull_request:
branches: [main]
paths-ignore:
- "**/*.md"
- "docs/**"
- "website/**"
permissions:
contents: read
pull-requests: write # needed to post/update PR comments
concurrency:
group: lint-${{ github.ref }}
@@ -29,7 +33,6 @@ concurrency:
jobs:
lint-diff:
name: ruff + ty diff
if: inputs.event_name == 'pull_request'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
@@ -39,19 +42,19 @@ jobs:
fetch-depth: 0 # need full history for merge-base + worktree
- name: Install uv
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5
- name: Install ruff + ty
uses: ./.github/actions/retry
with:
command: uv tool install ruff && uv tool install ty
run: |
uv tool install ruff
uv tool install ty
- name: Determine base ref
id: base
run: |
# For PRs, diff against the merge base with the target branch.
# For pushes to main, diff against the previous commit on main.
if [ "${{ inputs.event_name }}" = "pull_request" ]; then
if [ "${{ github.event_name }}" = "pull_request" ]; then
BASE_SHA=$(git merge-base "origin/${{ github.base_ref }}" HEAD)
BASE_REF="origin/${{ github.base_ref }}"
else
@@ -100,8 +103,6 @@ jobs:
echo "base ty: $(wc -c < .lint-reports/base/ty.json) bytes"
- name: Generate diff summary
env:
HEAD_REF: ${{ inputs.event_name == 'pull_request' && github.head_ref || github.ref_name }}
run: |
python scripts/lint_diff.py \
--base-ruff .lint-reports/base/ruff.json \
@@ -109,10 +110,51 @@ jobs:
--base-ty .lint-reports/base/ty.json \
--head-ty .lint-reports/head/ty.json \
--base-ref "${{ steps.base.outputs.ref }}" \
--head-ref "$HEAD_REF" \
--head-ref "${{ github.event_name == 'pull_request' && github.head_ref || github.ref_name }}" \
--output .lint-reports/summary.md
cat .lint-reports/summary.md >> "$GITHUB_STEP_SUMMARY"
- name: Upload reports as artifact
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4
with:
name: lint-reports
path: .lint-reports/
retention-days: 14
- name: Post / update PR comment
if: github.event_name == 'pull_request' && github.event.pull_request.head.repo.full_name == github.repository
continue-on-error: true
uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7
with:
script: |
const fs = require('fs');
const body = fs.readFileSync('.lint-reports/summary.md', 'utf8');
const marker = '<!-- lint-diff-summary -->';
const fullBody = marker + '\n' + body;
const { data: comments } = await github.rest.issues.listComments({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
});
const existing = comments.find(c => c.body && c.body.includes(marker));
if (existing) {
await github.rest.issues.updateComment({
owner: context.repo.owner,
repo: context.repo.repo,
comment_id: existing.id,
body: fullBody,
});
} else {
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: fullBody,
});
}
ruff-blocking:
# Enforce the rules in pyproject.toml [tool.ruff.lint.select]. Currently
# PLW1514 (unspecified-encoding) — catches bare ``open()`` /
@@ -128,12 +170,10 @@ jobs:
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Install uv
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5
- name: Install ruff
uses: ./.github/actions/retry
with:
command: uv tool install ruff
run: uv tool install ruff
- name: ruff check .
# No --exit-zero, no || true. Exit code propagates to the job,
-95
View File
@@ -1,95 +0,0 @@
name: Lockfile diff
# Advisory PR comment showing the *semantic* diff of package-lock.json
# changes — which packages were added/removed/updated and their versions.
# The raw textual diff of a lockfile is unreadable (npm reorders entries
# and rewrites integrity hashes), so scripts/ci/lockfile_diff.py parses
# the ``packages`` map at the merge base and at HEAD and set-diffs the
# {install path: version} maps instead.
#
# The semantic diff is exposed as a workflow_call output ``review_status``
# (a JSON array in the unified status format) and an artifact
# (``lockfile-diff`` containing the markdown fragment) for the step
# summary.
#
# Never blocking — this is review signal, not enforcement.
on:
workflow_call:
outputs:
changed:
description: Whether package-lock.json changed relative to the target branch.
value: ${{ jobs.diff.outputs.changed }}
review_status:
description: JSON array of review status objects for the unified PR comment.
value: ${{ jobs.diff.outputs.review_status }}
permissions:
contents: read
concurrency:
group: lockfile-diff-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
diff:
name: package-lock.json semantic diff
runs-on: ubuntu-latest
timeout-minutes: 5
outputs:
changed: ${{ steps.diff.outputs.changed }}
review_status: ${{ steps.emit-status.outputs.review_status }}
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
fetch-depth: 0 # need history for the merge base
- name: Generate semantic lockfile diff
id: diff
run: |
set -euo pipefail
# Three-dot semantics by hand: diff from the merge base with the
# target branch to the PR head, so changes that landed on main
# after the branch point don't show up as this PR's doing.
BASE_SHA=$(git merge-base "origin/${{ github.base_ref }}" HEAD)
echo "Merge base: ${BASE_SHA}"
python3 scripts/ci/lockfile_diff.py \
--base "$BASE_SHA" \
--head HEAD \
--output /tmp/lockfile-diff.md
if [ -s /tmp/lockfile-diff.md ]; then
echo "changed=true" >> "$GITHUB_OUTPUT"
{
echo "## package-lock.json semantic diff"
echo ""
cat /tmp/lockfile-diff.md
} >> "$GITHUB_STEP_SUMMARY"
else
echo "changed=false" >> "$GITHUB_OUTPUT"
: > /tmp/lockfile-diff.md
fi
- name: Emit review_status
id: emit-status
run: |
set -euo pipefail
CHANGED="${{ steps.diff.outputs.changed }}"
STATUS="[]"
if [ "$CHANGED" = "true" ]; then
CONTENT=$(cat /tmp/lockfile-diff.md | python3 -c "import sys,json; print(json.dumps(sys.stdin.read()))")
STATUS="[{\"source\":\"lockfile-diff\",\"results\":[{\"kind\":\"action_required\",\"title\":\"package-lock.json\",\"summary\":\"Locked npm dependency versions changed.\",\"detail\":${CONTENT},\"how_to_fix\":\"Add the \`ci-reviewed\` label after verifying the version changes are expected.\"}]}"
else
STATUS="[]"
fi
echo "review_status=${STATUS}" >> "$GITHUB_OUTPUT"
- name: Upload diff artifact
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: lockfile-diff
path: /tmp/lockfile-diff.md
retention-days: 1
overwrite: true
+255
View File
@@ -0,0 +1,255 @@
name: Nix Lockfile Fix
on:
push:
branches: [main]
paths:
- 'package-lock.json'
- 'package.json'
- 'ui-tui/package.json'
- 'apps/desktop/package.json'
workflow_dispatch:
inputs:
pr_number:
description: 'PR number to fix (leave empty to run on the selected branch)'
required: false
type: string
issue_comment:
types: [edited]
permissions:
contents: write
pull-requests: write
concurrency:
group: nix-lockfile-fix-${{ github.event.issue.number || github.event.inputs.pr_number || github.ref }}
cancel-in-progress: false
jobs:
# ── Auto-fix on main ───────────────────────────────────────────────
# Fires when a push to main touches package.json or package-lock.json.
# Runs fix-lockfiles and pushes the hash update commit directly to main
# so Nix builds never stay broken.
#
# Safety invariants:
# 1. The fix commit only touches nix/*.nix files, which are NOT in
# the paths filter above, so this cannot re-trigger itself.
# 2. An explicit file-whitelist check before commit aborts if
# fix-lockfiles ever modifies unexpected files.
# 3. Job-level concurrency with cancel-in-progress: true ensures
# back-to-back pushes collapse to the newest; ref: main checkout
# always operates on the latest branch state.
# 4. Uses a GitHub App token (not GITHUB_TOKEN) so the fix commit
# triggers downstream nix.yml verification.
auto-fix-main:
if: github.event_name == 'push'
runs-on: ubuntu-latest
timeout-minutes: 25
concurrency:
group: auto-fix-main
cancel-in-progress: true
steps:
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@7bfa3a4717ef143a604ee0a99d859b8886a96d00 # v1.9.3
with:
app-id: ${{ secrets.APP_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
ref: main
token: ${{ steps.app-token.outputs.token }}
- uses: ./.github/actions/nix-setup
with:
cachix-auth-token: ${{ secrets.CACHIX_AUTH_TOKEN }}
- name: Apply lockfile hashes
id: apply
run: nix run .#fix-lockfiles -- --apply
- name: Commit & push
if: steps.apply.outputs.changed == 'true'
shell: bash
run: |
set -euo pipefail
# Ensure only nix/lib.nix (home of the single npmDepsHash) was
# modified — prevents accidental self-triggering if fix-lockfiles
# ever touches package files.
unexpected="$(git diff --name-only | grep -Ev '^nix/lib\.nix$' || true)"
if [ -n "$unexpected" ]; then
echo "::error::Unexpected modified files: $unexpected"
exit 1
fi
# Record the base SHA before committing — used to detect package
# file changes if we need to rebase after a non-fast-forward push.
BASE_SHA="$(git rev-parse HEAD)"
git config user.name 'github-actions[bot]'
git config user.email '41898282+github-actions[bot]@users.noreply.github.com'
git add nix/lib.nix
git commit -m "fix(nix): auto-refresh npm lockfile hashes" \
-m "Source: $GITHUB_SHA" \
-m "Run: $GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
# Retry push with rebase in case main advanced with an unrelated
# commit during the nix build. Without this, a non-fast-forward
# rejection silently loses the fix. If package files changed during
# the rebase, abort — a fresh auto-fix run will handle the new state.
for attempt in 1 2 3; do
if git push origin HEAD:main; then
exit 0
fi
echo "::warning::Push attempt $attempt failed (non-fast-forward?), rebasing…"
git fetch origin main
# If package files changed between our base and the new main,
# our computed hashes are stale. Abort and let the next triggered
# run recompute from the correct package-lock state.
pkg_changed="$(git diff --name-only "$BASE_SHA"..origin/main -- \
'package-lock.json' 'package.json' \
'ui-tui/package.json' 'apps/desktop/package.json' || true)"
if [ -n "$pkg_changed" ]; then
echo "::warning::Package files changed since hash computation — aborting; a fresh run will recompute"
exit 0
fi
git rebase origin/main
done
echo "::error::Failed to push after 3 rebase attempts"
exit 1
# ── PR fix (manual / checkbox) ─────────────────────────────────────
# Existing behavior: run on manual dispatch OR when a task-list
# checkbox in the sticky lockfile-check comment flips from [ ] to [x].
fix:
if: |
github.event_name == 'workflow_dispatch' ||
(github.event_name == 'issue_comment'
&& github.event.issue.pull_request != null
&& contains(github.event.comment.body, '[x] **Apply lockfile fix**')
&& !contains(github.event.changes.body.from, '[x] **Apply lockfile fix**'))
runs-on: ubuntu-latest
timeout-minutes: 25
steps:
- name: Authorize & resolve PR
id: resolve
uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7.0.1
with:
script: |
// 1. Verify the actor has write access — applies to both checkbox
// clicks and manual dispatch.
const { data: perm } =
await github.rest.repos.getCollaboratorPermissionLevel({
owner: context.repo.owner,
repo: context.repo.repo,
username: context.actor,
});
if (!['admin', 'write', 'maintain'].includes(perm.permission)) {
core.setFailed(
`${context.actor} lacks write access (has: ${perm.permission})`
);
return;
}
// 2. Resolve which ref to check out.
let prNumber = '';
if (context.eventName === 'issue_comment') {
prNumber = String(context.payload.issue.number);
} else if (context.eventName === 'workflow_dispatch') {
prNumber = context.payload.inputs.pr_number || '';
}
if (!prNumber) {
core.setOutput('ref', context.ref.replace(/^refs\/heads\//, ''));
core.setOutput('repo', context.repo.repo);
core.setOutput('owner', context.repo.owner);
core.setOutput('pr', '');
return;
}
const { data: pr } = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: Number(prNumber),
});
core.setOutput('ref', pr.head.ref);
core.setOutput('repo', pr.head.repo.name);
core.setOutput('owner', pr.head.repo.owner.login);
core.setOutput('pr', String(pr.number));
# Wipe the sticky lockfile-check comment to a "running" state as soon
# as the job is authorized, so the user sees their click was picked up
# before the ~minute of nix build work.
- name: Mark sticky as running
if: steps.resolve.outputs.pr != ''
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
number: ${{ steps.resolve.outputs.pr }}
message: |
### 🔄 Applying lockfile fix…
Triggered by @${{ github.actor }} — [workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}).
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
repository: ${{ steps.resolve.outputs.owner }}/${{ steps.resolve.outputs.repo }}
ref: ${{ steps.resolve.outputs.ref }}
token: ${{ secrets.GITHUB_TOKEN }}
fetch-depth: 0
- uses: ./.github/actions/nix-setup
with:
cachix-auth-token: ${{ secrets.CACHIX_AUTH_TOKEN }}
- name: Apply lockfile hashes
id: apply
run: nix run .#fix-lockfiles
- name: Commit & push
if: steps.apply.outputs.changed == 'true'
shell: bash
run: |
set -euo pipefail
git config user.name 'github-actions[bot]'
git config user.email '41898282+github-actions[bot]@users.noreply.github.com'
git add nix/lib.nix
git commit -m "fix(nix): refresh npm lockfile hashes"
git push
- name: Update sticky (applied)
if: steps.apply.outputs.changed == 'true' && steps.resolve.outputs.pr != ''
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
number: ${{ steps.resolve.outputs.pr }}
message: |
### ✅ Lockfile fix applied
Pushed a commit refreshing the npm lockfile hashes — [workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}).
- name: Update sticky (already current)
if: steps.apply.outputs.changed == 'false' && steps.resolve.outputs.pr != ''
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
number: ${{ steps.resolve.outputs.pr }}
message: |
### ✅ Lockfile hashes already current
Nothing to commit — [workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}).
- name: Update sticky (failed)
if: failure() && steps.resolve.outputs.pr != ''
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
number: ${{ steps.resolve.outputs.pr }}
message: |
### ❌ Lockfile fix failed
See the [workflow run](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}) for logs.
+105
View File
@@ -0,0 +1,105 @@
name: Nix
on:
push:
branches: [main]
pull_request:
permissions:
contents: read
pull-requests: write
concurrency:
group: nix-${{ github.ref }}
cancel-in-progress: true
jobs:
nix:
strategy:
matrix:
os: [ubuntu-latest, macos-latest]
runs-on: ${{ matrix.os }}
timeout-minutes: 30
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: ./.github/actions/nix-setup
with:
cachix-auth-token: ${{ secrets.CACHIX_AUTH_TOKEN }}
- name: Resolve head SHA
if: github.event_name == 'pull_request'
id: sha
shell: bash
run: |
FULL="${{ github.event.pull_request.head.sha || github.sha }}"
echo "full=$FULL" >> "$GITHUB_OUTPUT"
echo "short=${FULL:0:7}" >> "$GITHUB_OUTPUT"
- name: Check flake
id: flake
continue-on-error: true
run: nix flake check --print-build-logs
# When the flake check fails, run a targeted diagnostic to see if
# the failure is specifically a stale npm lockfile hash in one of the
# known npm subpackages (tui / web). This avoids surfacing a generic
# "build failed" message when the fix is a single known command.
- name: Diagnose npm lockfile hashes
id: hash_check
if: steps.flake.outcome == 'failure' && runner.os == 'Linux'
continue-on-error: true
env:
LINK_SHA: ${{ steps.sha.outputs.full }}
run: nix run .#fix-lockfiles -- --check
# If fix-lockfiles itself crashes (infrastructure blip, cache throttle,
# etc.) it won't set stale=true/false. Treat that as a distinct failure
# mode rather than silently ignoring it.
- name: Fail if hash check crashed without reporting
if: steps.hash_check.outcome == 'failure' && steps.hash_check.outputs.stale != 'true' && steps.hash_check.outputs.stale != 'false'
run: |
echo "::error::fix-lockfiles exited without reporting stale status — likely an infrastructure or script failure"
exit 1
- name: Post sticky PR comment (stale hashes)
if: steps.hash_check.outputs.stale == 'true' && github.event_name == 'pull_request'
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
message: |
### ⚠️ npm lockfile hash out of date
Checked against commit [`${{ steps.sha.outputs.short }}`](${{ github.server_url }}/${{ github.repository }}/commit/${{ steps.sha.outputs.full }}) (PR head at check time).
The `hash = "sha256-..."` line in these nix files no longer matches the committed `package-lock.json`:
${{ steps.hash_check.outputs.report }}
#### Apply the fix
- [ ] **Apply lockfile fix** — tick to push a commit with the correct hashes to this PR branch
- Or [run the Nix Lockfile Fix workflow](${{ github.server_url }}/${{ github.repository }}/actions/workflows/nix-lockfile-fix.yml) manually (pass PR `#${{ github.event.pull_request.number }}`)
- Or locally: `nix run .#fix-lockfiles` and commit the diff
# Clear the sticky comment when either the flake check passed outright (no
# hash check needed) or the hash check explicitly returned stale=false
# (check failed for a non-hash reason).
- name: Clear sticky PR comment (resolved)
if: |
github.event_name == 'pull_request' &&
(steps.hash_check.outputs.stale == 'false' ||
steps.flake.outcome == 'success')
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
delete: true
- name: Final fail if flake check failed
if: steps.flake.outcome == 'failure'
run: |
if [ "${{ steps.hash_check.outputs.stale }}" == "true" ]; then
echo "::error::Nix build failed due to stale npm lockfile hash. Run: nix run .#fix-lockfiles"
else
echo "::error::Nix flake check failed. See logs above."
fi
exit 1
+26 -85
View File
@@ -1,8 +1,8 @@
name: OSV-Scanner
# Scans lockfiles (uv.lock, package-lock.json) against the OSV vulnerability
# database. Runs on every PR/push (via the ci.yml orchestrator's workflow_call)
# and on a weekly schedule against main.
# database. Runs on every PR that touches a lockfile and on a weekly schedule
# against main.
#
# This is detection-only — OSV-Scanner does NOT open PRs or modify pins.
# It reports known CVEs in currently-pinned dependency versions so we can
@@ -10,21 +10,35 @@ name: OSV-Scanner
# (full SHA / exact version) is preserved; only the notification signal
# is added.
#
# Complements the supply-chain-audit.yml workflow (which scans for malicious
# code patterns in PR diffs) by covering the orthogonal "currently-pinned
# dep became known-vulnerable" case.
# Complements the existing supply-chain-audit.yml workflow (which scans
# for malicious code patterns in PR diffs) by covering the orthogonal
# "currently-pinned dep became known-vulnerable" case.
#
# Uses Google's officially-recommended reusable workflow, pinned by SHA.
# Findings land in the repo's Security tab (Code Scanning > OSV-Scanner).
# fail-on-vuln is disabled so the job does not block merges on pre-existing
# vulnerabilities in pinned deps that we may need to patch deliberately.
#
# The reusable workflow can't emit custom outputs, so a wrapper job
# downloads the SARIF result and summarizes the vulnerability count into
# a review_status for the unified PR comment.
on:
workflow_call:
pull_request:
branches: [main]
paths:
- 'uv.lock'
- 'pyproject.toml'
- 'package.json'
- 'package-lock.json'
- 'ui-tui/package.json'
- 'website/package.json'
- 'website/package-lock.json'
- '.github/workflows/osv-scanner.yml'
push:
branches: [main]
paths:
- 'uv.lock'
- 'pyproject.toml'
- 'package.json'
- 'package-lock.json'
- 'website/package-lock.json'
schedule:
# Weekly scan against main — catches CVEs published after merge for
# deps that haven't changed since.
@@ -32,7 +46,7 @@ on:
workflow_dispatch:
permissions:
# Required to upload SARIF file to CodeQL. See: https://github.com/github/codeql-action/issues/2117
# Required by the reusable workflow to upload SARIF to the Security tab.
actions: read
contents: read
security-events: write
@@ -40,7 +54,7 @@ permissions:
jobs:
scan:
name: Scan lockfiles
uses: google/osv-scanner-action/.github/workflows/osv-scanner-reusable.yml@9a498708959aeaef5ef730655706c5a1df1edbc2 # v2.3.8
uses: google/osv-scanner-action/.github/workflows/osv-scanner-reusable.yml@9a498708959aeaef5ef730655706c5a1df1edbc2 # v2.3.8
with:
# Scan explicit lockfiles rather than recursing, so we only look at
# the three sources of truth and skip vendored / test / worktree dirs.
@@ -49,76 +63,3 @@ jobs:
--lockfile=package-lock.json
--lockfile=website/package-lock.json
fail-on-vuln: false
emit-status:
name: Emit review status
runs-on: ubuntu-latest
needs: scan
if: always()
outputs:
review_status: ${{ steps.emit.outputs.review_status }}
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Download SARIF result
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
with:
name: osv-results
path: /tmp/osv-results
continue-on-error: true
- name: Emit review_status
id: emit
run: |
set -euo pipefail
STATUS="[]"
if [ -f /tmp/osv-results/osv-results.sarif ]; then
# Count vulnerabilities from the SARIF file
VULN_COUNT=$(python3 -c "
import json, sys
try:
with open('/tmp/osv-results/osv-results.sarif') as f:
data = json.load(f)
count = 0
vulns = []
for run in data.get('runs', []):
for result in run.get('results', []):
count += 1
rule_id = result.get('ruleId', 'unknown')
message = result.get('message', {}).get('text', '')
loc = result.get('locations', [{}])[0].get('physicalLocation', {}).get('artifactLocation', {}).get('uri', '')
vulns.append(f'- {rule_id} in {loc}: {message}')
print(count)
if vulns:
print('\n'.join(vulns[:20]), file=sys.stderr)
except Exception:
print(0)
")
VULN_DETAIL=""
if [ "$VULN_COUNT" -gt 0 ] 2>/dev/null; then
VULN_PLURAL=$([ "$VULN_COUNT" -eq 1 ] && echo "y" || echo "ies")
VULN_DETAIL=$(python3 -c "
import json, sys
try:
with open('/tmp/osv-results/osv-results.sarif') as f:
data = json.load(f)
vulns = []
for run in data.get('runs', []):
for result in run.get('results', []):
rule_id = result.get('ruleId', 'unknown')
loc = result.get('locations', [{}])[0].get('physicalLocation', {}).get('artifactLocation', {}).get('uri', '')
vulns.append(f'- {rule_id} in {loc}')
print(json.dumps('\n'.join(vulns[:20])))
except Exception:
print(json.dumps(''))
")
STATUS="[{\"source\":\"osv scan\",\"results\":[{\"kind\":\"warning\",\"title\":\"OSV vulnerability scan\",\"summary\":\"${VULN_COUNT} known vulnerabilit${VULN_PLURAL} found in pinned dependencies.\",\"detail\":${VULN_DETAIL},\"how_to_fix\":\"Review the findings in the [Security tab](../../security/code-scanning). Update the affected dependencies if a patched version is available.\"}]}]"
else
STATUS="[]"
fi
fi
echo "review_status=${STATUS}" >> "$GITHUB_OUTPUT"
-98
View File
@@ -1,98 +0,0 @@
name: Review labels
# Require explicit maintainer review when CI-sensitive files or the MCP
# catalog change. Previously this was split across two jobs in two
# workflows: ``ci-review`` in lint.yml (gated on ``ci_review``) and
# ``mcp-catalog-review`` in supply-chain-audit.yml (gated on
# ``mcp_catalog``). Both checked for their own label.
#
# Now consolidated: a single ``ci-reviewed`` label covers both. The
# comment sections tell the reviewer exactly what to verify per area,
# so one label is enough — the human reads the comment, not the label
# name.
#
# Outputs:
# ci_reviewed — "true" / "false" / "" (empty when neither lane ran)
# review_status — JSON array of status objects consumed by the review
# comment assembler. See scripts/ci/emit_review_status.py.
on:
workflow_call:
inputs:
ci_review:
description: Whether CI-sensitive files (eslint config, workflows, actions) changed.
type: boolean
default: false
mcp_catalog:
description: Whether the MCP catalog / installer changed.
type: boolean
default: false
supply_chain:
description: Whether the critical supply-chain scan found a risk requiring review.
type: boolean
default: false
outputs:
ci_reviewed:
description: Whether the ci-reviewed label is present. Empty when neither input was true.
value: ${{ jobs.check.outputs.ci_reviewed }}
review_status:
description: JSON array of status objects for the review comment assembler.
value: ${{ jobs.check.outputs.review_status }}
permissions:
contents: read
pull-requests: read # read PR labels
jobs:
check:
name: Review label gate
if: inputs.ci_review || inputs.mcp_catalog || inputs.supply_chain
runs-on: ubuntu-latest
timeout-minutes: 2
outputs:
ci_reviewed: ${{ steps.label-check.outputs.ci_reviewed }}
review_status: ${{ steps.build-status.outputs.review_status }}
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Check ci-reviewed label
id: label-check
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
REPO: ${{ github.repository }}
run: |
set -euo pipefail
PR="${{ github.event.pull_request.number }}"
LABELS=$(gh pr view "$PR" --repo "$REPO" --json labels --jq '.labels[].name' || true)
if echo "$LABELS" | grep -Fxq 'ci-reviewed'; then
echo "ci-reviewed label present."
echo "ci_reviewed=true" >> "$GITHUB_OUTPUT"
else
echo "ci-reviewed label missing."
echo "ci_reviewed=false" >> "$GITHUB_OUTPUT"
fi
- name: Build review_status JSON
id: build-status
env:
CI_REVIEW: ${{ inputs.ci_review }}
MCP_CATALOG: ${{ inputs.mcp_catalog }}
SUPPLY_CHAIN: ${{ inputs.supply_chain }}
LABEL_PRESENT: ${{ steps.label-check.outputs.ci_reviewed }}
run: |
set -euo pipefail
args=()
if [ "$CI_REVIEW" = "true" ]; then args+=(--ci-review); fi
if [ "$MCP_CATALOG" = "true" ]; then args+=(--mcp-catalog); fi
if [ "$SUPPLY_CHAIN" = "true" ]; then args+=(--supply-chain); fi
if [ "$LABEL_PRESENT" = "true" ]; then args+=(--label-present); fi
python3 scripts/ci/emit_review_status.py "${args[@]}" --output "$GITHUB_OUTPUT"
- name: Fail on missing label
if: steps.label-check.outputs.ci_reviewed != 'true'
run: |
echo "::error::CI-sensitive changes require the ci-reviewed label. Add the label and re-run this check."
exit 1
+2 -11
View File
@@ -20,7 +20,6 @@ jobs:
check-freshness:
if: github.repository == 'NousResearch/hermes-agent'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Probe live index
id: probe
@@ -29,7 +28,7 @@ jobs:
URL="https://hermes-agent.nousresearch.com/docs/api/skills-index.json"
echo "Probing $URL"
# -L follows redirects; -f fails on HTTP errors; -s suppresses progress
if ! curl -fsSL --retry 3 --retry-delay 10 -o /tmp/skills-index.json "$URL"; then
if ! curl -fsSL -o /tmp/skills-index.json "$URL"; then
echo "status=fetch-failed" >> "$GITHUB_OUTPUT"
echo "detail=Could not download $URL" >> "$GITHUB_OUTPUT"
exit 0
@@ -108,18 +107,10 @@ jobs:
echo "Summary: ${{ steps.probe.outputs.summary }}"
fi
- name: Get GitHub App token
if: steps.probe.outputs.status != 'ok'
id: app-token
uses: ./.github/actions/get-app-token
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- name: Open issue on degraded / failed probe
if: steps.probe.outputs.status != 'ok'
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
STATUS: ${{ steps.probe.outputs.status }}
DETAIL: ${{ steps.probe.outputs.detail }}
run: |
+13 -30
View File
@@ -3,50 +3,40 @@ name: Build Skills Index
on:
schedule:
# Run twice daily: 6 AM and 6 PM UTC
- cron: "0 6,18 * * *"
workflow_dispatch: # Manual trigger
- cron: '0 6,18 * * *'
workflow_dispatch: # Manual trigger
push:
branches: [main]
paths:
- "scripts/build_skills_index.py"
- ".github/workflows/skills-index.yml"
- 'scripts/build_skills_index.py'
- '.github/workflows/skills-index.yml'
permissions:
contents: read
actions: write # to trigger deploy-site.yml on schedule
actions: write # to trigger deploy-site.yml on schedule
jobs:
build-index:
# Only run on the upstream repository, not on forks
if: github.repository == 'NousResearch/hermes-agent'
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: "3.11"
python-version: '3.11'
- name: Install dependencies
uses: ./.github/actions/retry
with:
command: pip install httpx==0.28.1 pyyaml==6.0.2
run: pip install httpx==0.28.1 pyyaml==6.0.2
- name: Build skills index
env:
GITHUB_TOKEN: ${{ steps.app-token.outputs.token }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: python scripts/build_skills_index.py
- name: Upload index artifact
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4
with:
name: skills-index
path: website/static/api/skills-index.json
@@ -59,15 +49,8 @@ jobs:
needs: build-index
if: github.event_name == 'schedule' || github.event_name == 'workflow_dispatch'
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- name: Trigger Deploy Site workflow
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
run: gh workflow run deploy-site.yml --repo ${{ github.repository }} -f skills_index_run_id=${{ github.run_id }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: gh workflow run deploy-site.yml --repo ${{ github.repository }}
+110 -136
View File
@@ -1,5 +1,16 @@
name: Supply Chain Audit
on:
pull_request:
types: [opened, synchronize, reopened]
# No paths filter — the jobs must always run so required checks
# report a status (path-gated workflows leave checks "pending" forever
# when no matching files change, which blocks merge).
permissions:
pull-requests: write
contents: read
# Narrow, high-signal scanner. Only fires on critical indicators of supply
# chain attacks (e.g. the litellm-style payloads). Low-signal heuristics
# (plain base64, plain exec/eval, dependency/Dockerfile/workflow edits,
@@ -8,74 +19,57 @@ name: Supply Chain Audit
# the scanner. Keep this file's checks ruthlessly narrow: if you find
# yourself adding WARNING-tier patterns here again, make a separate
# advisory-only workflow instead.
#
# Path-gating is handled centrally by the ``ci.yml`` orchestrator's
# ``detect`` job. The orchestrator passes ``scan`` / ``deps`` booleans as
# inputs; this workflow's jobs gate on those inputs instead of re-computing
# the diff. MCP catalog review was previously here but has moved to
# ``review-labels.yml`` so it can be rerun independently.
#
# Outputs:
# review_status — JSON array of status objects consumed by the review
# comment assembler (scripts/ci/assemble_review_comment.py).
# critical_findings — "true" when the narrow critical-pattern scan found
# something. The review-label gate consumes this and
# owns the action-required result, so adding
# ``ci-reviewed`` can heal the run on rerun.
on:
workflow_call:
inputs:
event_name:
description: The event name from the calling orchestrator.
type: string
required: true
scan:
description: Whether supply-chain-relevant files changed.
type: boolean
required: true
deps:
description: Whether pyproject.toml changed.
type: boolean
required: true
outputs:
review_status:
description: JSON array of review status objects for the review comment assembler.
value: ${{ jobs.aggregate.outputs.review_status }}
critical_findings:
description: Whether the critical-pattern scan found a risk requiring maintainer review.
value: ${{ jobs.aggregate.outputs.critical_findings }}
permissions:
pull-requests: write
contents: read
jobs:
scan:
name: Scan PR for critical supply chain risks
if: inputs.scan
# ── Path filter (shared by both scan and dep-bounds) ───────────────
changes:
runs-on: ubuntu-latest
timeout-minutes: 15
outputs:
review_status: ${{ steps.emit-status.outputs.review_status }}
critical_findings: ${{ steps.scan.outputs.found }}
# True when any file the scanner cares about changed in this PR
scan: ${{ steps.filter.outputs.scan }}
# True when pyproject.toml changed in this PR
deps: ${{ steps.filter.outputs.deps }}
steps:
- name: Checkout
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
fetch-depth: 0
- name: Check for relevant file changes
id: filter
run: |
BASE="${{ github.event.pull_request.base.sha }}"
HEAD="${{ github.event.pull_request.head.sha }}"
SCAN_FILES=$(git diff --name-only "$BASE"..."$HEAD" -- \
'*.py' '**/*.py' '*.pth' '**/*.pth' \
'setup.py' 'setup.cfg' \
'sitecustomize.py' 'usercustomize.py' '__init__.pth' \
'pyproject.toml' || true)
if [ -n "$SCAN_FILES" ]; then
echo "scan=true" >> "$GITHUB_OUTPUT"
else
echo "scan=false" >> "$GITHUB_OUTPUT"
fi
DEPS_FILES=$(git diff --name-only "$BASE"..."$HEAD" -- 'pyproject.toml' || true)
if [ -n "$DEPS_FILES" ]; then
echo "deps=true" >> "$GITHUB_OUTPUT"
else
echo "deps=false" >> "$GITHUB_OUTPUT"
fi
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
scan:
name: Scan PR for critical supply chain risks
needs: changes
if: needs.changes.outputs.scan == 'true'
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
fetch-depth: 0
- name: Scan diff for critical patterns
id: scan
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
set -euo pipefail
@@ -83,7 +77,7 @@ jobs:
HEAD="${{ github.event.pull_request.head.sha }}"
# Added lines only, excluding lockfiles.
# Three-point diff (base...head) diffs from the merge base to HEAD,
# Three-dot diff (base...head) diffs from the merge base to HEAD,
# so only changes introduced by this PR are included — not changes
# that landed on main after the PR branched off.
DIFF=$(git diff "$BASE"..."$HEAD" -- . ':!uv.lock' ':!*.lock' ':!package-lock.json' ':!yarn.lock' || true)
@@ -107,7 +101,7 @@ jobs:
fi
# --- base64 decode + exec/eval on the same line (the litellm attack pattern) ---
B64_EXEC_HITS=$(echo "$DIFF" | grep -n '^+' | grep -iE 'base64\.(b64decode|decodebytes|urlsafe_b64decode)' | grep -iE 'exec\(|eval\(' | head -10 || true)
B64_EXEC_HITS=$(echo "$DIFF" | grep -n '^\+' | grep -iE 'base64\.(b64decode|decodebytes|urlsafe_b64decode)' | grep -iE 'exec\(|eval\(' | head -10 || true)
if [ -n "$B64_EXEC_HITS" ]; then
FINDINGS="${FINDINGS}
### 🚨 CRITICAL: base64 decode + exec/eval combo
@@ -121,7 +115,7 @@ jobs:
fi
# --- subprocess with encoded/obfuscated command argument ---
PROC_HITS=$(echo "$DIFF" | grep -n '^+' | grep -E 'subprocess\.(Popen|call|run)\s*\(' | grep -iE 'base64|\\x[0-9a-f]{2}|chr\(' | head -10 || true)
PROC_HITS=$(echo "$DIFF" | grep -n '^\+' | grep -E 'subprocess\.(Popen|call|run)\s*\(' | grep -iE 'base64|\\x[0-9a-f]{2}|chr\(' | head -10 || true)
if [ -n "$PROC_HITS" ]; then
FINDINGS="${FINDINGS}
### 🚨 CRITICAL: subprocess with encoded/obfuscated command
@@ -161,35 +155,49 @@ jobs:
echo "found=false" >> "$GITHUB_OUTPUT"
fi
- name: Emit review_status
id: emit-status
if: always()
- name: Post critical finding comment
if: steps.scan.outputs.found == 'true'
env:
FOUND: ${{ steps.scan.outputs.found }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
python3 - <<'PYEOF'
import json, os
BODY="## 🚨 CRITICAL Supply Chain Risk Detected
# The review-label gate renders and blocks critical findings. Keep
# this scan a fact-finder so adding ci-reviewed can rerun the gate
# without requiring the scanner itself to fail again.
status = []
This PR contains a pattern that has been used in real supply chain attacks. A maintainer must review the flagged code carefully before merging.
with open(os.environ["GITHUB_OUTPUT"], "a", encoding="utf-8") as f:
f.write(f"review_status={json.dumps(status)}\n")
PYEOF
$(cat /tmp/findings.md)
---
*Scanner only fires on high-signal indicators: .pth files, base64+exec/eval combos, subprocess with encoded commands, or install-hook files. Low-signal warnings were removed intentionally — if you're seeing this comment, the finding is worth inspecting.*"
gh pr comment "${{ github.event.pull_request.number }}" --body "$BODY" || echo "::warning::Could not post PR comment (expected for fork PRs — GITHUB_TOKEN is read-only)"
- name: Fail on critical findings
if: steps.scan.outputs.found == 'true'
run: |
echo "::error::CRITICAL supply chain risk patterns detected in this PR. See the PR comment for details."
exit 1
# Gate: reports success when scan was skipped (no relevant files changed).
# This ensures the required check always gets a status.
scan-gate:
name: Scan PR for critical supply chain risks
needs: changes
# always() so the gate still reports SUCCESS even if `changes` fails/is
# skipped — without it, a failed dependency would leave the required
# check unreported (i.e. "pending"), the exact failure mode this fixes.
if: always() && needs.changes.outputs.scan != 'true'
runs-on: ubuntu-latest
steps:
- run: echo "No supply-chain-relevant files changed, skipping scan."
dep-bounds:
name: Check PyPI dependency upper bounds
if: inputs.deps
needs: changes
if: needs.changes.outputs.deps == 'true'
runs-on: ubuntu-latest
timeout-minutes: 15
outputs:
review_status: ${{ steps.emit-status.outputs.review_status }}
steps:
- name: Checkout
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
fetch-depth: 0
@@ -209,7 +217,7 @@ jobs:
exit 0
fi
# Match PyPI dep specs that have >= and no < ceiling.
# Match PyPI dep specs that have >= but no < ceiling.
# Pattern: "package>=version" without a following ",<" bound.
# Excludes git+ URLs (which use commit SHAs) and comments.
UNBOUNDED=$(echo "$ADDED" | grep -oE '"[a-zA-Z0-9_-]+(\[[^\]]*\])?>=[ 0-9.]+"' | grep -v ',<' || true)
@@ -221,36 +229,26 @@ jobs:
echo "found=false" >> "$GITHUB_OUTPUT"
fi
- name: Emit review_status
id: emit-status
if: always()
- name: Post unbounded dep warning
if: steps.bounds.outputs.found == 'true'
env:
FOUND: ${{ steps.bounds.outputs.found }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
python3 - <<'PYEOF'
import json, os
BODY="## ⚠️ Unbounded PyPI Dependency Detected
found = os.environ.get("FOUND", "") == "true"
This PR adds PyPI dependencies without a \`<next_major\` upper bound. Per our [supply chain policy](../blob/main/CONTRIBUTING.md#dependency-pinning-policy-supply-chain-hardening), all PyPI deps must be pinned as \`>=floor,<next_major\`.
if found:
with open("/tmp/unbounded.txt", encoding="utf-8") as f:
detail = f.read()
status = [{
"source": "supply chain",
"results": [{
"kind": "action_required",
"title": "Unbounded PyPI dependencies",
"summary": "This PR adds PyPI dependencies without upper bounds.",
"detail": detail,
"how_to_fix": 'Add a `<next_major` upper bound, e.g. `"package>=1.2.0,<2"`. See CONTRIBUTING.md dependency pinning policy.'
}]
}]
else:
status = []
**Unbounded specs found:**
\`\`\`
$(cat /tmp/unbounded.txt)
\`\`\`
with open(os.environ["GITHUB_OUTPUT"], "a", encoding="utf-8") as f:
f.write(f"review_status={json.dumps(status)}\n")
PYEOF
**Fix:** Add an upper bound, e.g. \`\"package>=1.2.0,<2\"\`
---
*See PR #2810 and CONTRIBUTING.md for the full policy rationale.*"
gh pr comment "${{ github.event.pull_request.number }}" --body "$BODY" || echo "::warning::Could not post PR comment (expected for fork PRs)"
- name: Fail on unbounded deps
if: steps.bounds.outputs.found == 'true'
@@ -258,39 +256,15 @@ jobs:
echo "::error::PyPI dependencies without upper bounds detected. Add <next_major ceiling per CONTRIBUTING.md policy."
exit 1
aggregate:
name: Aggregate review statuses
needs: [scan, dep-bounds]
if: always()
# Gate: reports success when dep-bounds was skipped (no pyproject.toml changed).
# This ensures the required check always gets a status.
dep-bounds-gate:
name: Check PyPI dependency upper bounds
needs: changes
# always() so the gate still reports SUCCESS even if `changes` fails/is
# skipped — without it, a failed dependency would leave the required
# check unreported (i.e. "pending"), the exact failure mode this fixes.
if: always() && needs.changes.outputs.deps != 'true'
runs-on: ubuntu-latest
timeout-minutes: 15
outputs:
review_status: ${{ steps.merge.outputs.review_status }}
critical_findings: ${{ steps.merge.outputs.critical_findings }}
steps:
- name: Merge review statuses
id: merge
env:
SCAN_STATUS: ${{ needs.scan.outputs.review_status }}
DEP_STATUS: ${{ needs.dep-bounds.outputs.review_status }}
CRITICAL_FINDINGS: ${{ needs.scan.outputs.critical_findings }}
run: |
python3 - <<'PYEOF'
import json, os
merged = []
for key in ("SCAN_STATUS", "DEP_STATUS"):
raw = os.environ.get(key, "")
if not raw:
continue
try:
data = json.loads(raw)
except (json.JSONDecodeError, TypeError):
continue
if isinstance(data, list):
merged.extend(data)
with open(os.environ["GITHUB_OUTPUT"], "a", encoding="utf-8") as f:
f.write(f"review_status={json.dumps(merged)}\n")
f.write("critical_findings=" + os.environ.get("CRITICAL_FINDINGS", "false") + "\n")
PYEOF
- run: echo "No pyproject.toml changes, skipping dependency bounds check."
+57 -69
View File
@@ -1,61 +1,43 @@
name: Tests
on:
workflow_call:
inputs:
slice_count:
description: Number of parallel test slices
type: number
default: 8
push:
branches: [main]
paths-ignore:
- '**/*.md'
- 'docs/**'
pull_request:
branches: [main]
paths-ignore:
- '**/*.md'
- 'docs/**'
permissions:
contents: read
# Cancel in-progress runs for the same ref
# Cancel in-progress runs for the same PR/branch
concurrency:
group: tests-${{ github.ref }}
cancel-in-progress: true
jobs:
generate:
name: "Generate slices"
runs-on: ubuntu-latest
timeout-minutes: 10
outputs:
matrix: ${{ steps.matrix.outputs.matrix }}
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Restore duration cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: test_durations.json
key: test-durations
# Saves use test-durations-${run_id}, so the exact key above never
# matches — without this prefix fallback the cache ALWAYS missed,
# LPT slicing ran on no data, and unbalanced slices pushed heavy
# files toward the per-file timeout under load.
restore-keys: |
test-durations-
- name: Generate test slices
id: matrix
run: |
MATRIX=$(python3 scripts/run_tests_parallel.py --generate-slices ${{ inputs.slice_count }})
echo "matrix=$MATRIX" >> "$GITHUB_OUTPUT"
test:
name: Run tests slice ${{ matrix.slice.index }}/${{ inputs.slice_count }}
needs: generate
runs-on: ubuntu-latest
timeout-minutes: 30
strategy:
fail-fast: false
matrix: ${{ fromJSON(needs.generate.outputs.matrix) }}
matrix:
slice: [1, 2, 3, 4, 5, 6]
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Restore duration cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: test_durations.json
# Single stable key. main always overwrites, PRs always find it.
key: test-durations
- name: Install ripgrep (prebuilt binary)
run: |
@@ -63,7 +45,7 @@ jobs:
RG_VERSION=15.1.0
RG_SHA256=1c9297be4a084eea7ecaedf93eb03d058d6faae29bbc57ecdaf5063921491599
RG_TARBALL=ripgrep-${RG_VERSION}-x86_64-unknown-linux-musl.tar.gz
curl -sSfL --retry 3 --retry-delay 5 -o "$RG_TARBALL" \
curl -sSfL -o "$RG_TARBALL" \
"https://github.com/BurntSushi/ripgrep/releases/download/${RG_VERSION}/${RG_TARBALL}"
echo "${RG_SHA256} ${RG_TARBALL}" | sha256sum -c -
tar -xzf "$RG_TARBALL"
@@ -72,7 +54,7 @@ jobs:
rg --version
- name: Install uv
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5
with:
# Persist uv's download/wheel cache (~/.cache/uv) across runs.
# Keyed on the dependency manifests, so the cache is reused until
@@ -92,28 +74,40 @@ jobs:
# fails if the lock is out of sync with pyproject.toml), giving a
# reproducible env. It also creates .venv itself, so no separate
# `uv venv` step is needed.
uses: ./.github/actions/retry
with:
command: uv sync --locked --python 3.11 --extra all --extra dev
run: uv sync --locked --python 3.11 --extra all --extra dev
- name: Minimize uv cache
# Optimized for CI: prunes pre-built wheels that are cheap to
# re-download, keeping the persisted cache small and fast to restore.
run: uv cache prune --ci
- name: Run tests (slice ${{ matrix.slice.index }}/${{ inputs.slice_count }})
# Per-file isolation via scripts/run_tests.sh: each test file runs
# in its own freshly-spawned `python -m pytest <file>` subprocess
- name: Run tests (slice ${{ matrix.slice }}/6)
# Per-file isolation via scripts/run_tests_parallel.py: discovers
# every test_*.py file under tests/ (excluding integration/ + e2e/),
# then runs `python -m pytest <file>` in a freshly-spawned subprocess
# with bounded parallelism. No xdist, no shared workers, no
# module-level state leakage between files.
#
# File list is pre-computed by the generate job (--generate-slices)
# which runs LPT distribution once and passes the file list to each
# matrix job via --files. Previously each job re-discovered files and
# re-ran LPT independently — redundant N times.
# Why per-file (not per-test): per-test spawn cost (~250ms × 17k
# tests = 70min CPU minimum) blew the wall-clock budget. Per-file
# spawn (~250ms × ~850 files = ~3.5min) fits while still giving
# every file a fresh interpreter — the only isolation boundary
# that matters in practice (cross-file leakage was the original
# flake source; intra-file is the test author's responsibility).
#
# Why drop xdist entirely: xdist's persistent workers accumulate
# state across files, which is exactly the leakage we wanted to
# fix. ThreadPoolExecutor + subprocess.run is ~60 lines and does
# the job with cleaner semantics.
#
# Matrix slicing (--slice I/N): files are distributed across 6
# jobs by cached duration (LPT algorithm) so each job gets
# roughly equal wall time. Without a cache, files default to 2s
# estimate and get split roughly evenly by count — still correct,
# just not perfectly balanced.
run: |
source .venv/bin/activate
scripts/run_tests.sh --files '${{ matrix.slice.files }}'
python scripts/run_tests_parallel.py --slice ${{ matrix.slice }}/6
env:
# Ensure tests don't accidentally call real APIs
OPENROUTER_API_KEY: ""
@@ -121,12 +115,9 @@ jobs:
NOUS_API_KEY: ""
- name: Upload per-slice durations
# Advisory artifact (feeds slice balancing) — a transient artifact-
# service blip must not fail an otherwise-green test slice.
continue-on-error: true
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: test-durations-slice-${{ matrix.slice.index }}
name: test-durations-slice-${{ matrix.slice }}
path: test_durations.json
retention-days: 1
@@ -134,12 +125,11 @@ jobs:
# (including PRs) get balanced slicing.
save-durations:
needs: test
if: needs.test.result == 'success' && github.ref == 'refs/heads/main'
if: always() && github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Download all slice durations
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
with:
pattern: test-durations-slice-*
path: durations
@@ -159,17 +149,17 @@ jobs:
"
- name: Save merged duration cache
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: test_durations.json
key: test-durations-${{ github.run_id }}
key: test-durations
e2e:
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Install ripgrep (prebuilt binary)
run: |
@@ -177,7 +167,7 @@ jobs:
RG_VERSION=15.1.0
RG_SHA256=1c9297be4a084eea7ecaedf93eb03d058d6faae29bbc57ecdaf5063921491599
RG_TARBALL=ripgrep-${RG_VERSION}-x86_64-unknown-linux-musl.tar.gz
curl -sSfL --retry 3 --retry-delay 5 -o "$RG_TARBALL" \
curl -sSfL -o "$RG_TARBALL" \
"https://github.com/BurntSushi/ripgrep/releases/download/${RG_VERSION}/${RG_TARBALL}"
echo "${RG_SHA256} ${RG_TARBALL}" | sha256sum -c -
tar -xzf "$RG_TARBALL"
@@ -186,7 +176,7 @@ jobs:
rg --version
- name: Install uv
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5
with:
# Persist uv's download/wheel cache (~/.cache/uv) across runs.
# Keyed on the dependency manifests, so the cache is reused until
@@ -206,9 +196,7 @@ jobs:
# fails if the lock is out of sync with pyproject.toml), giving a
# reproducible env. It also creates .venv itself, so no separate
# `uv venv` step is needed.
uses: ./.github/actions/retry
with:
command: uv sync --locked --python 3.11 --extra all --extra dev
run: uv sync --locked --python 3.11 --extra all --extra dev
- name: Minimize uv cache
# Optimized for CI: prunes pre-built wheels that are cheap to
@@ -227,4 +215,4 @@ jobs:
env:
OPENROUTER_API_KEY: ""
OPENAI_API_KEY: ""
NOUS_API_KEY: ""
NOUS_API_KEY: ""
+25
View File
@@ -0,0 +1,25 @@
# .github/workflows/typecheck.yml
name: Typecheck
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
typecheck:
runs-on: ubuntu-latest
strategy:
matrix:
package:
[ui-tui, web, apps/bootstrap-installer, apps/desktop, apps/shared]
fail-fast: false # report all failures, not just the first one
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: 22
cache: npm
- run: npm ci
- run: npm run --prefix ${{ matrix.package }} typecheck
+20 -44
View File
@@ -5,11 +5,11 @@ name: Publish to PyPI
on:
push:
tags:
- "v20*" # CalVer tags: v2026.5.15, v2026.5.15.2, etc.
- 'v20*' # CalVer tags: v2026.5.15, v2026.5.15.2, etc.
workflow_dispatch:
inputs:
confirm_tag:
description: "Tag to publish (e.g. v2026.5.15). Must already exist."
description: 'Tag to publish (e.g. v2026.5.15). Must already exist.'
required: true
type: string
@@ -26,9 +26,8 @@ jobs:
build:
name: Build distribution 📦
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
# On workflow_dispatch, check out the confirmed tag.
@@ -44,37 +43,23 @@ jobs:
fi
- name: Set up Python
uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: "3.13"
python-version: '3.13'
- name: Install uv
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
- name: Set up Node.js
uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4
with:
node-version: "22"
node-version: '22'
- name: Build web dashboard
uses: ./.github/actions/retry
with:
command: npm ci
working-directory: web
- name: Compile web dashboard
run: npm run build
working-directory: web
run: cd web && npm ci && npm run build
- name: Build TUI bundle
uses: ./.github/actions/retry
with:
command: npm ci
working-directory: ui-tui
- name: Compile TUI bundle
run: npm run build
working-directory: ui-tui
run: cd ui-tui && npm ci && npm run build
- name: Bundle TUI into hermes_cli
run: |
@@ -96,7 +81,7 @@ jobs:
run: uv build --sdist --wheel
- name: Upload distribution artifacts
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4
with:
name: python-package-distributions
path: dist/
@@ -105,22 +90,21 @@ jobs:
name: Publish to PyPI
needs: build
runs-on: ubuntu-latest
timeout-minutes: 30
environment:
name: pypi
url: https://pypi.org/p/hermes-agent
permissions:
id-token: write # OIDC trusted publishing
id-token: write # OIDC trusted publishing
steps:
- name: Download distribution artifacts
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
with:
name: python-package-distributions
path: dist/
- name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b # v1.14.0
uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b # v1.14.0
with:
skip-existing: true
@@ -131,28 +115,20 @@ jobs:
if: startsWith(github.ref, 'refs/tags/')
needs: publish
runs-on: ubuntu-latest
timeout-minutes: 30
permissions:
contents: write # attach assets to the existing release
id-token: write # sigstore signing
contents: write # attach assets to the existing release
id-token: write # sigstore signing
steps:
- name: Download distribution artifacts
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4
with:
name: python-package-distributions
path: dist/
- name: Get GitHub App token
id: app-token
uses: ./.github/actions/get-app-token
with:
client-id: ${{ secrets.APP_CLIENT_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- name: Wait for GitHub Release to exist
env:
GITHUB_TOKEN: ${{ steps.app-token.outputs.token }}
GITHUB_TOKEN: ${{ github.token }}
# release.py creates the GitHub Release after pushing the tag,
# but this workflow starts from the tag push — wait for it.
run: |
@@ -169,7 +145,7 @@ jobs:
- name: Sign with Sigstore
if: env.skip_sign != 'true'
uses: sigstore/gh-action-sigstore-python@04cffa1d795717b140764e8b640de88853c92acc # v3.3.0
uses: sigstore/gh-action-sigstore-python@04cffa1d795717b140764e8b640de88853c92acc # v3.3.0
with:
inputs: >-
./dist/*.tar.gz
@@ -178,7 +154,7 @@ jobs:
- name: Attach signed artifacts to GitHub Release
if: env.skip_sign != 'true'
env:
GITHUB_TOKEN: ${{ steps.app-token.outputs.token }}
GITHUB_TOKEN: ${{ github.token }}
# release.py already created the GitHub Release — just upload
# the Sigstore signatures alongside the existing assets.
run: >-
+18 -31
View File
@@ -4,7 +4,7 @@ name: uv.lock check
# that modify pyproject.toml without regenerating uv.lock (or vice versa)
# must not merge, because the Docker build's `uv sync --frozen` step will
# fail on a stale lockfile and we'd rather catch it here than in the
# docker workflow on main.
# docker-publish workflow on main.
#
# ─────────────────────────────────────────────────────────────────────────
# IMPORTANT: this check runs against the MERGED state, not just your branch
@@ -44,32 +44,37 @@ name: uv.lock check
# the same way. Better to catch it here than after merge.
on:
workflow_call:
outputs:
review_status:
description: "JSON review status for the review-status aggregator"
value: ${{ jobs.check.outputs.review_status }}
push:
branches: [main]
paths:
- 'pyproject.toml'
- 'uv.lock'
- '.github/workflows/uv-lockfile-check.yml'
pull_request:
branches: [main]
paths:
- 'pyproject.toml'
- 'uv.lock'
- '.github/workflows/uv-lockfile-check.yml'
permissions:
contents: read
concurrency:
group: uv-lockfile-check-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
cancel-in-progress: ${{ github.event_name == 'pull_request' }}
jobs:
check:
name: uv lock --check
runs-on: ubuntu-latest
timeout-minutes: 5
outputs:
review_status: ${{ steps.verify.outputs.review_status }}
steps:
- name: Checkout code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
- name: Install uv
uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39 # 8.2.0
uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5
# `uv lock --check` re-resolves the project from pyproject.toml and
# compares the result to uv.lock, exiting non-zero if they disagree.
@@ -79,22 +84,8 @@ jobs:
# of this file) — failures often mean "your branch is behind main,
# rebase and regenerate uv.lock."
- name: Verify uv.lock is up-to-date
id: verify
run: |
# uv lock --check re-resolves against PyPI (network). Retry so a
# registry blip doesn't read as "lockfile stale". A genuinely stale
# lockfile fails all attempts (deterministic), costing only seconds.
ok=false
for i in 1 2 3; do
if uv lock --check; then
ok=true
break
fi
[ "$i" = 3 ] && break
echo "::warning::uv lock --check failed (attempt $i); retrying in 10s"
sleep 10
done
if [ "$ok" != true ]; then
if ! uv lock --check; then
cat <<'EOF' >> "$GITHUB_STEP_SUMMARY"
## ❌ uv.lock is out of sync with pyproject.toml
@@ -120,13 +111,9 @@ jobs:
This check is blocking because the Docker image build uses
`uv sync --frozen --extra all`, which rejects stale lockfiles
— catching it here avoids a ~15 min failed docker run
— catching it here avoids a ~15 min failed docker-publish run
on `main` post-merge.
EOF
echo "::error title=uv.lock out of sync::Run \`uv lock\` locally and commit the result. If on a PR, sync with main first."
review_status='[{"source":"uv.lock check","results":[{"kind":"action_required","title":"uv.lock out of sync","summary":"uv.lock is out of sync with pyproject.toml.","how_to_fix":"Run `uv lock` locally and commit the result. If on a PR, sync with main first:\n```\ngit fetch origin main\ngit rebase origin/main\nuv lock\ngit add uv.lock\ngit commit -m \"chore: refresh uv.lock\"\n```\n"}]}]'
echo "review_status=${review_status}" >> "$GITHUB_OUTPUT"
exit 1
fi
review_status='[]'
echo "review_status=${review_status}" >> "$GITHUB_OUTPUT"
+4 -39
View File
@@ -4,13 +4,9 @@
/_pycache/
*.pyc*
__pycache__/
act/
.act-sandbox-agent.*
.venv/
.venv
.vscode/
.env
.op.env
.env.local
.env.development.local
.env.test.local
@@ -23,6 +19,8 @@ act/
.notebooklm-playwright/
.pip-cache/
.uv-cache/
.tui-test/
tui-traces/
compose.hermes.local.yml
export*
__pycache__/model_tools.cpython-310.pyc
@@ -44,10 +42,7 @@ run_datagen_sonnet.sh
source-data/*
run_datagen_megascience_glm4-6.sh
data/*
# No trailing slash: also matches node_modules SYMLINKS (worktrees often
# symlink node_modules to the main checkout; the dir-only pattern let one
# slip into a commit and break `npm ci` on CI with ENOTDIR).
node_modules
node_modules/
browser-use/
agent-browser/
# Private keys
@@ -59,10 +54,6 @@ __pycache__/
hermes_agent.egg-info/
wandb/
testlogs
playwright-report/
test-results/
# Playwright visual regression baselines — cached from main in CI, not committed
*-snapshots/
# CLI config (may contain sensitive SSH paths)
cli-config.yaml
@@ -75,23 +66,10 @@ environments/benchmarks/evals/
# Web UI build output
hermes_cli/web_dist/
# Cross-process web UI build lock (flock target, always empty)
.web_ui_build.lock
apps/desktop/build/
apps/desktop/dist/
# tsc-emitted artifacts (a stray `tsc -b` compiles into src/, and vite then
# resolves the stale .js OVER the .tsx — never track these)
apps/desktop/src/**/*.js
apps/desktop/src/**/*.js.map
apps/desktop/src/**/*.d.ts
!apps/desktop/src/global.d.ts
!apps/desktop/src/vite-env.d.ts
apps/shared/src/**/*.js
apps/shared/src/**/*.js.map
apps/shared/src/**/*.d.ts
apps/desktop/release/
*.tsbuildinfo
apps/desktop/*.tsbuildinfo
# Web UI assets — synced from @nous-research/ui at build time via
# `npm run sync-assets` (see web/package.json).
@@ -141,9 +119,6 @@ docs/superpowers/*
# treat it as a local edit and autostash it on every run (#38529).
.hermes-bootstrap-complete
# Persistent dev sandbox dir (scripts/dev-sandbox.sh --persistent)
.hermes-sandbox/
# Interrupted-update breadcrumb + recovery lock written next to the shared venv
# by `hermes update` / launch-time self-heal. Runtime state, never a code change
# — ignore so `git status` stays clean and update's autostash skips them.
@@ -159,13 +134,3 @@ scripts/out/
# stores the published notes. They are not a build artifact and must never be
# committed to the repo root. See the hermes-release skill.
RELEASE_v*.md
# Desktop demo-run scratch output (hermes writes demo/*.txt during recorded
# walkthroughs). Throwaway artifacts, never part of the app.
apps/desktop/demo/
# PR infographics are rendered locally and embedded in PR descriptions via the
# image-provider (fal.media) URL — they are NEVER committed to the repo. The
# PR body is the archive. See the hermes-agent-dev skill's
# pr-infographic-workflow reference (storage rule + lapse #8 / #COMMIT-1).
infographic/
-4
View File
@@ -1,4 +0,0 @@
# Lockfiles must never be reformatted — main has a repo rule requiring
# team approval when lockfiles change, so an autofix PR touching one
# would hang waiting for review.
package-lock.json
+68 -133
View File
@@ -123,17 +123,6 @@ conservative at the waist.
without E2E proof, and plugins that touch core files.** Plugins live in their
own directory and work within the ABCs/hooks we provide; if a plugin needs
more, widen the generic plugin surface, don't special-case it in core.
- **Third-party products / other people's projects integrated into the core
tree.** Observability backends, vendor SaaS integrations, analytics dashboards,
and similar "someone else's product" plugins do NOT land under `plugins/` in
this repo. They place an ongoing maintenance burden on us to keep them working
against a fast-moving core, for a backend we don't own. Ship them as a
**standalone plugin repo** users install into `~/.hermes/plugins/` (or via a
pip entry point), and promote them in the Nous Research Discord
(`#plugins-skills-and-skins`). This is a coupling-and-maintenance decision, not
a quality bar — the plugin can be excellent and still be a close. PRs that add
such a directory to the tree are closed with a pointer to publish it as its own
repo.
### Before you call it a bug — verify the premise (and when NOT to close)
@@ -491,18 +480,18 @@ The dashboard embeds the real `hermes --tui` — **not** a rewrite. See `hermes
### Electron Desktop Chat App (`apps/desktop/`)
A **separate** chat surface from both the classic CLI and the dashboard's embedded TUI. It is an Electron + React + nanostore renderer (`@assistant-ui/react`) that talks to a `tui_gateway` backend over JSON-RPC (`requestGateway(method, params)`). The WebSocket/JSON-RPC transport lives in the framework-agnostic `apps/shared` package (`@hermes/shared``JsonRpcGatewayClient` + WS URL helpers), which the web dashboard (`web/`) also consumes; **desktop has no build/runtime dependency on the dashboard frontend** — it spawns a headless `hermes serve` backend server (the same gateway `dashboard` serves, minus the browser UI entirely: `serve` sets `headless_backend=True`, so `cmd_dashboard` skips `_build_web_ui` AND exports `HERMES_SERVE_HEADLESS=1` so `mount_spa()` disables the SPA even if a stray `web_dist/` exists — only the JSON-RPC/WS/API surface is reachable). `dashboard` and `serve` share `cmd_dashboard`/`start_server` but are independent surfaces — neither launches the other. The one exception is a backward-compat *fallback*: `serve` is newer, so the desktop spawn (`electron/backend-command.ts` + `backendSupportsServe()` in `electron/main.ts`) detects whether the resolved runtime registers `serve` and, only when it does not (an older managed install / PATH `hermes` the app hasn't updated yet), rewrites the argv to the legacy `dashboard --no-open`. Without that, a new app against an un-upgraded runtime would crash on an unknown subcommand and brick every mid-upgrade user. It does NOT embed `hermes --tui` — it has its own composer, transcript, and slash-command pipeline. For scoped Desktop architecture, state, resolver, transport, and testing rules, read `apps/desktop/AGENTS.md`.
A **separate** chat surface from both the classic CLI and the dashboard's embedded TUI. It is an Electron + React + nanostore renderer (`@assistant-ui/react`) that talks to a `tui_gateway` backend over JSON-RPC (`requestGateway(method, params)`). It does NOT embed `hermes --tui` — it has its own composer, transcript, and slash-command pipeline. Route desktop bugs to the `hermes-desktop-app-work` skill, not `hermes-dashboard-work`.
**Slash commands in the desktop app are curated client-side, then dispatched to the backend.** The pipeline:
- **Backend already provides everything.** `tui_gateway/server.py` `commands.catalog` (empty-query list) and `complete.slash` (typed-query completions) both include built-in commands, user `quick_commands`, AND skill-derived commands (`scan_skill_commands()` / `get_skill_commands()`). The desktop app does not need a new RPC to see skills.
- **The renderer curates via `apps/desktop/src/lib/desktop-slash-commands.ts`.** This is the load-bearing file. It holds `DESKTOP_COMMAND_SPECS` (the built-ins and their Desktop surfaces) plus `NO_DESKTOP_SURFACE` block-lists for terminal-only / messaging-only / picker-owned / settings-owned / advanced commands that should NOT clutter the desktop popover.
- **The renderer curates via `apps/desktop/src/lib/desktop-slash-commands.ts`.** This is the load-bearing file. It holds `DESKTOP_COMMANDS` (the ~19 built-ins shown in the palette) plus block-lists for terminal-only / messaging-only / picker-owned / settings-owned / advanced commands that should NOT clutter the desktop popover.
- `isDesktopSlashCommand(name)` — gates **execution**. Returns true for built-ins AND for any non-built-in (skill / quick command), so typed extension commands run.
- `isDesktopSlashSuggestion(name)` — gates **discovery/completion**. Used by BOTH completion paths in `app/chat/composer/hooks/use-slash-completions.ts` (empty-query catalog filter + typed-query `complete.slash` filter) and by `filterDesktopCommandsCatalog`.
- `isDesktopSlashExtensionCommand(name)` — true when the command is NOT a known Hermes built-in (i.e. a skill or user quick command). Both suggestion and catalog-filter paths allow extensions through so skill commands surface in the palette. (Added when fixing "skill commands missing from the desktop slash palette" — the curated allow-list was silently dropping every skill/quick command from completions even though they executed fine when typed.)
- **Dispatch** lives in `app/session/hooks/use-prompt-actions/slash.ts` (`runSlash`): built-ins that the desktop owns (`/skin`, `/help`, `/new`, …) are handled locally or via `commands.catalog`; everything else goes to `slash.exec`, falling back to `command.dispatch` (which the gateway resolves into skill / alias / exec directives). A skill command resolves to `{type: "skill", message}` and is submitted as a normal prompt.
- **Dispatch** lives in `app/session/hooks/use-prompt-actions.ts` (`runSlash`): built-ins that the desktop owns (`/skin`, `/help`, `/new`, …) are handled locally or via `commands.catalog`; everything else goes to `slash.exec`, falling back to `command.dispatch` (which the gateway resolves into skill / alias / exec directives). A skill command resolves to `{type: "skill", message}` and is submitted as a normal prompt.
**Rule:** the desktop slash palette's curation is about hiding noise (terminal-only / messaging-only built-ins), NOT about hiding user-activated extensions. Skill commands and `quick_commands` are extensions the backend surfaces — they belong in completions. If you tighten `desktop-slash-commands.ts`, keep `isDesktopSlashExtensionCommand` flowing into both the suggestion and catalog-filter paths. Tests: from `apps/desktop`, run `npx vitest run src/lib/desktop-slash-commands.test.ts` (workspace dependencies are installed at the repo root).
**Rule:** the desktop slash palette's curation is about hiding noise (terminal-only / messaging-only built-ins), NOT about hiding user-activated extensions. Skill commands and `quick_commands` are extensions the backend surfaces — they belong in completions. If you tighten `desktop-slash-commands.ts`, keep `isDesktopSlashExtensionCommand` flowing into both the suggestion and catalog-filter paths. Tests: `apps/desktop/src/lib/desktop-slash-commands.test.ts` (run via the repo-root `vitest`, since `apps/desktop` resolves deps from the root workspace install).
---
@@ -794,24 +783,6 @@ landing in this tree. PRs that add a new directory under
provider as its own repo. Existing in-tree providers stay; bug fixes
to them are welcome.
**No new third-party-product plugins in-tree (policy, June 2026):** the
same rule applies beyond memory providers. Plugins that integrate
someone else's product or project — observability/metrics backends,
vendor SaaS connectors, analytics dashboards, paid-service tie-ins —
must ship as **standalone plugin repos** that users install into
`~/.hermes/plugins/` (or via pip entry points). They register through
the existing plugin discovery path and use the ABCs/hooks/ctx surface
we expose; nothing special is needed in core. The reason is
maintenance load: every product we absorb into the tree becomes our
burden to keep working against a fast-moving core, for a backend we
don't own. Promote standalone plugins in the Nous Research Discord
(`#plugins-skills-and-skins`). PRs that add such a directory under
`plugins/` are closed with a pointer to publish it as its own repo —
this is a coupling decision, not a quality judgment. (The
`observability/`, `kanban/`, `disk-cleanup/`, etc. directories already
in the tree are existing precedent, not an invitation to add more
third-party-product plugins alongside them.)
### Model-provider plugins (`plugins/model-providers/<name>/`)
Every inference backend (openrouter, anthropic, gmi, deepseek, nvidia, …)
@@ -983,10 +954,9 @@ Enable/disable per platform via `hermes tools` (the curses UI) or the
## Delegation (`delegate_task`)
`tools/delegate_tool.py` spawns a subagent with an isolated
context + terminal session. By default the parent waits for the
child's summary before continuing its own loop. With `background=true`,
Hermes returns a delegation id immediately and the result re-enters the
conversation later through the async-delegation completion queue.
context + terminal session. Synchronous: the parent waits for the
child's summary before continuing its own loop — if the parent is
interrupted, the child is cancelled.
Two shapes:
@@ -998,8 +968,7 @@ Two shapes:
Roles:
- `role="leaf"` (default) — focused worker. Cannot call `delegate_task`,
`clarify`, `memory`, `send_message`, `cronjob`. Retains `execute_code`
(programmatic tool calling).
`clarify`, `memory`, `send_message`, `execute_code`.
- `role="orchestrator"` — retains `delegate_task` so it can spawn its
own workers. Gated by `delegation.orchestrator_enabled` (default true)
and bounded by `delegation.max_spawn_depth` (default 2).
@@ -1009,9 +978,9 @@ Key config knobs (under `delegation:` in `config.yaml`):
`orchestrator_enabled`, `subagent_auto_approve`, `inherit_mcp_toolsets`,
`max_iterations`.
Durability rule: background `delegate_task` is detached from the current
turn but still process-local. For work that must survive process restart, use
`cronjob` or `terminal(background=True, notify_on_complete=True)` instead.
Synchronicity rule: delegate_task is **not** durable. For long-running
work that must outlive the current turn, use `cronjob` or
`terminal(background=True, notify_on_complete=True)` instead.
---
@@ -1095,16 +1064,14 @@ kanban task.
- **CLI:** `hermes_cli/kanban.py` wires `hermes kanban` with verbs
`init`, `create`, `list` (alias `ls`), `show`, `assign`, `link`,
`unlink`, `comment`, `attach`, `attachments`, `attach-rm`, `complete`,
`block`, `unblock`, `archive`, `tail`, plus less-commonly-used `watch`,
`stats`, `runs`, `log`, `assignees`, `heartbeat`, `notify-*`,
`dispatch`, `daemon`, `gc`.
`unlink`, `comment`, `complete`, `block`, `unblock`, `archive`,
`tail`, plus less-commonly-used `watch`, `stats`, `runs`, `log`,
`assignees`, `heartbeat`, `notify-*`, `dispatch`, `daemon`, `gc`.
- **Worker/orchestrator toolset:** `tools/kanban_tools.py` exposes
`kanban_show`, `kanban_complete`, `kanban_block`, `kanban_heartbeat`,
`kanban_comment`, `kanban_create`, `kanban_link`, `kanban_attach`,
`kanban_attach_url`, `kanban_attachments`; profiles that explicitly
enable the `kanban` toolset outside a dispatcher-spawned task also get
`kanban_list` and `kanban_unblock` for board routing.
`kanban_comment`, `kanban_create`, `kanban_link`; profiles that
explicitly enable the `kanban` toolset outside a dispatcher-spawned
task also get `kanban_list` and `kanban_unblock` for board routing.
- **Dispatcher:** long-lived loop that (default every 60s) reclaims
stale claims, promotes ready tasks, atomically claims, and spawns
assigned profiles. Runs **inside the gateway** by default via
@@ -1207,7 +1174,7 @@ automatically scope to the active profile.
a unique credential (bot token, API key), call `acquire_scoped_lock()` from
`gateway.status` in the `connect()`/`start()` method and `release_scoped_lock()` in
`disconnect()`/`stop()`. This prevents two profiles from using the same credential.
See `plugins/platforms/irc/adapter.py` for the canonical pattern.
See `gateway/platforms/telegram.py` for the canonical pattern.
6. **Profile operations are HOME-anchored, not HERMES_HOME-anchored** — `_get_profiles_root()`
returns `Path.home() / ".hermes" / "profiles"`, NOT `get_hermes_home() / "profiles"`.
@@ -1281,7 +1248,6 @@ def profile_env(tmp_path, monkeypatch):
## Testing
### Python
**ALWAYS use `scripts/run_tests.sh`** — do not call `pytest` directly. The script enforces
hermetic environment parity with CI (unset credential vars, TZ=UTC, LANG=C.UTF-8,
`-n auto` xdist workers, in-tree subprocess-isolation plugin). Direct `pytest`
@@ -1293,41 +1259,65 @@ scripts/run_tests.sh # full suite, CI-parity
scripts/run_tests.sh tests/gateway/ # one directory
scripts/run_tests.sh tests/agent/test_foo.py::test_x # one test
scripts/run_tests.sh -v --tb=long # pass-through pytest flags
scripts/run_tests.sh --no-isolate tests/foo/ # disable subprocess isolation (faster, for debugging)
```
**Flake policy:** the runner auto-retries a failing test FILE once in a fresh
subprocess (`--file-retries`, default 1; `HERMES_TEST_FILE_RETRIES=0` to
disable). Pass-on-retry counts as green but is printed in a `⚠ FLAKY` summary
section with both attempts' output. A FLAKY report is a bug to fix, not noise
to ignore — timing-sensitive tests must not assume a quiet runner (loose
wall-clock bounds ≥ 2s, event-based sync, no `assert not _wait_until(...)`
negative-timing races).
### Subprocess-per-test isolation
#### Subprocess-per-test-file isolation
Every test runs in a freshly-spawned Python subprocess via the in-tree plugin
at `tests/_isolate_plugin.py`. This means module-level dicts/sets and
ContextVars from one test cannot leak into the next — the historic
`_reset_module_state` autouse fixture is gone.
Every test file runs in a freshly-spawned Python subprocess via `run_tests_parallel.py`. This means module-level dicts/sets and
ContextVars from one test file cannot leak into the next.
Implementation notes:
#### Why the wrapper
- The plugin uses `multiprocessing.get_context("spawn")`, which works on
Linux, macOS, and Windows alike (POSIX `fork` is not used).
- Per-test overhead is ~0.51.0s (Python startup + pytest collection). xdist
parallelism amortizes this across cores; on a 20-core box the full suite
finishes in roughly the same wall time as before, but flake-free.
- `isolate_timeout` (configured in `pyproject.toml`) caps each test at 30s.
Hangs are killed and surfaced as a failure report.
- Pass `--no-isolate` to disable isolation — useful when debugging a single
test interactively, or when you specifically want to verify state leakage.
- The plugin disables itself in child processes (sentinel envvar
`HERMES_ISOLATE_CHILD=1`), so there's no fork-bomb risk.
| | Without wrapper | With wrapper |
| ------------------- | ------------------------------------------- | ----------------------------------------- |
| Provider API keys | Whatever is in your env (auto-detects pool) | All env vars except a specific few unset. |
| HOME / `~/.hermes/` | Your real config+auth.json | Temp dir per test |
| Timezone | Local TZ (PDT etc.) | UTC |
| Locale | Whatever is set | C.UTF-8 |
### Why the wrapper (and why the old "just call pytest" doesn't work)
### Where to place what tests
Five real sources of local-vs-CI drift the script closes:
The CI change classifier (`scripts/ci/classify_changes.py`) runs specific jobs based on what files changed. A Python test that asserts
about the contents of `package.json`, `package-lock.json`, `.ts`/`.tsx`
source, or any other JS-side artifact will not run on a PR that only touches
those files. This means a regression can go green on a PR and red on `main` (where the
classifier fails open and runs everything).
| | Without wrapper | With wrapper |
|---|---|---|
| Provider API keys | Whatever is in your env (auto-detects pool) | All `*_API_KEY`/`*_TOKEN`/etc. unset |
| HOME / `~/.hermes/` | Your real config+auth.json | Temp dir per test |
| Timezone | Local TZ (PDT etc.) | UTC |
| Locale | Whatever is set | C.UTF-8 |
| xdist workers | `-n auto` = all cores | `-n auto` (safe — subprocess isolation prevents cross-worker flakes) |
Any test that reads or asserts about `package.json`,
`package-lock.json`, `tsconfig.json`, `.ts`/`.tsx`/`.js`/`.mjs`/`.cjs`
source files configuration belongs in the JS (vitest) test suite, not in `tests/*.py`.
`tests/conftest.py` also enforces points 1-4 as an autouse fixture so ANY pytest
invocation (including IDE integrations) gets hermetic behavior — but the wrapper
is belt-and-suspenders.
### Running without the wrapper (only if you must)
If you can't use the wrapper (e.g. inside an IDE that shells pytest directly),
at minimum activate the venv. The isolation plugin loads automatically from
`addopts` in `pyproject.toml`, so you get the same per-test process isolation
either way.
```bash
source .venv/bin/activate # or: source venv/bin/activate
python -m pytest tests/ -q
```
If you need to bypass isolation for fast feedback while debugging:
```bash
python -m pytest tests/agent/test_foo.py -q --no-isolate
```
Always run the full suite before pushing changes.
### Don't write change-detector tests
@@ -1377,58 +1367,3 @@ not the specific names.
Reviewers should reject new change-detector tests; authors should convert
them into invariants before re-requesting review.
### Never read source code in tests
A test that reads a source file's text is testing *the shape of the
source code*, not its behavior. This is a hard antipattern, banned outright.
Any test that reads a .py, .ts, .tsx, etc., file is suspect.
**Why it's actively harmful, not just weak:**
- It passes when the implementation is subtly broken (the regex matches a
call site that exists but is wired wrong) and fails when a correct
refactor changes formatting, variable names, or control flow with
identical runtime behavior. Both directions of failure are wrong.
- It can't be run against a built/bundled/minified artifact, so it silently
stops testing anything the moment code moves, gets renamed, or a
dependency reformats it.
- It actively blocks refactors: reviewers see "keeps a pattern intact" tests
fail during pure structural cleanup with no behavior change, and either
hand-wave the failure (dangerous) or waste time updating regexes that add
nothing (waste).
- It gives false confidence. a green suite full of source-regex tests
looks like coverage but has never once executed the code path it claims
to guard.
**Do not write:**
```ts
const source = fs.readFileSync(path.join(__dirname, 'main.ts'), 'utf8')
test('backend spawn hides the Windows console', () => {
assert.match(source, /spawn\(\s*backend\.command,\s*backend\.args[\s\S]{0,300}hiddenWindowsChildOptions/)
})
```
**Do write — extract the logic into a small pure/DI-testable function and
call it for real:**
```ts
// backend-spawn.ts
export function hiddenWindowsChildOptions(options: SpawnOptionsLike = {}, isWindows = process.platform === 'win32') {
if (!isWindows || 'windowsHide' in options) return options
return { ...options, windowsHide: true }
}
// backend-spawn.test.ts
test('windowsHide defaults to true on Windows, is left alone elsewhere', () => {
assert.equal(hiddenWindowsChildOptions({}, true).windowsHide, true)
assert.equal(hiddenWindowsChildOptions({}, false).windowsHide, undefined)
assert.equal(hiddenWindowsChildOptions({ windowsHide: false }, true).windowsHide, false)
})
```
If the logic lives inline in a god-file (`main.ts`, `cli.py`,
`gateway/run.py`) and extracting it feels disruptive: that's the actual
signal to do the extraction, not to regex around it.
-602
View File
@@ -1,602 +0,0 @@
# Contribuir a Hermes Agent
¡Gracias por contribuir a Hermes Agent! Esta guía cubre todo lo que necesitas: configurar tu entorno de desarrollo, entender la arquitectura, decidir qué construir y conseguir que tu PR sea aceptado.
---
## Prioridades de Contribución
Valoramos las contribuciones en este orden:
1. **Correcciones de errores** — bloqueos, comportamiento incorrecto, pérdida de datos. Siempre la máxima prioridad.
2. **Compatibilidad entre plataformas** — macOS, diferentes distribuciones de Linux y WSL2 en Windows. Queremos que Hermes funcione en todas partes.
3. **Fortalecimiento de seguridad** — inyección de shell, inyección de prompts, traversal de rutas, escalada de privilegios. Ver [Consideraciones de Seguridad](#consideraciones-de-seguridad).
4. **Rendimiento y robustez** — lógica de reintento, manejo de errores, degradación elegante.
5. **Nuevas habilidades** — pero solo las ampliamente útiles. Ver [¿Debería ser una Habilidad o una Herramienta?](#debería-ser-una-habilidad-o-una-herramienta)
6. **Nuevas herramientas** — raramente necesarias. La mayoría de las capacidades deberían ser habilidades. Ver más abajo.
7. **Documentación** — correcciones, aclaraciones, nuevos ejemplos.
---
## ¿Debería ser una Habilidad o una Herramienta?
Esta es la pregunta más común para los nuevos colaboradores. La respuesta casi siempre es **habilidad**.
### Hazlo una Habilidad cuando:
- La capacidad se puede expresar como instrucciones + comandos de shell + herramientas existentes
- Envuelve una CLI externa o API que el agente puede llamar a través de `terminal` o `web_extract`
- No necesita integración personalizada de Python ni gestión de claves API integrada en el agente
- Ejemplos: búsqueda en arXiv, flujos de trabajo de git, gestión de Docker, procesamiento de PDF, email a través de herramientas CLI
### Hazlo una Herramienta cuando:
- Requiere integración de extremo a extremo con claves API, flujos de autenticación o configuración de múltiples componentes gestionada por el harness del agente
- Necesita lógica de procesamiento personalizada que debe ejecutarse con precisión en cada ocasión (no "mejor esfuerzo" de la interpretación del LLM)
- Maneja datos binarios, streaming o eventos en tiempo real que no pueden pasar por el terminal
- Ejemplos: automatización de navegador (gestión de sesiones Browserbase), TTS (codificación de audio + entrega en plataforma), análisis de visión (manejo de imágenes base64)
### ¿Debería la Habilidad estar incluida?
Las habilidades incluidas (en `skills/`) se envían con cada instalación de Hermes. Deben ser **ampliamente útiles para la mayoría de los usuarios**:
- Manejo de documentos, investigación web, flujos de trabajo de desarrollo comunes, administración de sistemas
- Usadas regularmente por una amplia gama de personas
Si tu habilidad es oficial y útil pero no universalmente necesaria (ej., una integración de servicio de pago, una dependencia pesada), ponla en **`optional-skills/`** — se envía con el repositorio pero no está activada por defecto. Los usuarios pueden descubrirla a través de `hermes skills browse` (etiquetada como "oficial") e instalarla con `hermes skills install` (sin advertencia de terceros, confianza integrada).
Si tu habilidad es especializada, contribuida por la comunidad o de nicho, es mejor para un **Skills Hub** — súbela a un registro de habilidades y compártela en el [Discord de Nous Research](https://discord.gg/NousResearch). Los usuarios pueden instalarla con `hermes skills install`.
---
## Proveedores de Memoria: Publicar como Plugin Independiente
**Ya no aceptamos nuevos proveedores de memoria en este repositorio.** El conjunto de proveedores integrados en `plugins/memory/` (honcho, mem0, supermemory, byterover, hindsight, holographic, openviking, retaindb) está cerrado. Si quieres añadir un nuevo backend de memoria, publícalo como un **repositorio de plugin independiente** que los usuarios instalen en `~/.hermes/plugins/` (o a través de un entry point de pip).
Los plugins de memoria independientes:
- Implementan el mismo ABC `MemoryProvider` (`agent/memory_provider.py`) — `sync_turn`, `prefetch`, `shutdown` y opcionalmente `post_setup(hermes_home, config)` para integración con el asistente de configuración
- Usan el mismo sistema de descubrimiento — `discover_memory_providers()` los recoge desde directorios de plugins de usuario/proyecto y entry points de pip
- Se integran con `hermes memory setup` a través de `post_setup()` — sin necesidad de tocar el código base
- Pueden registrar sus propios subcomandos CLI a través de `register_cli(subparser)` en un archivo `cli.py`
- Obtienen todos los mismos hooks de ciclo de vida y plomería de configuración que los proveedores incluidos en el árbol
Los PRs que añadan un nuevo directorio bajo `plugins/memory/` serán cerrados con un puntero para publicar el proveedor como su propio repositorio. Los proveedores en árbol existentes se mantienen; las correcciones de errores para ellos son bienvenidas.
Esto no es una barra de calidad — es una decisión de acoplamiento y mantenimiento. Los proveedores de memoria son el tipo de plugin más común y no deberían vivir todos en este árbol.
---
## Configuración del Desarrollo
### Prerequisitos
| Requisito | Notas |
|-----------|-------|
| **Git** | Con la extensión `git-lfs` instalada |
| **Python 3.113.13** | uv lo instalará si falta |
| **uv** | Gestor de paquetes Python rápido ([instalar](https://docs.astral.sh/uv/)) |
| **Node.js 20+** | Opcional — necesario para herramientas de navegador y puente WhatsApp (coincide con los engines de `package.json` raíz) |
### Clonar e instalar
```bash
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
# Crear venv con Python 3.11
uv venv venv --python 3.11
export VIRTUAL_ENV="$(pwd)/venv"
# Instalar con todos los extras (mensajería, cron, menús CLI, herramientas de desarrollo)
uv pip install -e ".[all,dev]"
# Opcional: herramientas de navegador
npm install
```
### Configurar para desarrollo
```bash
mkdir -p ~/.hermes/{cron,sessions,logs,memories,skills}
cp cli-config.yaml.example ~/.hermes/config.yaml
touch ~/.hermes/.env
# Añadir al menos una clave de proveedor LLM:
echo "OPENROUTER_API_KEY=***" >> ~/.hermes/.env
```
### Ejecutar
```bash
# Enlace simbólico para acceso global
mkdir -p ~/.local/bin
ln -sf "$(pwd)/venv/bin/hermes" ~/.local/bin/hermes
# Verificar
hermes doctor
hermes chat -q "Hola"
```
### Ejecutar tests
```bash
# Preferido — coincide con CI (entorno hermético, 4 workers xdist); ver AGENTS.md
scripts/run_tests.sh
# Alternativa (activa el venv primero). El wrapper sigue recomendándose
# para paridad con GitHub Actions antes de abrir un PR:
pytest tests/ -v
```
---
## Estructura del Proyecto
```
hermes-agent/
├── run_agent.py # Clase AIAgent — bucle de conversación central, despacho de herramientas, persistencia de sesión
├── cli.py # Clase HermesCLI — TUI interactiva, integración prompt_toolkit
├── model_tools.py # Orquestación de herramientas (capa delgada sobre tools/registry.py)
├── toolsets.py # Agrupaciones y presets de herramientas (hermes-cli, hermes-telegram, etc.)
├── hermes_state.py # Base de datos de sesiones SQLite con búsqueda de texto completo FTS5, títulos de sesión
├── batch_runner.py # Procesamiento en lote paralelo para generación de trayectorias
├── agent/ # Internos del agente (módulos extraídos)
│ ├── prompt_builder.py # Ensamblaje del prompt del sistema (identidad, habilidades, archivos de contexto, memoria)
│ ├── context_compressor.py # Auto-resumición al acercarse a los límites de contexto
│ ├── auxiliary_client.py # Resuelve clientes OpenAI auxiliares (resumición, visión)
│ ├── display.py # KawaiiSpinner, formateo del progreso de herramientas
│ ├── model_metadata.py # Longitudes de contexto del modelo, estimación de tokens
│ └── trajectory.py # Ayudantes para guardar trayectorias
├── hermes_cli/ # Implementaciones de comandos CLI
│ ├── main.py # Punto de entrada, análisis de argumentos, despacho de comandos
│ ├── config.py # Gestión de configuración, migración, definiciones de variables de entorno
│ ├── setup.py # Asistente de configuración interactivo
│ ├── auth.py # Resolución de proveedor, OAuth, Nous Portal
│ ├── models.py # Listas de selección de modelos de OpenRouter
│ ├── banner.py # Banner de bienvenida, arte ASCII
│ ├── commands.py # Registro central de comandos de barra (CommandDef), autocompletado, ayudantes del gateway
│ ├── callbacks.py # Callbacks interactivos (aclarar, sudo, aprobación)
│ ├── doctor.py # Diagnósticos
│ ├── skills_hub.py # CLI del Skills Hub + comando de barra /skills
│ └── skin_engine.py # Motor de skins/temas — personalización visual de CLI basada en datos
├── tools/ # Implementaciones de herramientas (auto-registradas)
│ ├── registry.py # Registro central de herramientas (esquemas, manejadores, despacho)
│ ├── approval.py # Detección de comandos peligrosos + aprobación por sesión
│ ├── terminal_tool.py # Orquestación del terminal (sudo, ciclo de vida del entorno, backends)
│ ├── file_operations.py # read_file, write_file, búsqueda, patch, etc.
│ ├── web_tools.py # web_search, web_extract (Paralelo/Firecrawl + resumición Gemini)
│ ├── vision_tools.py # Análisis de imágenes a través de modelos multimodales
│ ├── delegate_tool.py # Lanzamiento de subagentes y ejecución paralela de tareas
│ ├── code_execution_tool.py # Python sandboxado con acceso a herramientas vía RPC
│ ├── session_search_tool.py # Búsqueda en conversaciones pasadas con FTS5 + ventanas ancladas
│ ├── cronjob_tools.py # Gestión de tareas programadas
│ ├── skill_tools.py # Búsqueda, carga y gestión de habilidades
│ └── environments/ # Backends de ejecución del terminal
│ ├── base.py # ABC BaseEnvironment
│ ├── local.py, docker.py, ssh.py, singularity.py, modal.py, daytona.py
├── gateway/ # Gateway de mensajería
│ ├── run.py # GatewayRunner — ciclo de vida de plataformas, enrutamiento de mensajes, cron
│ ├── config.py # Resolución de configuración de plataformas
│ ├── session.py # Almacén de sesiones, prompts de contexto, políticas de reset
│ └── platforms/ # Adaptadores de plataformas
│ ├── telegram.py, discord_adapter.py, slack.py, whatsapp.py
├── scripts/ # Scripts del instalador y puente
│ ├── install.sh # Instalador Linux/macOS
│ ├── install.ps1 # Instalador Windows PowerShell
│ └── whatsapp-bridge/ # Puente WhatsApp Node.js (Baileys)
├── skills/ # Habilidades incluidas (copiadas a ~/.hermes/skills/ en la instalación)
├── optional-skills/ # Habilidades opcionales oficiales (descubribles vía hub, no activadas por defecto)
├── tests/ # Suite de tests
├── website/ # Sitio de documentación (hermes-agent.nousresearch.com)
├── cli-config.yaml.example # Configuración de ejemplo (copiada a ~/.hermes/config.yaml)
└── AGENTS.md # Guía de desarrollo para asistentes de codificación IA
```
### Configuración del usuario (almacenada en `~/.hermes/`)
| Ruta | Propósito |
|------|-----------|
| `~/.hermes/config.yaml` | Configuración (modelo, terminal, toolsets, compresión, etc.) |
| `~/.hermes/.env` | Claves API y secretos |
| `~/.hermes/auth.json` | Credenciales OAuth (Nous Portal) |
| `~/.hermes/skills/` | Todas las habilidades activas (incluidas + instaladas desde hub + creadas por el agente) |
| `~/.hermes/memories/` | Memoria persistente (MEMORY.md, USER.md) |
| `~/.hermes/state.db` | Base de datos de sesiones SQLite |
| `~/.hermes/sessions/` | Índice de enrutamiento del gateway (`sessions.json`), migas de pan de solicitudes, transcripciones `*.jsonl` del gateway y (opcionalmente) snapshots JSON por sesión cuando `sessions.write_json_snapshots: true` está configurado. Los snapshots por sesión están desactivados por defecto; state.db es canónica. |
| `~/.hermes/cron/` | Datos de trabajos programados |
| `~/.hermes/whatsapp/session/` | Credenciales del puente WhatsApp |
---
## Descripción General de la Arquitectura
### Bucle Central
```
Mensaje del usuario → AIAgent._run_agent_loop()
├── Construir prompt del sistema (prompt_builder.py)
├── Construir kwargs de API (modelo, mensajes, herramientas, configuración de razonamiento)
├── Llamar al LLM (API compatible con OpenAI)
├── Si tool_calls en la respuesta:
│ ├── Ejecutar cada herramienta a través del despacho del registro
│ ├── Añadir resultados de herramientas a la conversación
│ └── Volver a la llamada al LLM
├── Si respuesta de texto:
│ ├── Persistir sesión en DB
│ └── Devolver final_response
└── Compresión de contexto si se acerca al límite de tokens
```
### Patrones de Diseño Clave
- **Herramientas auto-registradas**: Cada archivo de herramienta llama a `registry.register()` en el momento de importación. `model_tools.py` activa el descubrimiento importando todos los módulos de herramientas.
- **Agrupación en toolsets**: Las herramientas se agrupan en toolsets (`web`, `terminal`, `file`, `browser`, etc.) que pueden habilitarse/deshabilitarse por plataforma.
- **Persistencia de sesión**: Todas las conversaciones se almacenan en SQLite (`hermes_state.py`) con búsqueda de texto completo y títulos de sesión únicos.
- **Inyección efímera**: Los prompts del sistema y los mensajes de relleno se inyectan en el momento de la llamada API, nunca se persisten en la base de datos ni en los logs.
- **Abstracción de proveedor**: El agente funciona con cualquier API compatible con OpenAI. La resolución del proveedor ocurre en el momento de la inicialización.
- **Enrutamiento de proveedor**: Al usar OpenRouter, `provider_routing` en config.yaml controla la selección del proveedor.
---
## Estilo de Código
- **PEP 8** con excepciones prácticas (no imponemos longitud de línea estricta)
- **Comentarios**: Solo cuando se explica la intención no obvia, compromisos o peculiaridades de API. No narres lo que hace el código
- **Manejo de errores**: Captura excepciones específicas. Registra con `logger.warning()`/`logger.error()` — usa `exc_info=True` para errores inesperados
- **Multiplataforma**: Nunca asumas Unix. Ver [Compatibilidad Multiplataforma](#compatibilidad-multiplataforma)
---
## Añadir una Nueva Herramienta
Antes de escribir una herramienta, pregúntate: [¿debería ser una habilidad en su lugar?](#debería-ser-una-habilidad-o-una-herramienta)
Las herramientas se auto-registran en el registro central. Cada archivo de herramienta co-localiza su esquema, manejador y registro:
```python
"""my_tool — Breve descripción de lo que hace esta herramienta."""
import json
from tools.registry import registry
def my_tool(param1: str, param2: int = 10, **kwargs) -> str:
"""Manejador. Devuelve un resultado en cadena (a menudo JSON)."""
result = do_work(param1, param2)
return json.dumps(result)
MY_TOOL_SCHEMA = {
"type": "function",
"function": {
"name": "my_tool",
"description": "Qué hace esta herramienta y cuándo debería usarla el agente.",
"parameters": {
"type": "object",
"properties": {
"param1": {"type": "string", "description": "Qué es param1"},
"param2": {"type": "integer", "description": "Qué es param2", "default": 10},
},
"required": ["param1"],
},
},
}
def _check_requirements() -> bool:
"""Devuelve True si las dependencias de esta herramienta están disponibles."""
return True
registry.register(
name="my_tool",
toolset="my_toolset",
schema=MY_TOOL_SCHEMA,
handler=lambda args, **kw: my_tool(**args, **kw),
check_fn=_check_requirements,
)
```
**Conectar a un toolset (requerido):** Las herramientas integradas se auto-descubren: cualquier
archivo `tools/*.py` que contenga una llamada de nivel superior `registry.register(...)` es
importado por `discover_builtin_tools()` en `tools/registry.py` cuando `model_tools`
se carga. **No** hay una lista de importaciones manual en `model_tools.py` que mantener.
Todavía debes añadir el nombre de la herramienta a la lista apropiada en `toolsets.py`
(por ejemplo `_HERMES_CORE_TOOLS` o un toolset dedicado); de lo contrario la herramienta
se registra pero nunca se expone al agente.
Consulta `AGENTS.md` (sección **Adding New Tools**) para rutas conscientes del perfil y
orientación sobre plugins vs. núcleo.
---
## Añadir una Habilidad
Las habilidades incluidas viven en `skills/` organizadas por categoría. Las habilidades opcionales oficiales usan la misma estructura en `optional-skills/`:
```
skills/
├── research/
│ └── arxiv/
│ ├── SKILL.md # Requerido: instrucciones principales
│ └── scripts/ # Opcional: scripts auxiliares
│ └── search_arxiv.py
├── productivity/
│ └── ocr-and-documents/
│ ├── SKILL.md
│ ├── scripts/
│ └── references/
└── ...
```
### Formato de SKILL.md
```markdown
---
name: my-skill
description: Breve descripción (mostrada en los resultados de búsqueda de habilidades)
version: 1.0.0
author: Tu Nombre
license: MIT
platforms: [macos, linux] # Opcional — restringir a plataformas de SO específicas
required_environment_variables: # Opcional — metadatos de configuración segura al cargar
- name: MY_API_KEY
prompt: Clave API
help: Dónde obtenerla
required_for: funcionalidad completa
prerequisites: # Requisitos de tiempo de ejecución heredados opcionales
env_vars: [MY_API_KEY]
commands: [curl, jq]
metadata:
hermes:
tags: [Categoría, Subcategoría, Palabras clave]
related_skills: [other-skill-name]
fallback_for_toolsets: [web]
requires_toolsets: [terminal]
---
# Título de la Habilidad
Introducción breve.
## Cuándo Usar
Condiciones de activación — ¿cuándo debería el agente cargar esta habilidad?
## Referencia Rápida
Tabla de comandos o llamadas API comunes.
## Procedimiento
Instrucciones paso a paso que el agente sigue.
## Problemas Conocidos
Modos de fallo conocidos y cómo manejarlos.
## Verificación
Cómo confirma el agente que funcionó.
```
### Estándares de autoría de habilidades (OBLIGATORIOS)
Todo skill nuevo o modernizado — incluido, opcional o contribuido — debe cumplir estos estándares antes del merge:
1. **`description` ≤ 60 caracteres, una oración, termina con punto.** Las descripciones largas saturan la UI de listado de habilidades. Indica la capacidad, no la implementación. Sin palabras de marketing ("potente", "completo", "fluido", "avanzado").
2. **Las herramientas referenciadas en el cuerpo de SKILL.md deben ser herramientas nativas de Hermes o servidores MCP que la habilidad espere explícitamente.** Usa los nombres de herramientas en comillas invertidas: `` `terminal` ``, `` `web_extract` ``, `` `web_search` ``, `` `read_file` ``, `` `write_file` ``, etc.
3. **El campo `platforms:` auditado contra las importaciones reales del script.** Las habilidades que usen primitivos solo de POSIX deben declarar sus plataformas soportadas.
4. **`author` da crédito primero al colaborador humano.**
5. **El cuerpo de SKILL.md usa el orden moderno de secciones:** título, intro de 2-3 oraciones, luego: `## Cuándo Usar`, `## Prerequisitos`, `## Cómo Ejecutar`, `## Referencia Rápida`, `## Procedimiento`, `## Problemas Conocidos`, `## Verificación`.
6. **Los scripts van en `scripts/`, las referencias en `references/`, las plantillas en `templates/`.**
7. **Los tests viven en `tests/skills/test_<skill>_skill.py`** y usan solo stdlib + pytest + `unittest.mock`. Sin llamadas de red en vivo.
8. **Las adiciones a `.env.example` están aisladas en un bloque claramente delimitado.**
---
## Añadir una Skin / Tema
Hermes usa un sistema de skins basado en datos — no se necesitan cambios de código para añadir una nueva skin.
**Opción A: Skin de usuario (archivo YAML)**
Crea `~/.hermes/skins/<nombre>.yaml`:
```yaml
name: mitema
description: Breve descripción del tema
colors:
banner_border: "#HEX"
banner_title: "#HEX"
banner_accent: "#HEX"
banner_dim: "#HEX"
banner_text: "#HEX"
response_border: "#HEX"
spinner:
waiting_faces: ["(⚔)", "(⛨)"]
thinking_faces: ["(⚔)", "(⌁)"]
thinking_verbs: ["forjando", "planeando"]
branding:
agent_name: "Mi Agente"
welcome: "Mensaje de bienvenida"
response_label: " ⚔ Agente "
prompt_symbol: "⚔"
tool_prefix: "╎"
```
Todos los campos son opcionales — los valores faltantes se heredan de la skin predeterminada.
**Opción B: Skin integrada**
Añade al dict `_BUILTIN_SKINS` en `hermes_cli/skin_engine.py`. Usa el mismo esquema que arriba pero como dict de Python.
**Activar:**
- CLI: `/skin mitema` o establece `display.skin: mitema` en config.yaml
---
## Compatibilidad Multiplataforma
Hermes se ejecuta en Linux, macOS y Windows nativo (además de WSL2). Al escribir código
que toca el SO, asume que *cualquier* plataforma puede alcanzar tu ruta de código.
> **Antes de hacer PR:** ejecuta `scripts/check-windows-footguns.py` para detectar
> los patrones inseguros comunes de Windows en tu diff. Es basado en grep y barato;
> CI también lo ejecuta en cada PR.
### Reglas críticas
1. **Nunca llames `os.kill(pid, 0)` para comprobaciones de liveness.** En Windows **NO es una operación sin efecto**. Usa `psutil.pid_exists(pid)` en su lugar.
2. **Usa `shutil.which()` antes de hacer shell — no asumas que Windows tiene las herramientas que tiene Linux.** `ps`, `kill`, `grep`, `awk`, etc. simplemente no existen en Windows.
3. **`termios` y `fcntl` son solo de Unix.** Siempre captura tanto `ImportError` como `NotImplementedError`.
4. **Codificación de archivos.** Windows puede guardar archivos `.env` en `cp1252`. Siempre maneja errores de codificación.
5. **Gestión de procesos.** `os.setsid()`, `os.killpg()`, `os.fork()`, `os.getuid()` y el manejo de señales POSIX difieren en Windows.
6. **Señales que no existen en Windows:** `SIGALRM`, `SIGCHLD`, `SIGHUP`, `SIGUSR1`, `SIGUSR2`, etc.
7. **Separadores de ruta.** Usa `pathlib.Path` en lugar de concatenación de cadenas con `/`.
8. **Los enlaces simbólicos necesitan privilegios elevados en Windows** (a menos que el Modo Desarrollador esté activado).
9. **Los modos de archivo POSIX (0o600, 0o644, etc.) NO se aplican en NTFS** por defecto.
10. **Los daemons de fondo desacoplados en Windows necesitan `pythonw.exe`, NO `python.exe`.**
---
## Consideraciones de Seguridad
Hermes tiene acceso al terminal. La seguridad importa.
### Protecciones existentes
| Capa | Implementación |
|------|---------------|
| **Piping de contraseña sudo** | Usa `shlex.quote()` para prevenir inyección de shell |
| **Detección de comandos peligrosos** | Patrones regex en `tools/approval.py` con flujo de aprobación del usuario |
| **Inyección de prompts en cron** | Escáner en `tools/cronjob_tools.py` bloquea patrones de anulación de instrucciones |
| **Lista de denegación de escritura** | Rutas protegidas resueltas a través de `os.path.realpath()` para prevenir bypass de enlaces simbólicos |
| **Skills Guard** | Escáner de seguridad para habilidades instaladas desde el hub (`tools/skills_guard.py`) |
| **Sandbox de ejecución de código** | El proceso hijo `execute_code` se ejecuta con claves API eliminadas del entorno |
| **Fortalecimiento de contenedor** | Docker: todas las capacidades eliminadas, sin escalada de privilegios, límites de PID, tmpfs de tamaño limitado |
### Al contribuir código sensible a la seguridad
- **Siempre usa `shlex.quote()`** al interpolar entrada del usuario en comandos de shell
- **Resuelve enlaces simbólicos** con `os.path.realpath()` antes de comprobaciones de control de acceso basadas en rutas
- **No registres secretos.** Las claves API, tokens y contraseñas nunca deben aparecer en la salida de log
- **Captura excepciones amplias** alrededor de la ejecución de herramientas para que un solo fallo no bloquee el bucle del agente
- **Prueba en todas las plataformas** si tu cambio toca rutas de archivos, gestión de procesos o comandos de shell
### Política de fijación de dependencias (fortalecimiento de la cadena de suministro)
Tras el [compromiso de la cadena de suministro de litellm](https://github.com/BerriAI/litellm/issues/24512) en marzo de 2026 y la [campaña del gusano Mini Shai-Hulud](https://socket.dev/blog/tanstack-npm-packages-compromised-mini-shai-hulud-supply-chain-attack) en mayo de 2026, todas las dependencias deben seguir estas reglas:
| Tipo de fuente | Tratamiento requerido | Justificación |
|---|---|---|
| **Paquete PyPI** | `>=suelo,<siguiente_mayor` | Las versiones de PyPI son inmutables una vez publicadas, pero pueden empujarse nuevas versiones en tu rango. |
| **URL de Git** | SHA completo del commit | Las ramas y etiquetas son refs mutables; el SHA está direccionado por contenido. |
| **GitHub Actions** | SHA completo del commit + comentario de versión | Las etiquetas de acción son refs mutables. Fija como `uses: owner/action@<sha> # vX.Y.Z` |
| **Instalaciones pip solo de CI** | `==exacto` | Builds de CI herméticos; el cambio es aceptable. |
**Cada nueva dependencia de PyPI en un PR debe tener un límite superior `<siguiente_mayor`.** Los PRs que añadan especificaciones `>=X.Y.Z` sin límite superior serán rechazados.
---
## Proceso de Pull Request
### Nomenclatura de ramas
```
fix/descripcion # Correcciones de errores
feat/descripcion # Nuevas funcionalidades
docs/descripcion # Documentación
test/descripcion # Tests
refactor/descripcion # Reestructuración de código
```
### Antes de enviar
1. **Ejecutar tests**: `scripts/run_tests.sh` (recomendado; igual que CI) o `pytest tests/ -v` con el venv del proyecto activado
2. **Probar manualmente**: Ejecuta `hermes` y ejercita la ruta de código que cambiaste
3. **Verificar impacto multiplataforma**: Si tocas E/S de archivos, gestión de procesos o manejo del terminal, considera macOS, Linux y WSL2
4. **Mantén los PRs enfocados**: Un cambio lógico por PR. No mezcles una corrección de error con una refactorización con una nueva funcionalidad.
### Descripción del PR
Incluye:
- **Qué** cambió y **por qué**
- **Cómo probarlo** (pasos de reproducción para errores, ejemplos de uso para funcionalidades)
- **Qué plataformas** probaste
- Referencia cualquier issue relacionado
### Mensajes de commit
Usamos [Conventional Commits](https://www.conventionalcommits.org/):
```
<tipo>(<alcance>): <descripción>
```
| Tipo | Usar para |
|------|-----------|
| `fix` | Correcciones de errores |
| `feat` | Nuevas funcionalidades |
| `docs` | Documentación |
| `test` | Tests |
| `refactor` | Reestructuración de código (sin cambio de comportamiento) |
| `chore` | Build, CI, actualizaciones de dependencias |
Alcances: `cli`, `gateway`, `tools`, `skills`, `agent`, `install`, `whatsapp`, `security`, etc.
Ejemplos:
```
fix(cli): prevenir bloqueo en save_config_value cuando el modelo es una cadena
feat(gateway): añadir aislamiento de sesión multi-usuario de WhatsApp
fix(security): prevenir inyección de shell en el piping de contraseña sudo
test(tools): añadir tests unitarios para file_operations
```
---
## Reportar Issues
- Usa [GitHub Issues](https://github.com/NousResearch/hermes-agent/issues)
- Incluye: SO, versión de Python, versión de Hermes (`hermes version`), traza de error completa
- Incluye pasos para reproducir
- Verifica los issues existentes antes de crear duplicados
- Para vulnerabilidades de seguridad, por favor reporta de forma privada
---
## Comunidad
- **Discord**: [discord.gg/NousResearch](https://discord.gg/NousResearch) — para preguntas, mostrar proyectos y compartir habilidades
- **GitHub Discussions**: Para propuestas de diseño y discusiones de arquitectura
- **Skills Hub**: Sube habilidades especializadas a un registro y compártelas con la comunidad
---
## Licencia
Al contribuir, aceptas que tus contribuciones serán licenciadas bajo la [Licencia MIT](LICENSE).
+10 -96
View File
@@ -18,24 +18,6 @@ We value contributions in this order:
---
## Before You Start: Search First
A quick search before you build saves your time and keeps the PR queue clean — duplicates are common here, so it's worth a minute up front.
- **Search both open *and* merged PRs and issues** for your topic or error symptom — the duplicate-check in the PR template fires at review time, after you've already done the work:
```bash
gh search issues --repo NousResearch/hermes-agent "<your terms>"
gh search prs --repo NousResearch/hermes-agent --state all "<your terms>"
```
Or use the web UI: [issues](https://github.com/NousResearch/hermes-agent/issues?q=) · [PRs (all states)](https://github.com/NousResearch/hermes-agent/pulls?q=is%3Apr).
- **The issue tracker can lag the code.** Many requested features are already implemented in-tree, so also search the source (`search_files`, or your editor's grep) for the capability before proposing it.
- **If an open PR already addresses it**, consider reviewing or improving that one instead of opening a competing duplicate.
- **For larger work**, comment on the issue to signal you're working on it, so others don't start the same thing.
Related: #38284 covers the agent-side analog — Hermes itself checking existing issues and PRs before deep self-troubleshooting. This section is the human-contributor complement.
---
## Should it be a Skill or a Tool?
This is the most common question for new contributors. The answer is almost always **skill**.
@@ -85,23 +67,6 @@ This isn't a quality bar — it's a coupling-and-maintenance decision. Memory pr
---
## Third-Party Product Integrations: Ship as a Standalone Plugin
The same rule extends to **any plugin that integrates someone else's product or project** — observability/metrics backends, vendor SaaS connectors, analytics dashboards, paid-service tie-ins, and similar third-party integrations. **These do not land in this repo.**
The reason is maintenance load, not quality. Every external product absorbed into the core tree becomes ours to keep working against a fast-moving codebase, for a backend we don't own and can't control. Hermes ships a lot and the core moves quickly; coupling third-party products into it creates an open-ended burden on the maintainers.
Publish these as a **standalone plugin repo** instead:
- Implement the relevant ABC and use the existing plugin discovery path (`~/.hermes/plugins/`, project `.hermes/plugins/`, or a pip entry point) — see [Build a Hermes Plugin](https://hermes-agent.nousresearch.com/docs/guides/build-a-hermes-plugin)
- Register lifecycle hooks (`pre_tool_call`, `post_tool_call`, `pre_llm_call`, `post_llm_call`, `on_session_start`, `on_session_end`), tools (`ctx.register_tool`), and CLI subcommands (`ctx.register_cli_command`) through the surface we already expose — no core changes needed
- If your plugin needs a capability the framework doesn't expose, that's a feature request to **widen the generic plugin surface** (a new hook or `ctx` method) — never special-case your plugin in core
- Promote it in the [Nous Research Discord](https://discord.gg/NousResearch) `#plugins-skills-and-skins` channel so users can find and install it
A well-built third-party-product plugin can clear automated review and still be closed for this reason — it's a placement decision, not a verdict on the code. PRs that add such a directory under `plugins/` will be closed with a pointer to publish it as its own repo.
---
## Development Setup
### Prerequisites
@@ -109,60 +74,19 @@ A well-built third-party-product plugin can clear automated review and still be
| Requirement | Notes |
|-------------|-------|
| **Git** | With the `git-lfs` extension installed |
| **Python 3.113.13** | uv will install it if missing |
| **Python 3.11+** | uv will install it if missing |
| **uv** | Fast Python package manager ([install](https://docs.astral.sh/uv/)) |
| **Node.js 20+** | Optional — needed for browser tools and WhatsApp bridge (matches root `package.json` engines) |
### Install with the standard installer
For most contributors, the best development bootstrap is the same path users
take: run the standard installer, then work inside the repository it cloned.
The installer creates the Hermes venv, wires the `hermes` command, stamps the
install method for `hermes update`, and clones the full git project into
`$HERMES_HOME/hermes-agent` (usually `~/.hermes/hermes-agent`). That keeps your
development environment on the same layout the CLI, updater, lazy dependency
installer, gateway, and docs assume.
```bash
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
cd "${HERMES_HOME:-$HOME/.hermes}/hermes-agent"
# Add dev/test extras on top of the standard install.
uv pip install -e ".[all,dev]"
# Optional: browser tools / docs site dependencies.
npm install
```
After that, create branches and run tests from that checkout:
```bash
git checkout -b fix/description
scripts/run_tests.sh
```
### Manual clone fallback
Use this only if you intentionally do not want Hermes' managed install layout
(for example, a throwaway clone inside a container or CI job). If you install
this way, make sure you run the `hermes` entrypoint from this venv; running the
system `python3 -m hermes_cli.main` can pick up unrelated system Python
packages.
Create the venv **outside** the cloned source tree. A venv that lives inside
the directory the agent operates from can be wiped by a relative-path command
the agent runs against its own checkout (`rm -rf venv`, `uv venv venv`, etc.),
which silently destroys the running runtime mid-session. Keeping it outside the
tree means no relative path from the workspace resolves to it.
### Clone and install
```bash
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
# Create venv with Python 3.11, OUTSIDE the source tree
uv venv ~/.hermes/venvs/hermes-dev --python 3.11
export VIRTUAL_ENV="$HOME/.hermes/venvs/hermes-dev"
export PATH="$VIRTUAL_ENV/bin:$PATH"
# Create venv with Python 3.11
uv venv venv --python 3.11
export VIRTUAL_ENV="$(pwd)/venv"
# Install with all extras (messaging, cron, CLI menus, dev tools)
uv pip install -e ".[all,dev]"
@@ -185,17 +109,13 @@ echo "OPENROUTER_API_KEY=***" >> ~/.hermes/.env
### Run
```bash
# The standard installer already put `hermes` on PATH.
hermes doctor
hermes chat -q "Hello"
```
If you used the manual clone fallback, run `./hermes` from the checkout or
symlink this clone's venv explicitly:
```bash
# Symlink for global access
mkdir -p ~/.local/bin
ln -sf "$(pwd)/venv/bin/hermes" ~/.local/bin/hermes
# Verify
hermes doctor
hermes chat -q "Hello"
```
### Run tests
@@ -454,12 +374,6 @@ Brief intro.
## When to Use
Trigger conditions — when should the agent load this skill?
## Prerequisites
Env vars, install steps, MCP setup, API key sourcing.
## How to Run
Canonical invocation through the `terminal` tool.
## Quick Reference
Table of common commands or API calls.
+56 -82
View File
@@ -9,11 +9,8 @@ FROM ghcr.io/astral-sh/uv:0.11.6-python3.13-trixie@sha256:b3c543b6c4f23a5f2df228
FROM node:22-bookworm-slim@sha256:7af03b14a13c8cdd38e45058fd957bf00a72bbe17feac43b1c15a689c029c732 AS node_source
FROM debian:13.4
# Disable Python stdout buffering to ensure logs are printed immediately.
# Do not write .pyc files at runtime: /opt/hermes is immutable in the
# published container and writable state belongs under /opt/data.
# Disable Python stdout buffering to ensure logs are printed immediately
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1
# Store Playwright browsers outside the volume mount so the build-time
# install survives the /opt/data volume overlay at runtime.
@@ -26,8 +23,8 @@ ENV PLAYWRIGHT_BROWSERS_PATH=/opt/hermes/.playwright
# replaces tini with s6-overlay's /init (PID 1 = s6-svscan), which reaps
# zombies non-blockingly on SIGCHLD and additionally supervises the main
# hermes process, the dashboard, and per-profile gateways.
RUN apt-get -o Acquire::Retries=3 update && \
apt-get -o Acquire::Retries=3 install -y --no-install-recommends \
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates curl iputils-ping python3 python-is-python3 ripgrep ffmpeg gcc g++ make cmake python3-dev python3-venv libffi-dev libolm-dev procps git openssh-client docker-cli xz-utils && \
rm -rf /var/lib/apt/lists/*
@@ -40,30 +37,33 @@ RUN apt-get -o Acquire::Retries=3 update && \
# we map between them inline. The noarch + symlinks tarballs are
# architecture-independent and reused as-is.
#
# We use `curl` instead of `ADD` for ALL three tarballs: `ADD` evaluates its
# URL at parse time (no ARG / TARGETARCH substitution) and — critically for
# CI reliability — cannot retry, so a single GitHub-release CDN blip fails
# the whole 15-45 min build. curl -fsSL --retry 3 self-heals those blips,
# and every tarball is still checksum-verified below before extraction.
# We use `curl` instead of `ADD` for the per-arch tarball because `ADD`
# evaluates its URL at parse time, before any ARG / TARGETARCH substitution
# — splitting one URL per arch into two ADDs would download both on every
# build and leave dead bytes in the cache. A single curl + arch-keyed URL
# is simpler and cache-friendlier.
#
# Supply-chain integrity: every tarball is checksum-verified against the
# upstream-published SHA256. To bump S6_OVERLAY_VERSION, fetch the four
# `.sha256` files from the corresponding release and update the ARGs. The
# checksum lookup happens during build, so a compromised release artifact
# fails the build loudly instead of silently producing a tampered image.
ARG TARGETARCH
ARG S6_OVERLAY_VERSION=3.2.3.0
ARG S6_OVERLAY_NOARCH_SHA256=b720f9d9340efc8bb07528b9743813c836e4b02f8693d90241f047998b4c53cf
ARG S6_OVERLAY_X86_64_SHA256=a93f02882c6ed46b21e7adb5c0add86154f01236c93cd82c7d682722e8840563
ARG S6_OVERLAY_AARCH64_SHA256=0952056ff913482163cc30e35b2e944b507ba1025d78f5becbb89367bf344581
ARG S6_OVERLAY_SYMLINKS_SHA256=a60dc5235de3ecbcf874b9c1f18d73263ab99b289b9329aa950e8729c4789f0e
ADD https://github.com/just-containers/s6-overlay/releases/download/v${S6_OVERLAY_VERSION}/s6-overlay-noarch.tar.xz /tmp/
ADD https://github.com/just-containers/s6-overlay/releases/download/v${S6_OVERLAY_VERSION}/s6-overlay-symlinks-noarch.tar.xz /tmp/
RUN set -eu; \
case "${TARGETARCH:-amd64}" in \
amd64) s6_arch="x86_64"; s6_arch_sha="${S6_OVERLAY_X86_64_SHA256}" ;; \
arm64) s6_arch="aarch64"; s6_arch_sha="${S6_OVERLAY_AARCH64_SHA256}" ;; \
*) echo "Unsupported TARGETARCH=${TARGETARCH} for s6-overlay" >&2; exit 1 ;; \
esac; \
base="https://github.com/just-containers/s6-overlay/releases/download/v${S6_OVERLAY_VERSION}"; \
curl -fsSL --retry 3 -o /tmp/s6-overlay-noarch.tar.xz \
"${base}/s6-overlay-noarch.tar.xz"; \
curl -fsSL --retry 3 -o /tmp/s6-overlay-symlinks-noarch.tar.xz \
"${base}/s6-overlay-symlinks-noarch.tar.xz"; \
curl -fsSL --retry 3 -o /tmp/s6-overlay-arch.tar.xz \
"${base}/s6-overlay-${s6_arch}.tar.xz"; \
"https://github.com/just-containers/s6-overlay/releases/download/v${S6_OVERLAY_VERSION}/s6-overlay-${s6_arch}.tar.xz"; \
{ \
printf '%s %s\n' "${S6_OVERLAY_NOARCH_SHA256}" /tmp/s6-overlay-noarch.tar.xz; \
printf '%s %s\n' "${s6_arch_sha}" /tmp/s6-overlay-arch.tar.xz; \
@@ -73,19 +73,17 @@ RUN set -eu; \
tar -C / -Jxpf /tmp/s6-overlay-noarch.tar.xz; \
tar -C / -Jxpf /tmp/s6-overlay-arch.tar.xz; \
tar -C / -Jxpf /tmp/s6-overlay-symlinks-noarch.tar.xz; \
rm /tmp/s6-overlay-*.tar.xz /tmp/s6-overlay.sha256
# #34192 / #66679: backward-compat shim for orchestration templates that
# still reference the legacy /usr/bin/tini entrypoint (Hostinger's
# 'Hermes WebUI' catalog, NAS compose projects that preserve an old
# entrypoint on image update, etc.). A plain symlink to /init made the
# path exist, but forwarded tini flags like `-g` into s6-overlay's
# rc.init as the container CMD (`rc.init: 91: -g: not found`) and
# boot-looped any `restart: unless-stopped` deploy. The shim strips the
# tini CLI surface, then exec's /init + main-wrapper — see
# docker/tini-shim.sh. Safe to drop once the affected catalogs are
# updated.
COPY --chmod=0755 docker/tini-shim.sh /usr/bin/tini
rm /tmp/s6-overlay-*.tar.xz /tmp/s6-overlay.sha256; \
# #34192: backward-compat shim for orchestration templates that still\
# reference the legacy /usr/bin/tini entrypoint (e.g. Hostinger's\
# 'Hermes WebUI' catalog). The image has moved to s6-overlay /init\
# as PID 1 (see ENTRYPOINT below + the migration comment at the top\
# of this file), but external wrappers pinned to /usr/bin/tini will\
# crash with 'tini: No such file or directory' on startup. The shim\
# symlinks /usr/bin/tini -> /init so legacy wrappers exec the right\
# PID-1 reaper without behavior change for users on the current\
# ENTRYPOINT. Safe to drop once the affected catalogs are updated.\
ln -sf /init /usr/bin/tini
# Non-root user for runtime; UID can be overridden via HERMES_UID at runtime
RUN useradd -u 10000 -m -d /opt/data hermes
@@ -118,9 +116,6 @@ COPY package.json package-lock.json ./
COPY web/package.json web/
COPY ui-tui/package.json ui-tui/
COPY ui-tui/packages/hermes-ink/ ui-tui/packages/hermes-ink/
# apps/shared/ is copied IN FULL because web/package.json references it as a
# `file:` workspace dependency (same pattern as hermes-ink above).
COPY apps/shared/ apps/shared/
# `npm_config_install_links=false` forces npm to install `file:` deps as
# symlinks instead of copies. This is the default since npm 10+, which is
@@ -134,11 +129,8 @@ COPY apps/shared/ apps/shared/
# guards against a future regression if the source npm version changes.
ENV npm_config_install_links=false
RUN npm install --prefer-offline --no-audit --fetch-retries=5 && \
for i in 1 2 3; do \
npx playwright install --with-deps chromium --only-shell && break || \
{ [ "$i" = 3 ] && exit 1; echo "playwright install failed (attempt $i); retrying in 10s"; sleep 10; }; \
done && \
RUN npm install --prefer-offline --no-audit && \
npx playwright install --with-deps chromium --only-shell && \
npm cache clean --force
# ---------- Layer-cached Python dependency install ----------
@@ -189,46 +181,41 @@ RUN uv sync --frozen --no-install-project --extra all --extra messaging --extra
# invalidate the (relatively slow) web + ui-tui build layer.
COPY web/ web/
COPY ui-tui/ ui-tui/
COPY apps/shared/ apps/shared/
RUN cd web && npm run build && \
cd ../ui-tui && npm run build
# ---------- Source code ----------
# .dockerignore excludes node_modules, so the installs above survive.
# --link decouples this layer from parents for cache purposes; --chmod bakes
# the final read-only permissions at copy time so we skip the separate
# `chmod -R` pass that previously walked ~30k files across the venv +
# node_modules + source (21s amd64 / 222s arm64 — #49113). `a+rX,go-w`
# gives the non-root hermes user read + traverse but no write; root retains
# write so the build steps below don't need chmod u+w dances.
COPY --link --chmod=a+rX,go-w . .
COPY --chown=hermes:hermes . .
# ---------- Permissions ----------
# Link hermes-agent itself (editable). Deps are already installed in the
# cached layer above; `--no-deps` makes this a fast egg-link creation with no
# resolution or downloads.
RUN uv pip install --no-cache-dir --no-deps -e "."
# Wire the exec shim and install-method stamp. Files under /opt/hermes are
# already root-owned (COPY, uv sync, npm install all run as root) and
# read-only for the hermes user (go-w from the --chmod above).
# Make install dir world-readable so any HERMES_UID can read it at runtime.
# The venv needs to be traversable too.
# node_modules trees additionally need to be writable by the hermes user
# so the runtime `npm install` triggered by _tui_need_npm_install() in
# hermes_cli/main.py succeeds (see #18800). /opt/hermes/web is build-time
# only (HERMES_WEB_DIST points at hermes_cli/web_dist) and is intentionally
# not chowned here.
# /opt/hermes/gateway is runtime-writable: Python may create __pycache__ and
# gateway state artifacts beneath the package after services drop privileges,
# especially when the hermes UID is remapped at boot (#27221).
# The .venv MUST remain hermes-writable so lazy_deps.py can install
# remaining optional platform packages and future pin bumps at first use.
# Without this, `uv pip install` fails with EACCES and adapters silently
# fail to load. See tools/lazy_deps.py.
USER root
RUN mkdir -p /opt/hermes/bin && \
cp /opt/hermes/docker/hermes-exec-shim.sh /opt/hermes/bin/hermes && \
chmod 0755 /opt/hermes/bin/hermes && \
printf 'docker\n' > /opt/hermes/.install_method
# The ``.install_method`` stamp is baked next to the running code (the install
# tree), NOT into $HERMES_HOME. $HERMES_HOME (/opt/data) is a shared data
# volume that is commonly bind-mounted from the host and even shared with a
# host-side Desktop/CLI install; stamping it at boot used to clobber that
# host install's marker and wrongly block its ``hermes update``. A code-scoped
# stamp is read first by detect_install_method() and is immune to the share.
RUN chmod -R a+rX /opt/hermes && \
chown -R hermes:hermes /opt/hermes/.venv /opt/hermes/ui-tui /opt/hermes/gateway /opt/hermes/node_modules
# Start as root so the s6-overlay stage2 hook can usermod/groupmod and chown
# the data volume. Each supervised service then drops to the hermes user via
# `s6-setuidgid hermes` in its run script. If HERMES_UID is unset, services
# run as the default hermes user (UID 10000).
# ---------- Link hermes-agent itself (editable) ----------
# Deps are already installed in the cached layer above; `--no-deps` makes
# this a fast (~1s) egg-link creation with no resolution or downloads.
RUN uv pip install --no-cache-dir --no-deps -e "."
# ---------- Bake build-time git revision ----------
# .dockerignore excludes .git, so `git rev-parse HEAD` from inside the
# container always returns nothing — meaning `hermes dump` reports
@@ -244,11 +231,12 @@ RUN mkdir -p /opt/hermes/bin && \
#
# The arg is optional — local `docker build` without --build-arg simply
# omits the file, and the runtime falls back to live-git lookup. CI
# (.github/workflows/docker.yml) passes ${{ github.sha }} so
# (.github/workflows/docker-publish.yml) passes ${{ github.sha }} so
# every published image has it.
ARG HERMES_GIT_SHA=
RUN if [ -n "${HERMES_GIT_SHA}" ]; then \
printf '%s\n' "${HERMES_GIT_SHA}" > /opt/hermes/.hermes_build_sha; \
printf '%s\n' "${HERMES_GIT_SHA}" > /opt/hermes/.hermes_build_sha && \
chown hermes:hermes /opt/hermes/.hermes_build_sha; \
fi
# ---------- s6-overlay service wiring ----------
@@ -294,21 +282,6 @@ ENV HERMES_WEB_DIST=/opt/hermes/hermes_cli/web_dist
# check. (A separate launcher hardening is tracked independently.)
ENV HERMES_TUI_DIR=/opt/hermes/ui-tui
ENV HERMES_HOME=/opt/data
ENV HERMES_WRITE_SAFE_ROOT=/opt/data
ENV HERMES_DISABLE_LAZY_INSTALLS=1
# The published image seals /opt/hermes (root-owned, read-only) so a runtime
# lazy install can't mutate the agent's own venv and brick it. But opt-in
# backends (Firecrawl web search, Exa, Feishu, …) keep their SDKs in
# tools/lazy_deps.py — deliberately NOT baked into [all] (see pyproject.toml
# policy 2026-05-12: one quarantined release must not break every install).
# Redirect those lazy installs to a writable dir on the durable data volume.
# lazy_deps appends this dir to the END of sys.path, so a package installed
# here can only ADD modules — it can never shadow or downgrade a core module,
# so the sealed-venv guarantee holds even with installs re-enabled. The dir
# is seeded + chowned to the hermes user by docker/stage2-hook.sh and lives
# on the /opt/data volume, so it persists across container recreates / image
# updates (an ABI stamp invalidates it if a rebuild bumps the interpreter).
ENV HERMES_LAZY_INSTALL_TARGET=/opt/data/lazy-packages
# `docker exec` privilege-drop shim. When operators run
# `docker exec <c> hermes ...` they default to root, and any file the
@@ -321,6 +294,7 @@ ENV HERMES_LAZY_INSTALL_TARGET=/opt/data/lazy-packages
# Recursion is impossible because the shim exec's the venv binary by
# absolute path (/opt/hermes/.venv/bin/hermes). See the shim source for
# the opt-out env var (HERMES_DOCKER_EXEC_AS_ROOT=1).
COPY --chmod=0755 docker/hermes-exec-shim.sh /opt/hermes/bin/hermes
# Pre-s6 entrypoint.sh did `source .venv/bin/activate` which exported
# the venv bin onto PATH; Architecture B's main-wrapper.sh does the
-3
View File
@@ -1,14 +1,11 @@
graft skills
graft optional-skills
graft optional-mcps
graft hermes_cli/web_dist
graft locales
# Bundled plugin manifests (plugin.yaml / plugin.yml). Without these the
# PluginManager scan (hermes_cli/plugins.py) finds zero plugins on installs
# built from the sdist (e.g. Homebrew, downstream packagers). package-data
# below covers the wheel; this covers the sdist. See #34034 / #28149.
recursive-include plugins plugin.yaml plugin.yml
# Gateway assets include images plus YAML catalogs such as status_phrases.yaml.
recursive-include gateway/assets *
global-exclude __pycache__
global-exclude *.py[cod]
-220
View File
@@ -1,220 +0,0 @@
<p align="center">
<img src="assets/banner.png" alt="Hermes Agent" width="100%">
</p>
# Hermes Agent ☤
<p align="center">
<a href="https://hermes-agent.nousresearch.com/">Hermes Agent</a> | <a href="https://hermes-agent.nousresearch.com/">Hermes Desktop</a>
</p>
<p align="center">
<a href="https://hermes-agent.nousresearch.com/docs/"><img src="https://img.shields.io/badge/Docs-hermes--agent.nousresearch.com-FFD700?style=for-the-badge" alt="Documentación"></a>
<a href="https://discord.gg/NousResearch"><img src="https://img.shields.io/badge/Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white" alt="Discord"></a>
<a href="https://github.com/NousResearch/hermes-agent/blob/main/LICENSE"><img src="https://img.shields.io/badge/Licencia-MIT-green?style=for-the-badge" alt="Licencia: MIT"></a>
<a href="https://nousresearch.com"><img src="https://img.shields.io/badge/Creado%20por-Nous%20Research-blueviolet?style=for-the-badge" alt="Creado por Nous Research"></a>
<a href="README.md"><img src="https://img.shields.io/badge/Lang-English-blue?style=for-the-badge" alt="English"></a>
<a href="README.zh-CN.md"><img src="https://img.shields.io/badge/Lang-中文-red?style=for-the-badge" alt="中文"></a>
<a href="README.ur-pk.md"><img src="https://img.shields.io/badge/Lang-اردو-green?style=for-the-badge" alt="اردو"></a>
</p>
**El agente de IA con mejora continua creado por [Nous Research](https://nousresearch.com).** Es el único agente con un bucle de aprendizaje integrado: crea habilidades a partir de la experiencia, las mejora durante el uso, se impulsa a sí mismo a persistir el conocimiento, busca en sus propias conversaciones pasadas y construye un modelo cada vez más profundo de quién eres a lo largo de las sesiones. Ejecútalo en un VPS de $5, un clúster de GPUs o infraestructura sin servidor que cuesta casi nada cuando está inactivo. No está atado a tu laptop — habla con él desde Telegram mientras trabaja en una VM en la nube.
Usa cualquier modelo que quieras — [Nous Portal](https://portal.nousresearch.com), [OpenRouter](https://openrouter.ai) (más de 200 modelos), [NovitaAI](https://novita.ai), [NVIDIA NIM](https://build.nvidia.com) (Nemotron), [Xiaomi MiMo](https://platform.xiaomimimo.com), [z.ai/GLM](https://z.ai), [Kimi/Moonshot](https://platform.moonshot.ai), [MiniMax](https://www.minimax.io), [Hugging Face](https://huggingface.co), OpenAI, o tu propio endpoint. Cambia con `hermes model` — sin cambios de código, sin dependencias.
<table>
<tr><td><b>Una interfaz de terminal real</b></td><td>TUI completa con edición multilínea, autocompletado de comandos, historial de conversaciones, interrupción y redirección, y salida de herramientas en streaming.</td></tr>
<tr><td><b>Vive donde tú vives</b></td><td>Telegram, Discord, Slack, WhatsApp, Signal y CLI — todo desde un único proceso gateway. Transcripción de notas de voz, continuidad de conversación entre plataformas.</td></tr>
<tr><td><b>Un bucle de aprendizaje cerrado</b></td><td>Memoria curada por el agente con recordatorios periódicos. Creación autónoma de habilidades tras tareas complejas. Las habilidades mejoran solas durante el uso. Búsqueda FTS5 de sesiones con resumención por LLM para recuperación entre sesiones. Modelado de usuario dialéctico <a href="https://github.com/plastic-labs/honcho">Honcho</a>. Compatible con el estándar abierto de <a href="https://agentskills.io">agentskills.io</a>.</td></tr>
<tr><td><b>Automatizaciones programadas</b></td><td>Planificador cron integrado con entrega a cualquier plataforma. Informes diarios, copias de seguridad nocturnas, auditorías semanales — todo en lenguaje natural, ejecutándose de forma autónoma.</td></tr>
<tr><td><b>Delega y paraleliza</b></td><td>Lanza subagentes aislados para flujos de trabajo paralelos. Escribe scripts de Python que llaman a herramientas vía RPC, convirtiendo pipelines de múltiples pasos en turnos de coste cero de contexto.</td></tr>
<tr><td><b>Funciona en cualquier lugar, no solo en tu laptop</b></td><td>Seis backends de terminal — local, Docker, SSH, Singularity, Modal y Daytona. Daytona y Modal ofrecen persistencia sin servidor — el entorno de tu agente hiberna cuando está inactivo y se activa bajo demanda, costando casi nada entre sesiones. Ejecútalo en un VPS de $5 o un clúster de GPUs.</td></tr>
<tr><td><b>Listo para investigación</b></td><td>Generación de trayectorias en lote, compresión de trayectorias para entrenar la próxima generación de modelos de llamadas a herramientas.</td></tr>
</table>
---
## Instalación rápida
### Linux, macOS, WSL2, Termux
```bash
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
```
### Windows (nativo, PowerShell)
> **Nota:** En Windows nativo, Hermes funciona sin WSL — la CLI, el gateway, la TUI y las herramientas funcionan de forma nativa. Si prefieres usar WSL2, el comando de Linux/macOS de arriba también funciona allí. ¿Encontraste un error? Por favor [crea un issue](https://github.com/NousResearch/hermes-agent/issues).
Ejecuta esto en PowerShell:
```powershell
iex (irm https://hermes-agent.nousresearch.com/install.ps1)
```
El instalador se encarga de todo: uv, Python 3.11, Node.js, ripgrep, ffmpeg, **y un Git Bash portátil** (MinGit, descomprimido en `%LOCALAPPDATA%\hermes\git` — no requiere administrador, completamente aislado de cualquier instalación de Git del sistema). Hermes usa este Git Bash incluido para ejecutar comandos de shell.
Si ya tienes Git instalado, el instalador lo detecta y lo usa en su lugar. De lo contrario, una descarga de ~45MB de MinGit es todo lo que necesitas — no tocará ni interferirá con ningún Git del sistema.
> **Android / Termux:** La ruta manual probada está documentada en la [guía de Termux](https://hermes-agent.nousresearch.com/docs/getting-started/termux). En Termux, Hermes instala el extra `.[termux]` curado porque el extra completo `.[all]` actualmente incluye dependencias de voz incompatibles con Android.
>
> **Windows:** Windows nativo es totalmente compatible — el comando de PowerShell de arriba instala todo. Si prefieres usar WSL2, el comando de Linux también funciona allí. La instalación nativa de Windows se encuentra en `%LOCALAPPDATA%\hermes`; WSL2 instala en `~/.hermes` como en Linux.
Después de la instalación:
```bash
source ~/.bashrc # recargar shell (o: source ~/.zshrc)
hermes # ¡empieza a chatear!
```
---
## Primeros pasos
```bash
hermes # CLI interactiva — inicia una conversación
hermes model # Elige tu proveedor y modelo LLM
hermes tools # Configura qué herramientas están habilitadas
hermes config set # Establece valores de configuración individuales
hermes gateway # Inicia el gateway de mensajería (Telegram, Discord, etc.)
hermes setup # Ejecuta el asistente de configuración completo
hermes claw migrate # Migra desde OpenClaw (si vienes de OpenClaw)
hermes update # Actualiza a la última versión
hermes doctor # Diagnostica cualquier problema
```
📖 **[Documentación completa →](https://hermes-agent.nousresearch.com/docs/)**
---
## Evita la colección de claves API — Nous Portal
Hermes funciona con cualquier proveedor que quieras — eso no cambiará. Pero si prefieres no recopilar cinco claves API separadas para el modelo, búsqueda web, generación de imágenes, TTS y un navegador en la nube, **[Nous Portal](https://portal.nousresearch.com)** las cubre todas bajo una sola suscripción:
- **Más de 300 modelos** — elige cualquiera con `/model <nombre>`
- **Tool Gateway** — búsqueda web (Firecrawl), generación de imágenes (FAL), texto a voz (OpenAI), navegador en la nube (Browser Use), todo enrutado a través de tu suscripción. Sin cuentas adicionales.
Un comando desde una instalación nueva:
```bash
hermes setup --portal
```
Esto te autentica vía OAuth, establece Nous como tu proveedor y activa el Tool Gateway. Comprueba qué está conectado en cualquier momento con `hermes portal info`. Detalles completos en la [página de documentación del Tool Gateway](https://hermes-agent.nousresearch.com/docs/user-guide/features/tool-gateway).
Puedes seguir usando tus propias claves por herramienta cuando quieras — el gateway es por backend, no todo o nada.
---
## Referencia rápida: CLI vs Mensajería
Hermes tiene dos puntos de entrada: inicia la interfaz de terminal con `hermes`, o ejecuta el gateway y habla con él desde Telegram, Discord, Slack, WhatsApp, Signal o Email. Una vez en una conversación, muchos comandos de barra son compartidos entre ambas interfaces.
| Acción | CLI | Plataformas de mensajería |
| ----------------------------------- | --------------------------------------------- | --------------------------------------------------------------------------------- |
| Empezar a chatear | `hermes` | Ejecuta `hermes gateway setup` + `hermes gateway start`, luego envía un mensaje al bot |
| Nueva conversación | `/new` o `/reset` | `/new` o `/reset` |
| Cambiar modelo | `/model [proveedor:modelo]` | `/model [proveedor:modelo]` |
| Establecer personalidad | `/personality [nombre]` | `/personality [nombre]` |
| Reintentar o deshacer último turno | `/retry`, `/undo` | `/retry`, `/undo` |
| Comprimir contexto / ver uso | `/compress`, `/usage`, `/insights [--days N]` | `/compress`, `/usage`, `/insights [days]` |
| Explorar habilidades | `/skills` o `/<nombre-habilidad>` | `/<nombre-habilidad>` |
| Interrumpir trabajo actual | `Ctrl+C` o enviar un nuevo mensaje | `/stop` o enviar un nuevo mensaje |
| Estado específico de plataforma | `/platforms` | `/status`, `/sethome` |
Para las listas de comandos completas, consulta la [guía de CLI](https://hermes-agent.nousresearch.com/docs/user-guide/cli) y la [guía del Gateway de Mensajería](https://hermes-agent.nousresearch.com/docs/user-guide/messaging).
---
## Documentación
Toda la documentación está en **[hermes-agent.nousresearch.com/docs](https://hermes-agent.nousresearch.com/docs/)**:
| Sección | Contenido |
| --------------------------------------------------------------------------------------------------- | ------------------------------------------------------------ |
| [Inicio rápido](https://hermes-agent.nousresearch.com/docs/getting-started/quickstart) | Instalar → configurar → primera conversación en 2 minutos |
| [Uso de CLI](https://hermes-agent.nousresearch.com/docs/user-guide/cli) | Comandos, atajos de teclado, personalidades, sesiones |
| [Configuración](https://hermes-agent.nousresearch.com/docs/user-guide/configuration) | Archivo de configuración, proveedores, modelos, todas las opciones |
| [Gateway de Mensajería](https://hermes-agent.nousresearch.com/docs/user-guide/messaging) | Telegram, Discord, Slack, WhatsApp, Signal, Home Assistant |
| [Seguridad](https://hermes-agent.nousresearch.com/docs/user-guide/security) | Aprobación de comandos, emparejamiento por DM, aislamiento en contenedor |
| [Herramientas y Toolsets](https://hermes-agent.nousresearch.com/docs/user-guide/features/tools) | Más de 40 herramientas, sistema de toolsets, backends de terminal |
| [Sistema de Habilidades](https://hermes-agent.nousresearch.com/docs/user-guide/features/skills) | Memoria procedimental, Skills Hub, creación de habilidades |
| [Memoria](https://hermes-agent.nousresearch.com/docs/user-guide/features/memory) | Memoria persistente, perfiles de usuario, mejores prácticas |
| [Integración MCP](https://hermes-agent.nousresearch.com/docs/user-guide/features/mcp) | Conecta cualquier servidor MCP para capacidades extendidas |
| [Programación Cron](https://hermes-agent.nousresearch.com/docs/user-guide/features/cron) | Tareas programadas con entrega a plataforma |
| [Archivos de Contexto](https://hermes-agent.nousresearch.com/docs/user-guide/features/context-files) | Contexto de proyecto que da forma a cada conversación |
| [Arquitectura](https://hermes-agent.nousresearch.com/docs/developer-guide/architecture) | Estructura del proyecto, bucle del agente, clases principales |
| [Contribuir](https://hermes-agent.nousresearch.com/docs/developer-guide/contributing) | Configuración de desarrollo, proceso de PR, estilo de código |
| [Referencia de CLI](https://hermes-agent.nousresearch.com/docs/reference/cli-commands) | Todos los comandos y flags |
| [Variables de Entorno](https://hermes-agent.nousresearch.com/docs/reference/environment-variables) | Referencia completa de variables de entorno |
---
## Migración desde OpenClaw
Si vienes de OpenClaw, Hermes puede importar automáticamente tu configuración, memorias, habilidades y claves API.
**Durante la configuración inicial:** El asistente de configuración (`hermes setup`) detecta automáticamente `~/.openclaw` y ofrece migrar antes de que comience la configuración.
**En cualquier momento después de instalar:**
```bash
hermes claw migrate # Migración interactiva (preset completo)
hermes claw migrate --dry-run # Vista previa de qué se migraría
hermes claw migrate --preset user-data # Migrar sin secretos
hermes claw migrate --overwrite # Sobreescribir conflictos existentes
```
Qué se importa:
- **SOUL.md** — archivo de personalidad
- **Memorias** — entradas de MEMORY.md y USER.md
- **Habilidades** — habilidades creadas por el usuario → `~/.hermes/skills/openclaw-imports/`
- **Lista de comandos permitidos** — patrones de aprobación
- **Configuración de mensajería** — configuración de plataformas, usuarios permitidos, directorio de trabajo
- **Claves API** — secretos en lista de permitidos (Telegram, OpenRouter, OpenAI, Anthropic, ElevenLabs)
- **Assets de TTS** — archivos de audio del espacio de trabajo
- **Instrucciones del espacio de trabajo** — AGENTS.md (con `--workspace-target`)
Consulta `hermes claw migrate --help` para todas las opciones, o usa la habilidad `openclaw-migration` para una migración guiada interactiva por el agente con vistas previas de dry-run.
---
## Contribuir
¡Las contribuciones son bienvenidas! Consulta la [Guía de Contribución](CONTRIBUTING.es.md) para la configuración del desarrollo, el estilo de código y el proceso de PR.
Inicio rápido para colaboradores — clona y comienza con `setup-hermes.sh`:
```bash
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
./setup-hermes.sh # instala uv, crea venv, instala .[all], enlaza ~/.local/bin/hermes
./hermes # detecta automáticamente el venv, no necesitas hacer `source` primero
```
Ruta manual (equivalente a lo anterior):
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv .venv --python 3.11
source .venv/bin/activate
uv pip install -e ".[all,dev]"
scripts/run_tests.sh
```
---
## Comunidad
- 💬 [Discord](https://discord.gg/NousResearch)
- 📚 [Skills Hub](https://agentskills.io)
- 🐛 [Issues](https://github.com/NousResearch/hermes-agent/issues)
- 🔌 [computer-use-linux](https://github.com/avifenesh/computer-use-linux) — Servidor MCP de control de escritorio Linux para Hermes y otros hosts MCP, con árboles de accesibilidad AT-SPI, entrada Wayland/X11, capturas de pantalla y targeting de ventanas del compositor.
- 🔌 [HermesClaw](https://github.com/AaronWong1999/hermesclaw) — Puente WeChat comunitario: Ejecuta Hermes Agent y OpenClaw en la misma cuenta de WeChat.
---
## Licencia
MIT — ver [LICENSE](LICENSE).
Creado por [Nous Research](https://nousresearch.com).
+9 -54
View File
@@ -13,12 +13,11 @@
<a href="https://nousresearch.com"><img src="https://img.shields.io/badge/Built%20by-Nous%20Research-blueviolet?style=for-the-badge" alt="Built by Nous Research"></a>
<a href="README.zh-CN.md"><img src="https://img.shields.io/badge/Lang-中文-red?style=for-the-badge" alt="中文"></a>
<a href="README.ur-pk.md"><img src="https://img.shields.io/badge/Lang-اردو-green?style=for-the-badge" alt="اردو"></a>
<a href="README.es.md"><img src="https://img.shields.io/badge/Lang-Español-orange?style=for-the-badge" alt="Español"></a>
</p>
**The self-improving AI agent built by [Nous Research](https://nousresearch.com).** It's the only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, searches its own past conversations, and builds a deepening model of who you are across sessions. Run it on a $5 VPS, a GPU cluster, or serverless infrastructure that costs nearly nothing when idle. It's not tied to your laptop — talk to it from Telegram while it works on a cloud VM.
Use any model you want — [Nous Portal](https://portal.nousresearch.com), OpenRouter, OpenAI, your own endpoint, and [many others](https://hermes-agent.nousresearch.com/docs/integrations/providers). Switch with `hermes model` — no code changes, no lock-in.
Use any model you want — [Nous Portal](https://portal.nousresearch.com), [OpenRouter](https://openrouter.ai) (200+ models), [NovitaAI](https://novita.ai) (AI-native cloud for Model API, Agent Sandbox, and GPU Cloud), [NVIDIA NIM](https://build.nvidia.com) (Nemotron), [Xiaomi MiMo](https://platform.xiaomimimo.com), [z.ai/GLM](https://z.ai), [Kimi/Moonshot](https://platform.moonshot.ai), [MiniMax](https://www.minimax.io), [Hugging Face](https://huggingface.co), OpenAI, or your own endpoint. Switch with `hermes model` — no code changes, no lock-in.
<table>
<tr><td><b>A real terminal interface</b></td><td>Full TUI with multiline editing, slash-command autocomplete, conversation history, interrupt-and-redirect, and streaming tool output.</td></tr>
@@ -65,41 +64,6 @@ source ~/.bashrc # reload shell (or: source ~/.zshrc)
hermes # start chatting!
```
### Troubleshooting
#### Windows Defender or antivirus flags `uv.exe` as malware
If your antivirus (Bitdefender, Windows Defender, etc.) quarantines `uv.exe` from the Hermes `bin` folder (`%LOCALAPPDATA%\hermes\bin\uv.exe`), this is a **false positive**. The file is Astral's `uv` — the Rust Python package manager Hermes bundles to manage its Python environment. ML-based antivirus engines commonly flag unsigned Rust binaries that download and install packages.
**To verify your copy is authentic:**
```powershell
# Install GitHub CLI if needed
winget install --id GitHub.cli
# Login to GitHub
gh auth login
# Run verification
$uv = "$env:LOCALAPPDATA\hermes\bin\uv.exe"
$ver = (& $uv --version).Split(' ')[1]
[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12
$zip = "$env:TEMP\uv.zip"
Invoke-WebRequest "https://github.com/astral-sh/uv/releases/download/$ver/uv-x86_64-pc-windows-msvc.zip" -OutFile $zip -UseBasicParsing
gh attestation verify $zip --repo astral-sh/uv
Expand-Archive $zip "$env:TEMP\uv_x" -Force
(Get-FileHash "$env:TEMP\uv_x\uv.exe").Hash -eq (Get-FileHash $uv).Hash
```
If attestation says "Verification succeeded" and the last line prints `True`, you're good.
**To whitelist Hermes:**
- **Windows Defender:** Run PowerShell as Admin → `Add-MpPreference -ExclusionPath "$env:LOCALAPPDATA\hermes\bin"`
- **Bitdefender:** Add an exception in the Bitdefender console (Protection > Antivirus > Settings > Manage Exceptions)
- Whitelist the **folder**, not the file hash — Hermes updates `uv` and the hash changes every version
For more context, see the upstream Astral reports: [astral-sh/uv#13553](https://github.com/astral-sh/uv/issues/13553), [astral-sh/uv#15011](https://github.com/astral-sh/uv/issues/15011), [astral-sh/uv#10079](https://github.com/astral-sh/uv/issues/10079).
---
## Getting Started
@@ -109,7 +73,6 @@ hermes # Interactive CLI — start a conversation
hermes model # Choose your LLM provider and model
hermes tools # Configure which tools are enabled
hermes config set # Set individual config values
hermes config get # Print individual config values
hermes gateway # Start the messaging gateway (Telegram, Discord, etc.)
hermes setup # Run the full setup wizard (configures everything at once)
hermes claw migrate # Migrate from OpenClaw (if coming from OpenClaw)
@@ -218,29 +181,21 @@ See `hermes claw migrate --help` for all options, or use the `openclaw-migration
We welcome contributions! See the [Contributing Guide](https://hermes-agent.nousresearch.com/docs/developer-guide/contributing) for development setup, code style, and PR process.
Quick start for contributors — use the standard installer, then work from the
full git checkout it creates at `$HERMES_HOME/hermes-agent` (usually
`~/.hermes/hermes-agent`). This matches the layout used by `hermes update`, the
managed venv, lazy dependencies, gateway, and docs tooling.
Quick start for contributors — clone and go with `setup-hermes.sh`:
```bash
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
cd "${HERMES_HOME:-$HOME/.hermes}/hermes-agent"
uv pip install -e ".[all,dev]"
scripts/run_tests.sh
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
./setup-hermes.sh # installs uv, creates venv, installs .[all], symlinks ~/.local/bin/hermes
./hermes # auto-detects the venv, no need to `source` first
```
Manual clone fallback (for throwaway clones/CI where you intentionally do not
want the managed install layout):
Create the venv outside the cloned source tree — a venv inside the directory
the agent operates from can be wiped by a relative-path command the agent runs
against its own checkout, destroying the running runtime mid-session.
Manual path (equivalent to the above):
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv ~/.hermes/venvs/hermes-dev --python 3.11
source ~/.hermes/venvs/hermes-dev/bin/activate
uv venv .venv --python 3.11
source .venv/bin/activate
uv pip install -e ".[all,dev]"
scripts/run_tests.sh
```
+7 -13
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@@ -39,11 +39,7 @@ curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
> **Android / Termux** 已测试的手动安装路径请参考 [Termux 指南](https://hermes-agent.nousresearch.com/docs/getting-started/termux)。在 Termux 上,Hermes 会安装精选的 `.[termux]` 扩展,因为完整的 `.[all]` 扩展会拉取 Android 不兼容的语音依赖。
>
> **Windows** 在 PowerShell 中运行:
> ```powershell
> iex (irm https://hermes-agent.nousresearch.com/install.ps1)
> ```
> 安装完成后,可能需要重启终端,然后运行 `hermes` 开始对话。
> **Windows** 原生 Windows 不受支持。请安装 [WSL2](https://learn.microsoft.com/zh-cn/windows/wsl/install) 并运行上述命令。
安装后:
@@ -168,18 +164,16 @@ hermes claw migrate --overwrite # 覆盖已有冲突
欢迎贡献!请参阅 [贡献指南](https://hermes-agent.nousresearch.com/docs/developer-guide/contributing) 了解开发设置、代码风格和 PR 流程。
贡献者快速开始——使用标准安装器,然后在它创建的完整 git checkout 中开发
`$HERMES_HOME/hermes-agent`(通常是 `~/.hermes/hermes-agent`)。这会匹配
`hermes update`、托管 venv、lazy dependencies、gateway 和 docs tooling 使用的布局。
贡献者快速开始——克隆并使用 `setup-hermes.sh`
```bash
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
cd "${HERMES_HOME:-$HOME/.hermes}/hermes-agent"
uv pip install -e ".[all,dev]"
scripts/run_tests.sh
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
./setup-hermes.sh # 安装 uv、创建 venv、安装 .[all]、创建符号链接 ~/.local/bin/hermes
./hermes # 自动检测 venv,无需先 source
```
手动克隆备用路径(用于一次性 clone / CI,或你明确不想使用 managed install layout 时):
手动安装(等效于上述命令):
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
-322
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@@ -1,322 +0,0 @@
# Política de Seguridad de Hermes Agent
Este documento describe el modelo de confianza de Hermes Agent, identifica el
único límite de seguridad que el proyecto trata como estructural y define el
alcance para los informes de vulnerabilidades.
## 1. Reportar una Vulnerabilidad
Reporta de forma privada a través de [GitHub Security Advisories](https://github.com/NousResearch/hermes-agent/security/advisories/new)
o **security@nousresearch.com**. No abras issues públicos para
vulnerabilidades de seguridad. **Hermes Agent no opera un programa de
recompensas por errores.**
Un informe útil incluye:
- Una descripción concisa y evaluación de severidad.
- El componente afectado, identificado por ruta de archivo y rango de líneas
(ej. `path/to/file.py:120-145`).
- Detalles del entorno (`hermes version`, SHA del commit, SO, versión de Python).
- Una reproducción contra `main` o el último release.
- Una declaración de qué límite de confianza del §2 se cruza.
Por favor lee el §2 y el §3 antes de enviar. Los informes que demuestren
límites de una heurística en proceso que esta política no trate como un
límite serán cerrados como fuera de alcance bajo el §3 — pero consulta el §3.2:
siguen siendo bienvenidos como issues o pull requests regulares, simplemente no
a través del canal de seguridad privado.
---
## 2. Modelo de Confianza
Hermes Agent es un agente personal de un solo inquilino. Su postura es
por capas, y las capas no tienen el mismo peso. Los reportadores y
operadores deben razonar sobre ellas en los mismos términos.
### 2.1 Definiciones
- **Proceso del agente.** El intérprete Python que ejecuta Hermes Agent,
incluyendo cualquier módulo Python que haya cargado (habilidades, plugins,
manejadores de hooks).
- **Backend de terminal.** Un objetivo de ejecución conectado para la
herramienta `terminal()`. El predeterminado ejecuta comandos directamente en el host.
Otros backends ejecutan comandos dentro de un contenedor, sandbox en la nube o
host remoto.
- **Superficie de entrada.** Cualquier canal a través del cual el contenido entra en el
contexto del agente: entrada del operador, fetches web, email, mensajes del gateway,
lecturas de archivos, respuestas del servidor MCP, resultados de herramientas.
- **Envolvente de confianza.** El conjunto de recursos a los que un operador ha otorgado
implícitamente acceso a Hermes Agent al ejecutarlo — típicamente, todo lo que
la propia cuenta de usuario del operador puede alcanzar en el host.
- **Postura.** Una declaración explícita en la documentación o código de Hermes Agent
sobre cómo una capa consumidora (adaptador, UI, escritor de archivos,
shell) debe tratar la salida del agente — ej. "el dashboard renderiza
la salida del agente como HTML inerte."
### 2.2 El Límite: Aislamiento a Nivel de SO
**El único límite de seguridad contra un LLM adversario es el
sistema operativo.** Nada dentro del proceso del agente constituye
contención — ni la puerta de aprobación, ni la redacción de salida, ni ningún
escáner de patrones, ni ninguna lista de herramientas permitidas. Cualquier componente dentro
del proceso que filtre la salida del LLM es una heurística operando sobre una
cadena influenciada por el atacante, y esta política lo trata como tal.
Hermes Agent admite dos posturas de aislamiento a nivel de SO. Abordan
diferentes amenazas y un operador debe elegir deliberadamente.
#### Aislamiento del backend de terminal
Un backend de terminal no predeterminado ejecuta comandos de shell emitidos por el LLM
dentro de un contenedor, host remoto o sandbox en la nube. Las herramientas de archivos
(`read_file`, `write_file`, `patch`) también se ejecutan a través de este backend,
ya que están implementadas sobre el contrato del shell — no pueden
alcanzar rutas que el backend no exponga.
Lo que confina: todo lo que el agente hace emitiendo operaciones de shell o
de archivos. Lo que **no** confina: todo lo que el agente hace en su propio
proceso Python. Eso incluye la herramienta de ejecución de código (lanzada como
subproceso del host), subprocesos MCP (lanzados desde el entorno del agente),
carga de plugins, despacho de hooks y carga de habilidades (todos importados en el
intérprete del agente).
El aislamiento del backend de terminal es la postura correcta cuando la preocupación es
que el LLM emita comandos de shell destructivos o escrituras de herramientas de archivo no deseadas, y el
operador es de confianza.
#### Envoltura del proceso completo
La envoltura del proceso completo ejecuta todo el árbol de procesos del agente dentro de un
sandbox. Cada ruta de código — shell, ejecución de código, MCP, herramientas de archivos,
plugins, hooks, carga de habilidades — está sujeta a la misma política de sistema de archivos,
red, proceso e (donde sea aplicable) inferencia.
Hermes Agent admite esto de dos maneras:
- **La propia imagen Docker de Hermes Agent y la configuración de Compose.** Más
liviana; el agente se ejecuta en un contenedor estándar con montajes y
política de red configurados por el operador.
- **[NVIDIA OpenShell](https://github.com/NVIDIA/OpenShell)**.
OpenShell proporciona sandboxes por sesión con política declarativa
a través de capas de sistema de archivos, red (egreso L7), proceso/syscall e
enrutamiento de inferencia. Las políticas de red e inferencia son
recargables en caliente. Las credenciales se inyectan desde un almacén de Proveedor
y nunca tocan el sistema de archivos del sandbox.
Bajo una envoltura de proceso completo, las heurísticas en proceso de Hermes Agent
(§2.4) funcionan como prevención de accidentes en capas sobre un límite real.
Esta es la postura soportada cuando el agente ingiere contenido de superficies
que el operador no controla — la web abierta, email entrante, canales de
múltiples usuarios, servidores MCP no confiables — y para despliegues en
producción o compartidos.
Los operadores que ejecuten el backend local predeterminado con superficies de entrada
no confiables, o que ejecuten un sandbox de backend de terminal esperando que contenga
rutas de código que no pasan por el shell, están operando fuera de la postura de
seguridad soportada.
### 2.3 Alcance de Credenciales
Hermes Agent filtra el entorno que pasa a sus componentes en proceso de
menor confianza: subprocesos de shell, subprocesos MCP y el proceso hijo
de ejecución de código. Las credenciales como las claves API del proveedor y los
tokens del gateway se eliminan por defecto; las variables declaradas explícitamente
por el operador o por una habilidad cargada se pasan.
Esto reduce la exfiltración casual. No es contención. Cualquier
componente que se ejecute dentro del proceso del agente (habilidades, plugins, manejadores
de hooks) puede leer lo que el agente mismo puede leer, incluidas las
credenciales en memoria. La mitigación contra un componente en proceso comprometido
es la revisión del operador antes de instalar (§2.4, §2.5), no el
saneamiento del entorno.
### 2.4 Heurísticas en Proceso
Los siguientes componentes filtran o advierten sobre el comportamiento del LLM. Son
útiles. No son límites.
- La **puerta de aprobación** detecta patrones de shell destructivos comunes
y le pide al operador confirmación antes de la ejecución. El shell es Turing-
completo; una lista de denegación sobre cadenas de shell es estructuralmente
incompleta. La puerta detecta errores en modo cooperativo, no salidas
adversariales.
- **La redacción de salida** elimina patrones similares a secretos de la visualización.
Un productor de salida motivado la evitará.
- **Skills Guard** escanea el contenido de habilidades instalables en busca de patrones
de inyección. Es una ayuda de revisión; el límite para habilidades de terceros
es la revisión del operador antes de instalar. Revisar una habilidad significa
leer su código Python y scripts, no solo su descripción SKILL.md —
las habilidades ejecutan Python arbitrario en el momento de importación.
### 2.5 Modelo de Confianza de Plugins
Los plugins se cargan en el proceso del agente y se ejecutan con todos los privilegios
del agente: pueden leer las mismas credenciales, llamar a las mismas
herramientas, registrar los mismos hooks e importar los mismos módulos que
cualquier cosa incluida en el árbol. El límite para los plugins de terceros es
la revisión del operador antes de instalar — la misma regla que las habilidades (§2.4),
mencionado por separado porque los plugins son arquitectónicamente más pesados
y a menudo incluyen sus propios servicios en segundo plano, oyentes de red
y dependencias.
Un plugin malicioso o con errores no es una vulnerabilidad en Hermes Agent
en sí mismo. Los errores en la ruta de instalación o descubrimiento de plugins de Hermes Agent
que impidan al operador ver lo que está instalando están en alcance bajo el §3.1.
### 2.6 Superficies Externas
Una **superficie externa** es cualquier canal fuera del proceso del agente local
a través del cual un llamador puede despachar trabajo del agente, resolver
aprobaciones o recibir salida del agente. Cada superficie tiene su propio
modelo de autorización, pero las reglas a continuación se aplican uniformemente.
**Superficies en Hermes Agent:**
- **Adaptadores de plataforma del gateway.** Integraciones de mensajería en
`gateway/platforms/` (Telegram, Discord, Slack, email, SMS, etc.)
y adaptadores análogos incluidos como plugins.
- **Superficies HTTP expuestas en red.** El adaptador del servidor API, el
plugin del dashboard, los endpoints HTTP del plugin kanban, y cualquier
otro plugin que vincule un socket de escucha.
- **Adaptadores de Editor / IDE.** El adaptador ACP (`acp_adapter/`) e
integraciones equivalentes que aceptan solicitudes de un proceso cliente local.
- **El gateway TUI (`tui_gateway/`).** Backend JSON-RPC para la
UI de terminal Ink, alcanzado a través de IPC local.
**Reglas uniformes:**
1. **Se requiere autorización en cada superficie que cruce un límite de confianza.** Para
superficies de mensajería y HTTP en red, el límite es la red: la autorización
significa una lista de llamadores permitidos configurada por el operador. Para superficies
de editor e IPC local (ACP, gateway TUI), el límite es la cuenta de usuario del host:
la autorización significa depender del control de acceso a nivel de SO (permisos
de archivos, vinculaciones solo a loopback) y no exponer la superficie más allá
del usuario local sin una capa de autenticación de red explícita.
2. **Se requiere una lista de permitidos para cada adaptador de red habilitado.**
Los adaptadores deben rechazar despachar trabajo del agente, resolver
aprobaciones o transmitir salida hasta que se establezca una lista de permitidos. Las rutas
de código que fallan de forma abierta cuando no hay lista de permitidos configurada son errores de código en
alcance bajo el §3.1.
3. **Los identificadores de sesión son manejadores de enrutamiento, no límites de autorización.**
Conocer el ID de sesión de otro llamador no otorga acceso a sus aprobaciones o salida;
la autorización siempre se vuelve a verificar contra la lista de permitidos (o equivalente
a nivel de SO).
4. **Dentro del conjunto autorizado, todos los llamadores tienen la misma confianza.**
Hermes Agent no modela capacidades por llamador dentro de un único adaptador.
Los operadores que necesiten separación de capacidades deben ejecutar instancias
de agente separadas con listas de permitidos separadas.
5. **Vincular una superficie solo local a una interfaz no-loopback es una decisión de
operador de emergencia (§3.2).** El dashboard y otros servidores HTTP de plugins
son predeterminados a loopback; exponerlos a través de `--host 0.0.0.0` o equivalente
hace que el fortalecimiento de exposición pública (§4) sea responsabilidad del operador.
---
## 3. Alcance
### 3.1 En Alcance
- Escape de una postura de aislamiento a nivel de SO declarada (§2.2): una
ruta de código controlada por el atacante alcanzando estado que la postura
afirmó confinar.
- Acceso no autorizado a superficie externa: un llamador fuera del conjunto de
autorización configurado (lista de permitidos, o equivalente a nivel de SO
para superficies de IPC local) despachando trabajo, recibiendo salida o
resolviendo aprobaciones (§2.6).
- Exfiltración de credenciales: filtración de credenciales del operador o
material de autorización de sesión a un destino fuera del envolvente de
confianza, a través de un mecanismo que debería haberlo prevenido
(error de saneamiento de entorno, registro del adaptador, error de transporte
que vacía credenciales a un upstream, etc.).
- Violaciones de la documentación del modelo de confianza: código que se comporta
contrariamente a lo que esta política, la propia documentación de Hermes Agent o
las expectativas razonables del operador predecirían — incluyendo casos donde
Hermes Agent ha documentado una postura sobre cómo su salida debe ser
renderizada por una capa consumidora (dashboard, adaptador de gateway,
escritor de archivos, shell) y una ruta de código rompe esa postura.
### 3.2 Fuera de Alcance
"Fuera de alcance" aquí significa "no es una vulnerabilidad de seguridad bajo esta
política." No significa "no vale la pena reportarlo." Las mejoras a las
heurísticas en proceso, ideas de fortalecimiento y correcciones de UX son bienvenidas como
issues o pull requests regulares — la puerta de aprobación siempre puede detectar
más patrones, la redacción puede volverse más inteligente, el comportamiento del adaptador
puede apretarse siempre. Estos elementos simplemente no van a través del canal de
divulgación privada y no reciben avisos.
- **Bypasses de heurísticas en proceso (§2.4)** — bypasses de regex de la puerta de aprobación,
bypasses de redacción, bypasses de patrones de Skills Guard, e informes
análogos contra heurísticas futuras. Estos componentes no son límites;
vencerlos no es una vulnerabilidad bajo esta política.
- **Inyección de prompts per se.** Hacer que el LLM emita salida inusual
— a través de contenido inyectado, alucinación, artefactos de entrenamiento,
o cualquier otra causa — no es en sí mismo una vulnerabilidad. "Logré
inyección de prompts" sin un resultado encadenado del §3.1 no es un informe
procesable bajo esta política.
- **Consecuencias de una postura de aislamiento elegida.** Los informes de que
una ruta de código que opera dentro del alcance de su postura puede hacer lo que esa
postura permite no son vulnerabilidades. Ejemplos: herramientas de shell o archivos
que alcanzan estado del host bajo el backend local; subprocesos de ejecución de código
o MCP que alcanzan estado del host bajo aislamiento de backend de terminal que solo
sandboxea el shell; informes cuyas precondiciones requieren acceso de escritura preexistente
a archivos de configuración o credenciales propiedad del operador (esos ya están dentro
del envolvente de confianza).
- **Configuraciones documentadas de emergencia.** Compensaciones seleccionadas por el operador
que deshabilitan explícitamente protecciones: `--insecure` y flags equivalentes
en el dashboard u otros componentes, aprobaciones deshabilitadas,
backend local en producción, perfiles de desarrollo que evitan
la seguridad de hermes-home, y similares. Los informes contra esas
configuraciones no son vulnerabilidades — eso es el trabajo del flag.
- **Habilidades y plugins contribuidos por la comunidad.** Las habilidades de terceros
(incluyendo el repositorio de habilidades de la comunidad) y los plugins de terceros
están en la superficie de revisión del operador, no en la superficie de confianza de Hermes Agent
(§2.4, §2.5). Una habilidad o plugin que haga algo
malicioso es el modo de falla esperado de uno que no fue
revisado, no una vulnerabilidad en Hermes Agent. Los errores en la ruta de
instalación de habilidades o plugins de Hermes Agent que impidan al
operador ver lo que está instalando están en alcance bajo el §3.1.
- **Exposición pública sin controles externos.** Exponer el
gateway o la API a la internet pública sin autenticación,
VPN o firewall.
- **Restricciones de lectura/escritura a nivel de herramienta en una postura donde el shell está
permitido.** Si una ruta es alcanzable a través de la herramienta terminal, los informes
de que otras herramientas de archivos pueden alcanzarla no añaden nada.
---
## 4. Fortalecimiento del Despliegue
La decisión de fortalecimiento más importante es hacer coincidir el aislamiento
(§2.2) con la confianza del contenido que el agente ingerirá. Más allá de eso:
- Ejecuta el agente como usuario no-root. La imagen de contenedor proporcionada
hace esto por defecto.
- Mantén las credenciales en el archivo de credenciales del operador con permisos
estrictos, nunca en la configuración principal, nunca en control de versiones.
Bajo OpenShell, usa el almacén de Proveedores en lugar de un archivo de
credenciales en disco.
- No expongas el gateway o la API a la internet pública sin
VPN, Tailscale o protección de firewall. Bajo OpenShell, usa la
capa de política de red para restringir el egreso.
- Configura una lista de llamadores permitidos para cada adaptador de red expuesto
que habilites (§2.6).
- Revisa las habilidades y plugins de terceros antes de instalar (§2.4,
§2.5). Para las habilidades, esto significa leer el Python y los scripts,
no solo SKILL.md. Los informes de Skills Guard y el registro de auditoría
de instalación son la superficie de revisión.
- Hermes Agent incluye guardias de cadena de suministro para lanzamientos de servidores
MCP y para cambios de dependencias / paquetes incluidos en CI; consulta
`CONTRIBUTING.es.md` para más detalles.
---
## 5. Divulgación
- **Ventana de divulgación coordinada:** 90 días desde el informe, o hasta que se
publique una corrección, lo que ocurra primero.
- **Canal:** el hilo GHSA o correspondencia por email con
security@nousresearch.com.
- **Crédito:** los reportadores reciben crédito en las notas de versión a menos que
se solicite anonimato.
+4 -5
View File
@@ -121,11 +121,10 @@ outside the supported security posture.
### 2.3 Credential Scoping
Hermes Agent filters the environment it passes to its lower-trust
in-process components: shell subprocesses, MCP subprocesses,
cron job scripts, and the code-execution child. Credentials like
provider API keys and gateway tokens are stripped by default;
variables explicitly declared by the operator or by a loaded
skill are passed through.
in-process components: shell subprocesses, MCP subprocesses, and
the code-execution child. Credentials like provider API keys and
gateway tokens are stripped by default; variables explicitly
declared by the operator or by a loaded skill are passed through.
This reduces casual exfiltration. It is not containment. Any
component running inside the agent process (skills, plugins, hook
+2 -54
View File
@@ -10,7 +10,6 @@ from __future__ import annotations
import asyncio
import json
import logging
import re
import tempfile
from concurrent.futures import TimeoutError as FutureTimeout
from contextvars import ContextVar, Token
@@ -128,64 +127,13 @@ def _proposal_for_patch_replace(arguments: dict[str, Any]) -> EditProposal:
)
def _extract_v4a_patch_paths(patch_body: str) -> list[str]:
paths: list[str] = []
for match in re.finditer(
r'^\*\*\*\s+(?:Update|Add|Delete)\s+File:\s*(.+)$',
patch_body,
re.MULTILINE,
):
path = match.group(1).strip()
if path:
paths.append(path)
for match in re.finditer(
r'^\*\*\*\s+Move\s+File:\s*(.+?)\s*->\s*(.+)$',
patch_body,
re.MULTILINE,
):
src = match.group(1).strip()
dst = match.group(2).strip()
if src:
paths.append(src)
if dst:
paths.append(dst)
return paths
def _proposal_for_patch_v4a(arguments: dict[str, Any]) -> EditProposal:
patch_body = arguments.get("patch")
if not isinstance(patch_body, str) or not patch_body:
raise ValueError("patch content required")
paths = _extract_v4a_patch_paths(patch_body)
if not paths:
raise ValueError("no file paths found in V4A patch")
proposal_path = paths[0] if len(paths) == 1 else ", ".join(paths)
old_text = _read_text_if_exists(paths[0]) if len(paths) == 1 else None
return EditProposal(
tool_name="patch",
path=proposal_path,
old_text=old_text,
# ACP only supports a single diff payload here. Surface the exact V4A
# patch content before execution so patch-mode calls are permissioned
# and denied patches cannot mutate.
new_text=patch_body,
arguments=dict(arguments),
)
def build_edit_proposal(tool_name: str, arguments: dict[str, Any]) -> EditProposal | None:
"""Return an edit proposal for supported file mutation calls."""
if tool_name == "write_file":
return _proposal_for_write_file(arguments)
if tool_name == "patch":
mode = arguments.get("mode", "replace")
if mode == "replace":
return _proposal_for_patch_replace(arguments)
if mode == "patch":
return _proposal_for_patch_v4a(arguments)
if tool_name == "patch" and arguments.get("mode", "replace") == "replace":
return _proposal_for_patch_replace(arguments)
return None
-5
View File
@@ -23,11 +23,6 @@ except ModuleNotFoundError:
# new code but ``uv pip install -e .`` didn't finish. Missing bootstrap
# means UTF-8 stdio setup is skipped on Windows; POSIX is unaffected.
pass
else:
# Stop a ``utils/``/``proxy/``/``ui/`` package in the launch directory from
# shadowing Hermes's own modules — ``hermes acp`` can be started from any
# cwd, including a project that has same-named packages on its path.
hermes_bootstrap.harden_import_path()
import argparse
import asyncio
+9 -16
View File
@@ -38,22 +38,19 @@ def _permission_option_supports_kind(kind: str) -> bool:
return True
def _build_permission_options(
*, allow_permanent: bool, smart_denied: bool = False,
) -> list[PermissionOption]:
def _build_permission_options(*, allow_permanent: bool) -> list[PermissionOption]:
"""Return ACP options that match Hermes approval semantics."""
options = [PermissionOption(
option_id="allow_once", kind="allow_once", name="Allow once",
)]
if not smart_denied:
options.append(PermissionOption(
options = [
PermissionOption(option_id="allow_once", kind="allow_once", name="Allow once"),
PermissionOption(
option_id="allow_session",
# ACP has no session-scoped kind, so use the closest persistent
# hint while keeping Hermes semantics in the option id.
kind="allow_always",
name="Allow for session",
))
if allow_permanent and not smart_denied:
),
]
if allow_permanent:
options.append(
PermissionOption(
option_id="allow_always",
@@ -62,7 +59,7 @@ def _build_permission_options(
),
)
options.append(PermissionOption(option_id="deny", kind="reject_once", name="Deny"))
if not smart_denied and _permission_option_supports_kind("reject_always"):
if _permission_option_supports_kind("reject_always"):
options.append(
PermissionOption(
option_id="deny_always",
@@ -132,15 +129,11 @@ def make_approval_callback(
description: str,
*,
allow_permanent: bool = True,
smart_denied: bool = False,
**_: object,
) -> str:
from agent.async_utils import safe_schedule_threadsafe
options = _build_permission_options(
allow_permanent=allow_permanent,
smart_denied=smart_denied,
)
options = _build_permission_options(allow_permanent=allow_permanent)
tool_call = _build_permission_tool_call(command, description)
coro = request_permission_fn(
+21 -71
View File
@@ -74,10 +74,6 @@ from acp_adapter.permissions import make_approval_callback
from acp_adapter.provenance import session_provenance_meta
from acp_adapter.session import SessionManager, SessionState, _expand_acp_enabled_toolsets
from acp_adapter.tools import build_tool_complete, build_tool_start
from tools.approval import (
reset_hermes_interactive_context,
set_hermes_interactive_context,
)
logger = logging.getLogger(__name__)
@@ -456,7 +452,7 @@ class HermesACPAgent(acp.Agent):
"tools": "List available tools",
"context": "Show conversation context info",
"reset": "Clear conversation history",
"compress": "Compress conversation context",
"compact": "Compress conversation context",
"steer": "Inject guidance into the currently running agent turn",
"queue": "Queue a prompt to run after the current turn finishes",
"version": "Show Hermes version",
@@ -485,7 +481,7 @@ class HermesACPAgent(acp.Agent):
"description": "Clear conversation history",
},
{
"name": "compress",
"name": "compact",
"description": "Compress conversation context",
},
{
@@ -828,7 +824,6 @@ class HermesACPAgent(acp.Agent):
try:
from model_tools import get_tool_definitions
from agent.memory_manager import inject_memory_provider_tools
enabled_toolsets = _expand_acp_enabled_toolsets(
getattr(state.agent, "enabled_toolsets", None) or ["hermes-acp"],
@@ -844,7 +839,6 @@ class HermesACPAgent(acp.Agent):
state.agent.valid_tool_names = {
tool["function"]["name"] for tool in state.agent.tools or []
}
inject_memory_provider_tools(state.agent)
invalidate = getattr(state.agent, "_invalidate_system_prompt", None)
if callable(invalidate):
invalidate()
@@ -1450,23 +1444,20 @@ class HermesACPAgent(acp.Agent):
# Approval callback is per-thread (thread-local, GHSA-qg5c-hvr5-hjgr).
# Set it INSIDE _run_agent so the TLS write happens in the executor
# thread — setting it here would write to the event-loop thread's TLS,
# not the executor's. Interactive routing uses a contextvar in
# tools.approval (set_hermes_interactive_context) rather than
# os.environ["HERMES_INTERACTIVE"], so concurrent executor workers can't
# race on a process-global flag — one session's restore can't drop
# another onto the non-interactive auto-approve path mid-run
# (GHSA-96vc-wcxf-jjff). The contextvar write is isolated by the
# contextvars.copy_context() wrapper around the executor call below.
# not the executor's. Also set HERMES_INTERACTIVE so approval.py
# takes the CLI-interactive path (which calls the registered
# callback via prompt_dangerous_approval) instead of the
# non-interactive auto-approve branch (GHSA-96vc-wcxf-jjff).
# ACP's conn.request_permission maps cleanly to the interactive
# callback shape — not the gateway-queue HERMES_EXEC_ASK path,
# which requires a notify_cb registered in _gateway_notify_cbs.
previous_approval_cb = None
interactive_token = None
previous_interactive = None
edit_approval_token = None
previous_session_id = None
def _run_agent() -> dict:
nonlocal previous_approval_cb, interactive_token, edit_approval_token, previous_session_id
nonlocal previous_approval_cb, previous_interactive, edit_approval_token, previous_session_id
# Bind HERMES_SESSION_KEY for this session so per-session caches
# (e.g. the interactive sudo password cache in tools.terminal_tool)
# scope to the ACP session rather than leaking across sessions
@@ -1498,10 +1489,9 @@ class HermesACPAgent(acp.Agent):
except Exception:
logger.debug("Could not set ACP edit approval requester", exc_info=True)
# Signal to tools.approval that we have an interactive callback
# and the non-interactive auto-approve path must not fire. Uses a
# contextvar (not os.environ) so concurrent executor workers don't
# race on the flag (GHSA-96vc-wcxf-jjff).
interactive_token = set_hermes_interactive_context(True)
# and the non-interactive auto-approve path must not fire.
previous_interactive = os.environ.get("HERMES_INTERACTIVE")
os.environ["HERMES_INTERACTIVE"] = "1"
# Propagate the originating ACP session id to tools that want to
# tag side-effects with it (e.g. ``kanban_create`` stamps it on
# the new task so clients can render a per-session board). Save
@@ -1521,9 +1511,11 @@ class HermesACPAgent(acp.Agent):
logger.exception("Agent error in session %s", session_id)
return {"final_response": f"Error: {e}", "messages": state.history}
finally:
# Restore the interactive contextvar for this context.
if interactive_token is not None:
reset_hermes_interactive_context(interactive_token)
# Restore HERMES_INTERACTIVE.
if previous_interactive is None:
os.environ.pop("HERMES_INTERACTIVE", None)
else:
os.environ["HERMES_INTERACTIVE"] = previous_interactive
# Restore HERMES_SESSION_ID symmetrically.
if previous_session_id is None:
os.environ.pop("HERMES_SESSION_ID", None)
@@ -1617,28 +1609,12 @@ class HermesACPAgent(acp.Agent):
self._send_session_info_update(session_id),
)
# Snapshot the runtime identity; the validator lets the
# background titler skip its LLM call if the session's model
# changed before it fires (#19027).
_title_model = getattr(state.agent, "model", None)
_title_provider = getattr(state.agent, "provider", None)
maybe_auto_title(
self.session_manager._get_db(),
session_id,
user_text,
final_response,
state.history,
main_runtime={
"model": getattr(state.agent, "model", None),
"provider": getattr(state.agent, "provider", None),
"base_url": getattr(state.agent, "base_url", None),
"api_key": getattr(state.agent, "api_key", None),
"api_mode": getattr(state.agent, "api_mode", None),
},
runtime_validator=lambda: (
getattr(state.agent, "model", None) == _title_model
and getattr(state.agent, "provider", None) == _title_provider
),
title_callback=_notify_title_update,
)
except Exception:
@@ -1756,7 +1732,7 @@ class HermesACPAgent(acp.Agent):
"tools": self._cmd_tools,
"context": self._cmd_context,
"reset": self._cmd_reset,
"compress": self._cmd_compress,
"compact": self._cmd_compact,
"steer": self._cmd_steer,
"queue": self._cmd_queue,
"version": self._cmd_version,
@@ -1803,25 +1779,10 @@ class HermesACPAgent(acp.Agent):
def _cmd_tools(self, args: str, state: SessionState) -> str:
try:
from model_tools import get_tool_definitions
from types import SimpleNamespace
from agent.memory_manager import inject_memory_provider_tools
toolsets = _expand_acp_enabled_toolsets(
getattr(state.agent, "enabled_toolsets", None) or ["hermes-acp"]
)
tools = get_tool_definitions(enabled_toolsets=toolsets, quiet_mode=True)
tool_view = SimpleNamespace(
tools=list(tools or []),
valid_tool_names={
tool.get("function", {}).get("name")
for tool in tools or []
if isinstance(tool, dict)
},
enabled_toolsets=toolsets,
_memory_manager=getattr(state.agent, "_memory_manager", None),
)
inject_memory_provider_tools(tool_view)
tools = tool_view.tools
if not tools:
return "No tools available."
lines = [f"Available tools ({len(tools)}):"]
@@ -1898,7 +1859,7 @@ class HermesACPAgent(acp.Agent):
lines.append(
f"Compression: due now (threshold ~{threshold_tokens:,}"
+ (f", {threshold_pct:.0f}%" if threshold_pct else "")
+ "). Run /compress."
+ "). Run /compact."
)
else:
lines.append(
@@ -1913,27 +1874,16 @@ class HermesACPAgent(acp.Agent):
if getattr(agent, "compression_enabled", True) is False:
lines.append("Compression is disabled for this agent.")
else:
lines.append("Tip: run /compress to compress manually before the threshold.")
lines.append("Tip: run /compact to compress manually before the threshold.")
return "\n".join(lines)
def _cmd_reset(self, args: str, state: SessionState) -> str:
state.history.clear()
reset_failed = False
try:
reset_session_state = getattr(state.agent, "reset_session_state", None)
if callable(reset_session_state):
reset_session_state()
except Exception:
reset_failed = True
logger.warning("ACP session state reset failed for %s", state.session_id, exc_info=True)
finally:
self.session_manager.save_session(state.session_id)
if reset_failed:
return "Conversation history cleared. Agent session state reset failed; see logs."
self.session_manager.save_session(state.session_id)
return "Conversation history cleared."
def _cmd_compress(self, args: str, state: SessionState) -> str:
def _cmd_compact(self, args: str, state: SessionState) -> str:
if not state.history:
return "Nothing to compress — conversation is empty."
try:
+26 -62
View File
@@ -26,18 +26,31 @@ from typing import Any, Dict, List, Optional
logger = logging.getLogger(__name__)
def _win_path_to_wsl(path: str) -> str | None:
"""Convert a Windows drive path to its WSL /mnt/<drive>/... equivalent."""
match = re.match(r"^([A-Za-z]):[\\/](.*)$", path)
if not match:
return None
drive = match.group(1).lower()
tail = match.group(2).replace("\\", "/")
return f"/mnt/{drive}/{tail}"
def _translate_acp_cwd(cwd: str) -> str:
"""Translate Windows ACP cwd values when Hermes itself is running in WSL.
Windows ACP clients can launch ``hermes acp`` inside WSL while still sending
editor workspaces as Windows drive paths (``E:\\Projects``) or
``\\\\wsl.localhost\\`` UNC paths. Store and execute against the POSIX form so
agents, tools, and persisted ACP sessions all agree on the usable workspace.
Native Linux/macOS keeps the original cwd unchanged.
editor workspaces as Windows drive paths such as ``E:\\Projects``. Store
and execute against the WSL mount path so agents, tools, and persisted ACP
sessions all agree on the usable workspace. Native Linux/macOS keeps the
original cwd unchanged.
"""
from hermes_constants import translate_cwd_for_wsl_backend
from hermes_constants import is_wsl
return translate_cwd_for_wsl_backend(str(cwd))
if not is_wsl():
return cwd
translated = _win_path_to_wsl(str(cwd))
return translated if translated is not None else cwd
def _normalize_cwd_for_compare(cwd: str | None) -> str:
@@ -48,9 +61,7 @@ def _normalize_cwd_for_compare(cwd: str | None) -> str:
# Normalize Windows drive paths into the equivalent WSL mount form so
# ACP history filters match the same workspace across Windows and WSL.
from hermes_constants import windows_path_to_wsl
translated = windows_path_to_wsl(expanded)
translated = _win_path_to_wsl(expanded)
if translated is not None:
expanded = translated
elif re.match(r"^/mnt/[A-Za-z]/", expanded):
@@ -450,47 +461,10 @@ class SessionManager:
except Exception:
logger.debug("Failed to update ACP session metadata", exc_info=True)
# When the agent owns persistence to this same SessionDB it has
# already flushed the live transcript incrementally during
# run_conversation (append_message), and it preserves pre-compaction
# turns non-destructively via archive_and_compact() — keeping them on
# disk as searchable active=0/compacted=1 rows. Calling
# replace_messages() here would then be a redundant double-write that
# DELETEs exactly those archived rows (and, after a compression-driven
# id rotation where agent.session_id no longer equals
# state.session_id, clobbers the ended parent transcript) — silent
# data loss for any ACP conversation long enough to compress.
#
# Only fall back to the destructive atomic replace when the agent is
# NOT persisting itself to this DB (e.g. a test agent factory, or a
# fresh create/fork whose copied history the agent has not flushed
# yet). That path still rolls back on a mid-rewrite failure so the
# previously persisted conversation survives (salvaged from #13675).
agent = state.agent
agent_db = getattr(agent, "_session_db", None)
agent_owns_persistence = (
agent_db is not None
and agent_db is db
and bool(getattr(agent, "_session_db_created", False))
)
if not agent_owns_persistence:
# Even when the current agent doesn't "own" persistence, the
# session on disk may already carry compaction-archived rows —
# e.g. after a model switch or a /restore, both of which mint a
# fresh agent with _session_db_created=False (so the check above
# is False) yet leave the durable archived transcript in place.
# A full-history replace would DELETE those archived rows just
# like the owned-agent case. Guard against it: when archived
# rows exist, replace ONLY the live (active=1) set and leave the
# archived turns untouched; otherwise the destructive replace is
# safe (fresh create/fork with no archived history to lose).
try:
has_archived = db.has_archived_messages(state.session_id)
except Exception:
has_archived = False
db.replace_messages(
state.session_id, state.history, active_only=has_archived
)
# Replace stored messages with current history atomically so a
# mid-rewrite failure rolls back and the previously persisted
# conversation is preserved (salvaged from #13675).
db.replace_messages(state.session_id, state.history)
except Exception:
logger.warning("Failed to persist ACP session %s", state.session_id, exc_info=True)
@@ -534,15 +508,9 @@ class SessionManager:
model = row.get("model") or None
# Load conversation history. repair_alternation: this restore feeds
# LIVE REPLAY — the loaded list becomes the resumed agent's working
# conversation. A durable ``user;user`` violation left in state.db would
# otherwise re-fire the pre-request defensive repair on every request
# for the rest of the session (see hermes_state.get_messages_as_conversation).
# Load conversation history.
try:
history = db.get_messages_as_conversation(
session_id, repair_alternation=True
)
history = db.get_messages_as_conversation(session_id)
except Exception:
logger.warning("Failed to load messages for ACP session %s", session_id, exc_info=True)
history = []
@@ -649,10 +617,6 @@ class SessionManager:
_register_task_cwd(session_id, cwd)
agent = AIAgent(**kwargs)
# Codex app-server sessions are spawned lazily on the first turn. Stamp
# the ACP workspace onto the agent so the Codex runtime starts from the
# editor/session cwd instead of the Hermes daemon's process cwd.
agent.session_cwd = cwd
# ACP stdio transport requires stdout to remain protocol-only JSON-RPC.
# Route any incidental human-readable agent output to stderr instead.
agent._print_fn = _acp_stderr_print
+4 -60
View File
@@ -3,7 +3,6 @@
from __future__ import annotations
import json
import logging
import uuid
from typing import Any, Dict, List, Optional
@@ -15,8 +14,6 @@ from acp.schema import (
ToolKind,
)
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Map hermes tool names -> ACP ToolKind
# ---------------------------------------------------------------------------
@@ -77,7 +74,7 @@ _POLISHED_TOOLS = {
"kanban_create", "kanban_show", "kanban_comment", "kanban_complete",
"kanban_block", "kanban_link", "kanban_heartbeat",
"yb_query_group_info", "yb_query_group_members", "yb_search_sticker",
"yb_send_dm", "yb_send_sticker",
"yb_send_dm", "yb_send_sticker", "mixture_of_agents",
}
@@ -113,12 +110,7 @@ def build_tool_title(tool_name: str, args: Dict[str, Any]) -> str:
if tool_name == "web_extract":
urls = args.get("urls", [])
if urls:
first = urls[0]
if isinstance(first, dict):
first = first.get("url") or first.get("href") or "?"
elif not isinstance(first, str):
first = "?"
return f"extract: {first}" + (f" (+{len(urls)-1})" if len(urls) > 1 else "")
return f"extract: {urls[0]}" + (f" (+{len(urls)-1})" if len(urls) > 1 else "")
return "web extract"
if tool_name == "process":
action = str(args.get("action") or "").strip() or "manage"
@@ -387,24 +379,6 @@ def _format_execute_code_result(result: Optional[str]) -> Optional[str]:
error = str(data.get("error") or "")
exit_code = data.get("exit_code")
parts = [f"Exit code: {exit_code}" if exit_code is not None else "Execution complete"]
if data.get("stdout_truncated"):
total = data.get("stdout_bytes_total")
captured = data.get("stdout_bytes_captured")
omitted = data.get("stdout_bytes_omitted")
if all(isinstance(v, int) for v in (captured, total, omitted)):
parts.extend([
"",
(
"Output truncated: "
f"captured {captured:,} of {total:,} bytes "
f"({omitted:,} omitted)."
),
])
else:
parts.extend(["", "Output truncated."])
warning = str(data.get("warning") or "").strip()
if warning:
parts.extend(["", "Warning:", warning])
if output:
parts.extend(["", "Output:", output])
if error:
@@ -643,7 +617,7 @@ def _format_session_search_result(result: Optional[str]) -> Optional[str]:
return None
mode = data.get("mode") or "search"
query = data.get("query")
lines = ["Recent sessions" if mode == "recent" else "Session search results" + (f" for `{query}`" if query else "")]
lines = ["Recent sessions" if mode == "recent" else f"Session search results" + (f" for `{query}`" if query else "")]
if not results:
lines.append(str(data.get("message") or "No matching sessions found."))
return "\n".join(lines)
@@ -1047,37 +1021,7 @@ def build_tool_start(
*,
edit_diff: Any = None,
) -> ToolCallStart:
"""Create a ToolCallStart event for the given hermes tool invocation.
A malformed tool argument (e.g. a non-string ``command``/``path`` from a
model that ignores the schema) must never abort the ACP tool-call render
``build_tool_start`` runs on the live tool-progress callback and during
session history replay. On any failure in the title/content/location
builders, fall back to a minimal, valid start event. Mirrors
``get_cute_tool_message`` in ``agent/display.py``, wrapped for the same
reason on the CLI side.
"""
try:
return _build_tool_start(
tool_call_id, tool_name, arguments, edit_diff=edit_diff
)
except Exception as exc: # noqa: BLE001 — a tool-call render must never abort the turn
logger.debug("ACP tool-start render failed for %r: %s", tool_name, exc)
safe_name = tool_name if isinstance(tool_name, str) and tool_name else "tool"
return acp.start_tool_call(
tool_call_id, safe_name, kind=get_tool_kind(safe_name),
content=None, locations=[], raw_input=None,
)
def _build_tool_start(
tool_call_id: str,
tool_name: str,
arguments: Dict[str, Any],
*,
edit_diff: Any = None,
) -> ToolCallStart:
"""Build the ToolCallStart event (unguarded; see ``build_tool_start``)."""
"""Create a ToolCallStart event for the given hermes tool invocation."""
kind = get_tool_kind(tool_name)
title = build_tool_title(tool_name, arguments)
locations = extract_locations(arguments)
+2 -2
View File
@@ -1,7 +1,7 @@
{
"id": "hermes-agent",
"name": "Hermes Agent",
"version": "0.19.0",
"version": "0.16.0",
"description": "Self-improving open-source AI agent by Nous Research with ACP editor integration, persistent memory, skills, and rich tool support.",
"repository": "https://github.com/NousResearch/hermes-agent",
"website": "https://hermes-agent.nousresearch.com/docs/user-guide/features/acp",
@@ -9,7 +9,7 @@
"license": "MIT",
"distribution": {
"uvx": {
"package": "hermes-agent[acp]==0.19.0",
"package": "hermes-agent[acp]==0.16.0",
"args": ["hermes-acp"]
}
}
+15 -355
View File
@@ -9,7 +9,7 @@ from typing import TYPE_CHECKING, Any, Optional
import httpx
from agent.anthropic_adapter import _is_oauth_token, resolve_anthropic_token
from hermes_cli.auth import AuthError, _read_codex_tokens, resolve_codex_runtime_credentials
from hermes_cli.auth import _read_codex_tokens, resolve_codex_runtime_credentials
from hermes_cli.runtime_provider import resolve_runtime_provider
if TYPE_CHECKING:
@@ -145,7 +145,7 @@ def build_nous_credits_snapshot(account_info) -> Optional[AccountUsageSnapshot]:
account info to show (fail-open: caller just shows nothing).
"""
try:
from hermes_cli.nous_account import nous_portal_topup_url
from hermes_cli.nous_account import nous_portal_billing_url
if account_info is None or not getattr(account_info, "logged_in", False):
return None
@@ -213,8 +213,7 @@ def build_nous_credits_snapshot(account_info) -> Optional[AccountUsageSnapshot]:
if not windows and not details:
return None
details.append(f"Top up: {nous_portal_topup_url(account_info)}")
details.append("(or run /topup)")
details.append(f"Manage / top up: {nous_portal_billing_url(account_info)}")
plan = getattr(sub, "plan", None) if sub is not None else None
return AccountUsageSnapshot(
@@ -338,189 +337,31 @@ def _snapshot_from_credits_state(state) -> Optional[AccountUsageSnapshot]:
return None
@dataclass(frozen=True)
class CreditsView:
"""Surface-agnostic data for the ``/topup`` balance view.
One portal fetch, one parse consumed identically by the CLI panel, the
gateway button, and any other money surface. Fail-open: when not logged in
or the portal is unreachable, ``logged_in`` is False / ``topup_url`` is None
and callers degrade gracefully.
"""
logged_in: bool
balance_lines: tuple[str, ...] = ()
identity_line: Optional[str] = None
topup_url: Optional[str] = None
depleted: bool = False
def build_credits_view(*, markdown: bool = False, timeout: float = 10.0) -> CreditsView:
"""Build the /topup balance view: balance block + identity line + top-up URL.
Reuses the same account fetch + snapshot + URL builder as the /usage credits
block, so the numbers always match. The balance block is the rendered
snapshot MINUS its trailing top-up/command-hint lines (the /topup surface
supplies its own affordance). Fail-open ``CreditsView(logged_in=False)``.
"""
not_logged_in = CreditsView(logged_in=False)
try:
from hermes_cli.auth import get_provider_auth_state
tok = (get_provider_auth_state("nous") or {}).get("access_token")
if not (isinstance(tok, str) and tok.strip()):
return not_logged_in
except Exception:
return not_logged_in
try:
import concurrent.futures
from hermes_cli.nous_account import (
get_nous_portal_account_info,
nous_portal_topup_url,
)
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
account = pool.submit(get_nous_portal_account_info, force_fresh=True).result(
timeout=timeout
)
except Exception:
logger.debug("credits ▸ /topup portal fetch failed (fail-open)", exc_info=True)
return not_logged_in
if account is None or not getattr(account, "logged_in", False):
return not_logged_in
snapshot = build_nous_credits_snapshot(account)
# Balance lines = the snapshot block minus the two trailing affordance lines
# ("Top up: <url>" + "(or run /topup)") that build_nous_credits_snapshot
# appends for the /usage surface. /topup renders its own button/panel.
balance_lines: list[str] = []
if snapshot is not None:
rendered = render_account_usage_lines(snapshot, markdown=markdown)
balance_lines = [
line
for line in rendered
if not line.lstrip().startswith("Top up:")
and not line.lstrip().startswith("(or run")
]
# Identity line — shown before any open (roadmap §4.4).
email = getattr(account, "email", None)
org_name = getattr(account, "org_name", None)
who: list[str] = []
if email:
who.append(str(email))
if org_name:
who.append(f"org {org_name}")
identity_line = ("Topping up as " + " / ".join(who)) if who else None
return CreditsView(
logged_in=True,
balance_lines=tuple(balance_lines),
identity_line=identity_line,
topup_url=nous_portal_topup_url(account),
depleted=getattr(account, "paid_service_access", None) is False,
)
def _codex_backend_urls(base_url: str) -> tuple[str, str, str]:
"""Resolve the Codex backend endpoints (usage, reset-credits list, consume).
Mirrors the Codex CLI's PathStyle split (codex-rs backend-client): base URLs
containing ``/backend-api`` use the ChatGPT ``/wham/...`` paths; everything
else uses ``/api/codex/...``.
"""
def _resolve_codex_usage_url(base_url: str) -> str:
normalized = (base_url or "").strip().rstrip("/")
if not normalized:
normalized = "https://chatgpt.com/backend-api/codex"
if normalized.endswith("/codex"):
normalized = normalized[: -len("/codex")]
prefix = normalized + ("/wham" if "/backend-api" in normalized else "/api/codex")
return (
prefix + "/usage",
prefix + "/rate-limit-reset-credits",
prefix + "/rate-limit-reset-credits/consume",
)
if "/backend-api" in normalized:
return normalized + "/wham/usage"
return normalized + "/api/codex/usage"
def _resolve_codex_usage_url(base_url: str) -> str:
return _codex_backend_urls(base_url)[0]
def _resolve_codex_usage_credentials(
base_url: Optional[str],
api_key: Optional[str],
) -> tuple[str, str, Optional[str]]:
"""Resolve Codex quota credentials from the native runtime path.
Prefer explicit live-agent credentials, then the legacy singleton OAuth
state, then the credential pool. Hermes's native OAuth setup now stores
device-code logins in the pool, so quota diagnostics must not depend only
on the older singleton store.
"""
explicit_key = str(api_key or "").strip()
if explicit_key:
return explicit_key, str(base_url or "").strip(), None
# Tier 2: the native runtime resolver. It ALREADY falls back to the
# credential pool when the singleton is empty (see
# ``resolve_codex_runtime_credentials`` — issue #32992), so in a pool-only
# setup this returns a usable ``source="credential_pool"`` token.
#
# Only ``AuthError`` ("no creds" / rate-limited) is caught so tier 3 can
# run: a broad ``except Exception`` would (a) mask a transient refresh /
# network failure and silently hand back a DIFFERENT pool account's usage,
# and (b) hide genuine programming errors. A refresh/network error must
# propagate — the outer ``fetch_account_usage`` guard fails open (shows
# nothing this turn) rather than reporting the wrong account.
#
# The ``account_id`` (for the ``ChatGPT-Account-Id`` header) is read
# best-effort: a partial/missing singleton token store must not sink an
# otherwise-usable resolver credential and force a header-less pool fallback.
try:
creds = resolve_codex_runtime_credentials(refresh_if_expiring=True)
account_id: Optional[str] = None
try:
token_data = _read_codex_tokens()
tokens = token_data.get("tokens") or {}
account_id = str(tokens.get("account_id", "") or "").strip() or None
except AuthError:
# Pool-only creds carry no singleton account_id; header is optional.
logger.debug("codex ▸ /usage account_id read failed (best-effort)", exc_info=True)
return creds["api_key"], str(creds.get("base_url", "") or "").strip(), account_id
except AuthError:
logger.debug("codex ▸ /usage runtime resolver returned no creds; trying pool", exc_info=True)
# Tier 3: direct pool select. Reached only when the resolver itself raises
# AuthError (e.g. singleton missing AND its own pool read found nothing at
# resolve time, but a pool entry is usable now). Pool credentials have no
# account_id concept, so the ChatGPT-Account-Id header is intentionally
# omitted here.
from agent.credential_pool import load_pool
pool = load_pool("openai-codex")
entry = pool.select()
if entry is None:
raise RuntimeError("No available openai-codex credential in credential pool")
return entry.runtime_api_key, str(entry.runtime_base_url or base_url or "").strip(), None
def _fetch_codex_account_usage(
base_url: Optional[str] = None,
api_key: Optional[str] = None,
) -> Optional[AccountUsageSnapshot]:
token, resolved_base_url, account_id = _resolve_codex_usage_credentials(base_url, api_key)
def _fetch_codex_account_usage() -> Optional[AccountUsageSnapshot]:
creds = resolve_codex_runtime_credentials(refresh_if_expiring=True)
token_data = _read_codex_tokens()
tokens = token_data.get("tokens") or {}
account_id = str(tokens.get("account_id", "") or "").strip() or None
headers = {
"Authorization": f"Bearer {token}",
"Authorization": f"Bearer {creds['api_key']}",
"Accept": "application/json",
"User-Agent": "codex-cli",
}
if account_id:
headers["ChatGPT-Account-Id"] = account_id
with httpx.Client(timeout=15.0) as client:
response = client.get(_resolve_codex_usage_url(resolved_base_url), headers=headers)
response = client.get(_resolve_codex_usage_url(creds.get("base_url", "")), headers=headers)
response.raise_for_status()
payload = response.json() or {}
rate_limit = payload.get("rate_limit") or {}
@@ -538,14 +379,6 @@ def _fetch_codex_account_usage(
)
)
details: list[str] = []
reset_credits = payload.get("rate_limit_reset_credits") or {}
banked = reset_credits.get("available_count")
if isinstance(banked, (int, float)) and int(banked) > 0:
count = int(banked)
plural = "s" if count != 1 else ""
details.append(
f"You have {count} reset{plural} banked - use /usage reset to activate"
)
credits = payload.get("credits") or {}
if credits.get("has_credits"):
balance = credits.get("balance")
@@ -563,179 +396,6 @@ def _fetch_codex_account_usage(
)
@dataclass(frozen=True)
class CodexResetRedeemResult:
"""Outcome of a `/usage reset` attempt against the Codex backend."""
status: str # reset | nothing_to_reset | no_credit | already_redeemed |
# not_exhausted | no_credits_banked | unavailable
message: str
available_count: int = 0
windows_reset: int = 0
@property
def redeemed(self) -> bool:
return self.status == "reset"
# Client-side guard threshold: a rate-limit window only counts as exhausted
# when it is fully used. Below this, redeeming a banked reset wastes most of
# its value, so we block and point at --force instead.
_CODEX_WINDOW_EXHAUSTED_PERCENT = 100.0
def redeem_codex_reset_credit(
*,
base_url: Optional[str] = None,
api_key: Optional[str] = None,
force: bool = False,
) -> CodexResetRedeemResult:
"""Redeem one banked Codex rate-limit reset credit (`/usage reset`).
Flow (mirrors the Codex CLI's reset-credits picker, codex-rs
``backend-client``):
1. ``GET .../usage`` read the current windows + banked credit count.
2. Guard: zero banked credits refuse. No window fully used and not
``force`` refuse with a warning (a banked reset restores the WHOLE
5h + weekly allowance; burning it early wastes it). The backend has
the same protection (``nothing_to_reset`` doesn't consume the
credit), but failing fast client-side gives a clearer message.
3. ``POST .../rate-limit-reset-credits/consume`` with a fresh UUID
idempotency key (``redeem_request_id``). No ``credit_id`` the
backend picks the next available credit, exactly like the CLI's
default "Full reset" option.
Never raises: every failure mode returns a ``CodexResetRedeemResult``
with a user-renderable message.
"""
import uuid
try:
token, resolved_base_url, account_id = _resolve_codex_usage_credentials(base_url, api_key)
except Exception:
return CodexResetRedeemResult(
status="unavailable",
message="No Codex credentials available. Run `hermes auth` to sign in with your ChatGPT account.",
)
usage_url, _credits_url, consume_url = _codex_backend_urls(resolved_base_url)
headers = {
"Authorization": f"Bearer {token}",
"Accept": "application/json",
"User-Agent": "codex-cli",
}
if account_id:
headers["ChatGPT-Account-Id"] = account_id
try:
with httpx.Client(timeout=15.0) as client:
usage_resp = client.get(usage_url, headers=headers)
usage_resp.raise_for_status()
payload = usage_resp.json() or {}
reset_credits = payload.get("rate_limit_reset_credits") or {}
raw_count = reset_credits.get("available_count")
available = int(raw_count) if isinstance(raw_count, (int, float)) else 0
if available <= 0:
return CodexResetRedeemResult(
status="no_credits_banked",
message="No banked reset credits on this account — nothing to redeem.",
)
rate_limit = payload.get("rate_limit") or {}
worst_used: Optional[float] = None
for key in ("primary_window", "secondary_window"):
used = (rate_limit.get(key) or {}).get("used_percent")
if isinstance(used, (int, float)):
worst_used = max(worst_used or 0.0, float(used))
exhausted = worst_used is not None and worst_used >= _CODEX_WINDOW_EXHAUSTED_PERCENT
if not exhausted and not force:
usage_note = (
f"your busiest window is only {worst_used:.0f}% used"
if worst_used is not None
else "your current usage could not be confirmed as exhausted"
)
plural = "s" if available != 1 else ""
return CodexResetRedeemResult(
status="not_exhausted",
message=(
f"⚠️ Not redeeming: {usage_note}. A banked reset restores your FULL "
f"5h + weekly limits, so spending it now would waste most of it. "
f"You have {available} reset{plural} banked. "
f"Use `/usage reset --force` to redeem anyway."
),
available_count=available,
)
consume_resp = client.post(
consume_url,
headers={**headers, "Content-Type": "application/json"},
json={"redeem_request_id": str(uuid.uuid4())},
)
consume_resp.raise_for_status()
body = consume_resp.json() or {}
except httpx.HTTPStatusError as exc:
code = exc.response.status_code
if code in (401, 403):
return CodexResetRedeemResult(
status="unavailable",
message=(
"Codex backend rejected the request (HTTP "
f"{code}). Reset credits require ChatGPT-account (OAuth) auth — "
"run `hermes auth` and sign in with your ChatGPT account."
),
)
return CodexResetRedeemResult(
status="unavailable",
message=f"Codex backend error (HTTP {code}) — try again shortly.",
)
except Exception as exc:
return CodexResetRedeemResult(
status="unavailable",
message=f"Could not reach the Codex backend: {exc}",
)
code = str(body.get("code", "") or "").strip().lower()
windows_reset = body.get("windows_reset")
windows_reset = int(windows_reset) if isinstance(windows_reset, (int, float)) else 0
remaining = max(0, available - 1)
plural = "s" if remaining != 1 else ""
if code == "reset":
return CodexResetRedeemResult(
status="reset",
message=(
f"✅ Reset redeemed — your usage limits have been reset. "
f"{remaining} banked reset{plural} remaining."
),
available_count=remaining,
windows_reset=windows_reset,
)
if code == "nothing_to_reset":
return CodexResetRedeemResult(
status="nothing_to_reset",
message=(
"Backend reports nothing to reset — your limits aren't exhausted. "
"The credit was NOT spent."
),
available_count=available,
)
if code == "no_credit":
return CodexResetRedeemResult(
status="no_credit",
message="Backend reports no available reset credit on this account.",
)
if code == "already_redeemed":
return CodexResetRedeemResult(
status="already_redeemed",
message="This redemption was already processed — no additional credit was spent.",
available_count=remaining,
)
return CodexResetRedeemResult(
status="unavailable",
message=f"Unexpected response from the Codex backend: {body!r}",
)
def _fetch_anthropic_account_usage() -> Optional[AccountUsageSnapshot]:
token = (resolve_anthropic_token() or "").strip()
if not token:
@@ -880,7 +540,7 @@ def fetch_account_usage(
return None
try:
if normalized == "openai-codex":
return _fetch_codex_account_usage(base_url=base_url, api_key=api_key)
return _fetch_codex_account_usage()
if normalized == "anthropic":
return _fetch_anthropic_account_usage()
if normalized == "openrouter":
+102 -915
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+129 -442
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@@ -65,7 +65,6 @@ THINKING_BUDGET = {"xhigh": 32000, "high": 16000, "medium": 8000, "low": 4000}
# maps to low on every model. See:
# https://platform.claude.com/docs/en/about-claude/models/migration-guide
ADAPTIVE_EFFORT_MAP = {
"ultra": "max",
"max": "max",
"xhigh": "xhigh",
"high": "high",
@@ -127,8 +126,6 @@ _FAST_MODE_SUPPORTED_SUBSTRINGS = ("opus-4-6", "opus-4.6")
_ANTHROPIC_OUTPUT_LIMITS = {
# Mythos-class named models (claude-fable-5, …) — 1M context, reasoning
"claude-fable": 128_000,
# Claude Sonnet 5
"claude-sonnet-5": 128_000,
# Claude 4.8
"claude-opus-4-8": 128_000,
# Claude 4.7
@@ -249,13 +246,7 @@ def _supports_adaptive_thinking(model: str) -> bool:
only returns False for the explicit legacy list of older Claude families
that require manual budget-based thinking. Non-Claude Anthropic-Messages
models (minimax, qwen3, ) return False so they keep the manual path.
Kimi / Moonshot models are the exception: their Anthropic-compatible
endpoints implement the adaptive contract (``thinking.type="adaptive"``
+ ``output_config.effort``, including ``xhigh`` and ``display``).
"""
if _model_name_is_kimi_family(model):
return True
if not _is_claude_model(model):
return False
m = model.lower()
@@ -381,7 +372,7 @@ def _detect_claude_code_version() -> str:
_CLAUDE_CODE_SYSTEM_PREFIX = "You are Claude Code, Anthropic's official CLI for Claude."
_MCP_TOOL_PREFIX = "mcp__"
_MCP_TOOL_PREFIX = "mcp_"
def _get_claude_code_version() -> str:
@@ -457,8 +448,7 @@ def _is_kimi_coding_endpoint(base_url: str | None) -> bool:
# Model-name prefixes that identify the Kimi / Moonshot family. Covers
# - official slugs: ``kimi-k2.5``, ``kimi_thinking``, ``moonshot-v1-8k``
# - common release lines: ``k1.5-...``, ``k2-thinking``, ``k25-...``, ``k2.5-...``,
# and the bare Coding Plan slug ``k3`` (plus ``k3.x``/``k3-...`` variants)
# - common release lines: ``k1.5-...``, ``k2-thinking``, ``k25-...``, ``k2.5-...``
# Matched case-insensitively against the post-``normalize_model_name`` form,
# so a caller's ``provider/vendor/model`` slug is handled the same as a
# bare name.
@@ -468,14 +458,8 @@ _KIMI_FAMILY_MODEL_PREFIXES = (
"k1.", "k1-",
"k2.", "k2-",
"k25", "k2.5",
"k3.", "k3-",
)
# Bare release slugs with no separator suffix (Kimi Coding Plan serves K3
# as the exact slug ``k3``). Kept exact-match so unrelated model names that
# merely start with the same characters don't get misclassified.
_KIMI_FAMILY_EXACT_SLUGS = frozenset({"k3"})
def _model_name_is_kimi_family(model: str | None) -> bool:
if not isinstance(model, str):
@@ -486,8 +470,6 @@ def _model_name_is_kimi_family(model: str | None) -> bool:
# Strip vendor prefix (e.g. ``moonshotai/kimi-k2.5`` → ``kimi-k2.5``)
if "/" in m:
m = m.rsplit("/", 1)[-1]
if m in _KIMI_FAMILY_EXACT_SLUGS:
return True
return m.startswith(_KIMI_FAMILY_MODEL_PREFIXES)
@@ -551,9 +533,8 @@ def _requires_bearer_auth(base_url: str | None) -> bool:
Some third-party /anthropic endpoints implement Anthropic's Messages API but
require Authorization: Bearer instead of Anthropic's native x-api-key header.
MiniMax's global and China Anthropic-compatible endpoints, Azure AI
Foundry's Anthropic-style endpoint, and Palantir Foundry's LLM proxy
follow this pattern.
MiniMax's global and China Anthropic-compatible endpoints, and Azure AI
Foundry's Anthropic-style endpoint follow this pattern.
"""
normalized = _normalize_base_url_text(base_url)
if not normalized:
@@ -562,11 +543,6 @@ def _requires_bearer_auth(base_url: str | None) -> bool:
return (
normalized.startswith(("https://api.minimax.io/anthropic", "https://api.minimaxi.com/anthropic"))
or "azure.com" in normalized
# Palantir Foundry LLM proxy (<org>.palantirfoundry.com/api/v2/llm/proxy/anthropic)
# rejects x-api-key with 401 and requires Authorization: Bearer.
# Hostname match (not substring) so e.g. evil.com/palantirfoundry
# paths don't trigger Bearer auth.
or base_url_host_matches(normalized, "palantirfoundry.com")
)
@@ -697,9 +673,6 @@ def _build_anthropic_client_with_bearer_hook(
kwargs = {
"timeout": timeout_obj,
"http_client": http_client,
# Delegate retry to hermes's outer loop (honors Retry-After); the SDK
# default max_retries=2 ignores it and double-retries. (#26293)
"max_retries": 0,
# The SDK requires *something* for api_key/auth_token. Our
# event hook overrides Authorization per request so this value
# is never sent. The sentinel string makes accidental leaks
@@ -778,18 +751,9 @@ def build_anthropic_client(
from httpx import Timeout
normalized_base_url = _normalize_base_url_text(base_url)
if normalized_base_url:
import re as _re
normalized_base_url = _re.sub(r"/v1/?$", "", normalized_base_url.rstrip("/"))
_read_timeout = timeout if (isinstance(timeout, (int, float)) and timeout > 0) else 900.0
kwargs = {
"timeout": Timeout(timeout=float(_read_timeout), connect=10.0),
# Delegate all rate-limit / 5xx retry to hermes's outer conversation
# loop, which honors Retry-After. The SDK default (max_retries=2) uses
# its own 1-2s backoff that ignores Retry-After and double-retries
# inside our loop — burning request slots against a bucket that won't
# refill for minutes. (#26293)
"max_retries": 0,
}
if normalized_base_url:
# Azure Anthropic endpoints require an ``api-version`` query parameter.
@@ -841,7 +805,7 @@ def build_anthropic_client(
kwargs["auth_token"] = api_key
kwargs["default_headers"] = {
"anthropic-beta": ",".join(all_betas),
"user-agent": f"claude-code/{_get_claude_code_version()} (external, cli)",
"user-agent": f"claude-cli/{_get_claude_code_version()} (external, cli)",
"x-app": "cli",
}
else:
@@ -885,9 +849,6 @@ def build_anthropic_bedrock_client(region: str):
return _anthropic_sdk.AnthropicBedrock(
aws_region=region,
timeout=Timeout(timeout=900.0, connect=10.0),
# Delegate retry to hermes's outer loop (honors Retry-After); the SDK
# default max_retries=2 ignores it and double-retries. (#26293)
max_retries=0,
default_headers={"anthropic-beta": ",".join([*_COMMON_BETAS, _CONTEXT_1M_BETA])},
)
@@ -950,72 +911,44 @@ def _read_claude_code_credentials_from_keychain() -> Optional[Dict[str, Any]]:
return None
def _read_claude_code_credentials_from_file() -> Optional[Dict[str, Any]]:
"""Read Claude Code OAuth credentials from ~/.claude/.credentials.json.
Returns dict with {accessToken, refreshToken?, expiresAt?, source} or None.
"""
cred_path = Path.home() / ".claude" / ".credentials.json"
if not cred_path.exists():
return None
try:
data = json.loads(cred_path.read_text(encoding="utf-8"))
except (json.JSONDecodeError, OSError, IOError) as e:
logger.debug("Failed to read ~/.claude/.credentials.json: %s", e)
return None
oauth_data = data.get("claudeAiOauth")
if not (oauth_data and isinstance(oauth_data, dict)):
return None
access_token = oauth_data.get("accessToken", "")
if not access_token:
return None
return {
"accessToken": access_token,
"refreshToken": oauth_data.get("refreshToken", ""),
"expiresAt": oauth_data.get("expiresAt", 0),
"source": "claude_code_credentials_file",
}
def read_claude_code_credentials() -> Optional[Dict[str, Any]]:
"""Read refreshable Claude Code OAuth credentials.
Reads from two possible sources and reconciles them:
Checks two sources in order:
1. macOS Keychain (Darwin only) "Claude Code-credentials" entry
2. ~/.claude/.credentials.json file
Selection rules when both are present:
- If exactly one is non-expired, prefer that one. (Handles the case
where Claude Code refreshes one source but not the other observed
in the wild on Claude Code 2.1.x.)
- Otherwise, prefer the source with the later ``expiresAt`` so that
any subsequent refresh uses the most recent ``refreshToken``.
This intentionally excludes ~/.claude.json primaryApiKey. Opencode's
subscription flow is OAuth/setup-token based with refreshable credentials,
and native direct Anthropic provider usage should follow that path rather
than auto-detecting Claude's first-party managed key.
Returns dict with {accessToken, refreshToken?, expiresAt?, source} or None.
Returns dict with {accessToken, refreshToken?, expiresAt?} or None.
"""
# Try macOS Keychain first (covers Claude Code >=2.1.114)
kc_creds = _read_claude_code_credentials_from_keychain()
file_creds = _read_claude_code_credentials_from_file()
if kc_creds:
return kc_creds
if kc_creds and file_creds:
kc_valid = is_claude_code_token_valid(kc_creds)
file_valid = is_claude_code_token_valid(file_creds)
if kc_valid and not file_valid:
return kc_creds
if file_valid and not kc_valid:
return file_creds
# Both valid or both expired: prefer the later expiresAt so the
# downstream refresh path uses the freshest refresh_token.
kc_exp = kc_creds.get("expiresAt", 0) or 0
file_exp = file_creds.get("expiresAt", 0) or 0
return kc_creds if kc_exp >= file_exp else file_creds
# Fall back to JSON file
cred_path = Path.home() / ".claude" / ".credentials.json"
if cred_path.exists():
try:
data = json.loads(cred_path.read_text(encoding="utf-8"))
oauth_data = data.get("claudeAiOauth")
if oauth_data and isinstance(oauth_data, dict):
access_token = oauth_data.get("accessToken", "")
if access_token:
return {
"accessToken": access_token,
"refreshToken": oauth_data.get("refreshToken", ""),
"expiresAt": oauth_data.get("expiresAt", 0),
"source": "claude_code_credentials_file",
}
except (json.JSONDecodeError, OSError, IOError) as e:
logger.debug("Failed to read ~/.claude/.credentials.json: %s", e)
return kc_creds or file_creds
return None
def is_claude_code_token_valid(creds: Dict[str, Any]) -> bool:
@@ -1069,7 +1002,7 @@ def refresh_anthropic_oauth_pure(refresh_token: str, *, use_json: bool = False)
data=data,
headers={
"Content-Type": content_type,
"User-Agent": _OAUTH_TOKEN_USER_AGENT,
"User-Agent": f"claude-cli/{_get_claude_code_version()} (external, cli)",
},
method="POST",
)
@@ -1098,40 +1031,8 @@ def refresh_anthropic_oauth_pure(refresh_token: str, *, use_json: bool = False)
def _refresh_oauth_token(creds: Dict[str, Any]) -> Optional[str]:
"""Attempt to refresh an expired Claude Code OAuth token.
Claude Code's OAuth refresh tokens are single-use: a successful refresh
rotates the pair and invalidates the old refresh token. Claude Code itself
also refreshes on its own schedule (IDE/CLI activity), so by the time
Hermes notices an expired token, Claude Code may have already rotated it.
POSTing our now-stale refresh token in that window races Claude Code and
fails with ``invalid_grant``.
So before refreshing, re-read the live credential sources. If Claude Code
has already produced a valid token, adopt it and skip the POST entirely.
Only fall back to refreshing ourselves when no fresh credential is found.
"""
# Claude Code may have already refreshed — adopt its token rather than
# racing it with our (possibly already-rotated) refresh token. Only adopt
# when the live re-read produced a DIFFERENT token with a real future
# expiry: re-adopting the same credential we were just handed would be a
# no-op, and a 0/absent ``expiresAt`` means "managed key / unknown expiry"
# (see is_claude_code_token_valid) which must NOT be treated as a fresh
# refresh here.
current = read_claude_code_credentials()
if current:
current_token = current.get("accessToken", "")
current_exp = current.get("expiresAt", 0) or 0
if (
current_token
and current_token != creds.get("accessToken", "")
and current_exp > 0
and is_claude_code_token_valid(current)
):
logger.debug("Adopted Claude Code's already-refreshed OAuth token")
return current_token
refresh_token = (current or {}).get("refreshToken", "") or creds.get("refreshToken", "")
"""Attempt to refresh an expired Claude Code OAuth token."""
refresh_token = creds.get("refreshToken", "")
if not refresh_token:
logger.debug("No refresh token available — cannot refresh")
return None
@@ -1255,46 +1156,6 @@ def _prefer_refreshable_claude_code_token(env_token: str, creds: Optional[Dict[s
return None
def _resolve_anthropic_pool_token() -> Optional[str]:
"""Return the first available Anthropic OAuth token from credential_pool.
Read-only: enumerates with ``clear_expired=False, refresh=False`` so a bare
token *resolve* (which runs from diagnostic/read-only call sites such as
``account_usage`` and ``hermes models``) never mutates ``~/.hermes/auth.json``
or makes a network refresh call. Refresh-on-expiry is owned by the API call
path's pool recovery, not the resolver.
"""
try:
from agent.credential_pool import AUTH_TYPE_OAUTH, load_pool
except Exception:
return None
try:
pool = load_pool("anthropic")
# Enumerate read-only (clear_expired=False, refresh=False): never persist
# to auth.json or trigger a network refresh from a bare resolve. select()
# is deliberately NOT used — it runs clear_expired=True, refresh=True,
# which would violate this read-only contract.
entries = pool._available_entries(clear_expired=False, refresh=False)
except Exception:
logger.debug("Failed to read Anthropic credential_pool", exc_info=True)
return None
for entry in entries:
if getattr(entry, "auth_type", None) != AUTH_TYPE_OAUTH:
continue
# access_token is a declared field but a persisted entry can carry an
# explicit null (or a partially-written OAuth entry), so coerce before
# strip — a bare None.strip() here would escape the try/excepts above
# and crash the whole resolver, taking down the source #5 fallback too.
# Matches the aux-client analog (auxiliary_client.py: str(key or "")).
token = (getattr(entry, "access_token", None) or "").strip()
if token:
return token
return None
def resolve_anthropic_token() -> Optional[str]:
"""Resolve an Anthropic token from all available sources.
@@ -1303,8 +1164,7 @@ def resolve_anthropic_token() -> Optional[str]:
2. CLAUDE_CODE_OAUTH_TOKEN env var
3. Claude Code credentials (~/.claude.json or ~/.claude/.credentials.json)
with automatic refresh if expired and a refresh token is available
4. Anthropic credential_pool OAuth entry (~/.hermes/auth.json)
5. ANTHROPIC_API_KEY env var (regular API key, or legacy fallback)
4. ANTHROPIC_API_KEY env var (regular API key, or legacy fallback)
Returns the token string or None.
"""
@@ -1331,12 +1191,7 @@ def resolve_anthropic_token() -> Optional[str]:
if resolved_claude_token:
return resolved_claude_token
# 4. Hermes credential_pool OAuth entry.
resolved_pool_token = _resolve_anthropic_pool_token()
if resolved_pool_token:
return resolved_pool_token
# 5. Regular API key, or a legacy OAuth token saved in ANTHROPIC_API_KEY.
# 4. Regular API key, or a legacy OAuth token saved in ANTHROPIC_API_KEY.
# This remains as a compatibility fallback for pre-migration Hermes configs.
api_key = os.getenv("ANTHROPIC_API_KEY", "").strip()
if api_key:
@@ -1393,29 +1248,10 @@ def run_oauth_setup_token() -> Optional[str]:
# Stores credentials in ~/.hermes/.anthropic_oauth.json (our own file).
_OAUTH_CLIENT_ID = "9d1c250a-e61b-44d9-88ed-5944d1962f5e"
# Anthropic migrated the OAuth token endpoint to platform.claude.com;
# console.anthropic.com now 404s. Callers should iterate _OAUTH_TOKEN_URLS
# (new host first, console fallback). _OAUTH_TOKEN_URL is kept as the primary
# for backward compatibility with existing imports and now points at the live host.
_OAUTH_TOKEN_URLS = [
"https://platform.claude.com/v1/oauth/token",
"https://console.anthropic.com/v1/oauth/token",
]
_OAUTH_TOKEN_URL = _OAUTH_TOKEN_URLS[0]
# User-Agent sent on the OAuth *token endpoint* (login exchange + refresh).
# Anthropic rate-limits (HTTP 429) any token-endpoint request whose UA starts
# with ``claude-code/`` — verified empirically against platform.claude.com:
# ``claude-code/2.1.200`` and ``Mozilla/5.0`` -> 429; ``axios/*``, ``node``,
# and SDK-style UAs -> 400 (reached code validation). The real Claude Code CLI
# exchanges the auth code with a bare axios client (``axios/<ver>``), NOT its
# ``claude-code/`` inference UA. We mirror that here. NOTE: the *inference* path
# (build_anthropic_kwargs) still uses the ``claude-code/`` UA + ``x-app: cli`` —
# that fingerprint is required there and is NOT throttled on the messages API.
_OAUTH_TOKEN_USER_AGENT = "axios/1.7.9"
_OAUTH_TOKEN_URL = "https://console.anthropic.com/v1/oauth/token"
_OAUTH_REDIRECT_URI = "https://console.anthropic.com/oauth/code/callback"
_OAUTH_SCOPES = "org:create_api_key user:profile user:inference"
def _get_hermes_oauth_file() -> Path:
return get_hermes_home() / ".anthropic_oauth.json"
_HERMES_OAUTH_FILE = get_hermes_home() / ".anthropic_oauth.json"
def _generate_pkce() -> tuple:
@@ -1510,37 +1346,18 @@ def run_hermes_oauth_login_pure() -> Optional[Dict[str, Any]]:
"code_verifier": verifier,
}).encode()
# Anthropic migrated the OAuth token endpoint to platform.claude.com;
# console.anthropic.com now 404s. Try the new host first, then fall
# back to console for older deployments (mirrors the refresh path).
# UA is _OAUTH_TOKEN_USER_AGENT (a non-claude-code UA) — see the
# constant's definition for why the token endpoint must not send
# claude-code/ (429 UA-prefix block).
result = None
last_error = None
for endpoint in _OAUTH_TOKEN_URLS:
req = urllib.request.Request(
endpoint,
data=exchange_data,
headers={
"Content-Type": "application/json",
"User-Agent": _OAUTH_TOKEN_USER_AGENT,
},
method="POST",
)
try:
with urllib.request.urlopen(req, timeout=15) as resp:
result = json.loads(resp.read().decode())
break
except Exception as exc:
last_error = exc
logger.debug("Anthropic token exchange failed at %s: %s", endpoint, exc)
continue
req = urllib.request.Request(
_OAUTH_TOKEN_URL,
data=exchange_data,
headers={
"Content-Type": "application/json",
"User-Agent": f"claude-cli/{_get_claude_code_version()} (external, cli)",
},
method="POST",
)
if result is None:
raise last_error if last_error is not None else ValueError(
"Anthropic token exchange failed"
)
with urllib.request.urlopen(req, timeout=15) as resp:
result = json.loads(resp.read().decode())
except Exception as e:
print(f"Token exchange failed: {e}")
return None
@@ -1563,10 +1380,9 @@ def run_hermes_oauth_login_pure() -> Optional[Dict[str, Any]]:
def read_hermes_oauth_credentials() -> Optional[Dict[str, Any]]:
"""Read Hermes-managed OAuth credentials from ~/.hermes/.anthropic_oauth.json."""
oauth_file = _get_hermes_oauth_file()
if oauth_file.exists():
if _HERMES_OAUTH_FILE.exists():
try:
data = json.loads(oauth_file.read_text(encoding="utf-8"))
data = json.loads(_HERMES_OAUTH_FILE.read_text(encoding="utf-8"))
if data.get("accessToken"):
return data
except (json.JSONDecodeError, OSError, IOError) as e:
@@ -1591,10 +1407,7 @@ def _is_bedrock_model_id(model: str) -> bool:
"""
lower = model.lower()
# Regional inference-profile prefixes
if any(lower.startswith(p) for p in (
"global.", "us.", "eu.", "apac.", "ap.", "au.", "jp.",
"ca.", "sa.", "me.", "af.",
)):
if any(lower.startswith(p) for p in ("global.", "us.", "eu.", "ap.", "jp.")):
return True
# Bare Bedrock model IDs: provider.model-family
if lower.startswith("anthropic."):
@@ -1933,18 +1746,6 @@ def _sanitize_replay_block(b: Dict[str, Any]) -> Optional[Dict[str, Any]]:
return None
def _apply_assistant_cache_control_to_last_cacheable_block(
blocks: List[Dict[str, Any]],
cache_control: Any,
) -> None:
if not isinstance(cache_control, dict):
return
for block in reversed(blocks):
if isinstance(block, dict) and block.get("type") in {"text", "tool_use"}:
block.setdefault("cache_control", dict(cache_control))
break
def _convert_assistant_message(m: Dict[str, Any]) -> Dict[str, Any]:
"""Convert an assistant message to Anthropic content blocks.
@@ -1999,9 +1800,6 @@ def _convert_assistant_message(m: Dict[str, Any]) -> Dict[str, Any]:
clean["input"] = redacted
replayed.append(clean)
if replayed:
_apply_assistant_cache_control_to_last_cacheable_block(
replayed, m.get("cache_control")
)
return {"role": "assistant", "content": replayed}
blocks = _extract_preserved_thinking_blocks(m)
@@ -2027,9 +1825,6 @@ def _convert_assistant_message(m: Dict[str, Any]) -> Dict[str, Any]:
"name": fn.get("name", ""),
"input": parsed_args,
})
_apply_assistant_cache_control_to_last_cacheable_block(
blocks, m.get("cache_control")
)
# Kimi's /coding endpoint (Anthropic protocol) requires assistant
# tool-call messages to carry reasoning_content when thinking is
# enabled server-side. Preserve it as a thinking block so Kimi
@@ -2129,7 +1924,7 @@ def _convert_user_message(content: Any) -> Dict[str, Any]:
if isinstance(content, list):
converted_blocks = _convert_content_to_anthropic(content)
if not converted_blocks or all(
(b.get("text") or "").strip() == ""
b.get("text", "").strip() == ""
for b in converted_blocks
if isinstance(b, dict) and b.get("type") == "text"
):
@@ -2145,81 +1940,57 @@ def _strip_orphaned_tool_blocks(result: List[Dict[str, Any]]) -> None:
"""Strip tool_use blocks with no matching tool_result, and vice versa.
Context compression or session truncation can remove either side of a
tool-call pair, or insert messages between a tool_use and its result.
Anthropic requires each tool_use to have a matching tool_result in the
IMMEDIATELY FOLLOWING user message a global ID match is not enough.
tool-call pair. Anthropic rejects both orphans with HTTP 400.
Mutates ``result`` in place.
"""
# Pass 1: For each assistant message with tool_use blocks, check that
# EACH tool_use ID has a matching tool_result in the immediately following
# user message. Strip tool_use blocks that lack an adjacent result —
# Anthropic rejects non-adjacent pairs with HTTP 400 even when the IDs
# match somewhere later in the conversation.
for i, m in enumerate(result):
if m.get("role") != "assistant" or not isinstance(m.get("content"), list):
continue
tool_use_ids_in_turn = {
b.get("id")
for b in m["content"]
if isinstance(b, dict) and b.get("type") == "tool_use"
}
if not tool_use_ids_in_turn:
continue
# Collect result IDs from the immediately following user message only.
adjacent_result_ids: set = set()
if i + 1 < len(result):
nxt = result[i + 1]
if nxt.get("role") == "user" and isinstance(nxt.get("content"), list):
for block in nxt["content"]:
if isinstance(block, dict) and block.get("type") == "tool_result":
adjacent_result_ids.add(block.get("tool_use_id"))
orphaned = tool_use_ids_in_turn - adjacent_result_ids
if not orphaned:
continue
kept = [
b
for b in m["content"]
if not (isinstance(b, dict) and b.get("type") == "tool_use" and b.get("id") in orphaned)
]
# If stripping an orphaned tool_use mutated a turn that also carries a
# signed thinking block, that block's Anthropic signature was computed
# against the ORIGINAL (un-stripped) turn content and is now invalid.
# Anthropic rejects the replayed turn with HTTP 400 "thinking blocks in
# the latest assistant message cannot be modified". Flag the turn so
# _manage_thinking_signatures can demote the dead signature instead of
# replaying it verbatim. See hermes-agent: extended-thinking + parallel
# tool batch interrupted mid-flight → non-retryable 400 crash-loop.
if len(kept) != len(m["content"]) and any(
isinstance(b, dict) and b.get("type") in {"thinking", "redacted_thinking"}
for b in m["content"]
):
m["_thinking_signature_invalidated"] = True
m["content"] = kept if kept else [{"type": "text", "text": "(tool call removed)"}]
# Pass 2: Rebuild the set of tool_use IDs that survived pass 1, then
# strip tool_result blocks that no longer have any matching tool_use
# anywhere in the conversation.
surviving_tool_use_ids: set = set()
# Strip orphaned tool_use blocks (no matching tool_result follows)
tool_result_ids = set()
for m in result:
if m.get("role") == "assistant" and isinstance(m.get("content"), list):
if m["role"] == "user" and isinstance(m["content"], list):
for block in m["content"]:
if isinstance(block, dict) and block.get("type") == "tool_use":
surviving_tool_use_ids.add(block.get("id"))
if block.get("type") == "tool_result":
tool_result_ids.add(block.get("tool_use_id"))
for m in result:
if m.get("role") != "user" or not isinstance(m.get("content"), list):
continue
new_content = [
b
for b in m["content"]
if not (isinstance(b, dict) and b.get("type") == "tool_result")
or b.get("tool_use_id") in surviving_tool_use_ids
]
if len(new_content) != len(m["content"]):
m["content"] = new_content if new_content else [{"type": "text", "text": "(tool result removed)"}]
if m["role"] == "assistant" and isinstance(m["content"], list):
kept = [
b
for b in m["content"]
if b.get("type") != "tool_use" or b.get("id") in tool_result_ids
]
# If stripping an orphaned tool_use mutated a turn that also carries a
# signed thinking block, that block's Anthropic signature was computed
# against the ORIGINAL (un-stripped) turn content and is now invalid.
# Anthropic rejects the replayed turn with HTTP 400 "thinking blocks in
# the latest assistant message cannot be modified". Flag the turn so
# _manage_thinking_signatures can demote the dead signature instead of
# replaying it verbatim. See hermes-agent: extended-thinking + parallel
# tool batch interrupted mid-flight → non-retryable 400 crash-loop.
if len(kept) != len(m["content"]) and any(
isinstance(b, dict) and b.get("type") in {"thinking", "redacted_thinking"}
for b in m["content"]
):
m["_thinking_signature_invalidated"] = True
m["content"] = kept
if not m["content"]:
m["content"] = [{"type": "text", "text": "(tool call removed)"}]
# Strip orphaned tool_result blocks (no matching tool_use precedes them)
tool_use_ids = set()
for m in result:
if m["role"] == "assistant" and isinstance(m["content"], list):
for block in m["content"]:
if block.get("type") == "tool_use":
tool_use_ids.add(block.get("id"))
for m in result:
if m["role"] == "user" and isinstance(m["content"], list):
m["content"] = [
b
for b in m["content"]
if b.get("type") != "tool_result" or b.get("tool_use_id") in tool_use_ids
]
if not m["content"]:
m["content"] = [{"type": "text", "text": "(tool result removed)"}]
def _merge_consecutive_roles(result: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
@@ -2296,6 +2067,13 @@ def _manage_thinking_signatures(
"""
_THINKING_TYPES = frozenset(("thinking", "redacted_thinking"))
_is_third_party = _is_third_party_anthropic_endpoint(base_url)
# Kimi / DeepSeek share a contract: strip signed Anthropic blocks
# (neither upstream can validate Anthropic signatures), preserve unsigned
# ones synthesised from reasoning_content. See #13848, #16748.
_preserve_unsigned_thinking = (
_is_kimi_family_endpoint(base_url, model)
or _is_deepseek_anthropic_endpoint(base_url)
)
last_assistant_idx = None
for i in range(len(result) - 1, -1, -1):
@@ -2307,12 +2085,8 @@ def _manage_thinking_signatures(
if m.get("role") != "assistant" or not isinstance(m.get("content"), list):
continue
if _is_kimi_family_endpoint(base_url, model):
# Kimi does not enforce thinking signatures — replay as-is
# (shared cleanup below still strips cache markers + the internal flag).
pass
elif _is_deepseek_anthropic_endpoint(base_url):
# DeepSeek: strip signed, preserve unsigned.
if _preserve_unsigned_thinking:
# Kimi / DeepSeek: strip signed, preserve unsigned.
new_content = []
for b in m["content"]:
if not isinstance(b, dict) or b.get("type") not in _THINKING_TYPES:
@@ -2412,24 +2186,6 @@ def _evict_old_screenshots(result: List[Dict[str, Any]]) -> None:
]
def _ensure_leading_user_turn(result: List[Dict[str, Any]]) -> None:
"""Anthropic requires messages[0] to have role=user.
After a second context compaction on the auto path the summary can be
emitted as role=assistant with nothing in front of it (the system prompt
lives outside messages[] or is extracted into the separate ``system``
param), so messages[0] ends up assistant and the Messages API rejects
the request with HTTP 400 often masked by a misleading
"tool_use ids were found without tool_result blocks" error (#52160).
Mirror the Bedrock Converse adapter, which unconditionally prepends a
minimal user turn when the first message is not user
(convert_messages_to_converse).
"""
if result and result[0].get("role") != "user":
result.insert(0, {"role": "user", "content": [{"type": "text", "text": " "}]})
def convert_messages_to_anthropic(
messages: List[Dict],
base_url: str | None = None,
@@ -2488,7 +2244,6 @@ def convert_messages_to_anthropic(
_strip_orphaned_tool_blocks(result)
result = _merge_consecutive_roles(result)
_ensure_leading_user_turn(result)
_manage_thinking_signatures(result, base_url, model)
_evict_old_screenshots(result)
@@ -2591,46 +2346,25 @@ def build_anthropic_kwargs(
text = text.replace("Nous Research", "Anthropic")
block["text"] = text
# 3. Normalize tool names so NOTHING goes on the OAuth wire with a
# single-underscore ``mcp_`` prefix. Anthropic's subscription/OAuth
# billing classifier treats a single-underscore ``mcp_`` tool name as
# a third-party-app fingerprint and rejects the request with HTTP 400
# "Third-party apps now draw from extra usage, not plan limits"
# (verified empirically: a single ``mcp_foo`` tool flips a request
# from plan-billing to the extra-usage lane; ``mcp__foo`` is accepted).
#
# Two cases, both must land on the double-underscore ``mcp__`` form:
# a) bare Hermes-native tools (``read_file``) -> ``mcp__read_file``
# b) native MCP server tools registered under their full
# single-underscore ``mcp_<server>_<tool>`` name
# (``mcp_linear_get_issue``) -> ``mcp__linear_get_issue``
# Case (b) is the gap that the bare ``mcp_``->``mcp__`` constant swap
# left open: those tools were *skipped* and stayed single-underscore,
# so any session with an MCP server configured still tripped the
# classifier. normalize_response reverses both forms via registry
# lookup so the dispatcher still sees the original name. GH-25255.
def _to_oauth_wire_name(name: str) -> str:
if name.startswith("mcp__"):
return name # already correct, don't double-prefix
if name.startswith("mcp_"):
# single-underscore native MCP tool -> promote to double
return "mcp__" + name[len("mcp_"):]
return _MCP_TOOL_PREFIX + name # bare name -> mcp__<name>
# 3. Prefix tool names with mcp_ (Claude Code convention)
# Skip names that already begin with the marker — native MCP server
# tools (from mcp_servers: in config.yaml) are registered under their
# full mcp_<server>_<tool> name and would double-prefix otherwise,
# breaking round-trip registry lookup in normalize_response. GH-25255.
if anthropic_tools:
for tool in anthropic_tools:
if "name" in tool:
tool["name"] = _to_oauth_wire_name(tool["name"])
if "name" in tool and not tool["name"].startswith(_MCP_TOOL_PREFIX):
tool["name"] = _MCP_TOOL_PREFIX + tool["name"]
# 4. Apply the same normalization to tool names in message history
# (tool_use blocks) so replayed turns match the wire names above.
# 4. Prefix tool names in message history (tool_use and tool_result blocks)
for msg in anthropic_messages:
content = msg.get("content")
if isinstance(content, list):
for block in content:
if isinstance(block, dict):
if block.get("type") == "tool_use" and "name" in block:
block["name"] = _to_oauth_wire_name(block["name"])
if not block["name"].startswith(_MCP_TOOL_PREFIX):
block["name"] = _MCP_TOOL_PREFIX + block["name"]
elif block.get("type") == "tool_result" and "tool_use_id" in block:
pass # tool_result uses ID, not name
@@ -2663,19 +2397,25 @@ def build_anthropic_kwargs(
# MiniMax Anthropic-compat endpoints support thinking (manual mode only,
# not adaptive). Haiku does NOT support extended thinking — skip entirely.
#
# Kimi / Moonshot models also use adaptive thinking: their
# Anthropic-compatible endpoints (api.moonshot.cn/anthropic,
# api.kimi.com/coding) accept ``thinking.type="adaptive"`` +
# ``output_config.effort``, and the replay-validation 400s that
# originally motivated dropping the parameter (#13848) no longer
# occur. (Kimi on chat_completions enables thinking via extra_body
# in the ChatCompletionsTransport — see #13503.)
# Kimi's /coding endpoint speaks the Anthropic Messages protocol but has
# its own thinking semantics: when ``thinking.enabled`` is sent, Kimi
# validates the message history and requires every prior assistant
# tool-call message to carry OpenAI-style ``reasoning_content``. The
# Anthropic path never populates that field, and
# ``convert_messages_to_anthropic`` strips all Anthropic thinking blocks
# on third-party endpoints — so the request fails with HTTP 400
# "thinking is enabled but reasoning_content is missing in assistant
# tool call message at index N". Kimi's reasoning is driven server-side
# on the /coding route, so skip Anthropic's thinking parameter entirely
# for that host. (Kimi on chat_completions enables thinking via
# extra_body in the ChatCompletionsTransport — see #13503.)
#
# On 4.7+ the `thinking.display` field defaults to "omitted", which
# silently hides reasoning text that Hermes surfaces in its CLI. We
# request "summarized" so the reasoning blocks stay populated — matching
# 4.6 behavior and preserving the activity-feed UX during long tool runs.
if reasoning_config and isinstance(reasoning_config, dict):
_is_kimi_coding = _is_kimi_family_endpoint(base_url, model)
if reasoning_config and isinstance(reasoning_config, dict) and not _is_kimi_coding:
if reasoning_config.get("enabled") is not False and "haiku" not in model.lower():
effort = str(reasoning_config.get("effort", "medium")).lower()
budget = THINKING_BUDGET.get(effort, 8000)
@@ -2771,56 +2511,3 @@ def sanitize_anthropic_kwargs(api_kwargs: Any, *, log_prefix: str = "") -> Any:
sorted(leaked),
)
return api_kwargs
def _is_stream_unavailable_error(exc: Exception) -> bool:
"""Return True when an Anthropic stream call should fall back to create()."""
err_lower = str(exc).lower()
if "stream" in err_lower and "not supported" in err_lower:
return True
if "invokemodelwithresponsestream" in err_lower:
from agent.bedrock_adapter import is_streaming_access_denied_error
return is_streaming_access_denied_error(exc)
return False
def create_anthropic_message(
client: Any,
api_kwargs: dict,
*,
log_prefix: str = "",
prefer_stream: bool = True,
) -> Any:
"""Create an Anthropic message, aggregating via stream when available.
Some Anthropic-compatible gateways are SSE-only: they ignore non-streaming
requests and return ``text/event-stream`` even for ``messages.create()``.
The SDK can surface that as raw text, so callers that expect a Message then
crash on ``.content``. Prefer ``messages.stream().get_final_message()`` to
match the main turn path, falling back to ``create()`` only for providers
that explicitly do not support streaming, such as restricted Bedrock roles.
"""
sanitize_anthropic_kwargs(api_kwargs, log_prefix=log_prefix)
messages_api = getattr(client, "messages", None)
stream_fn = getattr(messages_api, "stream", None)
if prefer_stream and callable(stream_fn):
stream_kwargs = dict(api_kwargs)
stream_kwargs.pop("stream", None)
try:
with stream_fn(**stream_kwargs) as stream:
return stream.get_final_message()
except Exception as exc:
if not _is_stream_unavailable_error(exc):
raise
logger.debug(
"%sAnthropic Messages stream unavailable; falling back to "
"messages.create(): %s",
log_prefix,
exc,
)
create_kwargs = dict(api_kwargs)
create_kwargs.pop("stream", None)
return messages_api.create(**create_kwargs)
-16
View File
@@ -66,19 +66,3 @@ def safe_schedule_threadsafe(
coro.close()
log.log(log_level, "%s: %s", log_message, exc)
return None
def consume_detached_task_result(task: "asyncio.Future[Any]") -> None:
"""Retrieve a detached task's result without surfacing cancellation.
Used as an ``add_done_callback`` on tasks that were cancelled and
detached (e.g. an adapter close path that swallows ``CancelledError``
past its teardown deadline). Observing ``task.exception()`` prevents
"exception was never retrieved" noise on the event loop; cancellation
and any terminal error are deliberately swallowed the task's owner
already gave up on it.
"""
try:
task.exception()
except (asyncio.CancelledError, Exception):
pass
-138
View File
@@ -1,138 +0,0 @@
"""Ambient session-accounting context for auxiliary LLM calls.
Auxiliary calls (vision, compression, title generation, web_extract,
session_search, ...) funnel through ``agent.auxiliary_client`` which has no
session handle so their token usage was historically discarded, leaving
dashboard analytics blind to aux model spend (issue #23270).
Instead of threading ``session_db``/``session_id`` parameters through every
aux call site, the agent loop publishes them here (mirroring the Nous Portal
conversation context in ``agent.portal_tags``) and the auxiliary client
records usage at its single response-validation chokepoint.
ContextVar semantics give us the right isolation for free:
* concurrent agents in one process (gateway sessions, delegate subagents)
never see each other's accounting context;
* worker threads spawned via ``tools.thread_context.propagate_context_to_thread``
(MoA fan-out, background review) inherit the parent turn's context;
* asyncio tasks inherit the context of the code that created them.
MoA reference/aggregator slots are explicitly EXCLUDED from recording:
``agent/conversation_loop.py`` already folds MoA advisor usage and cost into
the main loop's ``update_token_counts`` delta, so recording them here would
double-count (see ``_EXCLUDED_TASKS``).
"""
from __future__ import annotations
import logging
from contextvars import ContextVar
from typing import Any, Optional
logger = logging.getLogger(__name__)
# (session_db, session_id) for the active agent turn, or None outside one.
_accounting: ContextVar[Optional[tuple]] = ContextVar(
"aux_accounting_context", default=None
)
# Aux tasks whose usage is already accounted by the main loop — recording
# them here would double-count. MoA advisor/aggregator usage is folded into
# conversation_loop's update_token_counts delta (tokens AND cost).
_EXCLUDED_TASKS = frozenset({"moa_reference", "moa_aggregator"})
def set_accounting_context(session_db: Any, session_id: Optional[str]):
"""Publish the active session's accounting handles for aux usage recording.
Called by the agent loop at turn entry. Returns the ContextVar token so
callers can ``reset_accounting_context(token)`` on turn exit. Publishing
``None`` handles (no DB / no session id) clears the context.
"""
if session_db is None or not session_id:
return _accounting.set(None)
return _accounting.set((session_db, session_id))
def reset_accounting_context(token) -> None:
"""Restore the previous accounting context (pair with ``set_...``)."""
try:
_accounting.reset(token)
except Exception:
_accounting.set(None)
def get_accounting_context() -> Optional[tuple]:
"""Return ``(session_db, session_id)`` for the active turn, or ``None``."""
return _accounting.get()
def record_aux_usage(
response: Any,
task: Optional[str],
*,
provider: Optional[str] = None,
base_url: Optional[str] = None,
) -> None:
"""Record an auxiliary response's token usage against the ambient session.
Called from the auxiliary client's response-validation chokepoint. Strictly
best-effort: any failure is swallowed (accounting must never break an aux
call). No-ops when:
* no accounting context is published (call is outside any agent turn),
* the task is main-loop-accounted (MoA slots see ``_EXCLUDED_TASKS``),
* the response carries no usage object.
The model is read from ``response.model`` (accurate even after the aux
client's provider-fallback chains); *provider*/*base_url* reflect the
originally-resolved route and are best-effort.
"""
try:
if not task or task in _EXCLUDED_TASKS:
return
ctx = _accounting.get()
if ctx is None:
return
session_db, session_id = ctx
raw_usage = getattr(response, "usage", None)
if raw_usage is None:
return
from agent.usage_pricing import estimate_usage_cost, normalize_usage
usage = normalize_usage(raw_usage, provider=provider)
if not (
usage.input_tokens or usage.output_tokens
or usage.cache_read_tokens or usage.cache_write_tokens
or usage.reasoning_tokens
):
return
model = str(getattr(response, "model", "") or "") or "unknown"
estimated_cost = None
try:
cost = estimate_usage_cost(
model, usage, provider=provider, base_url=base_url
)
if cost.amount_usd is not None:
estimated_cost = float(cost.amount_usd)
except Exception:
logger.debug("Aux usage cost estimation failed", exc_info=True)
session_db.record_auxiliary_usage(
session_id,
task,
model=model,
billing_provider=provider,
billing_base_url=base_url,
input_tokens=usage.input_tokens,
output_tokens=usage.output_tokens,
cache_read_tokens=usage.cache_read_tokens,
cache_write_tokens=usage.cache_write_tokens,
reasoning_tokens=usage.reasoning_tokens,
estimated_cost_usd=estimated_cost,
)
except Exception:
logger.debug("Aux usage recording failed (non-fatal)", exc_info=True)
+291 -2378
View File
File diff suppressed because it is too large Load Diff
+64 -447
View File
@@ -18,151 +18,15 @@ for invariants and PR review criteria.
from __future__ import annotations
import contextlib
import json
import logging
import os
from typing import Any, Dict, List, Optional
from agent.thread_scoped_output import thread_scoped_silence
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Background-review aux-model selector + routed digest.
#
# The review fork runs on the MAIN model by default ("auto"), replaying the
# full conversation — already warm in the prompt cache, so cheap cache reads.
# Optimal and unchanged. A user can route the review to a different, cheaper
# model via auxiliary.background_review.{provider,model}. A different model
# cannot reuse the parent's cache (different key), so the fork is cold
# regardless — replaying the full transcript would just cold-write it. So when
# (and only when) routed to a different model, we replay a compact DIGEST to
# minimise cold-written tokens. Same model -> full replay; different model ->
# digest. That's the whole policy.
# ---------------------------------------------------------------------------
def _resolve_review_runtime(agent: Any) -> Dict[str, Any]:
"""Resolve provider/model/credentials for the review fork.
Default (auto / unset / same as parent): inherit the parent's live runtime
(with codex_app_server -> codex_responses downgrade). ``routed`` is False
the fork uses the main model and the warm cache, exactly as before. When
``auxiliary.background_review.{provider,model}`` names a concrete model
different from the parent's, resolve that runtime and set ``routed=True``.
"""
parent_runtime = agent._current_main_runtime()
parent_api_mode = parent_runtime.get("api_mode") or None
if parent_api_mode == "codex_app_server":
parent_api_mode = "codex_responses"
parent = {
"provider": agent.provider,
"model": agent.model,
"api_key": parent_runtime.get("api_key") or None,
"base_url": parent_runtime.get("base_url") or None,
"api_mode": parent_api_mode,
"credential_pool": getattr(agent, "_credential_pool", None),
"request_overrides": dict(getattr(agent, "request_overrides", {}) or {}),
"max_tokens": getattr(agent, "max_tokens", None),
"command": getattr(agent, "acp_command", None),
"args": list(getattr(agent, "acp_args", []) or []),
"routed": False,
}
try:
from hermes_cli.config import load_config
cfg = load_config()
except Exception:
return parent
aux = cfg.get("auxiliary", {}) if isinstance(cfg.get("auxiliary"), dict) else {}
task = aux.get("background_review", {}) if isinstance(aux.get("background_review"), dict) else {}
task_provider = (str(task.get("provider", "")).strip() or None)
task_model = (str(task.get("model", "")).strip() or None)
task_base_url = (str(task.get("base_url", "")).strip() or None)
task_api_key = (str(task.get("api_key", "")).strip() or None)
if not (task_provider and task_provider != "auto" and task_model):
return parent
if task_provider == (agent.provider or "") and task_model == (agent.model or ""):
return parent # same model/provider as parent -> not routed
try:
from hermes_cli.runtime_provider import resolve_runtime_provider
rp = resolve_runtime_provider(
requested=task_provider,
target_model=task_model,
explicit_api_key=task_api_key,
explicit_base_url=task_base_url,
)
return {
"provider": rp.get("provider") or task_provider,
"model": rp.get("model") or task_model,
"api_key": rp.get("api_key"),
"base_url": rp.get("base_url"),
"api_mode": rp.get("api_mode"),
"credential_pool": rp.get("credential_pool"),
"request_overrides": dict(rp.get("request_overrides") or {}),
"max_tokens": rp.get("max_output_tokens"),
"command": rp.get("command"),
"args": list(rp.get("args") or []),
"routed": True,
}
except Exception as e:
logger.debug("background-review aux routing failed (%s); using main model", e)
return parent
def _msg_text(m: Dict) -> str:
c = m.get("content")
if isinstance(c, str):
return c.strip()
if isinstance(c, list):
return " ".join(b.get("text", "") for b in c if isinstance(b, dict)).strip()
return ""
def _digest_history(messages_snapshot: List[Dict], tail: int = 24) -> List[Dict]:
"""Compact replay for the routed (different-model) path only.
Keeps the recent ``tail`` messages verbatim, collapses older turns into one
synthetic user-role digest, preserving role alternation. Used ONLY when
routed to a different model (cache cold regardless, so fewer cold-written
tokens is a pure win). Never on the main-model path (full replay stays warm).
"""
msgs = list(messages_snapshot or [])
if len(msgs) <= tail:
return msgs
keep = msgs[-tail:]
while keep and isinstance(keep[0], dict) and keep[0].get("role") == "tool":
tail += 1
if len(msgs) <= tail:
return msgs
keep = msgs[-tail:]
old = msgs[:-len(keep)]
lines: List[str] = []
for m in old:
if not isinstance(m, dict):
continue
role = m.get("role")
text = _msg_text(m).replace("\n", " ")
if role == "user" and text:
lines.append(f"USER: {text[:300]}")
elif role == "assistant":
tcs = m.get("tool_calls") or []
if tcs:
names = [(tc.get("function") or {}).get("name", "?") for tc in tcs if isinstance(tc, dict)]
lines.append(f"ASSISTANT[tools: {', '.join(names)}]")
if text:
lines.append(f"ASSISTANT: {text[:200]}")
digest = {
"role": "user",
"content": (
"[Earlier conversation digest — older turns summarised to bound the "
"review's cold-write cost on the routed aux model. Recent turns "
"follow verbatim below.]\n" + "\n".join(lines)
),
}
return [digest] + keep
# Review-prompt strings — used by ``spawn_background_review_thread`` to build
# the user-message that the forked review agent receives. AIAgent exposes
# them as class attributes (``_MEMORY_REVIEW_PROMPT`` etc.) for back-compat;
@@ -373,25 +237,18 @@ _COMBINED_REVIEW_PROMPT = (
def summarize_background_review_actions(
review_messages: List[Dict],
prior_snapshot: List[Dict],
notification_mode: str = "on",
) -> List[str]:
"""Build the human-facing action summary for a background review pass.
Walks the review agent's session messages and collects successful memory
and skill-management actions to surface to the user. Tool messages already
present in ``prior_snapshot`` are skipped so stale inherited results are
not re-surfaced as fresh background work (issue #14944).
Walks the review agent's session messages and collects "successful tool
action" descriptions to surface to the user (e.g. "Memory updated").
Tool messages already present in ``prior_snapshot`` are skipped so we
don't re-surface stale results from the prior conversation that the
review agent inherited via ``conversation_history`` (issue #14944).
``notification_mode`` controls display detail:
- ``off``: return no actions.
- ``on``: generic "Memory updated"/tool messages.
- ``verbose``: include compact content previews from tool-call arguments.
Matching is by ``tool_call_id`` when available, with a content-equality
fallback for tool messages that lack one.
"""
mode = str(notification_mode or "on").lower()
if mode == "off":
return []
verbose = mode == "verbose"
existing_tool_call_ids = set()
existing_tool_contents = set()
for prior in prior_snapshot or []:
@@ -405,43 +262,6 @@ def summarize_background_review_actions(
if isinstance(content, str):
existing_tool_contents.add(content)
# Map review-agent tool results back to the calls that produced them. The
# result JSON only says "Entry added"; the call arguments contain action,
# target, and content previews. Restricting to notify_tools also prevents
# helper tools from surfacing as memory work just because they succeeded.
notify_tools = {"memory", "skill_manage"}
all_tool_call_ids: set = set()
call_details: dict = {}
for msg in review_messages or []:
if not isinstance(msg, dict) or msg.get("role") != "assistant":
continue
for tc in msg.get("tool_calls", []) or []:
if not isinstance(tc, dict):
continue
fn = tc.get("function", {}) or {}
fn_name = fn.get("name", "")
tcid = tc.get("id")
if tcid:
all_tool_call_ids.add(tcid)
if fn_name not in notify_tools:
continue
try:
args = json.loads(fn.get("arguments", "{}"))
except (json.JSONDecodeError, TypeError):
args = {}
if tcid:
call_details[tcid] = {
"tool": fn_name,
"action": args.get("action", "?"),
"target": args.get("target", "memory"),
"content": args.get("content", ""),
"old_text": args.get("old_text", ""),
"operations": args.get("operations") or [],
"name": args.get("name", ""),
"old_string": args.get("old_string", ""),
"new_string": args.get("new_string", ""),
}
actions: List[str] = []
for msg in review_messages or []:
if not isinstance(msg, dict) or msg.get("role") != "tool":
@@ -453,136 +273,26 @@ def summarize_background_review_actions(
content_str = msg.get("content")
if isinstance(content_str, str) and content_str in existing_tool_contents:
continue
if tcid and all_tool_call_ids and tcid not in call_details:
continue
try:
data = json.loads(msg.get("content", "{}"))
except (json.JSONDecodeError, TypeError):
continue
# ``data`` may not be a dict — some memory/skill tool responses in
# older codepaths or wrapper MCP servers return a top-level JSON
# list (e.g. ``[{"success": true, ...}]``) or a scalar. The original
# isinstance check below silently skips non-dict payloads, which
# is correct, but ``data.get("_change")`` further down can still
# hand back a list and break ``change.get("description", "")``.
# Defensively normalize everything through a dict-typed alias so
# the rest of the function can stay terse without per-call
# ``isinstance`` guards (#59437).
if not isinstance(data, dict) or not data.get("success"):
continue
message = data.get("message", "")
detail = call_details.get(tcid) or {}
if not isinstance(detail, dict):
detail = {}
target = data.get("target", "") or detail.get("target", "")
is_skill = detail.get("tool") == "skill_manage"
message_lower = message.lower()
if not verbose:
if "created" in message_lower:
actions.append(message)
continue
if "updated" in message_lower:
actions.append(message)
continue
if is_skill and "patched" in message_lower:
actions.append(message)
continue
if is_skill:
label = "Skill"
elif target:
target = data.get("target", "")
if "created" in message.lower():
actions.append(message)
elif "updated" in message.lower():
actions.append(message)
elif "added" in message.lower() or (target and "add" in message.lower()):
label = "Memory" if target == "memory" else "User profile" if target == "user" else target
actions.append(f"{label} updated")
elif "Entry added" in message:
label = "Memory" if target == "memory" else "User profile" if target == "user" else target
actions.append(f"{label} updated")
elif "removed" in message.lower() or "replaced" in message.lower():
label = "Memory" if target == "memory" else "User profile" if target == "user" else target
else:
continue
if verbose:
action = detail.get("action", "")
content = detail.get("content", "")
old_text = detail.get("old_text", "")
skill_name = detail.get("name", "")
# ``operations`` may be anything callable put into the JSON
# arguments. Anything non-iterable that isn't a list[str]
# of dicts becomes unusable here, so coerce defensively.
ops_raw = detail.get("operations")
operations: list = (
ops_raw if isinstance(ops_raw, list) else []
)
max_preview = 120
if is_skill:
# ``_change`` is a free-form dict the skill tool leaves in
# the response. Older / wrapper MCP backends return it
# as a list, an int, or a JSON-shaped scalar — normalize
# to a dict so the .get() calls downstream don't
# AttributeError (#59437).
change_raw = data.get("_change")
change: dict = (
change_raw if isinstance(change_raw, dict) else {}
)
old_string = (
change.get("old", "") or detail.get("old_string", "")
)
new_string = (
change.get("new", "") or detail.get("new_string", "")
)
description = change.get("description", "")
if action == "patch" and (old_string or new_string):
old_preview = old_string[:80].replace("\n", " ") + (
"" if len(old_string) > 80 else ""
)
new_preview = new_string[:80].replace("\n", " ") + (
"" if len(new_string) > 80 else ""
)
actions.append(
f"📝 Skill '{skill_name}' patched: "
f"\"{old_preview}\"\"{new_preview}\""
)
elif action == "create" and description:
actions.append(f"📝 Skill '{skill_name}' created: {description}")
elif action == "edit" and description:
actions.append(f"📝 Skill '{skill_name}' rewritten: {description}")
else:
actions.append(f"📝 {message}" if message else f"Skill {action}")
elif operations:
for op in operations:
# Each element must be a dict-of-fields; some
# legacy codepaths serialize the entry as a bare
# string and the message dict doesn't exist. Skip
# non-dict items defensively — they have no
# actionable fields anyway (#59437).
if not isinstance(op, dict):
continue
op_act = op.get("action", "")
op_content = (op.get("content") or "")
op_old = (op.get("old_text") or "")
if op_act == "add" and op_content:
preview = op_content[:max_preview] + ("" if len(op_content) > max_preview else "")
actions.append(f"{label} {preview}")
elif op_act == "replace" and op_content:
preview = op_content[:max_preview] + ("" if len(op_content) > max_preview else "")
actions.append(f"{label} ✏️ {preview}")
elif op_act == "remove" and op_old:
preview = op_old[:60] + ("" if len(op_old) > 60 else "")
actions.append(f"{label} {preview}")
elif action == "add" and content:
preview = content[:max_preview] + ("" if len(content) > max_preview else "")
actions.append(f"{label} {preview}")
elif action == "replace" and content:
preview = content[:max_preview] + ("" if len(content) > max_preview else "")
actions.append(f"{label} ✏️ {preview}")
elif action == "remove" and old_text:
preview = old_text[:60] + ("" if len(old_text) > 60 else "")
actions.append(f"{label} {preview}")
else:
actions.append(f"{label} updated")
elif (
"added" in message_lower
or "replaced" in message_lower
or "removed" in message_lower
or "applied" in message_lower
or (target and "add" in message.lower())
or "Entry added" in message
):
actions.append(f"{label} updated")
return actions
@@ -648,15 +358,9 @@ def _run_review_in_thread(
review_agent = None
review_messages: List[Dict] = []
try:
# Silence stdout/stderr for THIS worker thread only. A process-global
# ``contextlib.redirect_stdout(devnull)`` here would also blank
# ``sys.stdout``/``sys.stderr`` for every other thread — including a
# gateway event-loop thread driving a Telegram long-poll — for the full
# duration of the review (tens of seconds), swallowing their console
# output (#55769 / #55925). ``thread_scoped_silence`` routes only this
# thread's writes to devnull and leaves all other threads on the real
# streams.
with thread_scoped_silence():
with open(os.devnull, "w", encoding="utf-8") as _devnull, \
contextlib.redirect_stdout(_devnull), \
contextlib.redirect_stderr(_devnull):
# Inherit the parent agent's live runtime (provider, model,
# base_url, api_key, api_mode) so the fork uses the exact
# same credentials the main turn is using. Without this,
@@ -665,13 +369,18 @@ def _run_review_in_thread(
# creds, or credential-pool setups where the resolver can't
# reconstruct auth from scratch -- producing the spurious
# "No LLM provider configured" warning at end of turn.
# _resolve_review_runtime() returns the parent's live runtime by
# default (routed=False; main model, warm cache), or — when the user
# set auxiliary.background_review.{provider,model} to a different
# model — that model's runtime (routed=True). The codex_app_server
# -> codex_responses downgrade is applied inside the resolver.
_rt = _resolve_review_runtime(agent)
_routed = bool(_rt.get("routed"))
_parent_runtime = agent._current_main_runtime()
_parent_api_mode = _parent_runtime.get("api_mode") or None
# The review fork needs to call agent-loop tools (memory,
# skill_manage). Those tools require Hermes' own dispatch,
# which the codex_app_server runtime bypasses entirely
# (it runs the turn inside codex's subprocess). So when
# the parent is on codex_app_server, downgrade the review
# fork to codex_responses — same auth/credentials, but
# talks to the OpenAI Responses API directly so Hermes
# owns the loop and the agent-loop tools dispatch.
if _parent_api_mode == "codex_app_server":
_parent_api_mode = "codex_responses"
# skip_memory=True keeps the review fork from
# touching external memory plugins (honcho, mem0,
# supermemory, etc.). Without it, the fork's
@@ -690,70 +399,28 @@ def _run_review_in_thread(
# Match parent's toolset config so ``tools[]`` is byte-identical
# in the request body — Anthropic's cache key includes it.
# (The runtime whitelist below still restricts dispatch.)
_fork_kwargs: Dict[str, Any] = {}
if isinstance(_rt.get("max_tokens"), int):
_fork_kwargs["max_tokens"] = _rt["max_tokens"]
if isinstance(_rt.get("command"), str) and _rt["command"]:
_fork_kwargs["acp_command"] = _rt["command"]
_fork_kwargs["acp_args"] = _rt.get("args") or []
# Match parent's reasoning config so the fork's ``thinking`` /
# ``output_config`` are byte-identical in the request body —
# Anthropic's cache key is namespaced by ``thinking`` presence.
# Same-model path only: when routed to a different aux model the
# cache is cold regardless (parity buys nothing) and the parent's
# effort vocabulary may not be valid for the routed model/provider
# (e.g. OpenRouter ``extra_body.reasoning.effort`` is forwarded
# unclamped; codex_responses passes ``max``/``ultra`` through
# unmapped except on gpt-5.6/xAI). Let the routed fork use
# provider defaults — matching the ``not _routed`` gate on
# _cached_system_prompt below.
if not _routed:
_fork_kwargs["reasoning_config"] = getattr(agent, "reasoning_config", None)
review_agent = AIAgent(
model=_rt.get("model") or agent.model,
model=agent.model,
max_iterations=16,
quiet_mode=True,
platform=agent.platform,
provider=_rt.get("provider") or agent.provider,
api_mode=_rt.get("api_mode"),
base_url=_rt.get("base_url") or None,
api_key=_rt.get("api_key") or None,
credential_pool=_rt.get("credential_pool"),
request_overrides=_rt.get("request_overrides") or {},
provider=agent.provider,
api_mode=_parent_api_mode,
base_url=_parent_runtime.get("base_url") or None,
api_key=_parent_runtime.get("api_key") or None,
credential_pool=getattr(agent, "_credential_pool", None),
parent_session_id=agent.session_id,
enabled_toolsets=getattr(agent, "enabled_toolsets", None),
disabled_toolsets=getattr(agent, "disabled_toolsets", None),
skip_memory=True,
**_fork_kwargs,
)
review_agent._memory_write_origin = "background_review"
review_agent._memory_write_context = "background_review"
# The review fork pins the parent's cached system prompt and keeps
# ``tools[]`` byte-identical to the parent so its outbound request
# hits the same provider cache prefix (see the toolset-parity note
# above). The between-turns MCP refresh in build_turn_context would
# add late-connecting MCP tools to this fork and break that parity,
# so opt the review fork out of it.
review_agent._skip_mcp_refresh = True
review_agent._memory_store = agent._memory_store
review_agent._memory_enabled = agent._memory_enabled
review_agent._user_profile_enabled = agent._user_profile_enabled
review_agent._memory_nudge_interval = 0
review_agent._skill_nudge_interval = 0
# PERSISTENCE ISOLATION (the curator-takeover root cause): the fork
# shares the parent's session_id (set below, for prompt-cache
# warmth), so without this it would write its harness turn ("Review
# the conversation above and update the skill library…") + its own
# response straight into the user's REAL session in state.db. On the
# user's next live turn the agent re-reads that injected user message
# as a standing instruction and "becomes" the curator, refusing the
# actual task. _persist_disabled hard-stops every DB write/lazy-open
# path (_flush_messages_to_session_db, _ensure_db_session,
# _get_session_db_for_recall); the review writes only to the skill
# and memory stores via its tools, which is all it needs.
review_agent._persist_disabled = True
review_agent._session_db = None
review_agent._session_json_enabled = False
# Suppress all status/warning emits from the fork so the
# user only sees the final successful-action summary.
# Without this, mid-review "Iteration budget exhausted",
@@ -772,28 +439,16 @@ def _run_review_in_thread(
# issue #25322 and PR #17276 for the full analysis +
# measured impact (~26% end-to-end cost reduction on
# Sonnet 4.5).
# Share the parent's warm cached system prompt ONLY when the review
# runs on the SAME model (not routed). When routed to a different
# model the parent's cached prompt is for the wrong model/cache key
# and would miss anyway, so let the routed fork build its own.
if not _routed:
review_agent._cached_system_prompt = agent._cached_system_prompt
# Defensive: pin session_start + session_id to the
# parent's so any code path that re-renders parts of
# the system prompt (compression, plugin hooks) still
# produces byte-identical output. The cached-prompt
# assignment above already short-circuits the normal
# rebuild path, but these pins guarantee parity even
# if a future code path bypasses the cache.
review_agent.session_start = agent.session_start
review_agent._cached_system_prompt = agent._cached_system_prompt
# Defensive: pin session_start + session_id to the
# parent's so any code path that re-renders parts of
# the system prompt (compression, plugin hooks) still
# produces byte-identical output. The cached-prompt
# assignment above already short-circuits the normal
# rebuild path, but these pins guarantee parity even
# if a future code path bypasses the cache.
review_agent.session_start = agent.session_start
review_agent.session_id = agent.session_id
# The fork shares the parent's live session_id (pinned above for
# prefix-cache parity). It is single-lifecycle and calls close()
# right after this run_conversation(); without opting out, close()
# would finalize the parent's still-active session row mid
# conversation (the review fires every ~10 turns). Leave session
# finalization to the real owner (CLI close / gateway reset / cron).
review_agent._end_session_on_close = False
# Never let the review fork compress. It shares the parent's
# session_id, so if it won a compression race it would rotate the
# parent into a NEW child that the gateway never adopts (the fork
@@ -812,17 +467,10 @@ def _run_review_in_thread(
clear_thread_tool_whitelist,
)
# Gate the built-in memory tool on the profile's memory_enabled flag.
# Hardcoding ["memory", "skills"] granted the review LLM the MEMORY.md
# read/write tool even when a profile set memory_enabled: false,
# contaminating a memory-disabled profile (#54937 layer 2).
review_toolsets = ["skills"]
if review_agent._memory_enabled or review_agent._user_profile_enabled:
review_toolsets.insert(0, "memory")
review_whitelist = {
t["function"]["name"]
for t in get_tool_definitions(
enabled_toolsets=review_toolsets,
enabled_toolsets=["memory", "skills"],
quiet_mode=True,
)
}
@@ -834,20 +482,6 @@ def _run_review_in_thread(
),
)
try:
from tools.skill_manager_tool import _reset_background_review_read_marks
_reset_background_review_read_marks()
except Exception:
pass
try:
# Routed to a different model -> replay a digest (cache is cold
# on that model anyway, so minimise cold-written tokens). Same
# model -> replay the full snapshot (warm cache reads).
_review_history = (
_digest_history(messages_snapshot) if _routed
else messages_snapshot
)
review_agent.run_conversation(
user_message=(
prompt
@@ -855,7 +489,7 @@ def _run_review_in_thread(
"management tools. Other tools will be denied "
"at runtime — do not attempt them."
),
conversation_history=_review_history,
conversation_history=messages_snapshot,
)
finally:
clear_thread_tool_whitelist()
@@ -885,29 +519,10 @@ def _run_review_in_thread(
# the review agent inherits that history and would otherwise
# re-surface stale "created"/"updated" messages from the prior
# conversation as if they just happened (issue #14944).
#
# Wrapped in try/except: a buggy/legacy tool response shape
# (e.g. ``_change`` returned as a list instead of a dict, #59437)
# must NOT take down the whole review with an AttributeError,
# since the caller's outer except logs only "Background
# memory/skill review failed" and discards every successful
# action the fork DID complete before the crash. Coerce an
# exception into an empty actions list so the partial valid
# actions from earlier in the messages are returned instead.
try:
actions = summarize_background_review_actions(
review_messages,
messages_snapshot,
notification_mode=getattr(agent, "memory_notifications", "on"),
)
except Exception as e:
logger.warning(
"summarize_background_review_actions returned partial results "
"after exception (treating as empty); suppressing AttributeError "
"that previously aborted the entire review (#59437): %s",
e,
)
actions = []
actions = summarize_background_review_actions(
review_messages,
messages_snapshot,
)
if actions:
summary = " · ".join(dict.fromkeys(actions))
@@ -927,14 +542,16 @@ def _run_review_in_thread(
logger.warning("Background memory/skill review failed: %s", e)
agent._emit_auxiliary_failure("background review", e)
finally:
# Safety-net cleanup for the exception path. Normal completion already
# shut down inside the thread-scoped silence above. Re-enter the
# thread-scoped silence here so teardown output (Honcho flush, Hindsight
# sync, background thread joins) stays quiet even on the exception path,
# without blanking other threads' streams.
# Safety-net cleanup for the exception path. Normal
# completion already shut down inside redirect_stdout above.
# Re-open devnull here so any teardown output (Honcho flush,
# Hindsight sync, background thread joins) stays silent even
# on the exception path where redirect_stdout already exited.
if review_agent is not None:
try:
with thread_scoped_silence():
with open(os.devnull, "w", encoding="utf-8") as _fn, \
contextlib.redirect_stdout(_fn), \
contextlib.redirect_stderr(_fn):
try:
review_agent.shutdown_memory_provider()
except Exception:
-131
View File
@@ -1,131 +0,0 @@
"""System-battery read-out for the CLI/TUI status bar.
Reads the host battery through ``psutil`` (already a Hermes dependency) and
exposes a compact, colour-coded label. Everything degrades to "unavailable"
when there is no battery (desktops, servers, VMs) or when the read fails, so
callers can render the result unconditionally and simply show nothing.
The status bar repaints often (every keystroke and on a ~1s idle refresh), so
:func:`read_battery` memoises the last reading for a few seconds instead of
hitting ``psutil`` on every frame.
"""
from __future__ import annotations
import time
from dataclasses import dataclass
from typing import Optional
@dataclass(frozen=True)
class BatteryStatus:
"""A single battery reading.
``available`` is False on machines without a battery (or when the read
failed). ``percent`` is clamped to 0-100. ``plugged`` is True when on AC
power, False on battery, and None when the platform can't tell.
"""
available: bool
percent: Optional[int] = None
plugged: Optional[bool] = None
@property
def charging(self) -> bool:
return bool(self.plugged)
UNAVAILABLE = BatteryStatus(available=False)
# Colour buckets, mirroring the status-bar context styles but inverted (a full
# battery is "good", an empty one is "critical").
CATEGORY_GOOD = "good"
CATEGORY_WARN = "warn"
CATEGORY_BAD = "bad"
CATEGORY_CRITICAL = "critical"
CATEGORY_DIM = "dim"
_CACHE_TTL_SECONDS = 8.0
_cache: Optional[tuple[float, BatteryStatus]] = None
def _read_battery_uncached() -> BatteryStatus:
try:
import psutil
except Exception:
return UNAVAILABLE
# ``sensors_battery`` is missing on some platforms/builds of psutil.
reader = getattr(psutil, "sensors_battery", None)
if reader is None:
return UNAVAILABLE
try:
batt = reader()
except Exception:
return UNAVAILABLE
if batt is None:
return UNAVAILABLE
percent: Optional[int] = None
raw_percent = getattr(batt, "percent", None)
if raw_percent is not None:
try:
percent = max(0, min(100, int(round(float(raw_percent)))))
except (TypeError, ValueError):
percent = None
plugged = getattr(batt, "power_plugged", None)
if plugged is not None:
plugged = bool(plugged)
return BatteryStatus(available=True, percent=percent, plugged=plugged)
def read_battery(use_cache: bool = True) -> BatteryStatus:
"""Return the current battery status (cached for a few seconds)."""
global _cache
if use_cache and _cache is not None:
ts, cached = _cache
if time.monotonic() - ts < _CACHE_TTL_SECONDS:
return cached
status = _read_battery_uncached()
_cache = (time.monotonic(), status)
return status
def clear_cache() -> None:
"""Drop the memoised reading (used by tests)."""
global _cache
_cache = None
def battery_category(status: BatteryStatus) -> str:
"""Bucket a reading into a colour category: good/warn/bad/critical/dim."""
if not status.available or status.percent is None:
return CATEGORY_DIM
# On AC power the level isn't a concern — always read as healthy.
if status.charging:
return CATEGORY_GOOD
pct = status.percent
if pct <= 10:
return CATEGORY_CRITICAL
if pct <= 20:
return CATEGORY_BAD
if pct <= 50:
return CATEGORY_WARN
return CATEGORY_GOOD
def battery_glyph(status: BatteryStatus) -> str:
"""Return the leading glyph: a bolt while charging, else a battery."""
return "\u26a1" if status.charging else "\U0001f50b" # ⚡ / 🔋
def format_battery(status: BatteryStatus) -> str:
"""Return a compact label like ``🔋 82%`` / ``⚡ 82%`` (empty if N/A)."""
if not status.available or status.percent is None:
return ""
return f"{battery_glyph(status)} {status.percent}%"
+29 -230
View File
@@ -58,34 +58,17 @@ _bedrock_runtime_client_cache: Dict[str, Any] = {}
_bedrock_control_client_cache: Dict[str, Any] = {}
_MIN_BOTO3_VERSION = (1, 34, 59)
def _require_boto3():
"""Import boto3, raising a clear error if not installed or too old."""
"""Import boto3, raising a clear error if not installed."""
try:
import boto3
return boto3
except ImportError:
raise ImportError(
"The 'boto3' package is required for the AWS Bedrock provider. "
"Install it with: pip install boto3\n"
"Or install Hermes with Bedrock support: pip install -e '.[bedrock]'"
)
# converse() / converse_stream() were added in boto3 1.34.59.
# When Hermes is installed editable into system Python, the system boto3
# (e.g. Ubuntu 24.04 ships 1.34.46) may take precedence over the venv
# version pinned in pyproject.toml.
try:
version = tuple(int(x) for x in boto3.__version__.split(".")[:3])
except (AttributeError, ValueError):
return boto3 # can't parse — don't block on version check
if version < _MIN_BOTO3_VERSION:
raise RuntimeError(
f"boto3 {boto3.__version__} does not support converse_stream "
f"(minimum 1.34.59 required). Upgrade with: "
f"pip install --upgrade boto3"
)
return boto3
def _get_bedrock_runtime_client(region: str):
@@ -448,10 +431,7 @@ def is_anthropic_bedrock_model(model_id: str) -> bool:
"""
model_lower = model_id.lower()
# Strip regional prefix if present
for prefix in (
"global.", "us.", "eu.", "apac.", "ap.", "au.", "jp.",
"ca.", "sa.", "me.", "af.",
):
for prefix in ("us.", "global.", "eu.", "ap.", "jp."):
if model_lower.startswith(prefix):
model_lower = model_lower[len(prefix):]
break
@@ -493,26 +473,6 @@ def convert_tools_to_converse(tools: List[Dict]) -> List[Dict]:
return result
# Bedrock's Converse API rejects any text content block whose text is empty
# OR whitespace-only (ValidationException: "text content blocks must contain
# non-whitespace text"). A lone space is whitespace and is rejected too — the
# placeholder MUST itself be non-whitespace. Ref: issue #9486.
_EMPTY_TEXT_PLACEHOLDER = "(empty)"
def _safe_text(text) -> str:
"""Return ``text`` if it's non-whitespace, else a non-whitespace placeholder.
Handles None, empty string, and whitespace-only string (spaces, tabs,
newlines) all of which Bedrock's Converse API rejects as text content.
"""
if text is None:
return _EMPTY_TEXT_PLACEHOLDER
if not isinstance(text, str):
text = str(text)
return text if text.strip() else _EMPTY_TEXT_PLACEHOLDER
def _convert_content_to_converse(content) -> List[Dict]:
"""Convert OpenAI message content (string or list) to Converse content blocks.
@@ -520,27 +480,26 @@ def _convert_content_to_converse(content) -> List[Dict]:
- Plain text strings [{"text": "..."}]
- Content arrays with text/image_url parts mixed text/image blocks
Replaces empty/whitespace-only text blocks with a non-whitespace
placeholder Bedrock's Converse API rejects messages where a text
content block is empty or whitespace-only (ValidationException:
"text content blocks must contain non-whitespace text"). Ref: issue #9486.
Filters out empty text blocks Bedrock's Converse API rejects messages
where a text content block has an empty ``text`` field (ValidationException:
"text content blocks must be non-empty"). Ref: issue #9486.
"""
if content is None:
return [{"text": _safe_text(content)}]
return [{"text": " "}]
if isinstance(content, str):
return [{"text": _safe_text(content)}]
return [{"text": content}] if content.strip() else [{"text": " "}]
if isinstance(content, list):
blocks = []
for part in content:
if isinstance(part, str):
blocks.append({"text": _safe_text(part)})
blocks.append({"text": part})
continue
if not isinstance(part, dict):
continue
part_type = part.get("type", "")
if part_type == "text":
text = part.get("text", "")
blocks.append({"text": _safe_text(text)})
blocks.append({"text": text if text else " "})
elif part_type == "image_url":
image_url = part.get("image_url", {})
url = image_url.get("url", "") if isinstance(image_url, dict) else ""
@@ -552,27 +511,18 @@ def _convert_content_to_converse(content) -> List[Dict]:
mime_part = header[5:].split(";")[0]
if mime_part:
media_type = mime_part
# Decode base64 to raw bytes — boto3 re-encodes at the
# wire layer, so passing the base64 string directly
# results in double-encoding and Bedrock rejects it with
# "Failed to sanitize image". Ref: #33317.
import base64
try:
raw_bytes = base64.b64decode(data)
except Exception:
raw_bytes = data.encode("utf-8")
blocks.append({
"image": {
"format": media_type.split("/")[-1] if "/" in media_type else "jpeg",
"source": {"bytes": raw_bytes},
"source": {"bytes": data},
}
})
else:
# Remote URL — Converse doesn't support URLs directly,
# include as text reference for the model.
blocks.append({"text": f"[Image: {url}]"})
return blocks if blocks else [{"text": _EMPTY_TEXT_PLACEHOLDER}]
return [{"text": _safe_text(content)}]
return blocks if blocks else [{"text": " "}]
return [{"text": str(content)}]
def convert_messages_to_converse(
@@ -602,18 +552,14 @@ def convert_messages_to_converse(
content = msg.get("content")
if role == "system":
# System messages become the system prompt. Blank/whitespace-only
# parts are dropped entirely (not placeholder-filled) since a
# system prompt made up of only placeholder text is meaningless.
# System messages become the system prompt
if isinstance(content, str) and content.strip():
system_blocks.append({"text": content})
elif isinstance(content, list):
for part in content:
if isinstance(part, dict) and part.get("type") == "text":
text = part.get("text", "")
if isinstance(text, str) and text.strip():
system_blocks.append({"text": text})
elif isinstance(part, str) and part.strip():
system_blocks.append({"text": part.get("text", "")})
elif isinstance(part, str):
system_blocks.append({"text": part})
continue
@@ -624,7 +570,7 @@ def convert_messages_to_converse(
tool_result_block = {
"toolResult": {
"toolUseId": tool_call_id,
"content": [{"text": _safe_text(result_content)}],
"content": [{"text": result_content}],
}
}
# In Converse, tool results go in a "user" role message
@@ -663,7 +609,7 @@ def convert_messages_to_converse(
})
if not content_blocks:
content_blocks = [{"text": _EMPTY_TEXT_PLACEHOLDER}]
content_blocks = [{"text": " "}]
# Merge with previous assistant message if needed (strict alternation)
if converse_msgs and converse_msgs[-1]["role"] == "assistant":
@@ -689,11 +635,11 @@ def convert_messages_to_converse(
# Converse requires the first message to be from the user
if converse_msgs and converse_msgs[0]["role"] != "user":
converse_msgs.insert(0, {"role": "user", "content": [{"text": _EMPTY_TEXT_PLACEHOLDER}]})
converse_msgs.insert(0, {"role": "user", "content": [{"text": " "}]})
# Converse requires the last message to be from the user
if converse_msgs and converse_msgs[-1]["role"] != "user":
converse_msgs.append({"role": "user", "content": [{"text": _EMPTY_TEXT_PLACEHOLDER}]})
converse_msgs.append({"role": "user", "content": [{"text": " "}]})
return (system_blocks if system_blocks else None, converse_msgs)
@@ -817,7 +763,6 @@ def stream_converse_with_callbacks(
on_tool_start=None,
on_reasoning_delta=None,
on_interrupt_check=None,
on_event=None,
) -> SimpleNamespace:
"""Process a Bedrock ConverseStream event stream with real-time callbacks.
@@ -837,12 +782,6 @@ def stream_converse_with_callbacks(
on supported models (Claude 4.6+).
on_interrupt_check: Called on each event. Should return True if the
agent has been interrupted and streaming should stop.
on_event: Called once at the top of the loop body for EVERY yielded
Bedrock event (text/tool-input/reasoning/metadata deltas alike),
before any branching. Provides a wire-level liveness signal so an
external watchdog can distinguish "still receiving events" from
"stream wedged with no data". Errors raised by the callback are
swallowed so a liveness hook can never abort the stream.
Returns:
An OpenAI-compatible SimpleNamespace response, identical in shape to
@@ -858,15 +797,6 @@ def stream_converse_with_callbacks(
usage_data: Dict[str, int] = {}
for event in event_stream.get("stream", []):
# Wire-level liveness signal: fire on EVERY yielded event (text, tool
# input, reasoning, metadata) before branching so an external watchdog
# can tell a still-flowing stream from a wedged one. Best-effort — a
# liveness callback must never be able to abort the stream.
if on_event is not None:
try:
on_event()
except Exception:
pass
# Check for interrupt
if on_interrupt_check and on_interrupt_check():
break
@@ -1005,14 +935,11 @@ def build_converse_kwargs(
if system_prompt:
kwargs["system"] = system_prompt
from agent.anthropic_adapter import _forbids_sampling_params
if temperature is not None:
kwargs["inferenceConfig"]["temperature"] = temperature
if not _forbids_sampling_params(model):
if temperature is not None:
kwargs["inferenceConfig"]["temperature"] = temperature
if top_p is not None:
kwargs["inferenceConfig"]["topP"] = top_p
if top_p is not None:
kwargs["inferenceConfig"]["topP"] = top_p
if stop_sequences:
kwargs["inferenceConfig"]["stopSequences"] = stop_sequences
@@ -1349,24 +1276,9 @@ def classify_bedrock_error(error_message: str) -> str:
# detection is unavailable.
BEDROCK_CONTEXT_LENGTHS: Dict[str, int] = {
# Anthropic Claude models on Bedrock.
# Context windows per Anthropic's official models comparison
# (https://platform.claude.com/docs/en/about-claude/models/overview).
# Fable / Sonnet 5 / Opus 4.8 / 4.7 / 4.6 / Sonnet 4.6 have 1M generally
# available (no beta header required as of April 2026). Sonnet 4.5 and
# Sonnet 4 had their `context-1m-2025-08-07` beta retired on
# April 30, 2026, so they are standard 200K; Haiku 4.5 is 200K.
# These 1M entries must match agent/model_metadata.py
# DEFAULT_CONTEXT_LENGTHS or the agent compresses context prematurely.
# Keys are matched by longest-substring, so the versioned 4-6/4-7/4-8
# entries win over the generic "anthropic.claude-opus-4" fallback.
"anthropic.claude-fable-5": 1_000_000,
"anthropic.claude-fable": 1_000_000,
"anthropic.claude-sonnet-5": 1_000_000,
"anthropic.claude-opus-4-8": 1_000_000,
"anthropic.claude-opus-4-7": 1_000_000,
"anthropic.claude-opus-4-6": 1_000_000,
"anthropic.claude-sonnet-4-6": 1_000_000,
# Anthropic Claude models on Bedrock
"anthropic.claude-opus-4-6": 200_000,
"anthropic.claude-sonnet-4-6": 200_000,
"anthropic.claude-sonnet-4-5": 200_000,
"anthropic.claude-haiku-4-5": 200_000,
"anthropic.claude-opus-4": 200_000,
@@ -1393,22 +1305,9 @@ BEDROCK_CONTEXT_LENGTHS: Dict[str, int] = {
# Default for unknown Bedrock models
BEDROCK_DEFAULT_CONTEXT_LENGTH = 128_000
# Probe tiers (in tokens). We send a request padded just past each tier and
# read the real window from Bedrock's length-validation error. Two reasons
# this is tiered rather than one giant request:
# 1. A wildly oversized payload (e.g. 5M tokens) makes Bedrock return an
# opaque InternalServerException after retries instead of a clean
# ValidationException — so we must stay within a sane overage.
# 2. Stepping up lets us discover larger windows (2M+) without over-padding
# smaller ones.
# Each tier value is the *padding target*; the error reports the true maximum,
# which is what we actually return.
_BEDROCK_PROBE_TIERS = (1_300_000, 2_200_000)
_WORDS_PER_TOKEN = 0.9 # conservative: ensures the padded prompt clears the tier
def _static_bedrock_context_length(model_id: str) -> int:
"""Longest-substring-match lookup against the static fallback table.
def get_bedrock_context_length(model_id: str) -> int:
"""Look up the context window size for a Bedrock model.
Uses substring matching so versioned IDs like
``anthropic.claude-sonnet-4-6-20250514-v1:0`` resolve correctly.
@@ -1421,103 +1320,3 @@ def _static_bedrock_context_length(model_id: str) -> int:
best_key = key
best_val = val
return best_val
def probe_bedrock_context_length(model_id: str, region: str) -> Optional[int]:
"""Discover a Bedrock model's real context window by provoking a length error.
Bedrock does not expose the context window via any metadata API
(``get-foundation-model`` omits it, ``Converse`` metrics omit it,
``CountTokens`` is unsupported on several models). The only authoritative
source is the ``ValidationException`` raised when a prompt exceeds the
window:
"The model returned the following errors: prompt is too long:
1300032 tokens > 1000000 maximum"
Length validation happens *before* inference, so an oversized request is
rejected immediately and cheaply no tokens are generated and no input is
actually processed. We pad a request just past each tier in
``_BEDROCK_PROBE_TIERS`` and parse the reported ``maximum``. Tiers exist
because (a) a *wildly* oversized payload makes Bedrock fail with an opaque
InternalServerException instead of a clean length error, and (b) stepping
up discovers larger windows without over-padding smaller ones.
Returns the detected window, or ``None`` if the probe could not run
(missing credentials, network error, or no parseable limit) so the caller
can fall back to the static table.
"""
try:
from agent.model_metadata import parse_context_limit_from_error
except ImportError: # pragma: no cover — same package
return None
try:
client = _get_bedrock_runtime_client(region)
except Exception as exc: # boto3 missing / credential resolution failure
logger.debug("Bedrock context probe skipped for %s: %s", model_id, exc)
return None
last_error = ""
for tier_tokens in _BEDROCK_PROBE_TIERS:
pad_words = int(tier_tokens / _WORDS_PER_TOKEN)
oversized = "data " * pad_words
try:
client.converse(
modelId=model_id,
messages=[{"role": "user", "content": [{"text": oversized}]}],
inferenceConfig={"maxTokens": 8},
)
# Accepted a prompt this large → the window is at least this tier.
# Returning the tier as a lower bound is safe and avoids inventing
# a number we can't confirm.
logger.debug(
"Bedrock context probe for %s accepted ~%s-token prompt; "
"window is at least that", model_id, f"{tier_tokens:,}",
)
return tier_tokens
except Exception as exc:
msg = str(exc)
last_error = msg
limit = parse_context_limit_from_error(msg)
if limit and limit >= 1024:
logger.info(
"Probed Bedrock context window for %s: %s tokens",
model_id, f"{limit:,}",
)
return limit
# No parseable limit at this tier (opaque server error, auth,
# throttle). Try the next, smaller-overage strategy is N/A here —
# tiers ascend — so just continue; if all fail we return None.
continue
logger.debug(
"Bedrock context probe for %s returned no parseable limit: %s",
model_id, last_error[:200],
)
return None
def get_bedrock_context_length(model_id: str, region: str = "", probe: bool = True) -> int:
"""Resolve the context window for a Bedrock model.
Resolution order:
1. Live probe against Bedrock (authoritative; cached by the caller).
2. Static fallback table (longest-substring match).
3. Conservative default.
The static table is intentionally a *fallback*, not the primary source:
AWS ships new model versions (opus-4-7, opus-4-8, ...) faster than the
table can track, and a stale entry silently caps the window (e.g. a
1M-token Opus pinned to 200K via an ``opus-4`` substring match). The
probe asks Bedrock directly so every model current or future gets its
real window with no table maintenance.
``probe=False`` (or an empty ``region``) skips the network call and uses
the static table only used by pure-offline/display code paths.
"""
if probe and region:
probed = probe_bedrock_context_length(model_id, region)
if probed:
return probed
return _static_bedrock_context_length(model_id)
-323
View File
@@ -1,323 +0,0 @@
"""Shared dollar-denominated usage model for the billing/subscription surfaces.
The single source of truth behind the ``/usage`` and ``/subscription`` usage
bars (TUI + CLI). User feedback (Jun 2026): the terminal surfaces show
**dollars**, never "credits", and every usage bar must make the monthly
subscription allowance and separately-purchased top-up dollars distinctly
visible.
Data source: the NAS account-info fetch (``NousPortalAccountInfo``), whose
``paid_service_access_info`` carries the three dollar magnitudes we render
(despite the legacy ``*_credits`` field names, these are USD floats):
- ``subscription_credits_remaining`` -> plan dollars left this month
- ``purchased_credits_remaining`` -> top-up dollars left (rolls over)
- ``total_usable_credits`` -> total spendable
plus ``subscription.monthly_credits`` (the plan's monthly $ allowance, the
denominator for the "% used" plan bar) and ``current_period_end`` (renewal).
Design: two SEPARATE bars (decided with the user) rather than one crammed
three-segment bar at terminal widths three same-glyph density segments are
unreadable. The plan bar is "spent vs allowance this month" (carries % used);
the top-up bar is "money you bought, doesn't expire". Each gets full
resolution and a single fill glyph, so the bar is never ambiguous and never
relies on color.
Fail-open everywhere: any missing/non-finite field degrades to fewer bars or a
magnitudes-only view; a logged-out / unreachable portal yields
``available=False`` and the surface shows nothing.
"""
from __future__ import annotations
import logging
import math
import os
from dataclasses import dataclass, field
from typing import Any, Optional
logger = logging.getLogger(__name__)
# Below this TOTAL spendable ($), a paid account is flagged "low" — the alert
# state that nudges top-up/upgrade before a mid-run cutoff. Product threshold
# (user feedback): "any amount below $5 should be an alert status."
LOW_BALANCE_THRESHOLD_USD = 5.0
def _finite(value: Any) -> Optional[float]:
"""Return value as a float iff it's a real finite number (not bool/NaN/Inf)."""
if isinstance(value, bool) or not isinstance(value, (int, float)):
return None
f = float(value)
return f if math.isfinite(f) else None
def _fmt_usd(value: Optional[float]) -> str:
"""``$X.YY`` for display. ``None`` -> ``$0.00`` (callers gate on presence)."""
return f"${(value or 0.0):,.2f}"
def format_renews(value: Optional[str]) -> Optional[str]:
"""Format an ISO date/timestamp as a human date, e.g. ``Jul 24, 2026``.
Accepts ``2026-07-24``, ``2026-07-24T11:05:01.000Z``, etc. Returns the raw
string unchanged if it can't be parsed (never raises), and ``None`` for
empty input.
"""
if not value:
return None
from datetime import datetime
text = str(value).strip()
if not text:
return None
iso = text[:-1] + "+00:00" if text.endswith("Z") else text
try:
dt = datetime.fromisoformat(iso)
except ValueError:
# Fall back to a bare date prefix (YYYY-MM-DD) if present.
try:
dt = datetime.strptime(text[:10], "%Y-%m-%d")
except ValueError:
return text
# %-d isn't portable to Windows; build the day without a leading zero.
return f"{dt.strftime('%b')} {dt.day}, {dt.year}"
@dataclass(frozen=True)
class UsageBar:
"""One full-resolution bar: ``spent`` of ``total``, plus a remaining figure.
``kind`` is ``"plan"`` (monthly allowance, shows % used) or ``"topup"``
(purchased dollars, no denominator ``spent`` is 0 and ``total`` ==
``remaining`` so it renders as a full bar of available balance).
"""
kind: str # "plan" | "topup"
remaining_usd: float
total_usd: float
spent_usd: float = 0.0
@property
def pct_used(self) -> Optional[int]:
if self.kind != "plan" or self.total_usd <= 0:
return None
return max(0, min(100, round(self.spent_usd / self.total_usd * 100)))
@property
def fill_fraction(self) -> float:
"""Fraction of the bar that should read as 'remaining' (filled)."""
if self.total_usd <= 0:
return 0.0
return max(0.0, min(1.0, self.remaining_usd / self.total_usd))
@dataclass(frozen=True)
class UsageModel:
"""Surface-agnostic dollar usage model shared by /usage and /subscription.
``status`` classifies the account for copy selection:
- ``"free"`` : no paid access / no subscription (free models only)
- ``"low"`` : paid, but total spendable < $5 (ALERT)
- ``"healthy"`` : paid, total spendable >= $5
- ``"depleted"`` : paid access lost (balance exhausted)
"""
available: bool
status: str = "free"
plan_name: Optional[str] = None
renews_at: Optional[str] = None
renews_display: Optional[str] = None
subscription_remaining_usd: Optional[float] = None
topup_remaining_usd: Optional[float] = None
total_spendable_usd: Optional[float] = None
plan_bar: Optional[UsageBar] = None
topup_bar: Optional[UsageBar] = None
@property
def has_topup(self) -> bool:
return bool(self.topup_remaining_usd and self.topup_remaining_usd > 0)
def usage_model_from_account(account_info: Any) -> UsageModel:
"""Build a :class:`UsageModel` from a ``NousPortalAccountInfo``. Fail-open.
Returns ``UsageModel(available=False)`` when there's no usable account info
(logged out, no entitlement block). Never raises.
"""
try:
if account_info is None or not getattr(account_info, "logged_in", False):
return UsageModel(available=False)
access = getattr(account_info, "paid_service_access_info", None)
sub = getattr(account_info, "subscription", None)
paid = getattr(account_info, "paid_service_access", None)
sub_remaining = _finite(getattr(access, "subscription_credits_remaining", None)) if access else None
topup_remaining = _finite(getattr(access, "purchased_credits_remaining", None)) if access else None
total_usable = _finite(getattr(access, "total_usable_credits", None)) if access else None
plan_name = getattr(sub, "plan", None) if sub is not None else None
renews_at = getattr(sub, "current_period_end", None) if sub is not None else None
monthly = _finite(getattr(sub, "monthly_credits", None)) if sub is not None else None
has_subscription = bool(plan_name) or (monthly is not None and monthly > 0)
# Total spendable: prefer the server's total; else sum the parts we have.
if total_usable is not None:
total_spendable = total_usable
else:
parts = [v for v in (sub_remaining, topup_remaining) if v is not None]
total_spendable = sum(parts) if parts else None
# Status classification.
if paid is False:
status = "depleted"
elif not has_subscription and not (topup_remaining and topup_remaining > 0):
# No plan and no purchased balance -> free-models-only.
status = "free"
elif total_spendable is not None and total_spendable < LOW_BALANCE_THRESHOLD_USD:
status = "low"
else:
status = "healthy"
# Plan bar — only with a positive monthly allowance AND a remaining we
# can place on it. spent = cap - remaining, clamped (a debt/over-cap
# balance reads as fully spent rather than a nonsensical negative).
plan_bar: Optional[UsageBar] = None
if monthly is not None and monthly > 0 and sub_remaining is not None:
remaining = max(0.0, min(monthly, sub_remaining))
plan_bar = UsageBar(
kind="plan",
remaining_usd=remaining,
total_usd=monthly,
spent_usd=max(0.0, monthly - sub_remaining),
)
# Top-up bar — only when there are purchased dollars to show. No
# denominator (top-up has no monthly cap), so it renders full = balance.
topup_bar: Optional[UsageBar] = None
if topup_remaining is not None and topup_remaining > 0:
topup_bar = UsageBar(
kind="topup",
remaining_usd=topup_remaining,
total_usd=topup_remaining,
spent_usd=0.0,
)
return UsageModel(
available=True,
status=status,
plan_name=plan_name,
renews_at=renews_at,
renews_display=format_renews(renews_at),
subscription_remaining_usd=sub_remaining,
topup_remaining_usd=topup_remaining,
total_spendable_usd=total_spendable,
plan_bar=plan_bar,
topup_bar=topup_bar,
)
except Exception:
logger.debug("usage ▸ model build failed (fail-open)", exc_info=True)
return UsageModel(available=False)
def build_usage_model(*, timeout: float = 10.0) -> UsageModel:
"""Fetch account-info and build the shared usage model. Fail-open.
Dev override: ``HERMES_DEV_CREDITS_FIXTURE`` short-circuits to a fixture so
every usage state is testable without a live account (mirrors the existing
``/usage`` credits-block fixture path).
"""
fixture = _dev_fixture_usage_model()
if fixture is not None:
return fixture
try:
from hermes_cli.auth import get_provider_auth_state
tok = (get_provider_auth_state("nous") or {}).get("access_token")
if not (isinstance(tok, str) and tok.strip()):
return UsageModel(available=False)
except Exception:
return UsageModel(available=False)
try:
import concurrent.futures
from hermes_cli.nous_account import get_nous_portal_account_info
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
account = pool.submit(get_nous_portal_account_info, force_fresh=True).result(timeout=timeout)
return usage_model_from_account(account)
except Exception:
logger.debug("usage ▸ portal fetch failed (fail-open)", exc_info=True)
return UsageModel(available=False)
# =============================================================================
# Dev fixtures (throwaway scaffolding — env-var driven, no live portal)
# =============================================================================
def _dev_fixture_usage_model() -> Optional[UsageModel]:
"""Map ``HERMES_DEV_CREDITS_FIXTURE`` to a usage model for offline UX work.
Recognized names: ``free | healthy | low | topup | depleted``. Returns
``None`` when the env var is unset (real portal path runs).
"""
name = (os.getenv("HERMES_DEV_CREDITS_FIXTURE") or "").strip().lower()
if not name:
return None
if name == "free":
return UsageModel(available=True, status="free", plan_name=None)
if name in ("healthy", "mid"):
return UsageModel(
available=True,
status="healthy",
plan_name="Plus",
renews_at="2026-07-01",
subscription_remaining_usd=14.0,
total_spendable_usd=14.0,
plan_bar=UsageBar(kind="plan", remaining_usd=14.0, total_usd=20.0, spent_usd=6.0),
)
if name in ("topup", "top-up"):
return UsageModel(
available=True,
status="healthy",
plan_name="Plus",
renews_at="2026-07-01",
subscription_remaining_usd=14.0,
topup_remaining_usd=12.0,
total_spendable_usd=26.0,
plan_bar=UsageBar(kind="plan", remaining_usd=14.0, total_usd=20.0, spent_usd=6.0),
topup_bar=UsageBar(kind="topup", remaining_usd=12.0, total_usd=12.0, spent_usd=0.0),
)
if name == "low":
return UsageModel(
available=True,
status="low",
plan_name="Plus",
renews_at="2026-07-01",
subscription_remaining_usd=3.4,
total_spendable_usd=3.4,
plan_bar=UsageBar(kind="plan", remaining_usd=3.4, total_usd=20.0, spent_usd=16.6),
)
if name == "depleted":
return UsageModel(
available=True,
status="depleted",
plan_name="Plus",
renews_at="2026-07-01",
subscription_remaining_usd=0.0,
total_spendable_usd=0.0,
plan_bar=UsageBar(kind="plan", remaining_usd=0.0, total_usd=20.0, spent_usd=20.0),
)
return None
-458
View File
@@ -1,458 +0,0 @@
"""Surface-agnostic core for the Phase 2b Remote Spending screens.
One fetch/parse per concern, consumed identically by the CLI handler
(``cli.py::_show_billing``), the TUI JSON-RPC methods
(``tui_gateway/server.py``), and any other surface. Mirrors the proven
``agent/account_usage.py::build_credits_view`` pattern: parse the server payload
into a frozen dataclass; **fail open** when not logged in or the portal is
unreachable, return a struct with ``logged_in=False`` and let the surface degrade
gracefully (never crash).
Money discipline: the server emits decimal STRINGS (``"142.5"``, not fixed 2dp).
We keep them as :class:`decimal.Decimal` end-to-end and only format for display.
"""
from __future__ import annotations
import logging
import os
import uuid
from dataclasses import dataclass, field
from decimal import Decimal, InvalidOperation
from typing import Any, Optional
logger = logging.getLogger(__name__)
# =============================================================================
# Decimal money helpers
# =============================================================================
def parse_money(value: Any) -> Optional[Decimal]:
"""Parse a server money value (decimal string) into :class:`Decimal`.
Returns None for missing/invalid input. Never raises. Accepts str/int (and,
defensively, float though the server always sends strings).
"""
if value is None:
return None
try:
# Decimal(str(...)) avoids binary-float artifacts if a float ever sneaks in.
return Decimal(str(value).strip())
except (InvalidOperation, ValueError, TypeError):
return None
def format_money(value: Optional[Decimal]) -> str:
"""Format a Decimal as ``$X`` / ``$X.YY`` for display.
Whole dollars show no decimals; any fractional amount shows exactly 2dp:
``Decimal("142.5")`` ``"$142.50"``, ``Decimal("100")`` ``"$100"``,
``Decimal("0.01")`` ``"$0.01"``.
"""
if value is None:
return ""
if value == value.to_integral_value():
# Whole dollars — no decimal point. format(..., "f") avoids 1E+3 for 1000.
return f"${format(value.to_integral_value(), 'f')}"
# Fractional — always show 2dp.
return f"${format(value.quantize(Decimal('0.01')), 'f')}"
# =============================================================================
# Parsed sub-structures
# =============================================================================
# resolvedVia → the human answer to "why THIS card?". Keys are the server's card
# resolution rungs (NAS card-on-file ladder); absent/unknown rungs render no label
# so the display degrades cleanly on servers that don't send resolvedVia yet.
_CARD_PROVENANCE_LABELS = {
"subPin": "the card on your subscription",
"customerDefault": "your default card saved on the portal",
"autoRefill": "your auto-reload card",
}
@dataclass(frozen=True)
class CardInfo:
brand: str
last4: str
# NAS card-on-file field (post card-resolver): which ladder rung found the
# card. Defaults off so pre-resolver payloads parse unchanged.
resolved_via: Optional[str] = None
@property
def masked(self) -> str:
# A Link payment method has no card number (last4 = "") — render the
# brand alone, not "Link ····".
if not self.last4:
return self.brand
return f"{self.brand} ····{self.last4}"
@property
def provenance(self) -> Optional[str]:
"""Human label for why this card was picked, or None (unknown rung /
server too old to say)."""
if self.resolved_via is None:
return None
return _CARD_PROVENANCE_LABELS.get(self.resolved_via)
@property
def display(self) -> str:
"""The one-line card display: ``Visa ····4242 — the card on your
subscription`` (or just the masked card when provenance is unknown)."""
label = self.provenance
return f"{self.masked}{label}" if label else self.masked
@dataclass(frozen=True)
class MonthlyCap:
limit_usd: Optional[Decimal] = None
spent_this_month_usd: Optional[Decimal] = None
is_default_ceiling: bool = False
@dataclass(frozen=True)
class AutoReloadCard:
kind: str # "canonical" | "distinct" | "none"
payment_method_id: Optional[str] = None
brand: Optional[str] = None
last4: Optional[str] = None
@dataclass(frozen=True)
class AutoReload:
enabled: bool = False
threshold_usd: Optional[Decimal] = None
reload_to_usd: Optional[Decimal] = None
card: Optional[AutoReloadCard] = None
@dataclass(frozen=True)
class BillingState:
"""Parsed ``GET /api/billing/state`` — the overview screen's data.
Fail-open: ``logged_in=False`` (and empty fields) when not logged in or the
portal is unreachable.
"""
logged_in: bool
org_id: Optional[str] = None
org_slug: Optional[str] = None
org_name: Optional[str] = None
role: Optional[str] = None # "OWNER" | "ADMIN" | "FINANCE_ADMIN" | "SECURITY_ADMIN" | "MEMBER"
can_change_plan_raw: Optional[bool] = None
balance_usd: Optional[Decimal] = None
cli_billing_enabled: bool = False
charge_presets: tuple[Decimal, ...] = ()
min_usd: Optional[Decimal] = None
max_usd: Optional[Decimal] = None
card: Optional[CardInfo] = None
monthly_cap: Optional[MonthlyCap] = None
auto_reload: Optional[AutoReload] = None
portal_url: Optional[str] = None
# When the fetch failed (vs cleanly not-logged-in), the message for the surface.
error: Optional[str] = None
@property
def is_admin(self) -> bool:
"""Deprecated/display only — a legacy OWNER/ADMIN check.
NOT a capability check; use :attr:`can_change_plan` for gating billing
plan-change actions.
"""
return (self.role or "").upper() in ("OWNER", "ADMIN")
@property
def can_change_plan(self) -> bool:
"""Server capability when supplied; otherwise the legacy role fallback."""
if self.can_change_plan_raw is not None:
return self.can_change_plan_raw
return self.is_admin
@property
def can_charge(self) -> bool:
"""True when the UI should offer charge/auto-reload actions.
Uses the server-granted plan-change capability (``can_change_plan``,
which itself falls back to the legacy OWNER/ADMIN role check when the
server omits ``canChangePlan``) AND the per-org kill-switch. This lets
the server grant charge capability to non-OWNER/ADMIN roles (e.g.
FINANCE_ADMIN) via ``canChangePlan``, instead of hard-coding the
deprecated 3-role admin check. (The server still enforces; this is
just for graying out actions the user can't take.)
"""
return self.can_change_plan and self.cli_billing_enabled
def _parse_card(raw: Any) -> Optional[CardInfo]:
if not isinstance(raw, dict):
return None
brand = raw.get("brand")
last4 = raw.get("last4")
if not (isinstance(brand, str) and isinstance(last4, str)):
return None
# Post-resolver fields — all optional so both payload generations parse.
resolved_via = raw.get("resolvedVia")
if not isinstance(resolved_via, str):
resolved_via = None
return CardInfo(brand=brand, last4=last4, resolved_via=resolved_via)
def _parse_monthly_cap(raw: Any) -> Optional[MonthlyCap]:
if not isinstance(raw, dict):
return None
return MonthlyCap(
limit_usd=parse_money(raw.get("limitUsd")),
spent_this_month_usd=parse_money(raw.get("spentThisMonthUsd")),
is_default_ceiling=bool(raw.get("isDefaultCeiling")),
)
def _parse_auto_reload(raw: Any) -> Optional[AutoReload]:
if not isinstance(raw, dict):
return None
return AutoReload(
enabled=bool(raw.get("enabled")),
threshold_usd=parse_money(raw.get("thresholdUsd")),
reload_to_usd=parse_money(raw.get("reloadToUsd")),
card=_parse_auto_reload_card(raw.get("card")),
)
def _parse_auto_reload_card(raw: Any) -> Optional[AutoReloadCard]:
if not isinstance(raw, dict):
return None
kind = raw.get("kind")
if kind not in ("canonical", "distinct", "none"):
return None
if kind in ("canonical", "none"):
return AutoReloadCard(kind=kind)
payment_method_id = raw.get("paymentMethodId")
brand = raw.get("brand")
last4 = raw.get("last4")
return AutoReloadCard(
kind=kind,
payment_method_id=payment_method_id if isinstance(payment_method_id, str) else None,
brand=brand if isinstance(brand, str) else None,
last4=last4 if isinstance(last4, str) else None,
)
def billing_state_from_payload(
payload: dict[str, Any], *, portal_url: Optional[str] = None
) -> BillingState:
"""Map a raw ``/api/billing/state`` JSON dict into :class:`BillingState`."""
raw_org = payload.get("org")
org: dict[str, Any] = raw_org if isinstance(raw_org, dict) else {}
raw_bounds = payload.get("bounds")
bounds: dict[str, Any] = raw_bounds if isinstance(raw_bounds, dict) else {}
presets: list[Decimal] = []
for item in payload.get("chargePresets") or ():
parsed = parse_money(item)
if parsed is not None:
presets.append(parsed)
return BillingState(
logged_in=True,
org_id=org.get("id"),
org_slug=org.get("slug"),
org_name=org.get("name"),
role=org.get("role"),
can_change_plan_raw=(
payload.get("canChangePlan")
if isinstance(payload.get("canChangePlan"), bool)
else None
),
balance_usd=parse_money(payload.get("balanceUsd")),
cli_billing_enabled=bool(payload.get("cliBillingEnabled")),
charge_presets=tuple(presets),
min_usd=parse_money(bounds.get("minUsd")),
max_usd=parse_money(bounds.get("maxUsd")),
card=_parse_card(payload.get("card")),
monthly_cap=_parse_monthly_cap(payload.get("monthlyCap")),
auto_reload=_parse_auto_reload(payload.get("autoReload")),
portal_url=portal_url,
)
# =============================================================================
# Fail-open builders (the surface front doors)
# =============================================================================
def build_billing_state(*, timeout: float = 15.0) -> BillingState:
"""Fetch + parse ``/api/billing/state``. Fail-open.
Returns ``BillingState(logged_in=False)`` when not logged in. On a portal/HTTP
failure, returns ``logged_in=False`` with ``error`` set so the surface can show
a clear message rather than crashing.
Dev override: ``HERMES_DEV_BILLING_FIXTURE`` short-circuits to a fixture so the
card-on-file / admin / scope states are testable offline (mirrors
``HERMES_DEV_CREDITS_FIXTURE`` for the usage model).
"""
fixture = _dev_fixture_billing_state()
if fixture is not None:
return fixture
try:
from hermes_cli.nous_billing import (
BillingAuthError,
BillingError,
_absolutize_portal_url,
get_billing_state,
resolve_portal_base_url,
)
except Exception:
return BillingState(logged_in=False, error="billing client unavailable")
try:
payload = get_billing_state(timeout=timeout)
except BillingAuthError:
return BillingState(logged_in=False)
except BillingError as exc:
logger.debug("billing ▸ /state fetch failed (fail-open)", exc_info=True)
return BillingState(logged_in=False, error=str(exc))
except Exception:
logger.debug("billing ▸ /state unexpected error (fail-open)", exc_info=True)
return BillingState(logged_in=False, error="could not load billing state")
# Prefer a server-supplied portalUrl if present (resolved to absolute in case
# it's relative); else build the standard one.
raw_portal = payload.get("portalUrl") if isinstance(payload, dict) else None
portal_url = _absolutize_portal_url(raw_portal) if raw_portal else None
if not portal_url:
try:
portal_url = _fallback_portal_url(resolve_portal_base_url())
except Exception:
portal_url = None
return billing_state_from_payload(payload, portal_url=portal_url)
def _fallback_portal_url(base: str) -> str:
"""Standard billing deep-link when the server omits ``portalUrl``."""
return f"{base.rstrip('/')}/billing?topup=open"
# =============================================================================
# Dev fixtures (throwaway scaffolding — env-var driven, no live portal)
# =============================================================================
def _dev_fixture_billing_state() -> Optional[BillingState]:
"""Map ``HERMES_DEV_BILLING_FIXTURE`` to a :class:`BillingState` for offline UX.
Recognized names::
nocard logged in · billing on · admin · NO card on file
card card on file · auto-reload off
card-autoreload card on file · auto-reload on
notadmin logged in · MEMBER role (billing actions disabled)
billing-off logged in · admin · per-org kill-switch OFF
logged-out not logged in
Returns ``None`` when the env var is unset (the real portal path runs).
Mirrors ``HERMES_DEV_CREDITS_FIXTURE``; the usage *bar* still comes from
``HERMES_DEV_CREDITS_FIXTURE`` (set both to pair a bar with a billing state).
"""
name = (os.getenv("HERMES_DEV_BILLING_FIXTURE") or "").strip().lower()
if not name:
return None
# Shared fixture portal host (matches subscription_view._DEV_FIXTURE_PORTAL —
# prod host, not staging; the ?topup=open suffix is the /topup deep-link).
portal = "https://portal.nousresearch.com/billing?topup=open"
common: dict[str, Any] = dict(
org_id="org_acme",
org_slug="acme",
org_name="Acme Inc",
role="OWNER",
balance_usd=Decimal("3.40"),
cli_billing_enabled=True,
charge_presets=(Decimal("10"), Decimal("25"), Decimal("50")),
min_usd=Decimal("5"),
max_usd=Decimal("500"),
portal_url=portal,
)
card = CardInfo(brand="Visa", last4="4242")
autoreload_on = AutoReload(enabled=True, threshold_usd=Decimal("5"), reload_to_usd=Decimal("25"))
if name in ("logged-out", "logged_out", "loggedout"):
return BillingState(logged_in=False)
if name == "nocard":
return BillingState(logged_in=True, card=None, **common)
if name == "card":
return BillingState(logged_in=True, card=card, **common)
if name in ("card-sub", "card_sub"):
# Post-resolver: the card came from the subscription (provenance label).
_sub_card = CardInfo(brand="Visa", last4="4242", resolved_via="subPin")
return BillingState(logged_in=True, card=_sub_card, **common)
if name in ("card-autoreload", "card_autoreload", "autoreload"):
return BillingState(logged_in=True, card=card, auto_reload=autoreload_on, **common)
if name in ("notadmin", "not-admin", "member"):
opts = {**common, "role": "MEMBER"}
return BillingState(logged_in=True, card=card, **opts)
if name in ("billing-off", "billing_off", "off"):
opts = {**common, "cli_billing_enabled": False}
return BillingState(logged_in=True, card=None, **opts)
# Unknown name → logged-out so the misconfiguration is visible.
return BillingState(logged_in=False, error=f"unknown HERMES_DEV_BILLING_FIXTURE: {name}")
# =============================================================================
# Idempotency
# =============================================================================
def new_idempotency_key() -> str:
"""Fresh UUID for a user-confirmed purchase (reuse on retry of the SAME buy).
The ``Idempotency-Key`` header is mandatory on ``POST /charge``; generate one
per confirmed purchase and reuse it across retries so a double-submit collapses
to a single charge. Never reuse a key across different amounts (the server
returns 409 idempotency_conflict).
"""
return str(uuid.uuid4())
# =============================================================================
# Amount validation (Screen 3 custom input)
# =============================================================================
@dataclass(frozen=True)
class AmountValidation:
ok: bool
amount: Optional[Decimal] = None
error: Optional[str] = None
def validate_charge_amount(
raw: str, *, min_usd: Optional[Decimal], max_usd: Optional[Decimal]
) -> AmountValidation:
"""Validate a custom charge amount against bounds + 2dp (multipleOf 0.01).
Mirrors the server's accept/reject so the UI can give instant feedback rather
than round-tripping a sure-to-fail charge. The server is still authoritative.
"""
cleaned = (raw or "").strip().lstrip("$").strip()
amount = parse_money(cleaned)
if amount is None:
return AmountValidation(ok=False, error="Enter a dollar amount, e.g. 100")
if amount <= 0:
return AmountValidation(ok=False, error="Amount must be greater than $0")
# multipleOf 0.01 — reject sub-cent precision.
if amount != amount.quantize(Decimal("0.01")):
return AmountValidation(ok=False, error="Amount can't be smaller than a cent")
if min_usd is not None and amount < min_usd:
return AmountValidation(ok=False, error=f"Minimum is {format_money(min_usd)}")
if max_usd is not None and amount > max_usd:
return AmountValidation(ok=False, error=f"Maximum is {format_money(max_usd)}")
return AmountValidation(ok=True, amount=amount)
-148
View File
@@ -1,148 +0,0 @@
"""Bounded reads of HTTP error response bodies.
When a provider returns a non-OK status on a *streaming* request, Hermes reads
the response body to build a useful diagnostic error. A bare ``response.read()``
on a streaming httpx response is unbounded in two dangerous ways:
1. A server can declare (or stream) an arbitrarily large body, so the read can
balloon memory.
2. A server can open the body and then stall forever (no ``Content-Length``,
no further bytes), so the read hangs the agent indefinitely.
Both are realistic against a misbehaving proxy, a hijacked endpoint, or a
provider having a bad day. The diagnostic body is only ever shown to the user
truncated to a few hundred characters, so reading megabytes or blocking
forever buys nothing.
``read_streaming_error_body`` bounds the read to a byte cap and enforces a
hard wall-clock deadline, returning the decoded text snippet. Callers pass the
returned text into their existing error builders instead of touching
``response.text`` (which would be unbounded / would raise after a partial
stream read).
A subtlety the implementation must respect: ``httpx``'s ``iter_bytes()`` blocks
*inside* the C/socket read while waiting for the next chunk. A wall-clock check
placed only between yielded chunks cannot interrupt a server that opens the
body and then stalls mid-chunk control never returns to Python until httpx's
own (often 30s+) read timeout fires. To guarantee a bounded stop regardless of
socket behavior, the read runs on a daemon worker thread and the caller waits
on it with a hard deadline; on timeout we close the response (which unblocks /
cancels the read) and return whatever partial bytes were collected.
Ported and adapted from openclaw/openclaw#95108 ("bound Anthropic error
streams"), generalized to cover Hermes's three streaming error-body sites
(native Gemini, Gemini Cloud Code, Antigravity Cloud Code).
"""
from __future__ import annotations
import logging
import threading
from typing import List, Optional
import httpx
logger = logging.getLogger(__name__)
# Defaults chosen to comfortably hold any real provider error envelope (Google
# RPC error JSON, Anthropic error JSON) while rejecting pathological bodies.
DEFAULT_ERROR_BODY_MAX_BYTES = 64 * 1024
# Hard wall-clock deadline for the whole bounded read. A streaming error body
# that does not finish within this window is abandoned and the connection is
# closed; we keep whatever partial bytes arrived.
DEFAULT_ERROR_BODY_TIMEOUT_S = 10.0
def read_streaming_error_body(
response: httpx.Response,
*,
max_bytes: int = DEFAULT_ERROR_BODY_MAX_BYTES,
timeout_s: float = DEFAULT_ERROR_BODY_TIMEOUT_S,
) -> str:
"""Read a non-OK streaming response body with a byte cap and a hard deadline.
Returns the decoded body text (UTF-8, errors replaced), truncated to
``max_bytes``. Never raises: any transport error, stall, or oversize
condition is swallowed and the best-effort partial text (or an empty
string) is returned, because this runs on the error path and must not
mask the original HTTP failure with a read error.
The byte cap protects against huge bodies; the wall-clock deadline (enforced
via a worker thread so it can interrupt a socket read that stalls mid-chunk)
protects against bodies that open and then hang.
"""
chunks: List[bytes] = []
state = {"truncated": False}
done = threading.Event()
def _drain() -> None:
total = 0
try:
for chunk in response.iter_bytes():
if not chunk:
continue
remaining = max_bytes - total
if remaining <= 0:
state["truncated"] = True
break
if len(chunk) > remaining:
chunks.append(chunk[:remaining])
total += remaining
state["truncated"] = True
break
chunks.append(chunk)
total += len(chunk)
except Exception as exc: # noqa: BLE001 - error path must not raise
logger.debug("bounded error-body read failed: %s", exc)
finally:
done.set()
worker = threading.Thread(
target=_drain, name="bounded-error-body-read", daemon=True
)
worker.start()
finished = done.wait(timeout=timeout_s)
if not finished:
logger.debug(
"bounded error-body read: hard timeout after %.1fs (%d bytes so far)",
timeout_s,
sum(len(c) for c in chunks),
)
# Closing the response cancels the in-flight socket read, letting the
# worker thread unwind. We do not join (it is a daemon and may be
# blocked in C); the partial `chunks` collected so far are returned.
_safe_close(response)
else:
_safe_close(response)
if state["truncated"]:
logger.debug(
"bounded error-body read: capped at %d bytes (max=%d)",
sum(len(c) for c in chunks),
max_bytes,
)
return b"".join(chunks).decode("utf-8", errors="replace")
def _safe_close(response: httpx.Response) -> None:
try:
response.close()
except Exception: # noqa: BLE001
pass
def read_error_body_or_default(
response: httpx.Response,
*,
max_bytes: int = DEFAULT_ERROR_BODY_MAX_BYTES,
timeout_s: float = DEFAULT_ERROR_BODY_TIMEOUT_S,
) -> Optional[str]:
"""Like ``read_streaming_error_body`` but returns ``None`` on empty body.
Convenience for callers that distinguish "no body" from "empty string".
"""
text = read_streaming_error_body(
response, max_bytes=max_bytes, timeout_s=timeout_s
)
return text or None
File diff suppressed because it is too large Load Diff
+30 -237
View File
@@ -127,21 +127,14 @@ def _chat_content_to_responses_parts(content: Any, *, role: str = "user") -> Lis
return converted
def _summarize_user_message_for_log(content: Any, *, sep: str = " ") -> str:
"""Flatten message content to a plain-text summary.
def _summarize_user_message_for_log(content: Any) -> str:
"""Return a short text summary of a user message for logging/trajectory.
Multimodal messages arrive as a list of ``{type:"text"|"image_url", ...}``
parts from the API server. Several consumers want a plain string:
- Logging, spinner previews, and trajectory files (the default ``sep=" "``).
- External memory providers, which feed the text to regexes
(``sanitize_context``) and text APIs a raw list crashes the sync with
``expected string or bytes-like object, got 'list'`` (use ``sep="\\n"``).
Text parts are joined with ``sep``; images become a ``[N image(s)]`` marker
so the turn isn't recorded as if the attachment never existed. Returns an
empty string for empty lists and ``str(content)`` for unexpected scalar
types.
parts from the API server. Logging, spinner previews, and trajectory
files all want a plain string this helper extracts the first chunk of
text and notes any attached images. Returns an empty string for empty
lists and ``str(content)`` for unexpected scalar types.
"""
if content is None:
return ""
@@ -164,7 +157,7 @@ def _summarize_user_message_for_log(content: Any, *, sep: str = " ") -> str:
text_bits.append(text)
elif ptype in {"image_url", "input_image"}:
image_count += 1
summary = sep.join(text_bits).strip()
summary = " ".join(text_bits).strip()
if image_count:
note = f"[{image_count} image{'s' if image_count != 1 else ''}]"
summary = f"{note} {summary}" if summary else note
@@ -262,39 +255,12 @@ def _responses_tools(tools: Optional[List[Dict[str, Any]]] = None) -> Optional[L
return converted or None
# Provider-executed built-in tool *declaration* types accepted on the
# Responses ``tools`` array. These are declared by ``type`` alone (no
# client-side name/parameters schema) and run server-side — the provider
# owns the implementation and reports progress via the matching ``*_call``
# output items. Hermes injects xAI's native ``web_search`` for the xAI
# transport (see agent/transports/codex.py); the rest are listed so the
# preflight validator passes them through rather than rejecting them as
# "unsupported type". Mirrors the ``*_call`` item-type set used in
# _normalize_codex_response.
_RESPONSES_BUILTIN_TOOL_TYPES = {
"web_search",
"web_search_preview",
"file_search",
"code_interpreter",
"image_generation",
"computer_use_preview",
"local_shell",
}
# ---------------------------------------------------------------------------
# Message format conversion
# ---------------------------------------------------------------------------
_RESPONSE_MESSAGE_STATUSES = {"completed", "incomplete", "in_progress"}
# The Responses API rejects input[].id longer than this with a non-retryable
# HTTP 400 ("string too long"). Codex-issued assistant message ids are
# server-assigned base64 blobs that can run 400+ chars, while Hermes-minted
# ids (msg_...) stay well under this cap and are worth keeping for
# prefix-cache hits. Drop only the oversized ones on replay.
_MAX_RESPONSES_ITEM_ID_LENGTH = 64
def _normalize_responses_message_status(value: Any, *, default: str = "completed") -> str:
"""Normalize a Responses assistant message status for replay.
@@ -314,7 +280,6 @@ def _chat_messages_to_responses_input(
messages: List[Dict[str, Any]],
*,
is_xai_responses: bool = False,
is_github_responses: bool = False,
replay_encrypted_reasoning: bool = True,
current_issuer_kind: Optional[str] = None,
) -> List[Dict[str, Any]]:
@@ -339,16 +304,6 @@ def _chat_messages_to_responses_input(
items from the conversation history and threads ``replay_enabled=False``
through this converter so subsequent turns send no reasoning items.
``is_github_responses`` drops the ``id`` field from replayed
``codex_message_items`` regardless of length. The Copilot backend
(api.githubcopilot.com/responses) binds these ids to a specific
backend "connection" credential-pool rotation, a gateway restart,
or routine load-balancer churn between turns all invalidate it and
rejects a stale id with HTTP 401 "input item ID does not belong to
this connection" even for short ids (see #32716). ``phase``/
``status``/``content`` are still replayed; only ``id`` is unsafe to
reuse across a Copilot connection.
``current_issuer_kind`` enables a per-item cross-issuer guard. The
Responses API's ``encrypted_content`` blob is decryptable only by the
endpoint that minted it replaying a Codex-issued blob against xAI
@@ -481,14 +436,8 @@ def _chat_messages_to_responses_input(
"content": normalized_content_parts,
}
item_id = raw_item.get("id")
if (
not is_github_responses
and isinstance(item_id, str)
and item_id.strip()
):
stripped_id = item_id.strip()
if len(stripped_id) <= _MAX_RESPONSES_ITEM_ID_LENGTH:
replay_item["id"] = stripped_id
if isinstance(item_id, str) and item_id.strip():
replay_item["id"] = item_id.strip()
phase = raw_item.get("phase")
if isinstance(phase, str) and phase.strip():
replay_item["phase"] = phase.strip()
@@ -600,11 +549,7 @@ def _chat_messages_to_responses_input(
# Input preflight / validation
# ---------------------------------------------------------------------------
def _preflight_codex_input_items(
raw_items: Any,
*,
is_github_responses: bool = False,
) -> List[Dict[str, Any]]:
def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
if not isinstance(raw_items, list):
raise ValueError("Codex Responses input must be a list of input items.")
@@ -745,14 +690,8 @@ def _preflight_codex_input_items(
"content": normalized_content,
}
item_id = item.get("id")
if (
not is_github_responses
and isinstance(item_id, str)
and item_id.strip()
):
stripped_id = item_id.strip()
if len(stripped_id) <= _MAX_RESPONSES_ITEM_ID_LENGTH:
normalized_item["id"] = stripped_id
if isinstance(item_id, str) and item_id.strip():
normalized_item["id"] = item_id.strip()
phase = item.get("phase")
if isinstance(phase, str) and phase.strip():
normalized_item["phase"] = phase.strip()
@@ -824,7 +763,6 @@ def _preflight_codex_api_kwargs(
api_kwargs: Any,
*,
allow_stream: bool = False,
is_github_responses: bool = False,
) -> Dict[str, Any]:
if not isinstance(api_kwargs, dict):
raise ValueError("Codex Responses request must be a dict.")
@@ -846,10 +784,7 @@ def _preflight_codex_api_kwargs(
instructions = str(instructions)
instructions = instructions.strip() or DEFAULT_AGENT_IDENTITY
normalized_input = _preflight_codex_input_items(
api_kwargs.get("input"),
is_github_responses=is_github_responses,
)
normalized_input = _preflight_codex_input_items(api_kwargs.get("input"))
tools = api_kwargs.get("tools")
normalized_tools = None
@@ -860,22 +795,7 @@ def _preflight_codex_api_kwargs(
for idx, tool in enumerate(tools):
if not isinstance(tool, dict):
raise ValueError(f"Codex Responses tools[{idx}] must be an object.")
tool_type = tool.get("type")
# Provider-executed built-in tools (xAI native web_search, code
# interpreter, etc.) are declared by ``type`` alone and carry no
# ``name``/``parameters`` schema — the provider owns the
# implementation. Pass them through verbatim instead of forcing
# them through the function-tool validation below (which would
# otherwise reject them with "unsupported type"). See
# agent/transports/codex.py for where xAI's native web_search is
# injected.
if tool_type in _RESPONSES_BUILTIN_TOOL_TYPES:
normalized_tools.append(dict(tool))
continue
if tool_type != "function":
if tool.get("type") != "function":
raise ValueError(f"Codex Responses tools[{idx}] has unsupported type {tool.get('type')!r}.")
name = tool.get("name")
@@ -1118,22 +1038,6 @@ def _normalize_codex_response(
differs from the one that minted the encrypted_content blob and drop
the item instead of triggering HTTP 400 invalid_encrypted_content.
"""
response_status = getattr(response, "status", None)
if isinstance(response_status, str):
response_status = response_status.strip().lower()
else:
response_status = None
incomplete_details = getattr(response, "incomplete_details", None)
incomplete_reason = ""
if isinstance(incomplete_details, dict):
incomplete_reason = str(incomplete_details.get("reason") or "").strip().lower()
elif incomplete_details is not None:
incomplete_reason = str(getattr(incomplete_details, "reason", "") or "").strip().lower()
response_incomplete_content_filter = (
response_status == "incomplete" and incomplete_reason == "content_filter"
)
output = getattr(response, "output", None)
if not isinstance(output, list) or not output:
# The Codex backend can return empty output when the answer was
@@ -1150,18 +1054,15 @@ def _normalize_codex_response(
content=[SimpleNamespace(type="output_text", text=out_text.strip())],
)]
response.output = output
elif response_incomplete_content_filter:
# This is a deterministic provider safety block, not a partial
# answer. Synthesize an empty message so finish_reason below becomes
# content_filter and the conversation loop can fallback/surface it
# instead of burning three continuation attempts.
output = [SimpleNamespace(
type="message", role="assistant", status="completed", content=[]
)]
response.output = output
else:
raise RuntimeError("Responses API returned no output items")
response_status = getattr(response, "status", None)
if isinstance(response_status, str):
response_status = response_status.strip().lower()
else:
response_status = None
if response_status in {"failed", "cancelled"}:
error_obj = getattr(response, "error", None)
error_msg = _format_responses_error(error_obj, response_status)
@@ -1173,38 +1074,10 @@ def _normalize_codex_response(
message_items_raw: List[Dict[str, Any]] = []
tool_calls: List[Any] = []
has_incomplete_items = response_status in {"queued", "in_progress", "incomplete"}
saw_streaming_or_item_incomplete = response_status in {"queued", "in_progress"}
saw_commentary_phase = False
saw_final_answer_phase = False
saw_reasoning_item = False
# Server-side built-in tool calls (xAI's native web_search, code
# interpreter, etc.) are executed by the provider and reported as
# discrete ``*_call`` output items. xAI's /v1/responses surface
# (e.g. grok-composer-2.5-fast on SuperGrok OAuth) routinely leaves
# these items at ``status="in_progress"`` even when the overall
# ``response.status == "completed"`` — the search ran to completion
# server-side, the per-item status simply isn't reconciled. These
# are NOT a signal that the model's turn is unfinished, so they must
# not flip ``has_incomplete_items``. Only the response-level status
# and genuine model output items (message/reasoning/function_call)
# govern the incomplete verdict. Without this guard, any turn where
# grok-composer invokes server-side search is misclassified as
# ``finish_reason="incomplete"`` and burns 3 fruitless continuation
# retries before failing with "Codex response remained incomplete
# after 3 continuation attempts". client-side function/custom tool
# calls keep their own in_progress handling below (they are skipped,
# not awaited).
_SERVER_SIDE_TOOL_CALL_TYPES = {
"web_search_call",
"file_search_call",
"code_interpreter_call",
"image_generation_call",
"computer_call",
"local_shell_call",
"mcp_call",
}
for item in output:
item_type = getattr(item, "type", None)
item_status = getattr(item, "status", None)
@@ -1213,38 +1086,21 @@ def _normalize_codex_response(
else:
item_status = None
if (
item_status in {"queued", "in_progress", "incomplete"}
and item_type not in _SERVER_SIDE_TOOL_CALL_TYPES
):
if item_status in {"queued", "in_progress", "incomplete"}:
has_incomplete_items = True
saw_streaming_or_item_incomplete = True
if item_type == "message":
item_phase = getattr(item, "phase", None)
normalized_phase = None
is_commentary_phase = False
if isinstance(item_phase, str):
normalized_phase = item_phase.strip().lower()
if normalized_phase in {"commentary", "analysis"}:
saw_commentary_phase = True
is_commentary_phase = True
elif normalized_phase in {"final_answer", "final"}:
saw_final_answer_phase = True
message_text = _extract_responses_message_text(item)
if message_text:
# Responses ``commentary``/``analysis`` phase text is mid-turn
# preamble/progress narration, never the turn's final answer
# (Codex CLI excludes it from last-message extraction; issues
# #24933 / #41293). Keep it out of assistant content so it
# can't be concatenated into — or leak as — the final response,
# but surface it through the reasoning channel so the CLI/
# gateway display it like thinking text. The exact message
# item is still preserved below for replay/cache continuity.
if is_commentary_phase:
reasoning_parts.append(message_text)
else:
content_parts.append(message_text)
content_parts.append(message_text)
raw_message_item: Dict[str, Any] = {
"type": "message",
"role": "assistant",
@@ -1339,11 +1195,7 @@ def _normalize_codex_response(
))
final_text = "\n".join([p for p in content_parts if p]).strip()
if (
not final_text
and hasattr(response, "output_text")
and not (saw_commentary_phase and not saw_final_answer_phase)
):
if not final_text and hasattr(response, "output_text"):
out_text = getattr(response, "output_text", "")
if isinstance(out_text, str):
final_text = out_text.strip()
@@ -1379,45 +1231,6 @@ def _normalize_codex_response(
# so the model keeps its chain-of-thought on the retry.
final_text = ""
# ── Reasoning-channel answer salvage (xAI grok) ──────────────
# grok-4.x on the xAI /v1/responses surface sometimes emits its final
# answer inside the reasoning item instead of as a ``message`` output
# item, marking where the answer starts with grok's internal
# ``<response>`` delimiter. Without salvage, the reasoning-only rule
# below classifies the turn ``incomplete`` — and because reasoning
# items on this surface carry no ``encrypted_content``, the interim
# message replays as nothing, so every continuation request is
# byte-identical to the one that just failed. The turn burns its 3
# retries and dies with "Codex response remained incomplete after 3
# continuation attempts" even though the answer was produced on the
# first attempt. Observed live with grok-4.20 on xai-oauth
# (2026-07-13). Promote the delimited tail to assistant content and
# keep the untagged prefix as thinking text.
if (
issuer_kind == "xai_responses"
and not final_text
and not tool_calls
and reasoning_parts
):
joined_reasoning = "\n\n".join(reasoning_parts)
marker = joined_reasoning.rfind("<response>")
if marker != -1:
salvaged = joined_reasoning[marker + len("<response>"):]
closing = salvaged.find("</response>")
if closing != -1:
salvaged = salvaged[:closing]
salvaged = salvaged.strip()
if salvaged:
logger.warning(
"xAI response delivered its final answer inside the "
"reasoning channel (<response> delimiter); promoting "
"%d chars to assistant content.",
len(salvaged),
)
final_text = salvaged
reasoning_prefix = joined_reasoning[:marker].strip()
reasoning_parts = [reasoning_prefix] if reasoning_prefix else []
assistant_message = SimpleNamespace(
content=final_text,
tool_calls=tool_calls,
@@ -1430,38 +1243,18 @@ def _normalize_codex_response(
if tool_calls:
finish_reason = "tool_calls"
elif response_incomplete_content_filter:
finish_reason = "content_filter"
elif leaked_tool_call_text:
finish_reason = "incomplete"
elif saw_streaming_or_item_incomplete:
finish_reason = "incomplete"
elif (has_incomplete_items or saw_commentary_phase) and not saw_final_answer_phase:
elif has_incomplete_items or (saw_commentary_phase and not saw_final_answer_phase):
finish_reason = "incomplete"
elif (reasoning_items_raw or reasoning_parts or saw_reasoning_item) and not final_text:
# Response contains only reasoning (encrypted thinking state and/or
# human-readable summary) with no visible content or tool calls.
#
# For the specially-handled backends (Codex, xAI, GitHub/Copilot),
# reasoning-only with status="completed" means "the model is still
# thinking and needs another turn" — treat it as incomplete so the
# Codex continuation path retries instead of falling into the
# empty-content retry loop.
#
# For all other backends (other:<base_url>, etc.), trust the provider's
# own response.status signal. When status == "completed" and no items
# are queued/in_progress/incomplete, reasoning alone is a valid final
# state — forcing "incomplete" causes multi-minute stalls as the
# continuation path re-issues calls (3 retries × up to 240s each).
# See https://github.com/NousResearch/hermes-agent/issues/64434
if response_status == "completed" and issuer_kind not in (
"codex_backend",
"xai_responses",
"github_responses",
):
finish_reason = "stop"
else:
finish_reason = "incomplete"
# human-readable summary) with no visible content or tool calls. The
# model is still thinking and needs another turn to produce the actual
# answer. Marking this as "stop" would send it into the empty-content
# retry loop which burns retries then fails — treat it as incomplete so
# the Codex continuation path handles it correctly.
finish_reason = "incomplete"
else:
finish_reason = "stop"
return assistant_message, finish_reason
+12 -648
View File
@@ -16,14 +16,11 @@ compatibility.
from __future__ import annotations
import json
import logging
import os
import time
from types import SimpleNamespace
from typing import Any, Callable, Dict, List
from agent.stream_single_writer import claim_stream_writer, stream_writer_is_current
from typing import Any, Dict, List
logger = logging.getLogger(__name__)
@@ -61,15 +58,6 @@ def _record_codex_app_server_usage(agent, turn) -> dict[str, Any]:
usage = getattr(turn, "token_usage_last", None)
if not isinstance(usage, dict) or not usage:
compressor = getattr(agent, "context_compressor", None)
if (
compressor is not None
and getattr(compressor, "awaiting_real_usage_after_compression", False)
):
# No usage means this turn cannot adjudicate the pending compaction.
# Consume the marker so a later unrelated reading is not charged to
# it and preflight deferral cannot stay latched indefinitely.
compressor.update_from_response({})
if agent._session_db and agent.session_id:
try:
if not agent._session_db_created:
@@ -77,9 +65,6 @@ def _record_codex_app_server_usage(agent, turn) -> dict[str, Any]:
agent._session_db.update_token_counts(
agent.session_id,
model=agent.model,
billing_provider=agent.provider,
billing_base_url=agent.base_url,
billing_mode="subscription_included",
api_call_count=1,
)
except Exception as exc:
@@ -188,430 +173,6 @@ def _record_codex_app_server_usage(agent, turn) -> dict[str, Any]:
}
def _record_codex_app_server_compaction(
agent,
turn,
*,
approx_tokens: int | None = None,
force: bool = False,
) -> bool:
"""Record a Codex-native context compaction boundary in Hermes state.
The app-server owns the compacted thread context, so Hermes should not
rewrite local transcript rows here; state.db records the boundary via the
session event/usage counters while preserving the visible transcript.
"""
if not force and not getattr(turn, "compacted", False):
return False
thread_id = getattr(turn, "thread_id", None) or ""
turn_id = getattr(turn, "turn_id", None) or ""
logger.info(
"codex app-server compaction observed: session=%s thread=%s turn=%s force=%s",
getattr(agent, "session_id", None) or "none",
thread_id,
turn_id,
force,
)
if not force:
try:
from agent.conversation_compression import COMPACTION_STATUS
agent._emit_status(COMPACTION_STATUS)
except Exception:
pass
compressor = getattr(agent, "context_compressor", None)
if compressor is not None:
compressor.compression_count = getattr(
compressor, "compression_count", 0
) + 1
compressor.last_compression_rough_tokens = approx_tokens or 0
# The app server has already completed a real compaction boundary. Its
# usage update (when supplied) is therefore the same real-vs-real
# effectiveness verdict used by the normal compression path.
record_boundary = getattr(
type(compressor), "record_completed_compaction", None
)
if callable(record_boundary):
# Codex owns this summary. A prior Hermes deterministic-fallback
# flag must not leak into the native boundary's quality verdict.
record_boundary(compressor, used_fallback=False)
elif hasattr(compressor, "_verify_compaction_cleared_threshold"):
compressor._verify_compaction_cleared_threshold = True
if not getattr(turn, "token_usage_last", None):
compressor.last_prompt_tokens = -1
compressor.last_completion_tokens = 0
compressor.awaiting_real_usage_after_compression = True
agent._last_compaction_in_place = False
try:
if getattr(agent, "event_callback", None):
agent.event_callback(
"session:compress",
{
"platform": getattr(agent, "platform", None) or "",
"session_id": getattr(agent, "session_id", None) or "",
"old_session_id": "",
"in_place": False,
"compression_count": getattr(
compressor, "compression_count", 0
)
if compressor is not None
else 0,
"runtime": "codex_app_server",
"thread_id": thread_id,
"turn_id": turn_id,
},
)
except Exception:
logger.debug("event_callback error on codex session:compress", exc_info=True)
return True
# ---------------------------------------------------------------------------
# Codex app-server → Hermes UI bridge (#33200)
#
# The codex_app_server runtime hands the entire turn to a subprocess and
# bypasses the normal Hermes tool loop. Without this bridge gateway
# adapters (Discord, Telegram, TUI) never see live tool-progress bubbles
# or interim assistant commentary while codex is working — the user just
# stares at a quiet channel until the final answer lands. The bridge
# translates raw codex JSON-RPC notifications into the same three agent
# callbacks the standard runtime fires:
# - tool_progress_callback("tool.started"|"tool.completed", name, ...)
# - _fire_stream_delta(text) for streaming agentMessage chunks
# - _emit_interim_assistant_message({...}) for completed agentMessages
# ---------------------------------------------------------------------------
# Codex item types that map to a Hermes tool_call in the projector (and
# therefore deserve a tool_progress bubble pair). The projector lives in
# agent/transports/codex_event_projector.py — keep these in sync so the
# tool name shown in the UI matches the name recorded in messages.
# webSearch is codex's built-in web search tool — it has no projector
# entry (codex handles it internally) but still deserves a bubble.
_CODEX_TOOL_ITEM_TYPES = frozenset(
{"commandExecution", "fileChange", "mcpToolCall", "dynamicToolCall", "webSearch"}
)
# Internal MCP server that wraps Hermes' native tools for codex. When
# codex calls back through it, the inner dispatch runs in a SEPARATE
# hermes-tools-mcp-server subprocess that has no access to the parent
# agent's tool_progress_callback — so the inner call can never surface
# its own native progress event. The codex-level mcpToolCall event IS
# the display event for those calls; we strip the mcp.hermes-tools.*
# namespacing and emit the bare tool name (web_search, browser_navigate,
# vision_analyze, ...) since the user thinks of these as Hermes tools,
# not as MCP calls.
_INTERNAL_MCP_SERVER = "hermes-tools"
def _codex_item_to_tool_name(item: dict) -> str:
"""Synthetic Hermes tool name for a codex item. Mirrors
CodexEventProjector so the progress bubble and the projected
tool_calls entry use the same identifier."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
return "exec_command"
if item_type == "fileChange":
return "apply_patch"
if item_type == "mcpToolCall":
server = item.get("server") or "mcp"
tool = item.get("tool") or "unknown"
if server == _INTERNAL_MCP_SERVER:
return tool
return f"mcp.{server}.{tool}"
if item_type == "dynamicToolCall":
return item.get("tool") or "dynamic"
if item_type == "webSearch":
return "web_search"
return item_type or "unknown"
def _codex_item_to_args(item: dict) -> dict:
"""Args dict surfaced to tool_progress_callback("tool.started", ...).
Mirrors the projector's _project_command / _project_file_change /
_project_mcp_tool_call / _project_dynamic_tool_call shapes."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
return {"command": item.get("command") or "",
"cwd": item.get("cwd") or ""}
if item_type == "fileChange":
return {"changes": [
{"kind": (c.get("kind") or {}).get("type") or "update",
"path": c.get("path") or ""}
for c in (item.get("changes") or []) if isinstance(c, dict)
]}
if item_type in {"mcpToolCall", "dynamicToolCall"}:
args = item.get("arguments") or {}
return args if isinstance(args, dict) else {"arguments": args}
if item_type == "webSearch":
return {"query": item.get("query") or ""}
return {}
def _codex_item_to_preview(item: dict) -> Any:
"""Short human-readable preview for the tool.started bubble. Returns
None when no useful preview is available (Hermes' UI tolerates None)."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
cmd = item.get("command") or ""
return cmd[:120] if cmd else None
if item_type == "fileChange":
paths = [c.get("path") for c in (item.get("changes") or [])
if isinstance(c, dict) and c.get("path")]
if not paths:
return None
preview = ", ".join(paths[:3])
if len(paths) > 3:
preview += f", +{len(paths) - 3} more"
return preview
if item_type in {"mcpToolCall", "dynamicToolCall"}:
args = item.get("arguments") or {}
if not isinstance(args, dict) or not args:
return None
try:
return json.dumps(args, ensure_ascii=False)[:120]
except (TypeError, ValueError):
return None
if item_type == "webSearch":
query = item.get("query") or ""
return query[:120] if query else None
return None
def _codex_item_completion_payload(item: dict) -> tuple[str, bool]:
"""Return (result_text, is_error) for a completed codex tool item.
Mirrors the projector's tool-result content so the bubble shows the
same outcome string that ends up in the messages list."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
out = item.get("aggregatedOutput") or ""
exit_code = item.get("exitCode")
is_error = bool(exit_code is not None and exit_code != 0)
if is_error:
out = f"[exit {exit_code}]\n{out}"
return out, is_error
if item_type == "fileChange":
status = item.get("status") or "unknown"
n = len(item.get("changes") or [])
return (
f"apply_patch status={status}, {n} change(s)",
status not in {"completed", "applied", "success"},
)
if item_type == "mcpToolCall":
error = item.get("error")
if error:
return (
f"[error] {json.dumps(error, ensure_ascii=False)[:1000]}",
True,
)
result = item.get("result")
return (
json.dumps(result, ensure_ascii=False)[:4000]
if result is not None else "",
False,
)
if item_type == "dynamicToolCall":
content_items = item.get("contentItems") or []
if isinstance(content_items, list) and content_items:
return (
json.dumps(content_items, ensure_ascii=False)[:4000],
not bool(item.get("success", True)),
)
success = item.get("success", True)
return f"success={success}", not bool(success)
return "", False
def make_codex_app_server_event_bridge(agent) -> Callable[[dict], None]:
"""Build an ``on_event`` callback that wires codex app-server JSON-RPC
notifications into Hermes' gateway UI callbacks.
Returns a single-argument callable suitable for
``CodexAppServerSession(on_event=...)``.
Translation map:
* ``item/started`` for tool-shaped items ``tool_progress_callback(
"tool.started", name, preview, args)``
* ``item/completed`` for tool-shaped items ``tool_progress_callback(
"tool.completed", name, None, None, duration=..., is_error=...,
result=...)``
* ``item/agentMessage/delta`` ``_fire_stream_delta(text)`` so chat
adapters can render the assistant's reply as it streams.
* ``item/reasoning/delta`` ``_fire_reasoning_delta(text)``
* ``item/completed`` for ``agentMessage``
``_emit_interim_assistant_message({"role": "assistant",
"content": text})``. The gateway's ``already_streamed`` check
dedupes against any text the stream-delta callback already
rendered for the same message.
All callback invocations are guarded a buggy display callback must
not tear down the codex turn loop. Errors are logged at DEBUG so the
notification stream keeps flowing regardless.
"""
# item_id -> (tool_name, args, started_wall_time). Populated on
# item/started and consumed on item/completed so duration is correct
# even when codex doesn't report durationMs.
started: dict[str, tuple[str, dict, float]] = {}
def _stable_call_id(item: dict, name: str) -> str:
"""Deterministic tool_call id mirroring CodexEventProjector, so a
live TUI tool card correlates with the same tool call after the
session is resumed and history is projected."""
from agent.transports.codex_event_projector import _deterministic_call_id
item_id = item.get("id") or ""
item_type = item.get("type") or ""
if item_type == "commandExecution":
return _deterministic_call_id("exec", item_id)
if item_type == "fileChange":
return _deterministic_call_id("apply_patch", item_id)
if item_type == "mcpToolCall":
server = item.get("server") or "mcp"
tool = item.get("tool") or "unknown"
return _deterministic_call_id(f"mcp__{server}__{tool}", item_id)
if item_type == "dynamicToolCall":
tool = item.get("tool") or "unknown"
return _deterministic_call_id(f"dyn_{tool}", item_id)
return _deterministic_call_id(name, item_id)
def _fire_tool_started(item: dict) -> None:
item_id = item.get("id") or ""
name = _codex_item_to_tool_name(item)
args = _codex_item_to_args(item)
if item_id:
started[item_id] = (name, args, time.monotonic())
cb = getattr(agent, "tool_progress_callback", None)
if cb is not None:
try:
cb("tool.started", name, _codex_item_to_preview(item), args)
except Exception:
logger.debug(
"tool_progress_callback raised on tool.started for %s",
name, exc_info=True,
)
# Authoritative stable-ID tool card (TUI / desktop). Fires
# alongside tool_progress so surfaces that render structured tool
# cards (not just progress bubbles) stay correlated with the
# projected history entry after a resume.
start_cb = getattr(agent, "tool_start_callback", None)
if start_cb is not None:
try:
start_cb(_stable_call_id(item, name), name, args)
except Exception:
logger.debug(
"tool_start_callback raised for %s", name, exc_info=True,
)
def _fire_tool_completed(item: dict) -> None:
item_id = item.get("id") or ""
name = _codex_item_to_tool_name(item)
prior = started.pop(item_id, None)
# Prefer codex's own durationMs when present so the bubble shows
# exact tool wall-time; fall back to our started timestamp; fall
# back to None if we never saw an item/started (some codex
# versions only emit completed for fast items).
duration: Any = None
codex_ms = item.get("durationMs")
if isinstance(codex_ms, (int, float)) and codex_ms >= 0:
duration = codex_ms / 1000.0
elif prior is not None:
duration = time.monotonic() - prior[2]
result, is_error = _codex_item_completion_payload(item)
cb = getattr(agent, "tool_progress_callback", None)
if cb is not None:
try:
cb("tool.completed", name, None, None,
duration=duration, is_error=is_error, result=result)
except Exception:
logger.debug(
"tool_progress_callback raised on tool.completed for %s",
name, exc_info=True,
)
complete_cb = getattr(agent, "tool_complete_callback", None)
if complete_cb is not None:
args = prior[1] if prior is not None else _codex_item_to_args(item)
try:
complete_cb(_stable_call_id(item, name), name, args, result)
except Exception:
logger.debug(
"tool_complete_callback raised for %s", name, exc_info=True,
)
def _fire_text_delta(params: dict) -> None:
text = params.get("delta") or params.get("text") or ""
if not isinstance(text, str) or not text:
return
fn = getattr(agent, "_fire_stream_delta", None)
if fn is None:
return
try:
fn(text)
except Exception:
logger.debug("_fire_stream_delta raised", exc_info=True)
def _fire_reasoning_delta(params: dict) -> None:
text = params.get("delta") or params.get("text") or ""
if not isinstance(text, str) or not text:
return
fn = getattr(agent, "_fire_reasoning_delta", None)
if fn is None:
return
try:
fn(text)
except Exception:
logger.debug("_fire_reasoning_delta raised", exc_info=True)
def _fire_agent_message_completed(item: dict) -> None:
text = item.get("text") or ""
if not isinstance(text, str) or not text.strip():
return
# display.show_commentary=false — mid-turn narration stays off the
# visible interim path on this runtime too (same contract as the
# codex_responses commentary channel).
if not getattr(agent, "show_commentary", True):
return
emit = getattr(agent, "_emit_interim_assistant_message", None)
if emit is None:
return
try:
emit({"role": "assistant", "content": text})
except Exception:
logger.debug(
"_emit_interim_assistant_message raised", exc_info=True,
)
def on_event(note: dict) -> None:
if not isinstance(note, dict):
return
method = note.get("method") or ""
params = note.get("params") or {}
if not isinstance(params, dict):
params = {}
if method == "item/agentMessage/delta":
_fire_text_delta(params)
return
if method in {"item/reasoning/delta", "item/reasoning/summaryDelta"}:
_fire_reasoning_delta(params)
return
item = params.get("item")
if not isinstance(item, dict):
return
item_type = item.get("type") or ""
if method == "item/started" and item_type in _CODEX_TOOL_ITEM_TYPES:
_fire_tool_started(item)
return
if method == "item/completed":
if item_type in _CODEX_TOOL_ITEM_TYPES:
_fire_tool_completed(item)
elif item_type == "agentMessage":
_fire_agent_message_completed(item)
return on_event
def run_codex_app_server_turn(
agent,
*,
@@ -628,18 +189,13 @@ def run_codex_app_server_turn(
Called from run_conversation() when agent.api_mode == "codex_app_server".
Returns the same dict shape as the chat_completions path.
"""
from agent.transports.codex_app_server_session import (
CodexAppServerSession,
_ServerRequestRouting,
)
from agent.transports.codex_app_server_session import CodexAppServerSession
# Lazy session: one CodexAppServerSession per AIAgent instance.
# Spawned on first turn, reused across turns, closed at AIAgent
# shutdown (see _cleanup hook).
if not hasattr(agent, "_codex_session") or agent._codex_session is None:
from agent.runtime_cwd import resolve_agent_cwd
cwd = getattr(agent, "session_cwd", None) or str(resolve_agent_cwd())
cwd = getattr(agent, "session_cwd", None) or os.getcwd()
# Approval callback: defer to Hermes' standard prompt flow if a
# CLI thread has installed one. Gateway / cron contexts get the
# codex-side fail-closed default.
@@ -648,43 +204,9 @@ def run_codex_app_server_turn(
approval_callback = _get_approval_callback()
except Exception:
approval_callback = None
# Gateway / cron contexts have no UI to surface codex's approval
# requests through, so codex app-server exec / apply_patch requests
# fail closed (silently decline) by default. When the user has
# explicitly opted out of Hermes approvals — via `approvals.mode: off`
# in config, the /yolo session toggle, or --yolo / HERMES_YOLO_MODE —
# honor that and let codex's own sandbox permission profile
# (~/.codex/config.toml) be the policy gate instead of double-gating
# with a missing Hermes UI. Defaults (manual/smart/unset) preserve the
# current fail-closed behavior — this is a no-op for those users.
auto_approve_requests = False
try:
from tools.approval import is_approval_bypass_active
auto_approve_requests = is_approval_bypass_active()
except Exception:
logger.debug(
"codex app-server: approval-bypass lookup failed; "
"keeping fail-closed default",
exc_info=True,
)
# Bridge codex JSON-RPC notifications (item/started, item/completed,
# item/agentMessage/delta, ...) into Hermes' gateway UI callbacks
# (tool_progress_callback, _fire_stream_delta,
# _emit_interim_assistant_message). Without this, Discord/Telegram
# users see no live tool-progress or interim commentary while
# codex_app_server is running — only the final answer (#33200).
# Supersedes the narrower item/started-only bridge from #38835.
agent._codex_session = CodexAppServerSession(
cwd=cwd,
approval_callback=approval_callback,
request_routing=_ServerRequestRouting(
auto_approve_exec=auto_approve_requests,
auto_approve_apply_patch=auto_approve_requests,
),
on_event=make_codex_app_server_event_bridge(agent),
)
# NOTE: the user message is ALREADY appended to messages by the
@@ -736,28 +258,6 @@ def run_codex_app_server_turn(
if turn.projected_messages:
messages.extend(turn.projected_messages)
# Persist the newly-projected assistant/tool messages ourselves.
# This path is an early return that bypasses conversation_loop, whose
# normal per-step _persist_session() calls would otherwise flush them.
# The inbound user turn was already flushed at turn start
# (turn_context.py _persist_session), and _flush_messages_to_session_db
# is idempotent via the intrinsic _DB_PERSISTED_MARKER — so this writes
# ONLY the new codex projected rows and does NOT re-write the user turn.
# Keeping the agent as the sole persister lets us return
# agent_persisted=True below, so the gateway skips its own DB write and
# we avoid the #860/#42039 duplicate user-message write (append_message
# is a raw INSERT with no dedup, so a gateway re-write would duplicate
# the already-flushed user turn). See gateway/run.py agent_persisted.
if getattr(agent, "_session_db", None) is not None:
try:
agent._flush_messages_to_session_db(messages)
except Exception:
logger.debug(
"codex app-server projected-message flush failed",
exc_info=True,
)
# Counter ticks for the agent-improvement loop.
# _turns_since_memory and _user_turn_count are ALREADY incremented
# in the run_conversation() pre-loop block (lines ~11793-11817) so we
@@ -768,7 +268,6 @@ def run_codex_app_server_turn(
agent._iters_since_skill = (
getattr(agent, "_iters_since_skill", 0) + turn.tool_iterations
)
_record_codex_app_server_compaction(agent, turn)
usage_result = _record_codex_app_server_usage(agent, turn)
api_calls = 1
@@ -791,7 +290,6 @@ def run_codex_app_server_turn(
original_user_message=original_user_message,
final_response=turn.final_text,
interrupted=False,
messages=messages,
)
except Exception:
logger.debug("external memory sync raised", exc_info=True)
@@ -820,18 +318,6 @@ def run_codex_app_server_turn(
"completed": not turn.interrupted and turn.error is None,
"partial": turn.interrupted or turn.error is not None,
"error": turn.error,
# The codex app-server runtime IS an early-return path that bypasses
# conversation_loop, but we flush the projected assistant/tool messages
# ourselves above (see the _flush_messages_to_session_db call after
# messages.extend). The inbound user turn was already flushed at turn
# start (turn_context._persist_session) and the flush dedups via
# _DB_PERSISTED_MARKER, so state.db ends up with each real message
# exactly once and session_search / conversation-distill see the full
# gateway conversation. Report agent_persisted=True so the gateway
# skips its own append_to_transcript DB write — writing again there
# would re-INSERT the already-flushed user turn (append_message has no
# dedup), reintroducing the #860 / #42039 duplicate-write bug.
"agent_persisted": True,
"codex_thread_id": turn.thread_id,
"codex_turn_id": turn.turn_id,
**usage_result,
@@ -876,48 +362,18 @@ def _event_field(event: Any, name: str, default: Any = None) -> Any:
return value if value is not None else default
def _item_field(item: Any, name: str, default: Any = None) -> Any:
"""Field access for nested Response items (attr-style SDK object or dict)."""
value = getattr(item, name, None)
if value is None and isinstance(item, dict):
value = item.get(name, default)
return value if value is not None else default
def _raise_stream_error(event: Any) -> None:
"""Raise a ``_StreamErrorEvent`` from a ``type=error`` SSE frame.
The Responses spec puts the failure details at the top level of the
frame (``{"type": "error", "code": ..., "message": ..., "param": ...}``),
but the official OpenAI SDK and several OpenAI-compatible proxies wrap
them in an HTTP-style nested envelope instead
(``{"type": "error", "error": {"code": ..., "message": ..., "param": ...}}``).
Read the top-level fields first, then fall back to the nested envelope so
the error classifier sees the provider's real code/message (rate-limit vs
context-overflow vs entitlement) rather than the generic placeholder.
Port of anomalyco/opencode#36130.
Imported lazily so this module stays importable from places that don't
pull in ``run_agent`` (e.g. plugin code, doc tools).
"""
from run_agent import _StreamErrorEvent
nested = _event_field(event, "error")
def _error_field(name: str) -> Any:
value = _event_field(event, name)
if value is None and nested is not None:
value = _item_field(nested, name)
return value
raw_message = _error_field("message")
if raw_message is not None and not isinstance(raw_message, str):
raw_message = str(raw_message)
message = (raw_message or "stream emitted error event").strip() or "stream emitted error event"
message = (_event_field(event, "message", "") or "stream emitted error event").strip()
raise _StreamErrorEvent(
message,
code=_error_field("code"),
param=_error_field("param"),
code=_event_field(event, "code"),
param=_event_field(event, "param"),
)
@@ -927,7 +383,6 @@ def _consume_codex_event_stream(
model: str,
on_text_delta=None,
on_reasoning_delta=None,
on_commentary_message=None,
on_first_delta=None,
on_event=None,
interrupt_check=None,
@@ -959,11 +414,7 @@ def _consume_codex_event_stream(
* ``on_text_delta(str)`` fires per ``response.output_text.delta``, suppressed
once a function_call event is seen (so tool-call turns don't bleed text
into the chat).
* ``on_reasoning_delta(str)`` fires per ``response.reasoning.*.delta`` and
``phase=analysis`` message deltas. When no dedicated commentary callback
is supplied, commentary also uses this legacy fallback.
* ``on_commentary_message(str)`` fires once per completed
``phase=commentary`` message, before any following tool item executes.
* ``on_reasoning_delta(str)`` fires per ``response.reasoning.*.delta``.
* ``on_first_delta()`` one-shot, fires on the first text delta only.
* ``on_event(event)`` fires for every event before any other processing.
Used for watchdog activity, debug logging, anything wire-shape-agnostic.
@@ -973,8 +424,6 @@ def _consume_codex_event_stream(
collected_text_deltas: List[str] = []
has_tool_calls = False
first_delta_fired = False
active_message_phase: str | None = None
commentary_text_deltas: List[str] = []
terminal_status: str = "completed"
terminal_usage: Any = None
terminal_response_id: str = None
@@ -1008,43 +457,9 @@ def _consume_codex_event_stream(
if event_type == "error":
_raise_stream_error(event)
# Track the phase of the active streamed message item. Codex/Harmony
# ``commentary``/``analysis`` text is mid-turn preamble/progress
# narration, never the final answer. We still collect completed output
# items for replay, but route those deltas to the reasoning callback so
# they display like thinking text instead of assistant content.
if event_type == "response.output_item.added":
item = _event_field(event, "item")
item_type = _item_field(item, "type", "")
if item_type == "message":
phase = _item_field(item, "phase", None)
active_message_phase = phase.strip().lower() if isinstance(phase, str) else None
if active_message_phase == "commentary":
commentary_text_deltas = []
else:
active_message_phase = None
if "function_call" in str(item_type):
has_tool_calls = True
continue
if "output_text.delta" in event_type or event_type == "response.output_text.delta":
delta_text = _event_field(event, "delta", "")
if delta_text and active_message_phase == "commentary":
commentary_text_deltas.append(delta_text)
# Preserve CLI/backward compatibility when no first-class
# commentary consumer is installed.
if on_commentary_message is None and on_reasoning_delta is not None:
try:
on_reasoning_delta(delta_text)
except Exception:
logger.debug("Codex stream on_reasoning_delta raised", exc_info=True)
elif delta_text and active_message_phase == "analysis":
if on_reasoning_delta is not None:
try:
on_reasoning_delta(delta_text)
except Exception:
logger.debug("Codex stream on_reasoning_delta raised", exc_info=True)
elif delta_text:
if delta_text:
collected_text_deltas.append(delta_text)
if not has_tool_calls:
if not first_delta_fired:
@@ -1078,27 +493,6 @@ def _consume_codex_event_stream(
done_item = _event_field(event, "item")
if done_item is not None:
collected_output_items.append(done_item)
done_phase = _item_field(done_item, "phase", None)
done_phase = done_phase.strip().lower() if isinstance(done_phase, str) else None
if done_phase == "commentary" and on_commentary_message is not None:
commentary_text = "".join(commentary_text_deltas).strip()
if not commentary_text:
content_parts = _item_field(done_item, "content", [])
if isinstance(content_parts, list):
commentary_text = "".join(
str(_item_field(part, "text", "") or "")
for part in content_parts
if _item_field(part, "type", "") == "output_text"
).strip()
if commentary_text:
try:
on_commentary_message(commentary_text)
except Exception:
logger.debug(
"Codex stream on_commentary_message raised",
exc_info=True,
)
commentary_text_deltas = []
continue
if event_type in _TERMINAL_EVENT_TYPES:
@@ -1199,14 +593,14 @@ def run_codex_stream(agent, api_kwargs: dict, client: Any = None, on_first_delta
def _on_reasoning_delta(text: str) -> None:
agent._fire_reasoning_delta(text)
def _on_commentary_message(text: str) -> None:
agent._fire_streamed_codex_commentary(text)
def _on_event(event: Any) -> None:
# TTFB watchdog and activity touch — runs once per SSE event.
agent._codex_stream_last_event_ts = time.time()
agent._touch_activity("receiving stream response")
def _interrupt_check() -> bool:
return bool(agent._interrupt_requested)
for attempt in range(max_stream_retries + 1):
if agent._interrupt_requested:
raise InterruptedError("Agent interrupted before Codex stream retry")
@@ -1226,27 +620,6 @@ def run_codex_stream(agent, api_kwargs: dict, client: Any = None, on_first_delta
continue
raise
# Claim the delta sink for THIS attempt (#65991) — parity with the
# chat_completions/anthropic/bedrock paths. If a prior attempt's
# stream is somehow still alive, this claim supersedes it so its
# late deltas are fenced out of the turn; conversely, a newer
# attempt supersedes us and the interrupt_check below stops our
# consumption immediately.
_writer_token = claim_stream_writer(agent)
def _interrupt_or_superseded(_tok=_writer_token) -> bool:
if agent._interrupt_requested:
return True
if not stream_writer_is_current(agent, _tok):
logger.warning(
"Codex streaming attempt superseded by a newer stream; "
"stopping consumption to preserve the single-writer "
"invariant (model=%s).",
api_kwargs.get("model", "unknown"),
)
return True
return False
try:
# Compatibility: some mocks/providers return a concrete response
# instead of an iterable. Pass it straight through.
@@ -1259,17 +632,9 @@ def run_codex_stream(agent, api_kwargs: dict, client: Any = None, on_first_delta
model=api_kwargs.get("model"),
on_text_delta=_on_text_delta,
on_reasoning_delta=_on_reasoning_delta,
on_commentary_message=(
_on_commentary_message
if (
getattr(agent, "interim_assistant_callback", None) is not None
and getattr(agent, "show_commentary", True)
)
else None
),
on_first_delta=on_first_delta,
on_event=_on_event,
interrupt_check=_interrupt_or_superseded,
interrupt_check=_interrupt_check,
)
except (_httpx.RemoteProtocolError, _httpx.ReadTimeout, _httpx.ConnectError, ConnectionError) as exc:
if attempt < max_stream_retries:
@@ -1318,5 +683,4 @@ __all__ = [
"run_codex_stream",
"run_codex_create_stream_fallback",
"_consume_codex_event_stream",
"make_codex_app_server_event_bridge",
]
+36 -192
View File
@@ -55,13 +55,11 @@ import json
import logging
import os
import re
import tempfile
import subprocess
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Optional
from hermes_cli._subprocess_compat import bounded_git_probe
logger = logging.getLogger("hermes.coding_context")
CODING_TOOLSET = "coding"
@@ -85,59 +83,6 @@ _PROJECT_MARKERS = (
# Agent-instruction files surfaced separately from manifests in the snapshot.
_CONTEXT_FILES = ("AGENTS.md", "CLAUDE.md", ".cursorrules")
# Source-file extensions that make a git repo a *code* workspace even with no
# manifest. Without this, `git init` on a notes/writing/research folder (a huge
# non-coding use case) would flip the whole session into the coding posture just
# for having a `.git`. A manifest still wins on its own (see `_PROJECT_MARKERS`).
_CODE_EXTENSIONS = frozenset({
".py", ".pyi", ".ipynb", ".js", ".jsx", ".ts", ".tsx", ".mjs", ".cjs",
".go", ".rs", ".java", ".kt", ".kts", ".scala", ".rb", ".php", ".c", ".h",
".cc", ".cpp", ".hpp", ".cs", ".swift", ".m", ".mm", ".dart", ".ex", ".exs",
".lua", ".sh", ".bash", ".zsh", ".sql", ".vue", ".svelte", ".r", ".jl",
".hs", ".clj", ".erl", ".pl",
})
# Dirs never worth scanning for the code check (deps/build/vcs/venv noise).
_CODE_SCAN_SKIP_DIRS = frozenset({
".git", "node_modules", "venv", ".venv", "__pycache__", "dist", "build",
"target", ".next", ".turbo", "vendor",
})
# Bounded sweep: a code workspace reveals itself in the first handful of entries.
_CODE_SCAN_MAX_ENTRIES = 500
def _has_code_files(root: Path) -> bool:
"""Cheap, bounded check for source files in a repo's top two levels.
Lets a git repo of loose scripts (no manifest) still read as a code
workspace while a bare notes/writing repo does not. Scans the root and its
immediate subdirectories only, capped at ``_CODE_SCAN_MAX_ENTRIES`` stats
a handful of readdirs at session start, not a full walk.
"""
seen = 0
stack = [(root, True)]
while stack:
directory, is_root = stack.pop()
try:
with os.scandir(directory) as entries:
for entry in entries:
seen += 1
if seen > _CODE_SCAN_MAX_ENTRIES:
return False
name = entry.name
try:
if entry.is_file():
if os.path.splitext(name)[1].lower() in _CODE_EXTENSIONS:
return True
elif is_root and entry.is_dir() and name not in _CODE_SCAN_SKIP_DIRS and not name.startswith("."):
stack.append((Path(entry.path), False))
except OSError:
continue
except OSError:
continue
return False
# Lockfile → package manager, checked in priority order.
_PY_LOCKFILES = (("uv.lock", "uv"), ("poetry.lock", "poetry"), ("Pipfile.lock", "pipenv"))
_JS_LOCKFILES = (
@@ -245,10 +190,6 @@ CODING_AGENT_GUIDANCE = (
"Verify, and know when to stop:\n"
"- Use `terminal` for git, builds, tests, and inspection. Run the relevant "
"tests/linter/build and confirm they pass before claiming the work is done.\n"
"- Terminal state persists across calls: current directory and exported "
"environment variables carry forward. Activate a virtualenv or export setup "
"vars once, then reuse that state instead of re-sourcing it before every "
"test command.\n"
"- Fix root causes, not symptoms: when you find a bug, check sibling call "
"paths for the same flaw and fix the class, not just the reported site.\n"
"- When fixing linter/type errors on a file, stop after about three "
@@ -353,29 +294,6 @@ def _coding_mode(config: Optional[dict[str, Any]]) -> str:
return "auto"
def _coding_instructions(config: Optional[dict[str, Any]]) -> str:
"""Standing operator instructions for the coding posture (config).
``agent.coding_instructions`` a string or list of strings appended to the
coding brief as an extra stable system block, so a user can pin project-wide
coding-workflow rules (e.g. "for UI work don't run tsc/lint until I approve;
clean the diff before committing") without editing the shipped brief.
Cache-safe: resolved once per session into the stable system-prompt tier,
like the rest of the posture.
"""
if config is None:
try:
from hermes_cli.config import load_config
config = load_config()
except Exception:
config = {}
raw = ((config or {}).get("agent", {}) or {}).get("coding_instructions", "")
if isinstance(raw, (list, tuple)):
return "\n".join(str(item).strip() for item in raw if str(item).strip())
return str(raw or "").strip()
def _resolve_cwd(cwd: Optional[str | Path]) -> Path:
if cwd:
return Path(cwd).expanduser()
@@ -412,18 +330,10 @@ def _marker_root(cwd: Path) -> Optional[Path]:
"""
current = cwd.resolve()
home = _home()
# Shared world-writable temp roots are never project roots: a stray
# manifest in /tmp (left by any process) must not flip every session
# whose cwd lives under the temp dir into the coding posture. Same
# reasoning as the $HOME skip below.
try:
temp_root = Path(tempfile.gettempdir()).resolve()
except Exception:
temp_root = None
for depth, parent in enumerate([current, *current.parents]):
if depth > 6:
break
if parent == home or (temp_root is not None and parent == temp_root):
if parent == home:
continue
for marker in _PROJECT_MARKERS:
if (parent / marker).exists():
@@ -454,16 +364,10 @@ def _detect_profile_name(mode: str, platform: str, cwd_str: str) -> str:
if platform and platform.strip().lower() not in INTERACTIVE_CODING_PLATFORMS:
return GENERAL_PROFILE.name
cwd = Path(cwd_str)
# A recognized project root (manifest / AGENTS.md / .cursorrules) is a code
# workspace on its own — cheap stat checks, no scan.
if _marker_root(cwd) is not None:
return CODING_PROFILE.name
git_root = _git_root(cwd)
if git_root is not None and git_root == _home():
git_root = None # dotfiles repo at $HOME — not a code workspace
# A bare git repo only counts when it actually holds code, so `git init` on a
# notes/writing/research folder stays in the general posture.
if git_root is not None and _has_code_files(git_root):
if git_root is not None or _marker_root(cwd) is not None:
return CODING_PROFILE.name
return GENERAL_PROFILE.name
@@ -490,9 +394,6 @@ class RuntimeMode:
# only to steer edit-format guidance toward the model's family — see
# ``_edit_format_line``. Fixed for the session, so cache-safe.
model: Optional[str] = None
# Standing operator instructions (``agent.coding_instructions``), appended
# as an extra stable system block. Empty unless the user configures it.
instructions: str = ""
@property
def kind(self) -> str:
@@ -539,10 +440,6 @@ class RuntimeMode:
workspace = build_coding_workspace_block(self.cwd)
if workspace:
blocks.append(workspace)
# Operator instructions ride their own block so the brief (block 0) stays
# byte-stable and cache-keyed independently of user config.
if self.instructions:
blocks.append(f"Operator instructions (from config):\n{self.instructions}")
return blocks
def compact_skill_categories(self) -> frozenset[str]:
@@ -595,7 +492,6 @@ def resolve_runtime_mode(
cwd=resolved_cwd,
config_mode=mode,
model=model,
instructions=_coding_instructions(config),
)
@@ -688,14 +584,16 @@ def _enabled_mcp_servers(config: Optional[dict[str, Any]]) -> list[str]:
def _git(cwd: Path, *args: str) -> str:
"""``git -C <cwd> <args>`` → stripped stdout, or ``""`` on any failure.
Uses the shared :func:`bounded_git_probe` so the post-kill cleanup is bounded
on Windows a plain ``subprocess.run(timeout=...)`` here deadlocked the agent
turn inside ``build_coding_workspace_block`` when a killed git left a suspended
descendant holding the pipe handles (issue #66037).
"""
return bounded_git_probe(["git", "-C", str(cwd), *args], timeout=_GIT_TIMEOUT)
try:
out = subprocess.run(
["git", "-C", str(cwd), *args],
capture_output=True,
text=True,
timeout=_GIT_TIMEOUT,
)
except (OSError, subprocess.SubprocessError):
return ""
return out.stdout.strip() if out.returncode == 0 else ""
def _parse_status(porcelain: str) -> tuple[dict[str, str], dict[str, int]]:
@@ -733,32 +631,25 @@ def _read_small(path: Path) -> str:
return ""
@dataclass(frozen=True)
class ProjectFacts:
"""Structured project facts — the model's verify loop, detected once.
def _project_facts(root: Path) -> list[str]:
"""Detected project facts for the workspace snapshot.
The same data that feeds the workspace snapshot, exposed structurally so
non-prompt consumers (e.g. the desktop verify UI) read it instead of
re-detecting and drifting from the prompt.
The point is to hand the model its *verify loop* up front which manifest,
which package manager, and the exact test/lint/build commands instead of
making it rediscover them every session. Cheap: stat calls plus reads of a
couple of small files; built once at prompt-build time (cache-safe).
"""
facts: list[str] = []
manifests: list[str]
package_managers: list[str]
verify_commands: list[str]
context_files: list[str]
def detect_project_facts(root: Path) -> ProjectFacts:
"""Detect manifests, package manager(s), verify commands, and context files.
Cheap: stat calls plus reads of a couple of small files. The single source
of truth for both the prompt snapshot (:func:`_project_facts`) and the
gateway's ``project.facts`` — so the UI never re-sniffs verify commands.
"""
manifests = [m for m in _PROJECT_MARKERS if m not in _CONTEXT_FILES and (root / m).is_file()]
package_managers = list(
dict.fromkeys(pm for lock, pm in (*_PY_LOCKFILES, *_JS_LOCKFILES) if (root / lock).is_file())
)
package_managers = [
pm for lock, pm in (*_PY_LOCKFILES, *_JS_LOCKFILES) if (root / lock).is_file()
]
if manifests:
line = f"- Project: {', '.join(manifests[:6])}"
if package_managers:
line += f" ({'/'.join(dict.fromkeys(package_managers))})"
facts.append(line)
verify: list[str] = []
if (root / "scripts" / "run_tests.sh").is_file():
@@ -778,61 +669,17 @@ def detect_project_facts(root: Path) -> ProjectFacts:
f"make {name}" for name in _VERIFY_TARGETS
if re.search(rf"^{re.escape(name)}\s*:", makefile, re.MULTILINE)
)
if verify:
deduped = list(dict.fromkeys(verify))[:_MAX_VERIFY_COMMANDS]
facts.append(f"- Verify: {'; '.join(deduped)}")
return ProjectFacts(
manifests=manifests,
package_managers=package_managers,
verify_commands=list(dict.fromkeys(verify))[:_MAX_VERIFY_COMMANDS],
context_files=[c for c in _CONTEXT_FILES if (root / c).is_file()],
)
def _project_facts(root: Path) -> list[str]:
"""Render :func:`detect_project_facts` as workspace-snapshot lines.
Hands the model its *verify loop* up front which manifest, which package
manager, and the exact test/lint/build commands instead of making it
rediscover them every session. Built once at prompt-build time; the string
output must stay byte-stable to preserve the prompt cache.
"""
f = detect_project_facts(root)
facts: list[str] = []
if f.manifests:
line = f"- Project: {', '.join(f.manifests[:6])}"
if f.package_managers:
line += f" ({'/'.join(f.package_managers)})"
facts.append(line)
if f.verify_commands:
facts.append(f"- Verify: {'; '.join(f.verify_commands)}")
if f.context_files:
facts.append(f"- Context files: {', '.join(f.context_files)}")
context_files = [c for c in _CONTEXT_FILES if (root / c).is_file()]
if context_files:
facts.append(f"- Context files: {', '.join(context_files)}")
return facts
def project_facts_for(cwd: Optional[str | Path] = None) -> Optional[dict[str, Any]]:
"""Structured project facts for ``cwd`` — ``None`` outside a workspace.
Same detection the system-prompt snapshot uses (git root, else marker root),
exposed for non-prompt consumers (the desktop verify UI) so they never
re-derive "are we coding?" or duplicate the verify-command sniffing.
"""
resolved = _resolve_cwd(cwd)
root = _git_root(resolved) or _marker_root(resolved)
if root is None:
return None
f = detect_project_facts(root)
return {
"root": str(root),
"manifests": f.manifests,
"packageManagers": f.package_managers,
"verifyCommands": f.verify_commands,
"contextFiles": f.context_files,
}
def build_coding_workspace_block(cwd: Optional[str | Path] = None) -> str:
"""Workspace snapshot for the system prompt (empty outside a workspace).
@@ -864,13 +711,10 @@ def build_coding_workspace_block(cwd: Optional[str | Path] = None) -> str:
lines.append("- Branch: (detached HEAD)")
# Linked worktree: the per-worktree git dir differs from the shared common dir.
# We surface the fact that it's a worktree (so the model knows branches/stashes
# are shared state) but deliberately do NOT expose the primary tree path —
# giving the model a second absolute path causes it to sometimes run commands
# in the wrong directory.
git_dir, common_dir = _git(root, "rev-parse", "--git-dir"), _git(root, "rev-parse", "--git-common-dir")
if git_dir and common_dir and Path(git_dir).resolve() != Path(common_dir).resolve():
lines.append("- Worktree: linked (git state shared with primary tree)")
main_tree = Path(common_dir).resolve().parent
lines.append(f"- Worktree: linked (primary tree at {main_tree})")
dirty = [f"{n} {label}" for label, n in (
("staged", counts["staged"]), ("modified", counts["modified"]),
-156
View File
@@ -1,156 +0,0 @@
"""Live session context-window breakdown for UI surfaces.
Estimates how the next provider request is composed: system prompt tiers,
tool schemas, and conversation history. Uses the same rough char/4 heuristic
as ``agent.model_metadata.estimate_request_tokens_rough`` so numbers align
with compression thresholds not exact tokenizer counts.
"""
from __future__ import annotations
import json
import re
from typing import Any, Dict, List, Optional, Sequence, Tuple
_SKILLS_BLOCK_RE = re.compile(r"<available_skills>.*?</available_skills>", re.DOTALL)
_SUBAGENT_TOOL_NAMES = frozenset({"delegate_task"})
_CATEGORY_COLORS = {
"system_prompt": "var(--context-usage-system)",
"tool_definitions": "var(--context-usage-tools)",
"rules": "var(--context-usage-rules)",
"skills": "var(--context-usage-skills)",
"mcp": "var(--context-usage-mcp)",
"subagent_definitions": "var(--context-usage-subagents)",
"memory": "var(--context-usage-memory)",
"conversation": "var(--context-usage-conversation)",
}
def _chars_to_tokens(text: str) -> int:
if not text:
return 0
return (len(text) + 3) // 4
def _json_tokens(value: Any) -> int:
if not value:
return 0
return _chars_to_tokens(json.dumps(value, ensure_ascii=False))
def _tool_name(tool: dict) -> str:
fn = tool.get("function") if isinstance(tool, dict) else None
if isinstance(fn, dict):
return str(fn.get("name") or "")
return str(tool.get("name") or "")
def _split_tools(tools: Sequence[dict]) -> Tuple[List[dict], List[dict], List[dict]]:
builtin: List[dict] = []
mcp: List[dict] = []
subagent: List[dict] = []
for tool in tools:
name = _tool_name(tool)
if name.startswith("mcp_"):
mcp.append(tool)
elif name in _SUBAGENT_TOOL_NAMES:
subagent.append(tool)
else:
builtin.append(tool)
return builtin, mcp, subagent
def _memory_blocks(agent: Any) -> Tuple[str, str]:
memory_block = ""
user_block = ""
store = getattr(agent, "_memory_store", None)
if store is None:
return memory_block, user_block
try:
if getattr(agent, "_memory_enabled", True):
memory_block = store.format_for_system_prompt("memory") or ""
if getattr(agent, "_user_profile_enabled", True):
user_block = store.format_for_system_prompt("user") or ""
except Exception:
pass
return memory_block, user_block
def _strip_blocks(text: str, *blocks: str) -> str:
out = text
for block in blocks:
if block:
out = out.replace(block, "")
return out.strip()
def compute_session_context_breakdown(
agent: Any,
messages: Optional[List[dict]] = None,
) -> Dict[str, Any]:
"""Return a Cursor-style context usage breakdown for one live agent."""
from agent.model_metadata import estimate_messages_tokens_rough
from agent.system_prompt import build_system_prompt_parts
parts = build_system_prompt_parts(agent)
stable = parts.get("stable", "") or ""
context = parts.get("context", "") or ""
volatile = parts.get("volatile", "") or ""
skills_match = _SKILLS_BLOCK_RE.search(stable)
skills_index = skills_match.group(0) if skills_match else ""
memory_block, user_block = _memory_blocks(agent)
memory_text = "\n\n".join(part for part in (memory_block, user_block) if part).strip()
system_core = _strip_blocks(stable, skills_index)
system_tail = _strip_blocks(volatile, memory_block, user_block)
system_prompt_text = "\n\n".join(part for part in (system_core, system_tail) if part).strip()
tools = list(getattr(agent, "tools", None) or [])
builtin_tools, mcp_tools, subagent_tools = _split_tools(tools)
conversation_tokens = estimate_messages_tokens_rough(messages or [])
categories = [
("system_prompt", "System prompt", _chars_to_tokens(system_prompt_text)),
("tool_definitions", "Tool definitions", _json_tokens(builtin_tools)),
("rules", "Rules", _chars_to_tokens(context)),
("skills", "Skills", _chars_to_tokens(skills_index)),
("mcp", "MCP", _json_tokens(mcp_tools)),
("subagent_definitions", "Subagent definitions", _json_tokens(subagent_tools)),
("memory", "Memory", _chars_to_tokens(memory_text)),
("conversation", "Conversation", conversation_tokens),
]
estimated_total = sum(tokens for _, _, tokens in categories)
comp = getattr(agent, "context_compressor", None)
context_max = int(getattr(comp, "context_length", 0) or 0) if comp else 0
measured_used = int(getattr(comp, "last_prompt_tokens", 0) or 0) if comp else 0
context_used = measured_used if measured_used > 0 else estimated_total
context_percent = (
max(0, min(100, round(context_used / context_max * 100)))
if context_max
else 0
)
return {
"categories": [
{
"color": _CATEGORY_COLORS.get(category_id, "var(--ui-text-tertiary)"),
"id": category_id,
"label": label,
"tokens": tokens,
}
for category_id, label, tokens in categories
if tokens > 0
],
"context_max": context_max,
"context_percent": context_percent,
"context_used": context_used,
"estimated_total": estimated_total,
"model": getattr(agent, "model", "") or "",
}
+187 -1953
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+5 -57
View File
@@ -26,31 +26,7 @@ Lifecycle:
"""
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
from agent.redact import redact_sensitive_text
MEMORY_CONTEXT_MAX_CHARS = 6_000
_MEMORY_CONTEXT_HEAD_CHARS = 4_000
_MEMORY_CONTEXT_TAIL_CHARS = 1_500
_MEMORY_CONTEXT_TRUNCATION_MARKER = "\n...[memory provider context truncated]...\n"
def sanitize_memory_context(memory_context: str) -> str:
"""Prepare provider context for a context-engine/LLM egress boundary."""
sanitized = redact_sensitive_text(
memory_context.strip(),
force=True,
redact_url_credentials=True,
)
if len(sanitized) <= MEMORY_CONTEXT_MAX_CHARS:
return sanitized
return (
sanitized[:_MEMORY_CONTEXT_HEAD_CHARS]
+ _MEMORY_CONTEXT_TRUNCATION_MARKER
+ sanitized[-_MEMORY_CONTEXT_TAIL_CHARS:]
)
from typing import Any, Dict, List
class ContextEngine(ABC):
@@ -111,10 +87,8 @@ class ContextEngine(ABC):
def compress(
self,
messages: List[Dict[str, Any]],
current_tokens: Optional[int] = None,
focus_topic: Optional[str] = None,
force: bool = False,
memory_context: str = "",
current_tokens: int = None,
focus_topic: str = None,
) -> List[Dict[str, Any]]:
"""Compact the message list and return the new message list.
@@ -129,12 +103,6 @@ class ContextEngine(ABC):
Engines that support guided compression should prioritise
preserving information related to this topic. Engines that
don't support it may simply ignore this argument.
force: Whether a user-requested compression should bypass an
engine-owned cooldown. Engines without cooldowns may ignore it.
memory_context: Text returned by memory providers immediately before
compaction. Summarizing engines should include non-empty text in
their handoff prompt. Older engines may omit this parameter; the
host filters unsupported optional arguments by signature.
"""
# -- Optional: pre-flight check ----------------------------------------
@@ -226,17 +194,12 @@ class ContextEngine(ABC):
Default returns the standard fields run_agent.py expects.
"""
# Clamp the -1 "compression just ran, awaiting real usage" sentinel
# (set by conversation_compression) to 0 so status readers don't see a
# raw -1 or a negative usage_percent on the transitional turn. Mirrors
# the CLI/gateway status-bar paths (cli.py, tui_gateway/server.py).
last_prompt = self.last_prompt_tokens if self.last_prompt_tokens > 0 else 0
return {
"last_prompt_tokens": last_prompt,
"last_prompt_tokens": self.last_prompt_tokens,
"threshold_tokens": self.threshold_tokens,
"context_length": self.context_length,
"usage_percent": (
min(100, last_prompt / self.context_length * 100)
min(100, self.last_prompt_tokens / self.context_length * 100)
if self.context_length else 0
),
"compression_count": self.compression_count,
@@ -260,19 +223,4 @@ class ContextEngine(ABC):
(e.g. recalculate DAG budgets, switch summary models).
"""
self.context_length = context_length
# Apply per-model threshold overrides if set (longest substring match).
# Falls back to _config_threshold_percent (the raw config value) when
# no override matches. Plugin engines that override update_model() can
# call resolve_model_threshold() for the same logic.
from agent.context_compressor import resolve_model_threshold
if not hasattr(self, "_config_threshold_percent"):
# Snapshot the pre-override percent ONCE so repeated model
# switches fall back to the engine's configured value, not the
# previous model's override.
self._config_threshold_percent = self.threshold_percent
self._base_threshold_percent = resolve_model_threshold(
model, getattr(self, "model_thresholds", {}),
self._config_threshold_percent,
)
self.threshold_percent = self._base_threshold_percent
self.threshold_tokens = int(context_length * self.threshold_percent)
+8 -55
View File
@@ -12,7 +12,6 @@ from pathlib import Path
from typing import Awaitable, Callable
from agent.model_metadata import estimate_tokens_rough
from hermes_cli._subprocess_compat import IS_WINDOWS, windows_hide_flags
_QUOTED_REFERENCE_VALUE = r'(?:`[^`\n]+`|"[^"\n]+"|\'[^\'\n]+\')'
REFERENCE_PATTERN = re.compile(
@@ -152,24 +151,13 @@ async def preprocess_context_references_async(
blocks: list[str] = []
injected_tokens = 0
# Expand all references concurrently. Each _expand_reference is independent
# (no shared state during expansion) — a message with several @url: refs
# would otherwise pay one full web_extract round-trip per ref in series.
# gather preserves positional order, so we reassemble warnings/blocks in the
# original ref order exactly as the prior serial loop did; the token-budget
# check below is unchanged (it runs once, after all refs are expanded).
expanded = await asyncio.gather(
*(
_expand_reference(
ref,
cwd_path,
url_fetcher=url_fetcher,
allowed_root=allowed_root_path,
)
for ref in refs
for ref in refs:
warning, block = await _expand_reference(
ref,
cwd_path,
url_fetcher=url_fetcher,
allowed_root=allowed_root_path,
)
)
for warning, block in expanded:
if warning:
warnings.append(warning)
if block:
@@ -302,7 +290,6 @@ def _expand_git_reference(
args: list[str],
label: str,
) -> tuple[str | None, str | None]:
_popen_kwargs = {"creationflags": windows_hide_flags()} if IS_WINDOWS else {}
try:
result = subprocess.run(
["git", *args],
@@ -311,7 +298,6 @@ def _expand_git_reference(
text=True,
timeout=30,
stdin=subprocess.DEVNULL,
**_popen_kwargs,
)
except subprocess.TimeoutExpired:
return f"{ref.raw}: git command timed out (30s)", None
@@ -339,9 +325,9 @@ async def _fetch_url_content(
async def _default_url_fetcher(url: str) -> str:
from tools.web_tools import web_extract_tool
raw = await web_extract_tool([url], format="markdown")
raw = await web_extract_tool([url], format="markdown", use_llm_processing=True)
payload = json.loads(raw)
docs = payload.get("results", [])
docs = payload.get("data", {}).get("documents", [])
if not docs:
return ""
doc = docs[0]
@@ -381,37 +367,6 @@ def _ensure_reference_path_allowed(path: Path) -> None:
continue
raise ValueError("path is a sensitive credential or internal Hermes path and cannot be attached")
# Anchor to the canonical read deny-list (agent/file_safety.get_read_block_error),
# the single source of truth used by the file/terminal read path. The narrow
# list above predates that guard and never caught the real credential stores:
# provider keys (auth.json), Anthropic OAuth tokens (.anthropic_oauth.json),
# MCP OAuth material (mcp-tokens/), webhook HMAC secrets, and project-local
# .env files. That gap matters because the gateway feeds UNTRUSTED remote
# message text into reference expansion, so `@file:~/.hermes/auth.json` from a
# chat peer would otherwise read the operator's keys straight into context.
# Routing through the canonical guard closes the gap today and keeps this path
# protected automatically whenever that deny-list grows.
try:
from agent.file_safety import get_read_block_error
if get_read_block_error(str(path)) is not None:
raise ValueError(
"path is a sensitive credential or internal Hermes path and cannot be attached"
)
except ValueError:
raise
except Exception:
# Fail CLOSED on the security path. This guard exists specifically to
# cover credential stores the narrow list above misses (auth.json,
# .anthropic_oauth.json, mcp-tokens/, ...). If the canonical lookup
# ever fails, silently falling through would re-open that exact hole —
# the gateway feeds untrusted remote text here, so a probe could then
# attach the operator's keys. Refuse instead: a spurious block on a
# legitimate file is a recoverable annoyance; a leaked credential is not.
raise ValueError(
"path could not be verified against the credential deny-list and cannot be attached"
)
def _strip_trailing_punctuation(value: str) -> str:
stripped = value.rstrip(TRAILING_PUNCTUATION)
@@ -528,7 +483,6 @@ def _iter_visible_entries(path: Path, cwd: Path, limit: int) -> list[Path]:
def _rg_files(path: Path, cwd: Path, limit: int) -> list[Path] | None:
_popen_kwargs = {"creationflags": windows_hide_flags()} if IS_WINDOWS else {}
try:
result = subprocess.run(
["rg", "--files", str(path.relative_to(cwd))],
@@ -537,7 +491,6 @@ def _rg_files(path: Path, cwd: Path, limit: int) -> list[Path] | None:
text=True,
timeout=10,
stdin=subprocess.DEVNULL,
**_popen_kwargs,
)
except (FileNotFoundError, OSError, subprocess.TimeoutExpired):
return None
File diff suppressed because it is too large Load Diff
+197 -1839
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File diff suppressed because it is too large Load Diff
+25 -90
View File
@@ -21,14 +21,8 @@ from pathlib import Path
from types import SimpleNamespace
from typing import Any
from openai.types.chat.chat_completion_message_tool_call import (
ChatCompletionMessageToolCall,
Function,
)
from agent.file_safety import get_read_block_error, get_write_denied_error
from agent.file_safety import get_read_block_error, is_write_denied
from agent.redact import redact_sensitive_text
from tools.environments.local import hermes_subprocess_env
ACP_MARKER_BASE_URL = "acp://copilot"
_DEFAULT_TIMEOUT_SECONDS = 900.0
@@ -76,6 +70,16 @@ def _resolve_args() -> list[str]:
def _resolve_home_dir() -> str:
"""Return a stable HOME for child ACP processes."""
try:
from hermes_constants import get_subprocess_home
profile_home = get_subprocess_home()
if profile_home:
return profile_home
except Exception:
pass
home = os.environ.get("HOME", "").strip()
if home:
return home
@@ -100,14 +104,8 @@ def _resolve_home_dir() -> str:
def _build_subprocess_env() -> dict[str, str]:
# Copilot ACP is a model-driving CLI executor: it legitimately needs LLM
# provider credentials. Route through the central helper so Tier-1 secrets
# (gateway bot tokens, GitHub auth, infra) are still stripped (#29157).
env = hermes_subprocess_env(inherit_credentials=True)
home = _resolve_home_dir()
env["HOME"] = home
from hermes_constants import apply_subprocess_home_env
apply_subprocess_home_env(env)
env = os.environ.copy()
env["HOME"] = _resolve_home_dir()
return env
@@ -233,73 +231,11 @@ def _render_message_content(content: Any) -> str:
return str(content).strip()
def _build_openai_tool_call(
*,
call_id: str,
name: str,
arguments: str,
) -> ChatCompletionMessageToolCall:
"""Build an OpenAI-compatible tool-call object for downstream handling."""
return ChatCompletionMessageToolCall(
id=call_id,
call_id=call_id,
response_item_id=None,
type="function",
function=Function(name=name, arguments=arguments),
)
def _completion_to_stream_chunks(completion: SimpleNamespace) -> list[SimpleNamespace]:
"""Convert a one-shot ACP response into OpenAI-style stream chunks."""
choice = completion.choices[0]
message = choice.message
tool_call_deltas = None
if message.tool_calls:
tool_call_deltas = []
for index, tool_call in enumerate(message.tool_calls):
tool_call_deltas.append(
SimpleNamespace(
index=index,
id=getattr(tool_call, "id", None),
type=getattr(tool_call, "type", "function"),
function=SimpleNamespace(
name=getattr(tool_call.function, "name", None),
arguments=getattr(tool_call.function, "arguments", None),
),
)
)
delta = SimpleNamespace(
role="assistant",
content=message.content or None,
tool_calls=tool_call_deltas,
reasoning_content=message.reasoning_content,
reasoning=message.reasoning,
)
data_chunk = SimpleNamespace(
choices=[
SimpleNamespace(
index=0,
delta=delta,
finish_reason=choice.finish_reason,
)
],
model=completion.model,
usage=None,
)
usage_chunk = SimpleNamespace(
choices=[],
model=completion.model,
usage=completion.usage,
)
return [data_chunk, usage_chunk]
def _extract_tool_calls_from_text(text: str) -> tuple[list[ChatCompletionMessageToolCall], str]:
def _extract_tool_calls_from_text(text: str) -> tuple[list[SimpleNamespace], str]:
if not isinstance(text, str) or not text.strip():
return [], ""
extracted: list[ChatCompletionMessageToolCall] = []
extracted: list[SimpleNamespace] = []
consumed_spans: list[tuple[int, int]] = []
def _try_add_tool_call(raw_json: str) -> None:
@@ -323,10 +259,12 @@ def _extract_tool_calls_from_text(text: str) -> tuple[list[ChatCompletionMessage
call_id = f"acp_call_{len(extracted)+1}"
extracted.append(
_build_openai_tool_call(
SimpleNamespace(
id=call_id,
call_id=call_id,
name=fn_name.strip(),
arguments=fn_args,
response_item_id=None,
type="function",
function=SimpleNamespace(name=fn_name.strip(), arguments=fn_args),
)
)
@@ -445,7 +383,6 @@ class CopilotACPClient:
timeout: float | None = None,
tools: list[dict[str, Any]] | None = None,
tool_choice: Any = None,
stream: bool = False,
**_: Any,
) -> Any:
prompt_text = _format_messages_as_prompt(
@@ -492,14 +429,11 @@ class CopilotACPClient:
)
finish_reason = "tool_calls" if tool_calls else "stop"
choice = SimpleNamespace(message=assistant_message, finish_reason=finish_reason)
completion = SimpleNamespace(
return SimpleNamespace(
choices=[choice],
usage=usage,
model=model or "copilot-acp",
)
if stream:
return _completion_to_stream_chunks(completion)
return completion
def _run_prompt(self, prompt_text: str, *, timeout_seconds: float) -> tuple[str, str]:
try:
@@ -727,9 +661,10 @@ class CopilotACPClient:
elif method == "fs/write_text_file":
try:
path = _ensure_path_within_cwd(str(params.get("path") or ""), cwd)
denied = get_write_denied_error(str(path))
if denied:
raise PermissionError(denied)
if is_write_denied(str(path)):
raise PermissionError(
f"Write denied: '{path}' is a protected system/credential file."
)
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(str(params.get("content") or ""))
response = {
+1 -1
View File
@@ -22,7 +22,7 @@ _PERSISTABLE_PROVIDER_SOURCES = frozenset({
("minimax-oauth", "oauth"),
("nous", "device_code"),
("openai-codex", "device_code"),
("xai-oauth", "device_code"),
("xai-oauth", "loopback_pkce"),
})
_SAFE_SECRETISH_METADATA_KEYS = frozenset({
+62 -480
View File
@@ -11,12 +11,10 @@ import uuid
import re
from dataclasses import dataclass, fields, replace
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple
from hermes_constants import OPENROUTER_BASE_URL
from hermes_cli.config import load_env
from agent.secret_scope import get_secret as _get_secret
from agent.credential_persistence import (
is_borrowed_credential_source,
sanitize_borrowed_credential_payload,
@@ -43,19 +41,11 @@ logger = logging.getLogger(__name__)
def _load_config_safe() -> Optional[dict]:
"""Load config.yaml read-only, returning None on any error.
Uses ``load_config_readonly()``: every consumer in this module only reads
(``get_pool_strategy``, ``_iter_custom_providers``, the model-config seed),
and the deepcopy that ``load_config()`` pays per call is what made
credential-pool checks the dominant cost of ``model.options`` the picker
calls ``load_pool()`` once per provider row, each of which loaded (and
deep-copied) the full config again.
"""
"""Load config.yaml, returning None on any error."""
try:
from hermes_cli.config import load_config_readonly
from hermes_cli.config import load_config
return load_config_readonly()
return load_config()
except Exception:
return None
@@ -90,7 +80,7 @@ _TERMINAL_AUTH_REASONS = frozenset({
# without losing recoverability — the user always has the option to re-add
# via ``hermes auth add``.
#
# Singleton-seeded entries (``device_code``, ``claude_code``)
# Singleton-seeded entries (``device_code``, ``loopback_pkce``, ``claude_code``)
# are NOT pruned because ``_seed_from_singletons`` would just re-create them
# on the next ``load_pool()`` with the same stale singleton tokens, defeating
# the cleanup. They remain in the pool marked DEAD until an explicit re-auth
@@ -122,20 +112,6 @@ EXHAUSTED_TTL_401_SECONDS = 5 * 60 # 5 minutes
EXHAUSTED_TTL_429_SECONDS = 60 * 60 # 1 hour
EXHAUSTED_TTL_DEFAULT_SECONDS = 60 * 60 # 1 hour
# Throttle window for the "no available entries" INFO line. Credential
# selection runs on a hot path (every model call, plus auxiliary tasks like
# compression/moa/titles), so when a pool is empty or fully exhausted the
# un-throttled log fires on *every* selection. On Windows several Hermes
# processes share one rotating log guarded by concurrent-log-handler's
# cross-process lock; that per-selection volume storms the lock
# (``RuntimeError: Cannot acquire lock after 20 attempts``), pegs a core, and
# stalls the asyncio event loop long enough to fail the Desktop backend
# readiness handshake ("Timed out connecting to Hermes backend after
# 15000ms"). Logging the condition at most once per window preserves the
# signal while removing the storm — same class of fix as the warn-once
# dedup in #58265.
NO_AVAILABLE_ENTRIES_LOG_THROTTLE_SECONDS = 60.0
# Pool key prefix for custom OpenAI-compatible endpoints.
# Custom endpoints all share provider='custom' but are keyed by their
# custom_providers name: 'custom:<normalized_name>'.
@@ -150,17 +126,6 @@ _EXTRA_KEYS = frozenset({
})
def _normalize_pool_auth_type(provider: str, token: Any, auth_type: Any) -> str:
"""Infer pool auth metadata for token formats with one unambiguous meaning."""
if (
provider == "anthropic"
and isinstance(token, str)
and token.startswith("sk-ant-oat")
):
return AUTH_TYPE_OAUTH
return str(auth_type or AUTH_TYPE_API_KEY)
@dataclass
class PooledCredential:
provider: str
@@ -190,11 +155,6 @@ class PooledCredential:
def __post_init__(self):
if self.extra is None:
self.extra = {}
self.auth_type = _normalize_pool_auth_type(
self.provider,
self.access_token,
self.auth_type,
)
def __getattr__(self, name: str):
if name in _EXTRA_KEYS:
@@ -483,102 +443,9 @@ def get_pool_strategy(provider: str) -> str:
return STRATEGY_FILL_FIRST
def credential_pool_matches_provider(
pool_or_provider: Any,
provider: Optional[str],
*,
base_url: Optional[str] = None,
) -> bool:
"""Return whether a pool belongs to the requested runtime provider.
Named custom endpoints intentionally use two identities: the live agent is
``custom`` while its pool is keyed ``custom:<name>``. Accept that pair only
when the runtime base URL resolves to the exact same custom pool key.
Empty string identities fail closed. Legacy pool adapters without a
``provider`` attribute remain compatible; production pools are scoped.
"""
raw_pool_provider = getattr(pool_or_provider, "provider", None)
if raw_pool_provider is None:
if isinstance(pool_or_provider, str):
raw_pool_provider = pool_or_provider
else:
# Backward compatibility for lightweight/unscoped pool adapters.
# Production CredentialPool instances always carry ``provider``;
# old plugins and tests may expose only select()/has_credentials().
return True
pool_provider = str(raw_pool_provider or "").strip().lower()
provider_norm = str(provider or "").strip().lower()
if not pool_provider or not provider_norm:
return False
if pool_provider == provider_norm:
return True
if provider_norm != "custom" or not pool_provider.startswith(CUSTOM_POOL_PREFIX):
return False
try:
matched_pool = get_custom_provider_pool_key(base_url or "")
except Exception:
return False
return str(matched_pool or "").strip().lower() == pool_provider
DEFAULT_MAX_CONCURRENT_PER_CREDENTIAL = 1
def _write_through_provider_state_to_global_root(
provider_id: str, state: Dict[str, Any]
) -> None:
"""Persist a rotated OAuth ``state`` into the global-root auth.json.
Best-effort write-through for the multi-profile rotation hazard
(#48415 / #43589): nous, openai-codex, and xai-oauth rotate the
refresh_token on refresh, so when a profile pool refresh rotates a grant
it resolved from the root fallback, the rotated chain must land back in
root. Otherwise root keeps a now-revoked refresh token and every other
profile reading the stale root grant dies with ``refresh_token_reused`` /
``invalid_grant`` once its access token expires.
Only updates ``providers.<provider_id>`` in the root store; never touches
the profile store (the caller already saved that). Swallows all errors a
failed write-through degrades to the pre-existing behavior (root stale), it
must never break the profile's own successful save. Mirrors
``hermes_cli.auth._write_through_xai_oauth_to_global_root`` (which covers
the non-pool xAI refresh path) for the credential-pool refresh path.
"""
try:
global_path = auth_mod._global_auth_file_path()
except Exception:
return
if global_path is None:
# Classic mode (profile == root); the profile save already hit root.
return
# Seat belt: under pytest, refuse to write the real user's
# ~/.hermes/auth.json even when HERMES_HOME points at a profile path
# (mirrors the read-side guard in _load_global_auth_store). Uses the
# unmodified HOME env, not Path.home() which fixtures may monkeypatch.
if os.environ.get("PYTEST_CURRENT_TEST"):
real_home_env = os.environ.get("HOME", "")
if real_home_env:
real_root = Path(real_home_env) / ".hermes" / "auth.json"
try:
if global_path.resolve(strict=False) == real_root.resolve(strict=False):
return
except Exception:
return
try:
auth_mod._persist_provider_state_to_store(
provider_id,
state,
global_path,
set_active=False,
)
except Exception as exc: # pragma: no cover - best effort
logger.debug(
"%s pool refresh: write-through to global root failed: %s",
provider_id,
exc,
)
class CredentialPool:
def __init__(self, provider: str, entries: List[PooledCredential]):
self.provider = provider
@@ -588,12 +455,6 @@ class CredentialPool:
self._lock = threading.Lock()
self._active_leases: Dict[str, int] = {}
self._max_concurrent = DEFAULT_MAX_CONCURRENT_PER_CREDENTIAL
# Monotonic timestamp of the last "no available entries" log, used to
# throttle that message so an empty/exhausted pool cannot storm the
# shared rotating log (see NO_AVAILABLE_ENTRIES_LOG_THROTTLE_SECONDS).
# Re-armed to None on every successful selection so a recover→re-exhaust
# transition logs promptly instead of being swallowed by a stale window.
self._last_no_entries_log_at: Optional[float] = None
def has_credentials(self) -> bool:
return bool(self._entries)
@@ -617,11 +478,10 @@ class CredentialPool:
self._entries[idx] = new
return
def _persist(self, *, removed_ids: Optional[List[str]] = None) -> None:
def _persist(self) -> None:
write_credential_pool(
self.provider,
[entry.to_dict() for entry in self._entries],
removed_ids=removed_ids,
)
def _is_terminal_auth_failure(
@@ -696,32 +556,17 @@ class CredentialPool:
file_refresh = creds.get("refreshToken", "")
file_access = creds.get("accessToken", "")
file_expires = creds.get("expiresAt", 0)
# Sync when either token changed. Access tokens can be re-issued
# without a new refresh token (silent re-issue path), so checking
# only refresh_token misses that case and leaves a stale
# access_token in the pool → 401 on every request until the pool
# entry's exhausted TTL expires.
entry_access = entry.access_token or ""
entry_refresh = entry.refresh_token or ""
if (file_access or file_refresh) and (
(file_access and file_access != entry_access)
or (file_refresh and file_refresh != entry_refresh)
):
logger.debug(
"Pool entry %s: syncing tokens from credentials file (tokens changed)",
entry.id,
)
# If the credentials file has a different token pair, sync it
if file_refresh and file_refresh != entry.refresh_token:
logger.debug("Pool entry %s: syncing tokens from credentials file (refresh token changed)", entry.id)
updated = replace(
entry,
access_token=file_access or entry.access_token,
refresh_token=file_refresh or entry.refresh_token,
expires_at_ms=file_expires or entry.expires_at_ms,
access_token=file_access,
refresh_token=file_refresh,
expires_at_ms=file_expires,
last_status=None,
last_status_at=None,
last_error_code=None,
last_error_reason=None,
last_error_message=None,
last_error_reset_at=None,
)
self._replace_entry(entry, updated)
self._persist()
@@ -804,11 +649,11 @@ class CredentialPool:
keeps the consumed refresh_token and the next ``_refresh_entry`` call
would replay it and get a ``refresh_token_reused``-style 4xx.
Only applies to entries seeded from the singleton (``device_code``);
manually added entries are independent credentials with their own
refresh-token lifecycle.
Only applies to entries seeded from the singleton (``loopback_pkce``);
manually added entries (``manual:xai_pkce``) are independent
credentials with their own refresh-token lifecycle.
"""
if self.provider != "xai-oauth" or entry.source != "device_code":
if self.provider != "xai-oauth" or entry.source != "loopback_pkce":
return entry
try:
with _auth_store_lock():
@@ -852,45 +697,6 @@ class CredentialPool:
logger.debug("Failed to sync xAI OAuth entry from auth.json: %s", exc)
return entry
def _sync_xai_oauth_entry_from_pool_store(
self, entry: PooledCredential
) -> PooledCredential:
"""Adopt a token pair rotated by another pool instance.
Direct xAI integrations load a fresh ``CredentialPool`` for each
request. Their in-memory locks therefore cannot protect xAI's
single-use refresh token across concurrent requests or processes.
This helper is called while the shared auth-store lock is held and
re-reads the exact persisted row before a refresh POST is attempted.
"""
if self.provider != "xai-oauth":
return entry
try:
persisted = next(
(
payload
for payload in read_credential_pool(self.provider)
if isinstance(payload, dict) and payload.get("id") == entry.id
),
None,
)
if not isinstance(persisted, dict):
return entry
stored = PooledCredential.from_dict(self.provider, persisted)
if (
stored.access_token != entry.access_token
or stored.refresh_token != entry.refresh_token
):
logger.debug(
"Pool entry %s: adopting xAI OAuth tokens rotated by another pool instance",
entry.id,
)
self._replace_entry(entry, stored)
return stored
except Exception as exc:
logger.debug("Failed to sync xAI OAuth entry from credential pool: %s", exc)
return entry
def _sync_nous_entry_from_auth_store(self, entry: PooledCredential) -> PooledCredential:
"""Sync a Nous pool entry from auth.json if tokens differ.
@@ -987,35 +793,12 @@ class CredentialPool:
"""
# Only sync entries that were seeded *from* a singleton. Manually
# added pool entries (source="manual:*") are independent credentials
# and must not write back to the singleton. All singleton-seeded
# device-code sources (nous, openai-codex, xAI) use ``device_code``.
if entry.source != "device_code":
# and must not write back to the singleton.
if entry.source not in {"device_code", "loopback_pkce"}:
return
try:
with _auth_store_lock():
auth_store = _load_auth_store()
# Decide BEFORE writing whether this profile is reading the
# grant from the global root (no own providers.<id> block) vs.
# genuinely shadowing it. A pool refresh rotates single-use
# OAuth refresh tokens, so a profile that resolved the grant
# from root MUST write the rotated chain back to root too —
# otherwise root keeps a revoked refresh token and every other
# profile reading the stale root grant dies with
# refresh_token_reused / invalid_grant once its access token
# expires. This mirrors the xAI write-through in
# hermes_cli.auth._save_xai_oauth_tokens (#43589); the pool
# refresh path is the Codex/xAI analog reported in #48415.
_wt_provider_id = {
"nous": "nous",
"openai-codex": "openai-codex",
"xai-oauth": "xai-oauth",
}.get(self.provider)
write_through_to_root = bool(_wt_provider_id) and not (
isinstance(auth_store.get("providers"), dict)
and isinstance(
auth_store["providers"].get(_wt_provider_id), dict
)
)
if self.provider == "nous":
state = _load_provider_state(auth_store, "nous")
if state is None:
@@ -1071,10 +854,6 @@ class CredentialPool:
return
_save_auth_store(auth_store)
if write_through_to_root and _wt_provider_id:
_write_through_provider_state_to_global_root(
_wt_provider_id, state
)
except Exception as exc:
logger.debug("Failed to sync %s pool entry back to auth store: %s", self.provider, exc)
@@ -1084,61 +863,6 @@ class CredentialPool:
self._mark_exhausted(entry, None)
return None
# Codex and xAI OAuth refresh tokens are single-use. The
# sync→POST→write-back sequence below must run atomically across Hermes
# processes: otherwise two processes can both adopt the same on-disk
# token, both POST it, and the loser gets ``refresh_token_reused``.
# Serialize the whole sequence through the shared cross-process
# auth-store flock (the same lock and extended-timeout pattern used by
# resolve_codex_runtime_credentials()). When a waiter finally acquires
# the lock, the in-lock re-sync below picks up the rotated token the
# winner persisted and skips the POST.
if self.provider in ("openai-codex", "xai-oauth"):
sync_entry = (
self._sync_codex_entry_from_auth_store
if self.provider == "openai-codex"
else self._sync_xai_oauth_entry_from_pool_store
)
with _auth_store_lock(
timeout_seconds=self._single_use_refresh_lock_timeout()
):
synced = sync_entry(entry)
if self.provider == "openai-codex":
if synced is not entry:
entry = synced
if not force and not self._entry_needs_refresh(entry):
return entry
return self._refresh_entry_impl(entry, force=force)
if (
synced.access_token != entry.access_token
or synced.refresh_token != entry.refresh_token
):
return synced
return self._refresh_entry_impl(synced, force=force)
return self._refresh_entry_impl(entry, force=force)
def _single_use_refresh_lock_timeout(self) -> float:
"""Lock timeout for single-use-refresh-token providers.
Covers the configured refresh POST timeout plus a margin so a slow
token endpoint cannot make the flock give up before the refresh
resolves. Reads the provider's ``HERMES_*_REFRESH_TIMEOUT_SECONDS``
override.
"""
env_var = (
"HERMES_CODEX_REFRESH_TIMEOUT_SECONDS"
if self.provider == "openai-codex"
else "HERMES_XAI_REFRESH_TIMEOUT_SECONDS"
)
refresh_timeout_seconds = auth_mod.env_float(env_var, 20)
return max(
float(auth_mod.AUTH_LOCK_TIMEOUT_SECONDS),
float(refresh_timeout_seconds) + 5.0,
)
def _refresh_entry_impl(
self, entry: PooledCredential, *, force: bool
) -> Optional[PooledCredential]:
try:
if self.provider == "anthropic":
from agent.anthropic_adapter import refresh_anthropic_oauth_pure
@@ -1259,8 +983,8 @@ class CredentialPool:
# consumed the refresh token between our proactive sync and the
# HTTP call. Re-check auth.json and adopt the fresh tokens if
# they have rotated since. Only meaningful for singleton-seeded
# (device_code) entries; manual entries don't share
# state with the singleton.
# (loopback_pkce) entries; manual entries don't share state with
# the singleton.
if self.provider == "xai-oauth":
synced = self._sync_xai_oauth_entry_from_auth_store(entry)
if synced.refresh_token != entry.refresh_token:
@@ -1282,8 +1006,8 @@ class CredentialPool:
# Terminal error: auth.json has no newer tokens — the stored
# refresh_token is dead. Clear it from auth.json so the next
# session does not re-seed the same revoked credentials, and
# remove all singleton-seeded xAI entries from the in-memory
# pool. Mirrors the Nous quarantine path above.
# remove all singleton-seeded (loopback_pkce) entries from the
# in-memory pool. Mirrors the Nous quarantine path above.
if auth_mod._is_terminal_xai_oauth_refresh_error(exc):
logger.debug(
"xAI OAuth refresh token is terminally invalid; clearing local token state"
@@ -1315,17 +1039,13 @@ class CredentialPool:
logger.debug(
"Failed to clear terminal xAI OAuth state: %s", clear_exc
)
removed_ids = [
item.id for item in self._entries
if item.source == "device_code"
]
self._entries = [
item for item in self._entries
if item.source != "device_code"
if item.source != "loopback_pkce"
]
if self._current_id == entry.id:
self._current_id = None
self._persist(removed_ids=removed_ids)
self._persist()
return None
# For openai-codex: same race as xAI/nous — another Hermes process
# may have consumed the refresh token between our proactive sync
@@ -1385,17 +1105,13 @@ class CredentialPool:
logger.debug(
"Failed to clear terminal Codex OAuth state: %s", clear_exc
)
removed_ids = [
item.id for item in self._entries
if item.source == "device_code"
]
self._entries = [
item for item in self._entries
if item.source != "device_code"
]
if self._current_id == entry.id:
self._current_id = None
self._persist(removed_ids=removed_ids)
self._persist()
return None
# For nous: another process may have consumed the refresh token
# between our proactive sync and the HTTP call. Re-sync from
@@ -1452,17 +1168,13 @@ class CredentialPool:
auth_mod.NOUS_DEVICE_CODE_SOURCE,
f"manual:{auth_mod.NOUS_DEVICE_CODE_SOURCE}",
}
removed_ids = [
item.id for item in self._entries
if item.source in singleton_sources
]
self._entries = [
item for item in self._entries
if item.source not in singleton_sources
]
if self._current_id == entry.id:
self._current_id = None
self._persist(removed_ids=removed_ids)
self._persist()
return None
self._mark_exhausted(entry, None)
return None
@@ -1499,7 +1211,7 @@ class CredentialPool:
if self.provider == "xai-oauth":
return auth_mod._xai_access_token_is_expiring(
entry.access_token,
auth_mod._xai_proactive_refresh_skew_seconds(entry.access_token),
auth_mod.XAI_ACCESS_TOKEN_REFRESH_SKEW_SECONDS,
)
if self.provider == "nous":
# Nous refresh can require network access and should happen when
@@ -1524,11 +1236,6 @@ class CredentialPool:
entries_to_prune: List[str] = []
available: List[PooledCredential] = []
for entry in self._entries:
# Borrowed credentials persist as metadata-only references and are
# hydrated from their live source on load. A stale duplicate row
# can remain unhydrated; never lease or select it as an empty key.
if entry.auth_type == AUTH_TYPE_API_KEY and not entry.runtime_api_key:
continue
# For anthropic claude_code entries, sync from the credentials file
# before any status/refresh checks. This picks up tokens refreshed
# by other processes (Claude Code CLI, other Hermes profiles).
@@ -1566,7 +1273,7 @@ class CredentialPool:
# tokens that another process (or a fresh `hermes model` ->
# xAI Grok OAuth login) has since rotated in auth.json.
if (self.provider == "xai-oauth"
and entry.source == "device_code"
and entry.source == "loopback_pkce"
and entry.last_status in {STATUS_EXHAUSTED, STATUS_DEAD}):
synced = self._sync_xai_oauth_entry_from_auth_store(entry)
if synced is not entry:
@@ -1629,35 +1336,16 @@ class CredentialPool:
pruned_ids = set(entries_to_prune)
self._entries = [e for e in self._entries if e.id not in pruned_ids]
if cleared_any:
self._persist(removed_ids=entries_to_prune)
self._persist()
return available
def _log_no_available_entries(self) -> None:
"""Emit the empty-pool INFO line at most once per throttle window.
Called on every selection while the pool is empty/exhausted. Without
throttling this storms the Windows cross-process log lock and stalls the
event loop (see NO_AVAILABLE_ENTRIES_LOG_THROTTLE_SECONDS).
"""
now = time.monotonic()
last = self._last_no_entries_log_at
if last is not None and (now - last) < NO_AVAILABLE_ENTRIES_LOG_THROTTLE_SECONDS:
return
self._last_no_entries_log_at = now
logger.info("credential pool: no available entries (all exhausted or empty)")
def _select_unlocked(self, *, refresh: bool = True) -> Optional[PooledCredential]:
available = self._available_entries(clear_expired=True, refresh=refresh)
def _select_unlocked(self) -> Optional[PooledCredential]:
available = self._available_entries(clear_expired=True, refresh=True)
if not available:
self._current_id = None
self._log_no_available_entries()
logger.info("credential pool: no available entries (all exhausted or empty)")
return None
# A successful selection means the pool recovered; re-arm the throttle
# so a later re-exhaustion logs immediately rather than being silenced
# by a window opened during the previous empty stretch.
self._last_no_entries_log_at = None
if self._strategy == STRATEGY_RANDOM:
entry = random.choice(available)
self._current_id = entry.id
@@ -1781,35 +1469,6 @@ class CredentialPool:
with self._lock:
return self._try_refresh_current_unlocked()
def try_refresh_matching(
self, api_key_hint: Optional[str] = None
) -> Optional[PooledCredential]:
"""Force-refresh the entry that supplied ``api_key_hint``.
Direct provider integrations may reload the pool after a request has
already failed, so they cannot rely on ``current_id`` identifying the
issuing credential. With no hint, select an entry without first doing
the normal proactive refresh; the forced refresh below must consume a
rotating refresh token exactly once.
"""
with self._lock:
entry = None
if api_key_hint:
entry = next(
(
candidate
for candidate in self._entries
if candidate.runtime_api_key == api_key_hint
),
None,
)
else:
entry = self.current() or self._select_unlocked(refresh=False)
if entry is None:
return None
self._current_id = entry.id
return self._try_refresh_current_unlocked()
def _try_refresh_current_unlocked(self) -> Optional[PooledCredential]:
entry = self.current()
if entry is None:
@@ -1851,11 +1510,7 @@ class CredentialPool:
replace(entry, priority=new_priority)
for new_priority, entry in enumerate(self._entries)
]
write_credential_pool(
self.provider,
[entry.to_dict() for entry in self._entries],
removed_ids=[removed.id],
)
self._persist()
if self._current_id == removed.id:
self._current_id = None
return removed
@@ -1893,15 +1548,11 @@ class CredentialPool:
def _upsert_entry(entries: List[PooledCredential], provider: str, source: str, payload: Dict[str, Any]) -> bool:
matching_indices = []
existing_idx = None
for idx, entry in enumerate(entries):
if entry.source == source:
matching_indices.append(idx)
existing_idx = matching_indices[0] if matching_indices else None
duplicate_indices = set(matching_indices[1:])
if duplicate_indices:
entries[:] = [entry for idx, entry in enumerate(entries) if idx not in duplicate_indices]
existing_idx = idx
break
if existing_idx is None:
payload.setdefault("id", uuid.uuid4().hex[:6])
@@ -1933,8 +1584,8 @@ def _upsert_entry(entries: List[PooledCredential], provider: str, source: str, p
# Runtime-only borrowed secret updates should refresh the in-memory
# entry without forcing auth.json churn when the disk-safe payload is
# unchanged (for example env keys with the same fingerprint).
return bool(duplicate_indices) or existing.to_dict() != updated.to_dict()
return bool(duplicate_indices)
return existing.to_dict() != updated.to_dict()
return False
def _normalize_pool_priorities(provider: str, entries: List[PooledCredential]) -> bool:
@@ -2015,7 +1666,7 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
_env_file = load_env()
def _env_val(key: str) -> str:
return (_env_file.get(key) or _get_secret(key, "") or "").strip()
return (_env_file.get(key) or os.environ.get(key) or "").strip()
anthropic_api_key = _env_val("ANTHROPIC_API_KEY")
anthropic_oauth_env = (
@@ -2131,16 +1782,11 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
from hermes_cli.copilot_auth import resolve_copilot_token, get_copilot_api_token
token, source = resolve_copilot_token()
if token:
api_token, enterprise_base_url = get_copilot_api_token(token)
api_token = get_copilot_api_token(token)
source_name = "gh_cli" if "gh" in source.lower() else f"env:{source}"
if not _is_suppressed(provider, source_name):
active_sources.add(source_name)
pconfig = PROVIDER_REGISTRY.get(provider)
# Use enterprise base URL from token exchange if available,
# otherwise fall back to the provider's default.
effective_base_url = enterprise_base_url or (
pconfig.inference_base_url if pconfig else ""
)
changed |= _upsert_entry(
entries,
provider,
@@ -2149,7 +1795,7 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
"source": source_name,
"auth_type": AUTH_TYPE_API_KEY,
"access_token": api_token,
"base_url": effective_base_url,
"base_url": pconfig.inference_base_url if pconfig else "",
"label": source,
},
)
@@ -2268,30 +1914,28 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
# (``providers["xai-oauth"]``). Surface them in the pool too so
# ``hermes auth list`` reflects the logged-in state and so the pool
# is the single source of truth for refresh during runtime resolution.
if _is_suppressed(provider, "loopback_pkce"):
return changed, active_sources
state = _load_provider_state(auth_store, "xai-oauth")
tokens = state.get("tokens") if isinstance(state, dict) else None
if isinstance(tokens, dict) and tokens.get("access_token"):
# Device code is the only supported xAI OAuth flow; the singleton is
# always surfaced as ``device_code`` (consistent with nous/codex).
source = "device_code"
if _is_suppressed(provider, source):
return changed, active_sources
active_sources.add(source)
active_sources.add("loopback_pkce")
from hermes_cli.auth import DEFAULT_XAI_OAUTH_BASE_URL
base_url = DEFAULT_XAI_OAUTH_BASE_URL
changed |= _upsert_entry(
entries,
provider,
source,
"loopback_pkce",
{
"source": source,
"source": "loopback_pkce",
"auth_type": AUTH_TYPE_OAUTH,
"access_token": tokens.get("access_token", ""),
"refresh_token": tokens.get("refresh_token"),
"base_url": base_url,
"last_refresh": state.get("last_refresh"),
"label": label_from_token(tokens.get("access_token", ""), source),
"label": label_from_token(tokens.get("access_token", ""), "loopback_pkce"),
},
)
@@ -2308,21 +1952,8 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
# changes to the .env file.
def _get_env_prefer_dotenv(key: str) -> str:
env_file = load_env()
raw = env_file.get(key, "").strip()
scoped_value = (_get_secret(key, "") or "").strip()
# If .env contains an unresolved op:// reference, prefer the
# already-resolved value supplied by the active secret scope (or by
# os.environ in legacy single-profile mode), set by
# load_hermes_dotenv() -> apply_onepassword_secrets()). The raw
# "op://Vault/Item/field" string would otherwise win and every
# provider auth attempt would receive a URL instead of a key. This
# happens during a partial migration, or when the user wrote op://
# references straight into .env rather than the secrets.onepassword
# config block. For every non-op:// value the original
# .env-takes-precedence behaviour is preserved unchanged.
if raw.startswith("op://") and scoped_value:
return scoped_value
return raw or scoped_value
val = env_file.get(key) or os.environ.get(key) or ""
return val.strip()
# Honour user suppression — `hermes auth remove <provider> <N>` for an
# env-seeded credential marks the env:<VAR> source as suppressed so it
@@ -2409,6 +2040,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
if _is_source_suppressed(provider, source):
continue
active_sources.add(source)
auth_type = AUTH_TYPE_OAUTH if provider == "anthropic" and not token.startswith("sk-ant-api") else AUTH_TYPE_API_KEY
base_url = env_url or pconfig.inference_base_url
if provider == "kimi-coding":
base_url = _resolve_kimi_base_url(token, pconfig.inference_base_url, env_url)
@@ -2423,39 +2055,25 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
env_var=env_var,
token=token,
base_url=base_url,
auth_type=auth_type,
),
)
return changed, active_sources
def _prune_stale_seeded_entries(
entries: List[PooledCredential],
active_sources: Set[str],
*,
prune_env_sources: bool = True,
) -> bool:
def _is_prunable(entry: PooledCredential) -> bool:
# ``env:*`` entries are persisted references that get re-hydrated from
# the environment on every load. A process that merely lacks the env
# var this call must NOT delete the on-disk entry for every other
# process — that destructive read is the bug behind #9331. Only prune
# an env source when ``prune_env_sources`` is explicitly requested
# (e.g. an `hermes auth` command that confirmed the source is gone).
if entry.source.startswith("env:"):
return prune_env_sources
# File-backed singletons (device-code OAuth, claude_code) and Hermes
# PKCE should disappear from the pool when their backing file is gone.
return (
is_borrowed_credential_source(entry.source, entry.provider)
or entry.source == "hermes_pkce"
)
def _prune_stale_seeded_entries(entries: List[PooledCredential], active_sources: Set[str]) -> bool:
retained = [
entry
for entry in entries
if _is_manual_source(entry.source)
or entry.source in active_sources
or not _is_prunable(entry)
or not (
is_borrowed_credential_source(entry.source, entry.provider)
# Hermes PKCE is Hermes-owned/persistable while present, but it is
# still a file-backed singleton and should disappear from the pool
# when the backing OAuth file is gone.
or entry.source == "hermes_pkce"
)
]
if len(retained) == len(entries):
return False
@@ -2539,64 +2157,28 @@ def _seed_custom_pool(pool_key: str, entries: List[PooledCredential]) -> Tuple[b
def load_pool(provider: str) -> CredentialPool:
provider = (provider or "").strip().lower()
raw_entries = read_credential_pool(provider)
disk_ids = {
entry.get("id")
for entry in raw_entries
if isinstance(entry, dict) and entry.get("id")
}
raw_needs_sanitization = any(
isinstance(payload, dict)
and sanitize_borrowed_credential_payload(payload, provider) != payload
for payload in raw_entries
)
entries = [PooledCredential.from_dict(provider, payload) for payload in raw_entries]
raw_needs_auth_normalization = any(
isinstance(payload, dict)
and _normalize_pool_auth_type(
provider,
payload.get("access_token"),
payload.get("auth_type", AUTH_TYPE_API_KEY),
) != payload.get("auth_type", AUTH_TYPE_API_KEY)
for payload in raw_entries
)
if raw_needs_auth_normalization:
# A profile may be reading this provider from the global-root fallback.
# Keep that fallback read-only: only the store that owns these rows may
# rewrite them. Loading the default/root profile will heal global rows.
active_pool = _load_auth_store().get("credential_pool")
active_entries = active_pool.get(provider) if isinstance(active_pool, dict) else None
raw_needs_auth_normalization = bool(active_entries)
if provider.startswith(CUSTOM_POOL_PREFIX):
# Custom endpoint pool — seed from custom_providers config and model config
custom_changed, custom_sources = _seed_custom_pool(provider, entries)
changed = raw_needs_sanitization or raw_needs_auth_normalization or custom_changed
changed = raw_needs_sanitization or custom_changed
changed |= _prune_stale_seeded_entries(entries, custom_sources)
else:
singleton_changed, singleton_sources = _seed_from_singletons(provider, entries)
env_changed, env_sources = _seed_from_env(provider, entries)
changed = (
raw_needs_sanitization
or raw_needs_auth_normalization
or singleton_changed
or env_changed
)
# ``load_pool()`` is a non-destructive read for env-seeded entries: a
# process missing a provider env var must not delete the persisted
# pool entry for every other process (#9331). File-backed singletons
# still prune when their backing file is gone.
changed |= _prune_stale_seeded_entries(
entries,
singleton_sources | env_sources,
prune_env_sources=False,
)
changed = raw_needs_sanitization or singleton_changed or env_changed
changed |= _prune_stale_seeded_entries(entries, singleton_sources | env_sources)
changed |= _normalize_pool_priorities(provider, entries)
if changed:
new_ids = {entry.id for entry in entries}
write_credential_pool(
provider,
[entry.to_dict() for entry in sorted(entries, key=lambda item: item.priority)],
removed_ids=disk_ids - new_ids,
)
return CredentialPool(provider, entries)
+8 -3
View File
@@ -265,7 +265,7 @@ def _remove_minimax_oauth(provider: str, removed) -> RemovalResult:
return result
def _remove_xai_oauth_device_code(provider: str, removed) -> RemovalResult:
def _remove_xai_oauth_loopback_pkce(provider: str, removed) -> RemovalResult:
"""xAI OAuth tokens live in auth.json providers.xai-oauth — clear them.
Without this step, ``hermes auth remove xai-oauth <N>`` silently undoes
@@ -275,6 +275,11 @@ def _remove_xai_oauth_device_code(provider: str, removed) -> RemovalResult:
entry from the still-present singleton credentials reappear with no
user feedback. Clearing the singleton in step with the suppression set
by the central dispatcher makes the removal stick.
Belt-and-braces against the manual entry path: ``hermes auth add
xai-oauth`` produces a ``manual:xai_pkce`` entry whose removal step
falls through to "unregistered → nothing to clean up" (correct
manual entries are pool-only).
"""
result = RemovalResult()
if _clear_auth_store_provider(provider):
@@ -418,8 +423,8 @@ def _register_all_sources() -> None:
description="auth.json providers.openai-codex + ~/.codex/auth.json",
))
register(RemovalStep(
provider="xai-oauth", source_id="device_code",
remove_fn=_remove_xai_oauth_device_code,
provider="xai-oauth", source_id="loopback_pkce",
remove_fn=_remove_xai_oauth_loopback_pkce,
description="auth.json providers.xai-oauth",
))
register(RemovalStep(
+1 -11
View File
@@ -286,16 +286,6 @@ def evaluate_credits_notices(
for band in CREDITS_USAGE_BANDS: # ascending → last match wins = highest
if uf >= band[0]:
current_band = band
# Top-up suppression: when the account holds purchased (top-up) credits,
# the subscription-cap gauge is the wrong denominator — warning "90% used"
# at a user sitting on $50 of top-up is noise (and it previously stuck
# PERMANENTLY alongside grant_spent at >=100%). Suppress the usage band
# entirely; the cap-reached case is covered by the grant_spent info notice
# below, which already names the remaining top-up balance. A top-up landing
# mid-session flips current_band → None and the clear path below removes
# any showing band line.
if state.purchased_micros > 0:
current_band = None
grant_cond = (
state.denominator_kind == "subscription_cap"
and uf is not None
@@ -355,7 +345,7 @@ def evaluate_credits_notices(
if show_depleted and "credits.depleted" not in active:
to_show.append(
AgentNotice(
text="✕ Credit access paused · run /topup to top up",
text="✕ Credit access paused · run /usage for balance",
level="error",
kind=CREDITS_NOTICE_KIND,
key="credits.depleted",
+10 -191
View File
@@ -45,37 +45,18 @@ def _strip_aux_credential(value: Any) -> Optional[str]:
class _ReviewRuntimeBinding(NamedTuple):
"""Provider/model for the curator review fork plus per-slot overrides."""
"""Provider/model for the curator review fork plus optional per-slot overrides."""
provider: str
model: str
explicit_api_key: Optional[str]
explicit_base_url: Optional[str]
request_overrides: Dict[str, Any]
def _merge_request_overrides(
runtime_overrides: Any,
slot_extra_body: Any,
) -> Dict[str, Any]:
"""Merge resolver metadata with task-local request body fields."""
merged = dict(runtime_overrides or {})
if isinstance(slot_extra_body, dict) and slot_extra_body:
extra_body = dict(merged.get("extra_body") or {})
extra_body.update(slot_extra_body)
merged["extra_body"] = extra_body
return merged
DEFAULT_INTERVAL_HOURS = 24 * 7 # 7 days
DEFAULT_MIN_IDLE_HOURS = 2
DEFAULT_STALE_AFTER_DAYS = 30
DEFAULT_ARCHIVE_AFTER_DAYS = 90
# Consolidation (the LLM umbrella-building fork) is OFF by default. The
# deterministic inactivity prune (apply_automatic_transitions) still runs
# whenever the curator is enabled; only the opinionated, aux-model-cost
# consolidation pass is opt-in.
DEFAULT_CONSOLIDATE = False
# ---------------------------------------------------------------------------
@@ -201,22 +182,6 @@ def get_prune_builtins() -> bool:
return bool(cfg.get("prune_builtins", True))
def get_consolidate() -> bool:
"""Whether the curator runs its LLM consolidation (umbrella-building) pass.
OFF by default. When off, a curator run does ONLY the deterministic
inactivity prune (mark stale / archive long-unused skills) and skips the
forked aux-model review entirely no consolidation, no umbrella-building,
no aux-model cost. Set ``curator.consolidate: true`` to opt back into the
LLM pass that merges overlapping skills into class-level umbrellas.
The explicit ``hermes curator run --consolidate`` flag overrides this for
a single invocation regardless of the config value.
"""
cfg = _load_config()
return bool(cfg.get("consolidate", DEFAULT_CONSOLIDATE))
# ---------------------------------------------------------------------------
# Idle / interval check
# ---------------------------------------------------------------------------
@@ -287,21 +252,6 @@ def should_run_now(now: Optional[datetime] = None) -> bool:
# Automatic state transitions (pure function, no LLM)
# ---------------------------------------------------------------------------
def _cron_referenced_skills() -> Set[str]:
"""Skill names referenced by any cron job (incl. paused/disabled).
Best-effort: a cron-module import error or corrupt jobs store must never
break the curator, so any failure yields an empty set (no protection,
but no crash).
"""
try:
from cron.jobs import referenced_skill_names as _refs
return _refs()
except Exception as e:
logger.debug("Curator could not read cron skill references: %s", e, exc_info=True)
return set()
def apply_automatic_transitions(now: Optional[datetime] = None) -> Dict[str, int]:
"""Walk every curator-managed skill and move active/stale/archived based on
the latest real activity timestamp. Pinned skills are never touched.
@@ -321,8 +271,6 @@ def apply_automatic_transitions(now: Optional[datetime] = None) -> Dict[str, int
stale_cutoff = now - timedelta(days=get_stale_after_days())
archive_cutoff = now - timedelta(days=get_archive_after_days())
cron_referenced = _cron_referenced_skills()
counts = {"marked_stale": 0, "archived": 0, "reactivated": 0, "checked": 0, "seeded": 0}
for row in _u.agent_created_report():
@@ -331,15 +279,6 @@ def apply_automatic_transitions(now: Optional[datetime] = None) -> Dict[str, int
if row.get("pinned"):
continue
# A skill referenced by any cron job (incl. paused/disabled) is in
# use by definition — resuming or the next fire must find it. The
# scheduler only bumps usage when a job actually fires, so jobs that
# fire less often than archive_after_days, paused jobs, and far-future
# one-shots would otherwise have their skills aged out from under
# them. Treat referenced skills like pinned: never auto-transition.
if name in cron_referenced:
continue
# First sight of a curation-eligible skill with no persisted record
# (e.g. a newly-eligible built-in): anchor its clock to now and defer.
if not row.get("_persisted", True):
@@ -356,18 +295,6 @@ def apply_automatic_transitions(now: Optional[datetime] = None) -> Dict[str, int
current = row.get("state", _u.STATE_ACTIVE)
# Never-used skills (use_count == 0) get a grace floor: don't archive
# one until it is at least stale_after_days old. A use=0 skill is
# absence of evidence, not evidence of staleness — a skill created
# recently may simply not have had its trigger come up yet.
never_used = int(row.get("use_count", 0) or 0) == 0
if never_used and anchor > stale_cutoff:
# Younger than the stale window — leave it alone entirely.
if current == _u.STATE_STALE:
_u.set_state(name, _u.STATE_ACTIVE)
counts["reactivated"] += 1
continue
if anchor <= archive_cutoff and current != _u.STATE_ARCHIVED:
ok, _msg = _u.archive_skill(name)
if ok:
@@ -429,10 +356,8 @@ CURATOR_REVIEW_PROMPT = (
"bodies + `references/`, `templates/`, and `scripts/` subfiles for "
"session-specific detail — not one-session-one-skill micro-entries.\n\n"
"Hard rules — do not violate:\n"
"1. DO NOT touch bundled, hub-installed, or external-dir skills "
"(`skills.external_dirs`). The candidate list below is already filtered "
"to local curator-managed skills only; external skills are externally "
"owned and read-only to this background curator.\n"
"1. DO NOT touch bundled or hub-installed skills. The candidate list "
"below is already filtered to agent-created skills only.\n"
"2. DO NOT delete any skill. Archiving (moving the skill's directory "
"into ~/.hermes/skills/.archive/) is the maximum destructive action. "
"Archives are recoverable; deletion is not.\n"
@@ -442,19 +367,10 @@ CURATOR_REVIEW_PROMPT = (
"back load-bearing UX (slash-command entry points referenced in docs and "
"tips) and are filtered out of the candidate list below — never resurrect "
"one as an archive or absorb target.\n"
"3c. DO NOT archive or prune any skill marked `cron=yes` in the candidate "
"list. A cron job depends on it and will fail to load it on its next "
"run. You MAY still consolidate it into an umbrella — but only because "
"the curator rewrites cron job skill references to follow consolidations; "
"never simply prune it.\n"
"4. DO NOT use usage counters as a reason to skip consolidation. The "
"counters are new and often mostly zero. Judge overlap on CONTENT, "
"not on use_count. 'use=0' is not evidence a skill is valuable; it's "
"absence of evidence either way. Corollary: 'use=0' is ALSO not a "
"reason to PRUNE a skill. Never archive a never-used skill (use=0) "
"unless it is at least 30 days old (check last_activity / created date) "
"AND its content is genuinely obsolete or fully absorbed elsewhere — a "
"recently-created skill simply may not have had its trigger come up yet.\n"
"absence of evidence either way.\n"
"5. DO NOT reject consolidation on the grounds that 'each skill has "
"a distinct trigger'. Pairwise distinctness is the wrong bar. The "
"right bar is: 'would a human maintainer write this as N separate "
@@ -532,9 +448,8 @@ CURATOR_REVIEW_PROMPT = (
"skill, or `absorbed_into=\"\"` when you're truly pruning with no "
"forwarding target. This drives cron-job skill-reference migration — "
"guessing from your YAML summary after the fact is fragile.\n"
" - terminal — move LOCAL candidate content into "
"a support subfile when package integrity requires it; never mv, cp, rm, "
"patch, or rewrite bundled, hub-installed, or external-dir skills\n\n"
" - terminal — mv a sibling into the archive "
"OR move its content into a support subfile\n\n"
"'keep' is a legitimate decision ONLY when the skill is already a "
"class-level umbrella and none of the proposed merges would improve "
"discoverability. 'This is narrow but distinct from its siblings' "
@@ -1474,14 +1389,12 @@ def _render_candidate_list() -> str:
rows = skill_usage.agent_created_report()
if not rows:
return "No agent-created skills to review."
cron_referenced = _cron_referenced_skills()
lines = [f"Agent-created skills ({len(rows)}):\n"]
for r in rows:
lines.append(
f"- {r['name']} "
f"state={r['state']} "
f"pinned={'yes' if r.get('pinned') else 'no'} "
f"cron={'yes' if r['name'] in cron_referenced else 'no'} "
f"activity={r.get('activity_count', 0)} "
f"use={r.get('use_count', 0)} "
f"view={r.get('view_count', 0)} "
@@ -1495,38 +1408,25 @@ def run_curator_review(
on_summary: Optional[Callable[[str], None]] = None,
synchronous: bool = False,
dry_run: bool = False,
consolidate: Optional[bool] = None,
) -> Dict[str, Any]:
"""Execute a single curator review pass.
Steps:
1. Apply automatic state transitions (pure, no LLM).
2. If consolidation is enabled AND there are agent-created skills, spawn
a forked AIAgent that runs the LLM review prompt against the current
candidate list.
2. If there are agent-created skills, spawn a forked AIAgent that runs
the LLM review prompt against the current candidate list.
3. Update .curator_state with last_run_at and a one-line summary.
4. Invoke *on_summary* with a user-visible description.
If *synchronous* is True, the LLM review runs in the calling thread; the
default is to spawn a daemon thread so the caller returns immediately.
*consolidate* gates the LLM umbrella-building pass. ``None`` (the default)
reads ``curator.consolidate`` from config (OFF by default). Passing
``True``/``False`` overrides the config for this invocation used by the
``hermes curator run --consolidate`` flag. When consolidation is off, only
the deterministic inactivity prune runs and the forked aux-model review is
skipped entirely (no aux-model cost).
If *dry_run* is True, the automatic stale/archive transitions are SKIPPED
and the LLM review pass is instructed to produce a report only no
skill_manage mutations, no terminal archive moves. The REPORT.md still
gets written and ``state.last_report_path`` still records it so users
can read what the curator WOULD have done. A dry-run also honors
*consolidate*: when consolidation is off, the preview only reports the
deterministic prune candidates.
can read what the curator WOULD have done.
"""
if consolidate is None:
consolidate = get_consolidate()
start = datetime.now(timezone.utc)
if dry_run:
# Count candidates without mutating state.
@@ -1589,53 +1489,6 @@ def run_curator_review(
before_report = []
before_names = {r.get("name") for r in before_report if isinstance(r, dict)}
# Consolidation gate. When off (the default), the curator does ONLY the
# deterministic inactivity prune above — no forked aux-model review, no
# umbrella-building, no aux-model cost. Record the run, write a report
# reflecting the prune-only outcome, and return without spawning a fork.
if not consolidate:
final_summary = (
f"{prefix}{auto_summary}; llm: skipped (consolidation off)"
)
llm_meta = {
"final": "",
"summary": "skipped (consolidation off)",
"model": "",
"provider": "",
"tool_calls": [],
"error": None,
}
elapsed = (datetime.now(timezone.utc) - start).total_seconds()
state2 = load_state()
state2["last_run_duration_seconds"] = elapsed
state2["last_run_summary"] = final_summary
try:
after_report = skill_usage.agent_created_report()
except Exception:
after_report = []
try:
report_path = _write_run_report(
started_at=start,
elapsed_seconds=elapsed,
auto_counts=counts,
auto_summary=auto_summary,
before_report=before_report,
before_names=before_names,
after_report=after_report,
llm_meta=llm_meta,
)
if report_path is not None:
state2["last_report_path"] = str(report_path)
except Exception as e:
logger.debug("Curator report write failed: %s", e, exc_info=True)
save_state(state2)
if on_summary:
try:
on_summary(f"curator: {final_summary}")
except Exception:
pass
return
llm_meta: Dict[str, Any] = {}
try:
candidate_list = _render_candidate_list()
@@ -1778,7 +1631,6 @@ def _resolve_review_runtime(cfg: Dict[str, Any]) -> _ReviewRuntimeBinding:
_task_model,
_strip_aux_credential(_cur_task.get("api_key")),
_strip_aux_credential(_cur_task.get("base_url")),
_merge_request_overrides({}, _cur_task.get("extra_body")),
)
# 2. Legacy curator.auxiliary.{provider,model} (deprecated, pre-unification)
@@ -1796,11 +1648,10 @@ def _resolve_review_runtime(cfg: Dict[str, Any]) -> _ReviewRuntimeBinding:
str(_legacy_model),
_strip_aux_credential(_legacy.get("api_key")),
_strip_aux_credential(_legacy.get("base_url")),
_merge_request_overrides({}, _legacy.get("extra_body")),
)
# 3. Fall through to the main chat model
return _ReviewRuntimeBinding(_main_provider, _main_model, None, None, {})
return _ReviewRuntimeBinding(_main_provider, _main_model, None, None)
def _resolve_review_model(cfg: Dict[str, Any]) -> tuple[str, str]:
@@ -1866,11 +1717,6 @@ def _run_llm_review(prompt: str) -> Dict[str, Any]:
_base_url = None
_api_mode = None
_resolved_provider = None
_credential_pool = None
_request_overrides: Dict[str, Any] = {}
_max_tokens = None
_acp_command = None
_acp_args = None
_model_name = ""
try:
from hermes_cli.config import load_config
@@ -1888,16 +1734,6 @@ def _run_llm_review(prompt: str) -> Dict[str, Any]:
_base_url = _rp.get("base_url")
_api_mode = _rp.get("api_mode")
_resolved_provider = _rp.get("provider") or _provider
_credential_pool = _rp.get("credential_pool")
_request_overrides = _merge_request_overrides(
_rp.get("request_overrides"),
_binding.request_overrides.get("extra_body"),
)
_max_tokens = _rp.get("max_output_tokens")
_acp_command = _rp.get("command")
_acp_args = list(_rp.get("args") or [])
if isinstance(_rp.get("model"), str) and _rp["model"].strip():
_model_name = _rp["model"].strip()
except Exception as e:
logger.debug("Curator provider resolution failed: %s", e, exc_info=True)
@@ -1906,21 +1742,12 @@ def _run_llm_review(prompt: str) -> Dict[str, Any]:
review_agent = None
try:
_agent_kwargs: Dict[str, Any] = {}
if isinstance(_max_tokens, int):
_agent_kwargs["max_tokens"] = _max_tokens
if isinstance(_acp_command, str) and _acp_command:
_agent_kwargs["acp_command"] = _acp_command
_agent_kwargs["acp_args"] = _acp_args or []
review_agent = AIAgent(
model=_model_name,
provider=_resolved_provider,
api_key=_api_key,
base_url=_base_url,
api_mode=_api_mode,
credential_pool=_credential_pool,
request_overrides=_request_overrides,
**_agent_kwargs,
# Umbrella-building over a large skill collection is worth a
# high iteration ceiling — the pass typically takes 50-100
# API calls against hundreds of candidate skills. The
@@ -1935,14 +1762,6 @@ def _run_llm_review(prompt: str) -> Dict[str, Any]:
# Disable recursive nudges — the curator must never spawn its own review.
review_agent._memory_nudge_interval = 0
review_agent._skill_nudge_interval = 0
# Tag this fork as autonomous background curation so skill_manage's
# background-review write guard fires. Without this the fork inherits
# the default "assistant_tool" origin, is_background_review() is False,
# and the external/bundled/hub-installed skill_manage guards never
# trigger during the curation pass they exist to protect against.
# turn_context.py binds this onto the write-origin ContextVar at turn
# start (see agent/turn_context.py).
review_agent._memory_write_origin = "background_review"
# Redirect the forked agent's stdout/stderr to /dev/null while it
# runs so its tool-call chatter doesn't pollute the foreground
+12 -33
View File
@@ -46,7 +46,7 @@ import shutil
import tarfile
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple
from typing import Any, Dict, List, Optional, Tuple
from hermes_constants import get_hermes_home
from agent.skill_utils import is_excluded_skill_path
@@ -98,12 +98,7 @@ def _backup_cron_jobs_into(dest: Path) -> Dict[str, Any]:
info["reason"] = "no cron/jobs.json present"
return info
try:
# utf-8-sig: same dialect as cron/jobs.load_jobs — a UTF-8 BOM left
# by Windows editors otherwise survives decoding as U+FEFF, breaks
# json.loads below, and misreports jobs_count as 0 with a spurious
# parse warning. The BOM-less text is also what gets written to the
# backup, so a later rollback restores a loadable file.
raw = src.read_text(encoding="utf-8-sig")
raw = src.read_text(encoding="utf-8")
except OSError as e:
logger.debug("Failed to read cron/jobs.json for backup: %s", e)
info["reason"] = f"read error: {e}"
@@ -213,17 +208,13 @@ def _write_manifest(dest: Path, reason: str, archive_path: Path,
)
def snapshot_skills(reason: str = "manual", *, protect_ids: Optional[Set[str]] = None) -> Optional[Path]:
def snapshot_skills(reason: str = "manual") -> Optional[Path]:
"""Create a tar.gz snapshot of ``~/.hermes/skills/`` and prune old ones.
Returns the snapshot directory path, or ``None`` if the snapshot was
skipped (backup disabled, skills dir missing, or an IO error occurred
in which case we log at debug and return None so the curator never
aborts a pass because of a backup failure).
``protect_ids`` is forwarded to the prune step so callers can guarantee
specific snapshot ids survive even when they fall outside the keep
window (rollback passes the id it is about to restore from).
"""
if not is_enabled():
logger.debug("Curator backup disabled by config; skipping snapshot")
@@ -285,19 +276,15 @@ def snapshot_skills(reason: str = "manual", *, protect_ids: Optional[Set[str]] =
pass
return None
_prune_old(keep=get_keep(), protect=protect_ids)
_prune_old(keep=get_keep())
logger.info("Curator snapshot created: %s (%s)", snap_id, reason)
return dest
def _prune_old(keep: int, protect: Optional[Set[str]] = None) -> List[str]:
def _prune_old(keep: int) -> List[str]:
"""Delete regular snapshots beyond the newest *keep*. Returns deleted
ids. Snapshot ids in *protect* are never deleted even when they fall
outside the keep window rollback() uses this so the mandatory
pre-rollback safety snapshot can never evict the very snapshot being
restored. Staging dirs (``.rollback-staging-*``) are implementation
detail and pruned independently on every call."""
protect = protect or set()
ids. Staging dirs (``.rollback-staging-*``) are implementation detail
and pruned independently on every call."""
backups = _backups_dir()
if not backups.exists():
return []
@@ -318,8 +305,6 @@ def _prune_old(keep: int, protect: Optional[Set[str]] = None) -> List[str]:
entries.sort(key=lambda t: t[0], reverse=True)
deleted: List[str] = []
for _, path in entries[keep:]:
if path.name in protect:
continue
try:
shutil.rmtree(path)
deleted.append(path.name)
@@ -469,16 +454,16 @@ def _restore_cron_skill_links(snapshot_dir: Path) -> Dict[str, Any]:
report["attempted"] = True # we tried but there was nothing to do
return report
# Load and rewrite the live jobs under the scheduler's cross-process lock.
# Load and rewrite the live jobs under the scheduler's lock.
try:
from cron.jobs import load_jobs, save_jobs, _jobs_lock
from cron.jobs import load_jobs, save_jobs, _jobs_file_lock
except ImportError as e:
report["error"] = f"cron module unavailable: {e}"
return report
report["attempted"] = True
try:
with _jobs_lock():
with _jobs_file_lock:
live_jobs = load_jobs()
changed = False
@@ -561,7 +546,7 @@ def rollback(backup_id: Optional[str] = None) -> Tuple[bool, str, Optional[Path]
if target is None:
return (
False,
"no matching backup found"
f"no matching backup found"
+ (f" for id '{backup_id}'" if backup_id else "")
+ " (use `hermes curator rollback --list` to see available snapshots)",
None,
@@ -579,13 +564,7 @@ def rollback(backup_id: Optional[str] = None) -> Tuple[bool, str, Optional[Path]
# out before touching anything — otherwise a failed extract could leave
# the user with no skills.
try:
# Protect the target from this snapshot's prune step: at the steady
# keep limit, pruning the oldest snapshot would otherwise delete the
# very snapshot we are about to extract from.
snapshot_skills(
reason=f"pre-rollback to {target.name}",
protect_ids={target.name},
)
snapshot_skills(reason=f"pre-rollback to {target.name}")
except Exception as e:
return (False, f"pre-rollback safety snapshot failed: {e}", None)
+32 -493
View File
@@ -6,17 +6,14 @@ Used by AIAgent._execute_tool_calls for CLI feedback.
import logging
import os
import re
import sys
import threading
import time
from dataclasses import dataclass, field
from difflib import unified_diff
from pathlib import Path
from typing import Any
from utils import safe_json_loads
from agent.redact import redact_sensitive_text
from agent.tool_result_classification import file_mutation_result_landed
# ANSI escape codes for coloring tool failure indicators
@@ -27,14 +24,6 @@ logger = logging.getLogger(__name__)
_ANSI_RESET = "\033[0m"
def _display_url(value: Any) -> str:
"""Extract a display-only URL without assuming model argument types."""
if isinstance(value, dict):
value = value.get("url") or value.get("href")
return value.strip() if isinstance(value, str) else ""
# Diff colors — resolved lazily from the skin engine so they adapt
# to light/dark themes. Falls back to sensible defaults on import
# failure. We cache after first resolution for performance.
@@ -179,244 +168,6 @@ def _oneline(text: str) -> str:
return " ".join(text.split())
def _truncate_preview(text: str, max_len: int | None) -> str:
if max_len and max_len > 0 and len(text) > max_len:
if max_len <= 3:
return "." * max_len
return text[:max_len - 3] + "..."
return text
_SHELL_SILENT_HEADS = {"cd", "pushd", "popd", "export", "set", "unset", "source", ".", "true", "false", ":"}
_SHELL_PIPE_TAIL_HEADS = {"head", "tail", "wc", "sort", "uniq"}
def _shell_basename(head: str) -> str:
return head.rsplit("/", 1)[-1] if head else ""
def _split_shell_words(segment: str) -> list[str]:
words: list[str] = []
buf: list[str] = []
quote: str | None = None
for i, ch in enumerate(segment):
if quote:
buf.append(ch)
if ch == quote and (i == 0 or segment[i - 1] != "\\"):
quote = None
continue
if ch in {"'", '"'}:
quote = ch
buf.append(ch)
continue
if ch.isspace():
if buf:
words.append("".join(buf))
buf = []
continue
buf.append(ch)
if buf:
words.append("".join(buf))
return words
def _strip_shell_pipe_tail(segment: str) -> str:
words = _split_shell_words(segment)
out: list[str] = []
for i, word in enumerate(words):
if word == "|" and _shell_basename(words[i + 1] if i + 1 < len(words) else "") in _SHELL_PIPE_TAIL_HEADS:
break
out.append(word)
return " ".join(out).strip()
def _split_shell_compound(command: str) -> list[str]:
segments: list[str] = []
buf: list[str] = []
quote: str | None = None
i = 0
while i < len(command):
ch = command[i]
if quote:
buf.append(ch)
if ch == quote and (i == 0 or command[i - 1] != "\\"):
quote = None
i += 1
continue
if ch in {"'", '"'}:
quote = ch
buf.append(ch)
i += 1
continue
op_len = 2 if command.startswith("&&", i) or command.startswith("||", i) else 1 if ch in {";", "\n"} else 0
if op_len:
segment = _strip_shell_pipe_tail("".join(buf).strip())
if segment:
segments.append(segment)
buf = []
i += op_len
continue
buf.append(ch)
i += 1
segment = _strip_shell_pipe_tail("".join(buf).strip())
if segment:
segments.append(segment)
return segments
def _shell_head_word(segment: str) -> str:
words = _split_shell_words(segment)
index = 0
while index < len(words) and re.match(r"^[A-Za-z_]\w*=", words[index]):
index += 1
return _shell_basename(words[index] if index < len(words) else "")
def _clean_shell_segment(segment: str) -> str:
words = _split_shell_words(segment)
out: list[str] = []
i = 0
while i < len(words):
word = words[i]
if re.match(r"^\d*(?:>>?|<)$", word):
i += 2
continue
if re.match(r"^\d*(?:>&|<&)\d+$", word) or re.match(r"^\d*>&\d+$", word):
i += 1
continue
out.append(word)
i += 1
return " ".join(out).strip()
def _is_shell_boundary_echo(segment: str) -> bool:
words = _split_shell_words(segment)
if _shell_basename(words[0] if words else "") != "echo":
return False
rest = " ".join(words[1:])
return bool(re.search(r"-{2,}|_exit=|(?:^|\s|=)\$[?{]|PIPESTATUS", rest))
def summarize_shell_command(command: str) -> str:
"""Compact shell wrapper/plumbing for display while preserving raw command elsewhere."""
original = _oneline(command)
if not original:
return ""
segments = _split_shell_compound(original)
if len(segments) <= 1:
return _clean_shell_segment(segments[0] if segments else original) or original
core: list[str] = []
for segment in segments:
cleaned = _clean_shell_segment(segment)
head = _shell_head_word(cleaned)
if cleaned and head not in _SHELL_SILENT_HEADS and not _is_shell_boundary_echo(cleaned):
core.append(cleaned)
if not core:
return original
if len(core) == 1:
return core[0]
count = len(core) - 1
return f"{core[0]} + {count} {'command' if count == 1 else 'commands'}"
def _read_file_line_label(args: dict) -> str:
offset = args.get("offset")
limit = args.get("limit")
if not isinstance(offset, int) or offset <= 0:
return ""
if not isinstance(limit, int) or limit <= 1:
return f"L{offset}"
return f"L{offset}-{offset + limit - 1}"
def redact_browser_typed_text_for_display(value: Any, typed_text: Any) -> Any:
"""Apply secret redaction to browser_type text in display-facing payloads.
Backends sometimes echo the attempted input in error strings or fallback
metadata. When the raw typed value contains a recognizable secret (API
key, token, JWT, etc.) the redacted form differs from the raw value, so we
replace every occurrence of the raw value with its redacted form before a
browser_type result reaches logs, callbacks, the model, or chat history.
Normal typed text (search queries, addresses, form fields) matches no
secret pattern, so it passes through unchanged and stays readable.
Redaction is forced here regardless of the global ``security.redact_secrets``
preference: a typed credential leaking into chat history is a security
boundary, not mere log hygiene.
"""
if typed_text is None:
return value
needle = str(typed_text)
if needle == "":
return value
redacted = redact_sensitive_text(needle, force=True)
if redacted == needle:
# Nothing secret-looking in the typed text; leave payload untouched.
return value
if isinstance(value, str):
return value.replace(needle, redacted)
if isinstance(value, dict):
return {
key: redact_browser_typed_text_for_display(item, typed_text)
for key, item in value.items()
}
if isinstance(value, list):
return [redact_browser_typed_text_for_display(item, typed_text) for item in value]
if isinstance(value, tuple):
return tuple(redact_browser_typed_text_for_display(item, typed_text) for item in value)
return value
def redact_tool_args_for_display(tool_name: str, args: dict | None) -> dict | None:
"""Return a copy of tool args safe for logs/progress UI.
For ``browser_type`` the ``text`` argument is run through the same
secret-pattern redactor used for logs. Recognizable credentials (API
keys, tokens) are masked before the value reaches tool progress
notifications; normal typed text is left intact for debuggability.
"""
if not isinstance(args, dict):
return args
if tool_name == "browser_type" and isinstance(args.get("text"), str):
safe_args = dict(args)
safe_args["text"] = redact_sensitive_text(args["text"], force=True)
return safe_args
return args
def _delegate_task_goal_parts(tasks: Any, *, per_goal_len: int) -> tuple[int, list[str]]:
if not isinstance(tasks, list):
return 0, []
goals: list[str] = []
for task in tasks:
if not isinstance(task, dict):
continue
raw_goal = task.get("goal")
goal = "?" if raw_goal is None else _oneline(str(raw_goal))
goals.append(_truncate_preview(goal or "?", per_goal_len))
return len(goals), goals
def build_tool_preview(tool_name: str, args: dict, max_len: int | None = None) -> str | None:
"""Build a short preview of a tool call's primary argument for display.
@@ -427,49 +178,31 @@ def build_tool_preview(tool_name: str, args: dict, max_len: int | None = None) -
max_len = _tool_preview_max_len
if not args:
return None
args = redact_tool_args_for_display(tool_name, args) or args
primary_args = {
"terminal": "command", "web_search": "query", "web_extract": "urls",
"read_file": "path", "write_file": "path", "patch": "path",
"search_files": "pattern", "browser_navigate": "url",
"browser_click": "ref", "browser_type": "text",
"image_generate": "prompt", "text_to_speech": "text",
"vision_analyze": "question",
"vision_analyze": "question", "mixture_of_agents": "user_prompt",
"skill_view": "name", "skills_list": "category",
"cronjob": "action",
"execute_code": "code", "delegate_task": "goal",
"clarify": "question", "skill_manage": "name",
}
# delegate_task: show goal (single) or individual task goals (batch)
if tool_name == "delegate_task":
tasks = args.get("tasks")
if tasks and isinstance(tasks, list):
task_count, goals = _delegate_task_goal_parts(tasks, per_goal_len=40)
preview = (
f"{task_count} tasks: " + " | ".join(goals)
if goals else f"{len(tasks)} parallel tasks"
)
return _truncate_preview(preview, max_len)
goal = args.get("goal", "")
if goal is None:
return None
preview = _oneline(str(goal))
return _truncate_preview(preview, max_len) if preview else None
if tool_name == "process":
action = args.get("action", "")
sid = args.get("session_id", "")
data = args.get("data", "")
timeout_val = args.get("timeout")
parts = [str(action) if action else ""]
parts = [action]
if sid:
parts.append(str(sid)[:16])
parts.append(sid[:16])
if data:
parts.append(f'"{_oneline(str(data)[:20])}"')
parts.append(f'"{_oneline(data[:20])}"')
if timeout_val and action == "wait":
parts.append(f"{timeout_val}s")
parts = [p for p in parts if p]
return " ".join(parts) if parts else None
if tool_name == "todo":
@@ -482,23 +215,6 @@ def build_tool_preview(tool_name: str, args: dict, max_len: int | None = None) -
else:
return f"planning {len(todos_arg)} task(s)"
if tool_name in {"terminal", "execute_code"}:
key = "code" if tool_name == "execute_code" else "command"
command = args.get(key)
if command is None:
return None
preview = summarize_shell_command(str(command))
return _truncate_preview(preview, max_len) if preview else None
if tool_name == "read_file":
path = args.get("path") or args.get("file") or args.get("filepath")
if path is None:
return None
label = Path(str(path).replace("\\", "/")).name or str(path)
line_label = _read_file_line_label(args)
preview = f"{label} {line_label}".strip()
return _truncate_preview(preview, max_len) if preview else None
if tool_name == "session_search":
query = _oneline(args.get("query", ""))
return f"recall: \"{query[:25]}{'...' if len(query) > 25 else ''}\""
@@ -524,16 +240,6 @@ def build_tool_preview(tool_name: str, args: dict, max_len: int | None = None) -
msg = msg[:17] + "..."
return f"to {target}: \"{msg}\""
if tool_name == "skill_view":
name = _oneline(str(args.get("name") or ""))
file_path = args.get("file_path")
if file_path:
file_path = _oneline(str(file_path))
preview = f"{name}{file_path}" if name else file_path
else:
preview = name
return _truncate_preview(preview, max_len) if preview else None
key = primary_args.get(tool_name)
if not key:
for fallback_key in ("query", "text", "command", "path", "name", "prompt", "code", "goal"):
@@ -556,168 +262,6 @@ def build_tool_preview(tool_name: str, args: dict, max_len: int | None = None) -
return preview
# =========================================================================
# Friendly tool labels (human-phrased verbs for built-in tools)
#
# Turns "web_search <query>" into "Searching the web for <query>" — the
# ChatGPT-style "Searching…/Reading…" surface. Curated and built-in only:
# we know each core tool's semantics, so the verb is fixed, not computed.
# Custom/plugin/MCP tools have no entry and fall back to the raw preview.
# =========================================================================
# Each entry maps a built-in tool name to its present-participle verb phrase.
# A trailing space-then-preview is appended by build_tool_label() when the
# tool's argument preview is available (e.g. "Reading docs/api.md").
_TOOL_VERBS: dict[str, str] = {
"web_search": "Searching the web",
"web_extract": "Reading",
"browser_navigate": "Browsing",
"browser_click": "Clicking",
"browser_type": "Typing",
"read_file": "Reading",
"write_file": "Writing",
"patch": "Editing",
"search_files": "Searching files",
"terminal": "Running",
"execute_code": "Running code",
"image_generate": "Generating image",
"video_generate": "Generating video",
"text_to_speech": "Generating speech",
"vision_analyze": "Looking at the image",
"session_search": "Searching past sessions",
"skill_view": "Reading skill",
"skills_list": "Listing skills",
"skill_manage": "Updating skill",
"delegate_task": "Delegating",
"cronjob": "Scheduling",
"clarify": "Asking",
"memory": "Updating memory",
"todo": "Updating tasks",
}
# Verbs that read better without the raw argument preview appended.
_TOOL_VERBS_NO_PREVIEW: frozenset[str] = frozenset({
"skills_list",
"session_search",
})
# Verbs that take a "for" connector before the preview (search-style phrasing):
# "Searching the web for <query>" reads better than "Searching the web <query>".
_TOOL_VERBS_FOR_CONNECTOR: frozenset[str] = frozenset({
"web_search",
"search_files",
})
_friendly_tool_labels: bool = True
def set_friendly_tool_labels(enabled: bool) -> None:
"""Toggle friendly human-phrased tool labels (display.friendly_tool_labels)."""
global _friendly_tool_labels
_friendly_tool_labels = bool(enabled)
def get_friendly_tool_labels() -> bool:
"""Return whether friendly tool labels are enabled."""
return _friendly_tool_labels
def get_tool_verb(tool_name: str) -> str | None:
"""Return the friendly verb for a built-in tool, or None.
Returns None when friendly labels are disabled or the tool has no curated
verb (custom/plugin/MCP tools). Callers that already hold a computed
argument preview can compose ``f"{verb} {preview}"`` themselves; use
:func:`tool_verb_connector` to pick the right joiner.
"""
if not _friendly_tool_labels:
return None
return _TOOL_VERBS.get(tool_name)
def tool_verb_connector(tool_name: str) -> str:
"""Return the connector between a verb and its preview (" for " or " ")."""
return " for " if tool_name in _TOOL_VERBS_FOR_CONNECTOR else " "
def verb_drops_preview(tool_name: str) -> bool:
"""Whether the verb should render alone, without the argument preview."""
return tool_name in _TOOL_VERBS_NO_PREVIEW
def build_status_phrase(tool_name: str, args: dict | None, max_len: int = 49) -> str | None:
"""Build a short present-tense status phrase for platform status surfaces.
Used by text-rendering "typing" indicators (Slack's
``assistant.threads.setStatus`` line) to show what the agent is doing
right now: ``is running scripts/run_tests.sh`` instead of a static
``is thinking...``. The phrase is phrased to follow the bot's display
name ("Hermes is running …"), so it starts lowercase with "is".
Pass ``args=None`` for a verb-only phrase (``is running``) used when
``display.live_status`` is ``verb`` to keep argument previews out of
shared channels.
Returns None for the ``_thinking`` pseudo-tool and when friendly labels
are disabled (callers fall back to their static default). ``max_len``
caps the total phrase length; Slack truncates its status line around 50
characters, so the default stays just under that.
"""
if not tool_name or tool_name == "_thinking":
return None
if not _friendly_tool_labels:
return None
verb = _TOOL_VERBS.get(tool_name)
if verb:
head = f"is {verb[0].lower()}{verb[1:]}"
else:
# Custom / plugin / MCP tools: generic but still informative.
head = f"is using {tool_name}"
phrase = head
if args and verb and tool_name not in _TOOL_VERBS_NO_PREVIEW:
preview = build_tool_preview(tool_name, args, max_len=None)
if preview:
# Previews can contain newlines (terminal commands); keep the
# status to the first line.
preview = preview.splitlines()[0].strip()
phrase = f"{head}{tool_verb_connector(tool_name)}{preview}"
if len(phrase) > max_len - 1:
phrase = phrase[: max_len - 2].rstrip() + ""
else:
phrase = phrase + ""
return phrase
def build_tool_label(tool_name: str, args: dict, max_len: int | None = None) -> str | None:
"""Build a human-phrased status label for a tool call.
For built-in tools with a known verb (``web_search`` -> "Searching the
web for ..."), returns the verb optionally followed by the argument
preview. For everything else (custom/plugin/MCP tools, or when friendly
labels are disabled) returns the raw preview, so callers can use this as a
drop-in replacement for :func:`build_tool_preview`.
"""
if not _friendly_tool_labels:
return build_tool_preview(tool_name, args, max_len=max_len)
verb = _TOOL_VERBS.get(tool_name)
if not verb:
return build_tool_preview(tool_name, args, max_len=max_len)
if tool_name in _TOOL_VERBS_NO_PREVIEW:
return verb
preview = build_tool_preview(tool_name, args, max_len=max_len)
if not preview:
return verb
if tool_name in _TOOL_VERBS_FOR_CONNECTOR:
return f"{verb} for {preview}"
return f"{verb} {preview}"
# =========================================================================
# Inline diff previews for write actions
# =========================================================================
@@ -1314,7 +858,21 @@ def _detect_tool_failure(tool_name: str, result: str | None) -> tuple[bool, str]
return False, ""
def _get_cute_tool_message(
def _used_free_parallel(result: str | None) -> bool:
"""True when a web result came from Parallel's free Search MCP.
Only the keyless Parallel path tags its result with ``provider="parallel"``;
the paid REST path and every other provider omit it. Used to label the tool
line "Parallel search" / "Parallel fetch" exactly when the free MCP served
the call.
"""
if not isinstance(result, str) or '"provider"' not in result:
return False
data = safe_json_loads(result)
return isinstance(data, dict) and str(data.get("provider", "")).lower() == "parallel"
def get_cute_tool_message(
tool_name: str, args: dict, duration: float, result: str | None = None,
) -> str:
"""Generate a formatted tool completion line for CLI quiet mode.
@@ -1324,7 +882,6 @@ def _get_cute_tool_message(
When *result* is provided the line is checked for failure indicators.
Failed tool calls get a red prefix and an informational suffix.
"""
args = redact_tool_args_for_display(tool_name, args) or args
dur = f"{duration:.1f}s"
is_failure, failure_suffix = _detect_tool_failure(tool_name, result)
skin_prefix = get_skin_tool_prefix()
@@ -1352,19 +909,19 @@ def _get_cute_tool_message(
return f"{line}{failure_suffix}"
if tool_name == "web_search":
return _wrap(f"┊ 🔍 search {_trunc(args.get('query', ''), 42)} {dur}")
verb = "Parallel search" if _used_free_parallel(result) else "search"
return _wrap(f"┊ 🔍 {verb:<9} {_trunc(args.get('query', ''), 42)} {dur}")
if tool_name == "web_extract":
verb = "Parallel fetch" if _used_free_parallel(result) else "fetch"
urls = args.get("urls", [])
if urls:
url = _display_url(urls[0] if isinstance(urls, list) else urls)
if not url:
return _wrap(f"┊ 📄 fetch pages {dur}")
url = urls[0] if isinstance(urls, list) else str(urls)
domain = url.replace("https://", "").replace("http://", "").split("/")[0]
extra = f" +{len(urls)-1}" if isinstance(urls, list) and len(urls) > 1 else ""
return _wrap(f"┊ 📄 fetch {_trunc(domain, 35)}{extra} {dur}")
return _wrap(f"┊ 📄 fetch pages {dur}")
extra = f" +{len(urls)-1}" if len(urls) > 1 else ""
return _wrap(f"┊ 📄 {verb:<9} {_trunc(domain, 35)}{extra} {dur}")
return _wrap(f"┊ 📄 {verb:<9} pages {dur}")
if tool_name == "terminal":
return _wrap(f"┊ 💻 $ {_trunc(build_tool_preview(tool_name, args) or args.get('command', ''), 42)} {dur}")
return _wrap(f"┊ 💻 $ {_trunc(args.get('command', ''), 42)} {dur}")
if tool_name == "process":
action = args.get("action", "?")
sid = args.get("session_id", "")[:12]
@@ -1372,7 +929,7 @@ def _get_cute_tool_message(
"wait": f"wait {sid}", "kill": f"kill {sid}", "write": f"write {sid}", "submit": f"submit {sid}"}
return _wrap(f"┊ ⚙️ proc {labels.get(action, f'{action} {sid}')} {dur}")
if tool_name == "read_file":
return _wrap(f"┊ 📖 read {_trunc(build_tool_preview(tool_name, args) or args.get('path', ''), 42)} {dur}")
return _wrap(f"┊ 📖 read {_path(args.get('path', ''))} {dur}")
if tool_name == "write_file":
return _wrap(f"┊ ✍️ write {_path(args.get('path', ''))} {dur}")
if tool_name == "patch":
@@ -1451,17 +1008,15 @@ def _get_cute_tool_message(
if tool_name == "skills_list":
return _wrap(f"┊ 📚 skills list {args.get('category', 'all')} {dur}")
if tool_name == "skill_view":
label = args.get("name", "")
file_path = args.get("file_path")
if file_path:
label = f"{label}{file_path}" if label else str(file_path)
return _wrap(f"┊ 📚 skill {_trunc(label, 44)} {dur}")
return _wrap(f"┊ 📚 skill {_trunc(args.get('name', ''), 30)} {dur}")
if tool_name == "image_generate":
return _wrap(f"┊ 🎨 create {_trunc(args.get('prompt', ''), 35)} {dur}")
if tool_name == "text_to_speech":
return _wrap(f"┊ 🔊 speak {_trunc(args.get('text', ''), 30)} {dur}")
if tool_name == "vision_analyze":
return _wrap(f"┊ 👁️ vision {_trunc(args.get('question', ''), 30)} {dur}")
if tool_name == "mixture_of_agents":
return _wrap(f"┊ 🧠 reason {_trunc(args.get('user_prompt', ''), 30)} {dur}")
if tool_name == "send_message":
return _wrap(f"┊ 📨 send {args.get('target', '?')}: \"{_trunc(args.get('message', ''), 25)}\" {dur}")
if tool_name == "cronjob":
@@ -1480,29 +1035,13 @@ def _get_cute_tool_message(
if tool_name == "delegate_task":
tasks = args.get("tasks")
if tasks and isinstance(tasks, list):
task_count, goals = _delegate_task_goal_parts(tasks, per_goal_len=30)
detail = " | ".join(goals) if goals else "parallel"
count_label = task_count or len(tasks)
return _wrap(f"┊ 🔀 delegate {count_label}x: {_trunc(detail, 35)} {dur}")
return _wrap(f"┊ 🔀 delegate {len(tasks)} parallel tasks {dur}")
return _wrap(f"┊ 🔀 delegate {_trunc(args.get('goal', ''), 35)} {dur}")
preview = build_tool_preview(tool_name, args) or ""
return _wrap(f"┊ ⚡ {tool_name[:9]:9} {_trunc(preview, 35)} {dur}")
def get_cute_tool_message(
tool_name: str, args: dict, duration: float, result: str | None = None,
) -> str:
"""Render a completion label without letting cosmetic failures escape."""
try:
return _get_cute_tool_message(tool_name, args, duration, result=result)
except Exception as exc: # noqa: BLE001 — display must never abort a turn
logger.debug("Tool completion label failed for %s: %s", tool_name, exc)
safe_name = tool_name[:9] if isinstance(tool_name, str) and tool_name else "tool"
safe_duration = f"{duration:.1f}s" if isinstance(duration, (int, float)) else "done"
return f"┊ ⚡ {safe_name:9} completed {safe_duration}"
# =========================================================================
# Honcho session line (one-liner with clickable OSC 8 hyperlink)
# =========================================================================
+29 -362
View File
@@ -31,9 +31,6 @@ class FailoverReason(enum.Enum):
# Billing / quota
billing = "billing" # 402 or confirmed credit exhaustion — rotate immediately
rate_limit = "rate_limit" # 429 or quota-based throttling — backoff then rotate
# Upstream model rate-limited (aggregator 429) — fallback to a different
# model, NOT credential rotation. The user's key is healthy.
upstream_rate_limit = "upstream_rate_limit"
# Server-side
overloaded = "overloaded" # 503/529 — provider overloaded, backoff
@@ -41,11 +38,6 @@ class FailoverReason(enum.Enum):
# Transport
timeout = "timeout" # Connection/read timeout — rebuild client + retry
# TLS certificate verification failure — deterministic for the host
# (TLS-inspecting proxy, missing/expired CA bundle, self-signed cert).
# Retrying reproduces the identical handshake failure, so fail fast
# with actionable guidance instead of burning retries.
ssl_cert_verification = "ssl_cert_verification"
# Context / payload
context_overflow = "context_overflow" # Context too large — compress, not failover
@@ -115,7 +107,6 @@ _BILLING_PATTERNS = [
"exceeded your current quota",
"account is deactivated",
"plan does not include",
"out of extra usage", # Anthropic OAuth Pro/Max overage bucket depleted (HTTP 400)
"out of funds",
"run out of funds",
"balance_depleted",
@@ -123,25 +114,6 @@ _BILLING_PATTERNS = [
"not available on the free tier",
]
# xAI's explicit Grok credit-exhaustion code. Keep the HTTP 403 special case
# provider-scoped: other providers' generic billing codes historically remain
# auth failures when they arrive as 403.
_XAI_SPENDING_LIMIT_ERROR_CODE = "personal-team-blocked:spending-limit"
# Structured provider codes that mean the account cannot serve paid traffic
# until credits/subscription capacity is restored. xAI returns its explicit
# Grok spending-limit signal as HTTP 403 rather than 402.
_BILLING_ERROR_CODES = frozenset({
"insufficient_quota",
"billing_not_active",
"payment_required",
"insufficient_credits",
"no_usable_credits",
"balance_depleted",
"model_not_supported_on_free_tier",
_XAI_SPENDING_LIMIT_ERROR_CODE,
})
# Patterns that indicate rate limiting (transient, will resolve)
_RATE_LIMIT_PATTERNS = [
"rate limit",
@@ -161,31 +133,6 @@ _RATE_LIMIT_PATTERNS = [
"servicequotaexceededexception",
]
# Patterns that indicate provider-side overload, NOT a per-credential rate
# limit or billing problem. The credential is valid — the server is just
# busy — so the correct recovery is "back off and retry the same key", never
# "rotate the credential" (rotating exhausts the pool while the endpoint is
# still busy; a single-key user has nothing to rotate to). Some providers
# (notably Z.AI / Zhipu) reuse HTTP 429 for server-wide overload, so the 429
# status path matches the body against this list before falling through to
# the rate_limit default. Phrases are kept narrow and overload-flavoured so a
# normal rate-limit message ("you have been rate-limited") doesn't hit this
# bucket. (#14038, #15297)
_OVERLOADED_PATTERNS = [
"overloaded",
"temporarily overloaded",
"service is temporarily overloaded",
"service may be temporarily overloaded",
"server is overloaded",
"server overloaded",
"service overloaded",
"service is overloaded",
"upstream overloaded",
"currently overloaded",
"at capacity",
"over capacity",
]
# Usage-limit patterns that need disambiguation (could be billing OR rate_limit)
_USAGE_LIMIT_PATTERNS = [
"usage limit",
@@ -269,11 +216,6 @@ _CONTEXT_OVERFLOW_PATTERNS = [
"context window",
"prompt is too long",
"prompt exceeds max length",
# NOTE: bare "max_tokens" is load-bearing — the output-cap-retry path keys
# off it (e.g. "max_tokens: 65536 > context_window: 200000 ..."). Do NOT
# remove it. Provider empty-response advisories also contain "very low
# max_tokens", but those are intercepted by _EMPTY_PROVIDER_RESPONSE_PATTERNS
# BEFORE this list is consulted, so they never mis-route into compression.
"max_tokens",
"maximum number of tokens",
# vLLM / local inference server patterns
@@ -291,8 +233,6 @@ _CONTEXT_OVERFLOW_PATTERNS = [
# Chinese error messages (some providers return these)
"超过最大长度",
"上下文长度",
# Z.AI / Zhipu GLM pattern (English form; error code 1210)
"tokens in request more than max tokens allowed",
# AWS Bedrock Converse API error patterns
"input is too long",
"max input token",
@@ -310,15 +250,6 @@ _MODEL_NOT_FOUND_PATTERNS = [
"no such model",
"unknown model",
"unsupported model",
# OpenRouter returns 404 with this message when none of the candidate
# endpoints for the selected model support tool/function calling.
# Classifying this as model_not_found triggers fallback to a different
# model or provider that does support tools. Without this entry the
# pattern falls through to ``unknown`` with ``retryable=True``, the
# retry loop burns all attempts on the same deterministic rejection,
# and the error surfaces as a confusing "model not found" message
# instead of automatically failing over. See PR #58446.
"no endpoints found that support tool use",
]
# Request-validation patterns — the request is malformed and will fail
@@ -399,14 +330,6 @@ _CONTENT_POLICY_BLOCKED_PATTERNS = [
# echo back; the underscore form is provider-specific enough.
"content_filter",
"responsibleaipolicyviolation",
# MiniMax output-layer safety filter. The error string is surfaced
# verbatim by MiniMax SDK / OpenAI-compatible endpoints, usually in the
# form "output new_sensitive (1027)" when the model's *output* (often a
# large tool-call argument block) trips the upstream safety filter and
# the SSE stream is truncated mid-flight. ``new_sensitive`` is the
# filter name and is narrow enough that billing / format / auth error
# strings will not collide. See #32421.
"new_sensitive",
]
# Auth patterns (non-status-code signals)
@@ -431,19 +354,6 @@ _THINKING_SIG_PATTERNS = [
# the exception type is generic (e.g. RuntimeError from a local shim that
# wraps a subprocess timeout). Checked before the type-based transport
# heuristics so custom-provider "timed out" errors don't fall through to
# Provider empty-response advisories (OpenRouter / nano-gpt / similar).
# Checked before context-overflow matching because the advisory text often
# mentions "max_tokens" as a possible cause, which historically sat in
# _CONTEXT_OVERFLOW_PATTERNS and sent healthy sessions into a compression
# death spiral ending in "Cannot compress further".
_EMPTY_PROVIDER_RESPONSE_PATTERNS = [
"returned an empty response",
"empty response despite retries",
"provider returned an empty response",
"model returning empty responses",
"empty response stream",
]
# the unknown bucket and get misreported as empty responses.
_TIMEOUT_MESSAGE_PATTERNS = [
"timed out",
@@ -491,29 +401,6 @@ _SERVER_DISCONNECT_PATTERNS = [
"incomplete chunked read",
]
# SSL certificate verification failures — deterministic, NOT transient.
#
# A failed certificate chain (TLS-inspecting corporate proxy, missing
# custom CA in the trust store, expired certificate, self-signed cert)
# fails identically on every retry. Burning the retry budget before
# surfacing the error hides the actionable fix from the user for minutes.
# Inspired by Claude Code v2.1.199 (July 2026), which made SSL certificate
# errors fail immediately with a fix hint instead of retrying.
#
# Must be checked BEFORE _SSL_TRANSIENT_PATTERNS — "certificate verify
# failed" messages usually also contain "[SSL:" which would otherwise
# match the transient list and retry forever.
_SSL_CERT_VERIFY_PATTERNS = [
"certificate verify failed", # Python ssl module canonical text
"certificate_verify_failed", # OpenSSL error token
"unable to get local issuer certificate",
"self-signed certificate",
"self signed certificate",
"certificate has expired",
"hostname mismatch, certificate is not valid",
"unable to verify the first certificate", # Node/undici phrasing (MCP bridges)
]
# SSL/TLS transient failure patterns — intentionally distinct from
# _SERVER_DISCONNECT_PATTERNS above.
#
@@ -793,14 +680,6 @@ def classify_api_error(
if classified is not None:
return classified
# Local MoA config drift is deterministic: a persisted session can retain
# a preset name that was later renamed/deleted. Retrying the same lookup
# cannot recover and makes a clear config error look like an API outage.
from agent.errors import MoAPresetNotFoundError
if isinstance(error, MoAPresetNotFoundError):
return _result(FailoverReason.model_not_found, retryable=False)
# ── 3. Error code classification ────────────────────────────────
if error_code:
@@ -819,22 +698,7 @@ def classify_api_error(
if classified is not None:
return classified
# ── 5. SSL certificate verification failures → fail fast ────────
# A broken certificate chain (TLS-inspecting proxy, missing custom CA,
# expired/self-signed cert) is deterministic for the host — every retry
# reproduces the identical handshake failure. Fail immediately with
# actionable guidance instead of burning the retry budget first.
# Checked BEFORE the transient-SSL patterns: cert-verify messages also
# contain "[ssl:" which would otherwise match the transient list.
# Inspired by Claude Code v2.1.199 (July 2026).
if any(p in error_msg for p in _SSL_CERT_VERIFY_PATTERNS):
return _result(
FailoverReason.ssl_cert_verification,
retryable=False,
should_fallback=False,
)
# ── 5b. SSL/TLS transient errors → retry as timeout (not compression) ──
# ── 5. SSL/TLS transient errors → retry as timeout (not compression) ──
# SSL alerts mid-stream are transport hiccups, not server-side context
# overflow signals. Classify before the disconnect check so a large
# session doesn't incorrectly trigger context compression when the real
@@ -853,26 +717,6 @@ def classify_api_error(
is_disconnect = any(p in error_msg for p in _SERVER_DISCONNECT_PATTERNS)
if is_disconnect and not status_code:
# Reasoning-model override: a transport disconnect on a reasoning
# model is much more likely the upstream proxy idle-killing a
# long thinking stream than a true context overflow — even on
# large sessions. The default disconnect+large-session routing
# below would otherwise send the user into the compression
# branch (should_compress=True) and silently delete
# conversation history on a phantom context-length error.
# Reasoning models have multi-minute thinking phases that
# routinely exceed the cloud gateway's idle window (NVIDIA
# NIM ~120s — first-party repro at NVIDIA/NemoClaw#4846;
# OpenAI worker / Anthropic stream-idle similar). The
# per-reasoning-model stale-timeout floor in
# agent/reasoning_timeouts.py raises the stale-detector
# threshold to tolerate long thinking, so a true
# transport-layer failure here is recoverable via the retry
# path — not via context compression. Reclassify as timeout.
# (Part 1 of Fixes #52310.)
from agent.reasoning_timeouts import get_reasoning_stale_timeout_floor
if get_reasoning_stale_timeout_floor(model) is not None:
return _result(FailoverReason.timeout, retryable=True)
# Absolute token/message-count thresholds are only a proxy for smaller
# context windows. Large-context sessions can have hundreds of
# messages while still being far below their actual token budget.
@@ -887,34 +731,12 @@ def classify_api_error(
)
return _result(FailoverReason.timeout, retryable=True)
# ── 7b. Stale-call circuit breaker → failover immediately ──────
# _check_stale_giveup() in agent/chat_completion_helpers.py raises a
# RuntimeError when the provider has been unresponsive for N
# consecutive stale attempts (default 5). The error is NOT a transport
# timeout — the circuit breaker fires *before* any network call to avoid
# an indefinite stall. Without this classification the RuntimeError
# falls through to FailoverReason.unknown (retryable=True), which burns
# all max_retries against the same dead provider (each retry hitting the
# circuit breaker instantly with zero network overhead) before fallback
# is attempted. Classify as non-retryable + should_fallback so the
# retry loop activates the next fallback provider on the first hit.
if (
error_type == "RuntimeError"
and "consecutive stale attempts" in error_msg
and "aborting this call" in error_msg
):
return _result(
FailoverReason.timeout,
retryable=False,
should_fallback=True,
)
# ── 8. Transport / timeout heuristics ───────────────────────────
# ── 7. Transport / timeout heuristics ───────────────────────────
if error_type in _TRANSPORT_ERROR_TYPES or isinstance(error, (TimeoutError, ConnectionError, OSError)):
return _result(FailoverReason.timeout, retryable=True)
# ── 9. Fallback: unknown ────────────────────────────────────────
# ── 8. Fallback: unknown ────────────────────────────────────────
return _result(FailoverReason.unknown, retryable=True)
@@ -953,11 +775,7 @@ def _classify_by_status(
# OpenRouter 403 "key limit exceeded" is actually billing. Other
# providers also use 403 for account-plan or credit exhaustion.
if (
(
provider == "xai-oauth"
and error_code.lower() == _XAI_SPENDING_LIMIT_ERROR_CODE
)
or "key limit exceeded" in error_msg
"key limit exceeded" in error_msg
or "spending limit" in error_msg
or any(p in error_msg for p in _BILLING_PATTERNS)
):
@@ -1025,35 +843,7 @@ def _classify_by_status(
)
if status_code == 429:
# Already checked long_context_tier above. Some providers (notably
# Z.AI / Zhipu) reuse HTTP 429 for server-wide overload — same status
# code as a true per-credential rate limit, but the credential is
# valid and the correct recovery is "back off and retry the same key",
# NOT "rotate the credential" (which exhausts the pool while the
# endpoint is still busy, and does nothing for a single-key user).
# Disambiguate on the error body so an overload 429 takes the
# transient-overload path instead of burning the pool. (#14038)
if any(p in error_msg for p in _OVERLOADED_PATTERNS):
return result_fn(
FailoverReason.overloaded,
retryable=True,
)
# Distinguish an OpenRouter-aggregator upstream 429 (an upstream model
# like DeepSeek rate-limited OpenRouter's aggregate traffic) from an
# account-level 429 (the user's key is actually throttled). OpenRouter
# wraps upstream errors with the outer message "Provider returned
# error" — the user's key is healthy, so marking it exhausted / rotating
# is wrong and burns the key for ~24min. Fall back to a different model.
if _is_openrouter_upstream_error(body, provider):
upstream_provider = _extract_upstream_provider_name(body)
ctx = {"upstream_provider": upstream_provider} if upstream_provider else {}
return result_fn(
FailoverReason.upstream_rate_limit,
retryable=True,
should_rotate_credential=False,
should_fallback=True,
error_context=ctx,
)
# Already checked long_context_tier above; this is a normal rate limit
return result_fn(
FailoverReason.rate_limit,
retryable=True,
@@ -1089,58 +879,11 @@ def _classify_by_status(
retryable=False,
should_fallback=True,
)
# Some local inference servers (notably llama.cpp / llama-server)
# report context overflow with an HTTP 500 instead of the standard
# 400/413. The request-validation guard above already ran, so any
# remaining explicit context-overflow signal routes into the
# compression-and-retry path (mirroring _classify_400) instead of
# blind server_error retries that exhaust and drop the turn.
# Empty-response advisories that mention "max_tokens" must not enter
# that compression path.
if any(p in error_msg for p in _EMPTY_PROVIDER_RESPONSE_PATTERNS):
return result_fn(
FailoverReason.server_error,
retryable=True,
should_compress=False,
)
if any(p in error_msg for p in _CONTEXT_OVERFLOW_PATTERNS):
return result_fn(
FailoverReason.context_overflow,
retryable=True,
should_compress=True,
)
return result_fn(FailoverReason.server_error, retryable=True)
if status_code in {503, 529}:
# Same overflow-as-5xx variant (server busy / model-load OOM, or a
# Cloudflare/Tailscale hop relabeling the status). Route explicit
# overflow bodies into compression; otherwise treat as transient
# overload and retry.
if any(p in error_msg for p in _EMPTY_PROVIDER_RESPONSE_PATTERNS):
return result_fn(
FailoverReason.server_error,
retryable=True,
should_compress=False,
)
if any(p in error_msg for p in _CONTEXT_OVERFLOW_PATTERNS):
return result_fn(
FailoverReason.context_overflow,
retryable=True,
should_compress=True,
)
return result_fn(FailoverReason.overloaded, retryable=True)
# 408 Request Timeout — a transient timing failure the server itself flags
# as safe to retry (RFC 9110 §15.5.9), not a malformed request. Commonly
# emitted by reverse proxies sitting in front of self-hosted backends
# (llama.cpp / Ollama / vLLM) when a long generation outruns the proxy's
# request-read window. Route to the dedicated ``timeout`` reason (rebuild
# client + retry) instead of falling through to the generic 4xx bucket
# below, which would abort the turn on a retry-safe error the same way it
# aborts a 400 Bad Request.
if status_code == 408:
return result_fn(FailoverReason.timeout, retryable=True)
# Other 4xx — non-retryable
if 400 <= status_code < 500:
return result_fn(
@@ -1234,7 +977,6 @@ def _classify_400(
"encrypted content for item" in error_msg
and "could not be verified" in error_msg
)
or "could not decrypt the provided encrypted_content" in error_msg
):
return result_fn(
FailoverReason.invalid_encrypted_content,
@@ -1247,8 +989,8 @@ def _classify_400(
# returns:
# "Unsupported parameter: 'max_tokens' is not supported with this model.
# Use 'max_completion_tokens' instead."
# That string contains the literal substring "max_tokens", which historically
# sat in _CONTEXT_OVERFLOW_PATTERNS — so without this guard the 400 is
# That string contains the literal substring "max_tokens", which is one of
# the _CONTEXT_OVERFLOW_PATTERNS — so without this guard the 400 is
# misclassified as context_overflow, routed into the compression loop,
# re-sent with the same bad parameter, and ends in "Cannot compress
# further". These errors are deterministic (every retry gets the identical
@@ -1270,17 +1012,6 @@ def _classify_400(
should_fallback=True,
)
# Empty-provider-response advisories must not enter compression. They
# often mention "max_tokens" as a possible cause and used to match the
# bare overflow pattern, then thrash compress until "Cannot compress
# further" on an otherwise healthy session (custom endpoints / nano-gpt).
if any(p in error_msg for p in _EMPTY_PROVIDER_RESPONSE_PATTERNS):
return result_fn(
FailoverReason.server_error,
retryable=True,
should_compress=False,
)
# Context overflow from 400
if any(p in error_msg for p in _CONTEXT_OVERFLOW_PATTERNS):
return result_fn(
@@ -1368,7 +1099,15 @@ def _classify_by_error_code(
should_rotate_credential=True,
)
if code_lower in _BILLING_ERROR_CODES:
if code_lower in {
"insufficient_quota",
"billing_not_active",
"payment_required",
"insufficient_credits",
"no_usable_credits",
"balance_depleted",
"model_not_supported_on_free_tier",
}:
return result_fn(
FailoverReason.billing,
retryable=False,
@@ -1455,17 +1194,6 @@ def _classify_by_message(
should_fallback=True,
)
# Overloaded / server-busy patterns — must come BEFORE the rate_limit and
# billing checks so that a message-only "overloaded" (no 503/529 status,
# e.g. some Anthropic-compatible proxies) classifies as a transient
# overload (backoff + retry) instead of falling through to `unknown` or
# incorrectly triggering credential rotation.
if any(p in error_msg for p in _OVERLOADED_PATTERNS):
return result_fn(
FailoverReason.overloaded,
retryable=True,
)
# Billing patterns
if any(p in error_msg for p in _BILLING_PATTERNS):
return result_fn(
@@ -1484,15 +1212,6 @@ def _classify_by_message(
should_fallback=True,
)
# Empty-provider-response advisories (often mention "max_tokens") must
# retry without compression — see the matching 400-path guard above.
if any(p in error_msg for p in _EMPTY_PROVIDER_RESPONSE_PATTERNS):
return result_fn(
FailoverReason.server_error,
retryable=True,
should_compress=False,
)
# Context overflow patterns
if any(p in error_msg for p in _CONTEXT_OVERFLOW_PATTERNS):
return result_fn(
@@ -1564,25 +1283,19 @@ def _extract_status_code(error: Exception) -> Optional[int]:
def _extract_error_body(error: Exception) -> dict:
"""Extract the structured error body from an SDK exception or its cause chain."""
current = error
for _ in range(5): # Match _extract_status_code() traversal depth.
body = getattr(current, "body", None)
if isinstance(body, dict):
return body
# Some errors have .response.json()
response = getattr(current, "response", None)
if response is not None:
try:
json_body = response.json()
if isinstance(json_body, dict):
return json_body
except Exception:
pass
cause = getattr(current, "__cause__", None) or getattr(current, "__context__", None)
if cause is None or cause is current:
break
current = cause
"""Extract the structured error body from an SDK exception."""
body = getattr(error, "body", None)
if isinstance(body, dict):
return body
# Some errors have .response.json()
response = getattr(error, "response", None)
if response is not None:
try:
json_body = response.json()
if isinstance(json_body, dict):
return json_body
except Exception:
pass
return {}
@@ -1650,49 +1363,3 @@ def _extract_message(error: Exception, body: dict) -> str:
return msg.strip()[:500]
# Fallback to str(error)
return str(error)[:500]
def _is_openrouter_upstream_error(body: Any, provider: str) -> bool:
"""Detect OpenRouter's aggregator-wrapped upstream provider errors.
OpenRouter returns errors from upstream model providers (DeepSeek,
Anthropic, etc.) wrapped with the outer message "Provider returned error"
and the real error nested in ``metadata.raw``. This signal means the
user's OpenRouter key is healthy — the upstream provider is the one that
failed so credential rotation is the wrong recovery.
"""
if not isinstance(body, dict):
return False
provider_lower = (provider or "").strip().lower()
err = body.get("error")
if not isinstance(err, dict):
return False
outer_msg = str(err.get("message") or "").strip().lower()
if outer_msg != "provider returned error":
return False
# Require either the explicit OpenRouter provider OR the metadata shape
# that only OpenRouter produces (metadata.raw / metadata.provider_name).
if provider_lower == "openrouter":
return True
metadata = err.get("metadata")
if isinstance(metadata, dict) and (
"raw" in metadata or "provider_name" in metadata
):
return True
return False
def _extract_upstream_provider_name(body: Any) -> Optional[str]:
"""Pull the upstream provider name out of OpenRouter's error metadata."""
if not isinstance(body, dict):
return None
err = body.get("error")
if not isinstance(err, dict):
return None
metadata = err.get("metadata")
if not isinstance(metadata, dict):
return None
name = metadata.get("provider_name")
if isinstance(name, str) and name.strip():
return name.strip()
return None
-13
View File
@@ -1,13 +0,0 @@
class SSLConfigurationError(Exception):
"""Raised when SSL/TLS certificate bundle configuration fails."""
pass
class EmptyStreamError(RuntimeError):
"""Raised when a provider closes a stream without yielding a response."""
pass
class MoAPresetNotFoundError(ValueError):
"""Raised when a persisted MoA preset no longer exists in config."""
+37 -90
View File
@@ -46,9 +46,11 @@ def build_write_denied_paths(home: str) -> set[str]:
# Top-level Anthropic PKCE credential store remains sensitive even
# when a profile is active; default/non-profile sessions still read it.
str(hermes_root / ".anthropic_oauth.json"),
# Bitwarden Secrets Manager encrypted disk cache.
str(hermes_home / "cache" / "bws_cache.enc.json"),
str(hermes_root / "cache" / "bws_cache.enc.json"),
os.path.join(home, ".bashrc"),
os.path.join(home, ".zshrc"),
os.path.join(home, ".profile"),
os.path.join(home, ".bash_profile"),
os.path.join(home, ".zprofile"),
os.path.join(home, ".netrc"),
os.path.join(home, ".pgpass"),
os.path.join(home, ".npmrc"),
@@ -80,35 +82,34 @@ def build_write_denied_prefixes(home: str) -> list[str]:
]
def get_safe_write_roots() -> set[str]:
"""Return resolved HERMES_WRITE_SAFE_ROOT paths. Supports multiple directories
separated by ``os.pathsep`` (``:`` on Unix, ``;`` on Windows).
E.g., ``/opt/data:/var/www/html`` on Unix, ``C:\\data;D:\\www`` on Windows."""
env = os.getenv("HERMES_WRITE_SAFE_ROOT", "")
if not env:
return set()
roots: set[str] = set()
for path in env.split(os.pathsep):
if path:
try:
resolved = os.path.realpath(os.path.expanduser(path))
roots.add(resolved)
except (OSError, ValueError):
continue
return roots
def get_safe_write_root() -> Optional[str]:
"""Return the resolved HERMES_WRITE_SAFE_ROOT path, or None if unset."""
root = os.getenv("HERMES_WRITE_SAFE_ROOT", "")
if not root:
return None
try:
return os.path.realpath(os.path.expanduser(root))
except Exception:
return None
def _classify_write_denial(path: str) -> Optional[str]:
"""Return ``'credential'``, ``'safe_root'``, or ``None`` if writes are allowed."""
def is_write_denied(path: str) -> bool:
"""Return True if path is blocked by the write denylist or safe root."""
home = os.path.realpath(os.path.expanduser("~"))
resolved = os.path.realpath(os.path.expanduser(str(path)))
if resolved in build_write_denied_paths(home):
return "credential"
return True
for prefix in build_write_denied_prefixes(home):
if resolved.startswith(prefix):
return "credential"
return True
# Hermes control-plane files: block both the ACTIVE profile's view
# (hermes_home) AND the global root view. Without the root pass, a
# profile-mode session leaves <root>/auth.json + <root>/config.yaml
# writable — letting a prompt-injected write_file overwrite the global
# files that every profile inherits from (same shape as #15981).
control_file_names = ("auth.json", "config.yaml", "webhook_subscriptions.json")
mcp_tokens_dir_name = "mcp-tokens"
hermes_dirs = []
@@ -121,60 +122,30 @@ def _classify_write_denial(path: str) -> Optional[str]:
continue
for base_real in hermes_dirs:
# Session transcripts are application-owned state. Letting the agent's
# generic file tools rewrite state.db or legacy JSON snapshots can
# falsify conversation history and invalidate resume/compression state.
try:
if resolved == os.path.realpath(os.path.join(base_real, "state.db")):
return True
sessions_real = os.path.realpath(os.path.join(base_real, "sessions"))
if resolved == sessions_real or resolved.startswith(sessions_real + os.sep):
return True
except Exception:
pass
for name in control_file_names:
try:
if resolved == os.path.realpath(os.path.join(base_real, name)):
return True
except Exception:
continue
try:
mcp_real = os.path.realpath(os.path.join(base_real, mcp_tokens_dir_name))
if resolved == mcp_real or resolved.startswith(mcp_real + os.sep):
return "credential"
return True
except Exception:
pass
try:
pairing_real = os.path.realpath(os.path.join(base_real, "pairing"))
if resolved == pairing_real or resolved.startswith(pairing_real + os.sep):
return "credential"
return True
except Exception:
pass
safe_roots = get_safe_write_roots()
if safe_roots:
allowed = False
for safe_root in safe_roots:
if resolved == safe_root or resolved.startswith(safe_root + os.sep):
allowed = True
break
if not allowed:
return "safe_root"
safe_root = get_safe_write_root()
if safe_root and not (resolved == safe_root or resolved.startswith(safe_root + os.sep)):
return True
return None
def is_write_denied(path: str) -> bool:
"""Return True if path is blocked by the write denylist or safe root."""
return _classify_write_denial(path) is not None
def get_write_denied_error(path: str, *, verb: str = "Write") -> Optional[str]:
"""Return a user/model-facing error when writes to ``path`` are blocked."""
denial = _classify_write_denial(path)
if denial is None:
return None
if denial == "safe_root":
roots_display = os.pathsep.join(sorted(get_safe_write_roots()))
return (
f"{verb} denied: '{path}' is outside HERMES_WRITE_SAFE_ROOT "
f"({roots_display}). Unset the variable or add this path's directory prefix."
)
return f"{verb} denied: '{path}' is a protected system/credential file."
return False
# Common secret-bearing project-local environment file basenames.
@@ -326,7 +297,7 @@ def get_read_block_error(path: str) -> Optional[str]:
# .env contents — .env.example is the documented-shape substitute. The
# terminal tool can still ``cat .env``; this is defense-in-depth, not a
# boundary (see module docstring).
if resolved.name.lower() in _BLOCKED_PROJECT_ENV_BASENAMES:
if resolved.name in _BLOCKED_PROJECT_ENV_BASENAMES:
return (
f"Access denied: {path} is a secret-bearing environment file "
"and cannot be read to prevent credential leakage. "
@@ -337,30 +308,6 @@ def get_read_block_error(path: str) -> Optional[str]:
return None
def raise_if_read_blocked(path: str) -> None:
"""Raise ``ValueError`` if ``path`` is a denied Hermes read (see
:func:`get_read_block_error`), else return.
Shared chokepoint for provider input-loading sites that read a local
file the model/tool supplied (e.g. image-gen ``image_url`` /
``reference_image_urls`` paths). Centralizes the guard so every provider
enforces the same read boundary with identical semantics instead of each
open-coding the try/except block (#57698).
Best-effort by design: if ``agent.file_safety`` machinery is somehow
unavailable at the call site the guard no-ops rather than breaking local
image loading consistent with the defense-in-depth (not security
boundary) framing of the denylist itself. The blocking ``ValueError`` from
a real hit still propagates; only unexpected internal errors are swallowed.
"""
try:
blocked = get_read_block_error(path)
except Exception: # noqa: BLE001 - guard must never break local-file loading
return
if blocked:
raise ValueError(blocked)
# ---------------------------------------------------------------------------
# Cross-profile write guard (#TBD)
#
+909
View File
@@ -0,0 +1,909 @@
"""OpenAI-compatible facade that talks to Google's Cloud Code Assist backend.
This adapter lets Hermes use the ``google-gemini-cli`` provider as if it were
a standard OpenAI-shaped chat completion endpoint, while the underlying HTTP
traffic goes to ``cloudcode-pa.googleapis.com/v1internal:{generateContent,
streamGenerateContent}`` with a Bearer access token obtained via OAuth PKCE.
Architecture
------------
- ``GeminiCloudCodeClient`` exposes ``.chat.completions.create(**kwargs)``
mirroring the subset of the OpenAI SDK that ``run_agent.py`` uses.
- Incoming OpenAI ``messages[]`` / ``tools[]`` / ``tool_choice`` are translated
to Gemini's native ``contents[]`` / ``tools[].functionDeclarations`` /
``toolConfig`` / ``systemInstruction`` shape.
- The request body is wrapped ``{project, model, user_prompt_id, request}``
per Code Assist API expectations.
- Responses (``candidates[].content.parts[]``) are converted back to
OpenAI ``choices[0].message`` shape with ``content`` + ``tool_calls``.
- Streaming uses SSE (``?alt=sse``) and yields OpenAI-shaped delta chunks.
Attribution
-----------
Translation semantics follow jenslys/opencode-gemini-auth (MIT) and the public
Gemini API docs. Request envelope shape
(``{project, model, user_prompt_id, request}``) is documented nowhere; it is
reverse-engineered from the opencode-gemini-auth and clawdbot implementations.
"""
from __future__ import annotations
import json
import logging
import time
import uuid
from types import SimpleNamespace
from typing import Any, Dict, Iterator, List, Optional
import httpx
from agent import google_oauth
from agent.gemini_schema import sanitize_gemini_tool_parameters
from agent.google_code_assist import (
CODE_ASSIST_ENDPOINT,
CodeAssistError,
ProjectContext,
resolve_project_context,
)
logger = logging.getLogger(__name__)
# =============================================================================
# Request translation: OpenAI → Gemini
# =============================================================================
_ROLE_MAP_OPENAI_TO_GEMINI = {
"user": "user",
"assistant": "model",
"system": "user", # handled separately via systemInstruction
"tool": "user", # functionResponse is wrapped in a user-role turn
"function": "user",
}
def _coerce_content_to_text(content: Any) -> str:
"""OpenAI content may be str or a list of parts; reduce to plain text."""
if content is None:
return ""
if isinstance(content, str):
return content
if isinstance(content, list):
pieces: List[str] = []
for p in content:
if isinstance(p, str):
pieces.append(p)
elif isinstance(p, dict):
if p.get("type") == "text" and isinstance(p.get("text"), str):
pieces.append(p["text"])
# Multimodal (image_url, etc.) — stub for now; log and skip
elif p.get("type") in {"image_url", "input_audio"}:
logger.debug("Dropping multimodal part (not yet supported): %s", p.get("type"))
return "\n".join(pieces)
return str(content)
def _translate_tool_call_to_gemini(tool_call: Dict[str, Any]) -> Dict[str, Any]:
"""OpenAI tool_call -> Gemini functionCall part."""
fn = tool_call.get("function") or {}
args_raw = fn.get("arguments", "")
try:
args = json.loads(args_raw) if isinstance(args_raw, str) and args_raw else {}
except json.JSONDecodeError:
args = {"_raw": args_raw}
if not isinstance(args, dict):
args = {"_value": args}
return {
"functionCall": {
"name": fn.get("name") or "",
"args": args,
},
# Sentinel signature — matches opencode-gemini-auth's approach.
# Without this, Code Assist rejects function calls that originated
# outside its own chain.
"thoughtSignature": "skip_thought_signature_validator",
}
def _translate_tool_result_to_gemini(message: Dict[str, Any]) -> Dict[str, Any]:
"""OpenAI tool-role message -> Gemini functionResponse part.
The function name isn't in the OpenAI tool message directly; it must be
passed via the assistant message that issued the call. For simplicity we
look up ``name`` on the message (OpenAI SDK copies it there) or on the
``tool_call_id`` cross-reference.
"""
name = str(message.get("name") or message.get("tool_call_id") or "tool")
content = _coerce_content_to_text(message.get("content"))
# Gemini expects the response as a dict under `response`. We wrap plain
# text in {"output": "..."}.
try:
parsed = json.loads(content) if content.strip().startswith(("{", "[")) else None
except json.JSONDecodeError:
parsed = None
response = parsed if isinstance(parsed, dict) else {"output": content}
return {
"functionResponse": {
"name": name,
"response": response,
},
}
def _build_gemini_contents(
messages: List[Dict[str, Any]],
) -> tuple[List[Dict[str, Any]], Optional[Dict[str, Any]]]:
"""Convert OpenAI messages[] to Gemini contents[] + systemInstruction."""
system_text_parts: List[str] = []
contents: List[Dict[str, Any]] = []
for msg in messages:
if not isinstance(msg, dict):
continue
role = str(msg.get("role") or "user")
if role == "system":
system_text_parts.append(_coerce_content_to_text(msg.get("content")))
continue
# Tool result message — emit a user-role turn with functionResponse
if role == "tool" or role == "function":
contents.append({
"role": "user",
"parts": [_translate_tool_result_to_gemini(msg)],
})
continue
gemini_role = _ROLE_MAP_OPENAI_TO_GEMINI.get(role, "user")
parts: List[Dict[str, Any]] = []
text = _coerce_content_to_text(msg.get("content"))
if text:
parts.append({"text": text})
# Assistant messages can carry tool_calls
tool_calls = msg.get("tool_calls") or []
if isinstance(tool_calls, list):
for tc in tool_calls:
if isinstance(tc, dict):
parts.append(_translate_tool_call_to_gemini(tc))
if not parts:
# Gemini rejects empty parts; skip the turn entirely
continue
contents.append({"role": gemini_role, "parts": parts})
system_instruction: Optional[Dict[str, Any]] = None
joined_system = "\n".join(p for p in system_text_parts if p).strip()
if joined_system:
system_instruction = {
"role": "system",
"parts": [{"text": joined_system}],
}
return contents, system_instruction
def _translate_tools_to_gemini(tools: Any) -> List[Dict[str, Any]]:
"""OpenAI tools[] -> Gemini tools[].functionDeclarations[]."""
if not isinstance(tools, list) or not tools:
return []
declarations: List[Dict[str, Any]] = []
for t in tools:
if not isinstance(t, dict):
continue
fn = t.get("function") or {}
if not isinstance(fn, dict):
continue
name = fn.get("name")
if not name:
continue
decl = {"name": str(name)}
if fn.get("description"):
decl["description"] = str(fn["description"])
params = fn.get("parameters")
if isinstance(params, dict):
decl["parameters"] = sanitize_gemini_tool_parameters(params)
declarations.append(decl)
if not declarations:
return []
return [{"functionDeclarations": declarations}]
def _translate_tool_choice_to_gemini(tool_choice: Any) -> Optional[Dict[str, Any]]:
"""OpenAI tool_choice -> Gemini toolConfig.functionCallingConfig."""
if tool_choice is None:
return None
if isinstance(tool_choice, str):
if tool_choice == "auto":
return {"functionCallingConfig": {"mode": "AUTO"}}
if tool_choice == "required":
return {"functionCallingConfig": {"mode": "ANY"}}
if tool_choice == "none":
return {"functionCallingConfig": {"mode": "NONE"}}
if isinstance(tool_choice, dict):
fn = tool_choice.get("function") or {}
name = fn.get("name")
if name:
return {
"functionCallingConfig": {
"mode": "ANY",
"allowedFunctionNames": [str(name)],
},
}
return None
def _normalize_thinking_config(config: Any) -> Optional[Dict[str, Any]]:
"""Accept thinkingBudget / thinkingLevel / includeThoughts (+ snake_case)."""
if not isinstance(config, dict) or not config:
return None
budget = config.get("thinkingBudget", config.get("thinking_budget"))
level = config.get("thinkingLevel", config.get("thinking_level"))
include = config.get("includeThoughts", config.get("include_thoughts"))
normalized: Dict[str, Any] = {}
if isinstance(budget, (int, float)):
normalized["thinkingBudget"] = int(budget)
if isinstance(level, str) and level.strip():
normalized["thinkingLevel"] = level.strip().lower()
if isinstance(include, bool):
normalized["includeThoughts"] = include
return normalized or None
def build_gemini_request(
*,
messages: List[Dict[str, Any]],
tools: Any = None,
tool_choice: Any = None,
temperature: Optional[float] = None,
max_tokens: Optional[int] = None,
top_p: Optional[float] = None,
stop: Any = None,
thinking_config: Any = None,
) -> Dict[str, Any]:
"""Build the inner Gemini request body (goes inside ``request`` wrapper)."""
contents, system_instruction = _build_gemini_contents(messages)
body: Dict[str, Any] = {"contents": contents}
if system_instruction is not None:
body["systemInstruction"] = system_instruction
gemini_tools = _translate_tools_to_gemini(tools)
if gemini_tools:
body["tools"] = gemini_tools
tool_cfg = _translate_tool_choice_to_gemini(tool_choice)
if tool_cfg is not None:
body["toolConfig"] = tool_cfg
generation_config: Dict[str, Any] = {}
if isinstance(temperature, (int, float)):
generation_config["temperature"] = float(temperature)
if isinstance(max_tokens, int) and max_tokens > 0:
generation_config["maxOutputTokens"] = max_tokens
if isinstance(top_p, (int, float)):
generation_config["topP"] = float(top_p)
if isinstance(stop, str) and stop:
generation_config["stopSequences"] = [stop]
elif isinstance(stop, list) and stop:
generation_config["stopSequences"] = [str(s) for s in stop if s]
normalized_thinking = _normalize_thinking_config(thinking_config)
if normalized_thinking:
generation_config["thinkingConfig"] = normalized_thinking
if generation_config:
body["generationConfig"] = generation_config
return body
def wrap_code_assist_request(
*,
project_id: str,
model: str,
inner_request: Dict[str, Any],
user_prompt_id: Optional[str] = None,
) -> Dict[str, Any]:
"""Wrap the inner Gemini request in the Code Assist envelope."""
return {
"project": project_id,
"model": model,
"user_prompt_id": user_prompt_id or str(uuid.uuid4()),
"request": inner_request,
}
# =============================================================================
# Response translation: Gemini → OpenAI
# =============================================================================
def _translate_gemini_response(
resp: Dict[str, Any],
model: str,
) -> SimpleNamespace:
"""Non-streaming Gemini response -> OpenAI-shaped SimpleNamespace.
Code Assist wraps the actual Gemini response inside ``response``, so we
unwrap it first if present.
"""
inner = resp.get("response") if isinstance(resp.get("response"), dict) else resp
candidates = inner.get("candidates") or []
if not isinstance(candidates, list) or not candidates:
return _empty_response(model)
cand = candidates[0]
content_obj = cand.get("content") if isinstance(cand, dict) else {}
parts = content_obj.get("parts") if isinstance(content_obj, dict) else []
text_pieces: List[str] = []
reasoning_pieces: List[str] = []
tool_calls: List[SimpleNamespace] = []
for i, part in enumerate(parts or []):
if not isinstance(part, dict):
continue
# Thought parts are model's internal reasoning — surface as reasoning,
# don't mix into content.
if part.get("thought") is True:
if isinstance(part.get("text"), str):
reasoning_pieces.append(part["text"])
continue
if isinstance(part.get("text"), str):
text_pieces.append(part["text"])
continue
fc = part.get("functionCall")
if isinstance(fc, dict) and fc.get("name"):
try:
args_str = json.dumps(fc.get("args") or {}, ensure_ascii=False)
except (TypeError, ValueError):
args_str = "{}"
tool_calls.append(SimpleNamespace(
id=f"call_{uuid.uuid4().hex[:12]}",
type="function",
index=i,
function=SimpleNamespace(name=str(fc["name"]), arguments=args_str),
))
finish_reason = "tool_calls" if tool_calls else _map_gemini_finish_reason(
str(cand.get("finishReason") or "")
)
usage_meta = inner.get("usageMetadata") or {}
usage = SimpleNamespace(
prompt_tokens=int(usage_meta.get("promptTokenCount") or 0),
completion_tokens=int(usage_meta.get("candidatesTokenCount") or 0),
total_tokens=int(usage_meta.get("totalTokenCount") or 0),
prompt_tokens_details=SimpleNamespace(
cached_tokens=int(usage_meta.get("cachedContentTokenCount") or 0),
),
)
message = SimpleNamespace(
role="assistant",
content="".join(text_pieces) if text_pieces else None,
tool_calls=tool_calls or None,
reasoning="".join(reasoning_pieces) or None,
reasoning_content="".join(reasoning_pieces) or None,
reasoning_details=None,
)
choice = SimpleNamespace(
index=0,
message=message,
finish_reason=finish_reason,
)
return SimpleNamespace(
id=f"chatcmpl-{uuid.uuid4().hex[:12]}",
object="chat.completion",
created=int(time.time()),
model=model,
choices=[choice],
usage=usage,
)
def _empty_response(model: str) -> SimpleNamespace:
message = SimpleNamespace(
role="assistant", content="", tool_calls=None,
reasoning=None, reasoning_content=None, reasoning_details=None,
)
choice = SimpleNamespace(index=0, message=message, finish_reason="stop")
usage = SimpleNamespace(
prompt_tokens=0, completion_tokens=0, total_tokens=0,
prompt_tokens_details=SimpleNamespace(cached_tokens=0),
)
return SimpleNamespace(
id=f"chatcmpl-{uuid.uuid4().hex[:12]}",
object="chat.completion",
created=int(time.time()),
model=model,
choices=[choice],
usage=usage,
)
def _map_gemini_finish_reason(reason: str) -> str:
mapping = {
"STOP": "stop",
"MAX_TOKENS": "length",
"SAFETY": "content_filter",
"RECITATION": "content_filter",
"OTHER": "stop",
}
return mapping.get(reason.upper(), "stop")
# =============================================================================
# Streaming SSE iterator
# =============================================================================
class _GeminiStreamChunk(SimpleNamespace):
"""Mimics an OpenAI ChatCompletionChunk with .choices[0].delta."""
pass
def _make_stream_chunk(
*,
model: str,
content: str = "",
tool_call_delta: Optional[Dict[str, Any]] = None,
finish_reason: Optional[str] = None,
reasoning: str = "",
) -> _GeminiStreamChunk:
delta_kwargs: Dict[str, Any] = {
"role": "assistant",
"content": None,
"tool_calls": None,
"reasoning": None,
"reasoning_content": None,
}
if content:
delta_kwargs["content"] = content
if tool_call_delta is not None:
delta_kwargs["tool_calls"] = [SimpleNamespace(
index=tool_call_delta.get("index", 0),
id=tool_call_delta.get("id") or f"call_{uuid.uuid4().hex[:12]}",
type="function",
function=SimpleNamespace(
name=tool_call_delta.get("name") or "",
arguments=tool_call_delta.get("arguments") or "",
),
)]
if reasoning:
delta_kwargs["reasoning"] = reasoning
delta_kwargs["reasoning_content"] = reasoning
delta = SimpleNamespace(**delta_kwargs)
choice = SimpleNamespace(index=0, delta=delta, finish_reason=finish_reason)
return _GeminiStreamChunk(
id=f"chatcmpl-{uuid.uuid4().hex[:12]}",
object="chat.completion.chunk",
created=int(time.time()),
model=model,
choices=[choice],
usage=None,
)
def _iter_sse_events(response: httpx.Response) -> Iterator[Dict[str, Any]]:
"""Parse Server-Sent Events from an httpx streaming response."""
buffer = ""
for chunk in response.iter_text():
if not chunk:
continue
buffer += chunk
while "\n" in buffer:
line, buffer = buffer.split("\n", 1)
line = line.rstrip("\r")
if not line:
continue
if line.startswith("data: "):
data = line[6:]
if data == "[DONE]":
return
try:
yield json.loads(data)
except json.JSONDecodeError:
logger.debug("Non-JSON SSE line: %s", data[:200])
def _translate_stream_event(
event: Dict[str, Any],
model: str,
tool_call_counter: List[int],
) -> List[_GeminiStreamChunk]:
"""Unwrap Code Assist envelope and emit OpenAI-shaped chunk(s).
``tool_call_counter`` is a single-element list used as a mutable counter
across events in the same stream. Each ``functionCall`` part gets a
fresh, unique OpenAI ``index`` keying by function name would collide
whenever the model issues parallel calls to the same tool (e.g. reading
three files in one turn).
"""
inner = event.get("response") if isinstance(event.get("response"), dict) else event
candidates = inner.get("candidates") or []
if not candidates:
return []
cand = candidates[0]
if not isinstance(cand, dict):
return []
chunks: List[_GeminiStreamChunk] = []
content = cand.get("content") or {}
parts = content.get("parts") if isinstance(content, dict) else []
for part in parts or []:
if not isinstance(part, dict):
continue
if part.get("thought") is True and isinstance(part.get("text"), str):
chunks.append(_make_stream_chunk(
model=model, reasoning=part["text"],
))
continue
if isinstance(part.get("text"), str) and part["text"]:
chunks.append(_make_stream_chunk(model=model, content=part["text"]))
fc = part.get("functionCall")
if isinstance(fc, dict) and fc.get("name"):
name = str(fc["name"])
idx = tool_call_counter[0]
tool_call_counter[0] += 1
try:
args_str = json.dumps(fc.get("args") or {}, ensure_ascii=False)
except (TypeError, ValueError):
args_str = "{}"
chunks.append(_make_stream_chunk(
model=model,
tool_call_delta={
"index": idx,
"name": name,
"arguments": args_str,
},
))
finish_reason_raw = str(cand.get("finishReason") or "")
if finish_reason_raw:
mapped = _map_gemini_finish_reason(finish_reason_raw)
if tool_call_counter[0] > 0:
mapped = "tool_calls"
chunks.append(_make_stream_chunk(model=model, finish_reason=mapped))
return chunks
# =============================================================================
# GeminiCloudCodeClient — OpenAI-compatible facade
# =============================================================================
MARKER_BASE_URL = "cloudcode-pa://google"
class _GeminiChatCompletions:
def __init__(self, client: "GeminiCloudCodeClient"):
self._client = client
def create(self, **kwargs: Any) -> Any:
return self._client._create_chat_completion(**kwargs)
class _GeminiChatNamespace:
def __init__(self, client: "GeminiCloudCodeClient"):
self.completions = _GeminiChatCompletions(client)
class GeminiCloudCodeClient:
"""Minimal OpenAI-SDK-compatible facade over Code Assist v1internal."""
def __init__(
self,
*,
api_key: Optional[str] = None,
base_url: Optional[str] = None,
default_headers: Optional[Dict[str, str]] = None,
project_id: str = "",
**_: Any,
):
# `api_key` here is a dummy — real auth is the OAuth access token
# fetched on every call via agent.google_oauth.get_valid_access_token().
# We accept the kwarg for openai.OpenAI interface parity.
self.api_key = api_key or "google-oauth"
self.base_url = base_url or MARKER_BASE_URL
self._default_headers = dict(default_headers or {})
self._configured_project_id = project_id
self._project_context: Optional[ProjectContext] = None
self._project_context_lock = False # simple single-thread guard
self.chat = _GeminiChatNamespace(self)
self.is_closed = False
self._http = httpx.Client(timeout=httpx.Timeout(connect=15.0, read=600.0, write=30.0, pool=30.0))
def close(self) -> None:
self.is_closed = True
try:
self._http.close()
except Exception:
pass
# Implement the OpenAI SDK's context-manager-ish closure check
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
def _ensure_project_context(self, access_token: str, model: str) -> ProjectContext:
"""Lazily resolve and cache the project context for this client."""
if self._project_context is not None:
return self._project_context
env_project = google_oauth.resolve_project_id_from_env()
creds = google_oauth.load_credentials()
stored_project = creds.project_id if creds else ""
# Prefer what's already baked into the creds
if stored_project:
self._project_context = ProjectContext(
project_id=stored_project,
managed_project_id=creds.managed_project_id if creds else "",
tier_id="",
source="stored",
)
return self._project_context
ctx = resolve_project_context(
access_token,
configured_project_id=self._configured_project_id,
env_project_id=env_project,
user_agent_model=model,
)
# Persist discovered project back to the creds file so the next
# session doesn't re-run the discovery.
if ctx.project_id or ctx.managed_project_id:
google_oauth.update_project_ids(
project_id=ctx.project_id,
managed_project_id=ctx.managed_project_id,
)
self._project_context = ctx
return ctx
def _create_chat_completion(
self,
*,
model: str = "gemini-2.5-flash",
messages: Optional[List[Dict[str, Any]]] = None,
stream: bool = False,
tools: Any = None,
tool_choice: Any = None,
temperature: Optional[float] = None,
max_tokens: Optional[int] = None,
top_p: Optional[float] = None,
stop: Any = None,
extra_body: Optional[Dict[str, Any]] = None,
timeout: Any = None,
**_: Any,
) -> Any:
access_token = google_oauth.get_valid_access_token()
ctx = self._ensure_project_context(access_token, model)
thinking_config = None
if isinstance(extra_body, dict):
thinking_config = extra_body.get("thinking_config") or extra_body.get("thinkingConfig")
inner = build_gemini_request(
messages=messages or [],
tools=tools,
tool_choice=tool_choice,
temperature=temperature,
max_tokens=max_tokens,
top_p=top_p,
stop=stop,
thinking_config=thinking_config,
)
wrapped = wrap_code_assist_request(
project_id=ctx.project_id,
model=model,
inner_request=inner,
)
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
"Authorization": f"Bearer {access_token}",
"User-Agent": "hermes-agent (gemini-cli-compat)",
"X-Goog-Api-Client": "gl-python/hermes",
"x-activity-request-id": str(uuid.uuid4()),
}
headers.update(self._default_headers)
if stream:
return self._stream_completion(model=model, wrapped=wrapped, headers=headers)
url = f"{CODE_ASSIST_ENDPOINT}/v1internal:generateContent"
response = self._http.post(url, json=wrapped, headers=headers)
if response.status_code != 200:
raise _gemini_http_error(response)
try:
payload = response.json()
except ValueError as exc:
raise CodeAssistError(
f"Invalid JSON from Code Assist: {exc}",
code="code_assist_invalid_json",
) from exc
return _translate_gemini_response(payload, model=model)
def _stream_completion(
self,
*,
model: str,
wrapped: Dict[str, Any],
headers: Dict[str, str],
) -> Iterator[_GeminiStreamChunk]:
"""Generator that yields OpenAI-shaped streaming chunks."""
url = f"{CODE_ASSIST_ENDPOINT}/v1internal:streamGenerateContent?alt=sse"
stream_headers = dict(headers)
stream_headers["Accept"] = "text/event-stream"
def _generator() -> Iterator[_GeminiStreamChunk]:
try:
with self._http.stream("POST", url, json=wrapped, headers=stream_headers) as response:
if response.status_code != 200:
# Materialize error body for better diagnostics
response.read()
raise _gemini_http_error(response)
tool_call_counter: List[int] = [0]
for event in _iter_sse_events(response):
for chunk in _translate_stream_event(event, model, tool_call_counter):
yield chunk
except httpx.HTTPError as exc:
raise CodeAssistError(
f"Streaming request failed: {exc}",
code="code_assist_stream_error",
) from exc
return _generator()
def _gemini_http_error(response: httpx.Response) -> CodeAssistError:
"""Translate an httpx response into a CodeAssistError with rich metadata.
Parses Google's error envelope (``{"error": {"code", "message", "status",
"details": [...]}}``) so the agent's error classifier can reason about
the failure ``status_code`` enables the rate_limit / auth classification
paths, and ``response`` lets the main loop honor ``Retry-After`` just
like it does for OpenAI SDK exceptions.
Also lifts a few recognizable Google conditions into human-readable
messages so the user sees something better than a 500-char JSON dump:
MODEL_CAPACITY_EXHAUSTED "Gemini model capacity exhausted for
<model>. This is a Google-side throttle..."
RESOURCE_EXHAUSTED w/o reason quota-style message
404 "Model <name> not found at cloudcode-pa..."
"""
status = response.status_code
# Parse the body once, surviving any weird encodings.
body_text = ""
body_json: Dict[str, Any] = {}
try:
body_text = response.text
except Exception:
body_text = ""
if body_text:
try:
parsed = json.loads(body_text)
if isinstance(parsed, dict):
body_json = parsed
except (ValueError, TypeError):
body_json = {}
# Dig into Google's error envelope. Shape is:
# {"error": {"code": 429, "message": "...", "status": "RESOURCE_EXHAUSTED",
# "details": [{"@type": ".../ErrorInfo", "reason": "MODEL_CAPACITY_EXHAUSTED",
# "metadata": {...}},
# {"@type": ".../RetryInfo", "retryDelay": "30s"}]}}
err_obj = body_json.get("error") if isinstance(body_json, dict) else None
if not isinstance(err_obj, dict):
err_obj = {}
err_status = str(err_obj.get("status") or "").strip()
err_message = str(err_obj.get("message") or "").strip()
_raw_details = err_obj.get("details")
err_details_list = _raw_details if isinstance(_raw_details, list) else []
# Extract google.rpc.ErrorInfo reason + metadata. There may be more
# than one ErrorInfo (rare), so we pick the first one with a reason.
error_reason = ""
error_metadata: Dict[str, Any] = {}
retry_delay_seconds: Optional[float] = None
for detail in err_details_list:
if not isinstance(detail, dict):
continue
type_url = str(detail.get("@type") or "")
if not error_reason and type_url.endswith("/google.rpc.ErrorInfo"):
reason = detail.get("reason")
if isinstance(reason, str) and reason:
error_reason = reason
md = detail.get("metadata")
if isinstance(md, dict):
error_metadata = md
elif retry_delay_seconds is None and type_url.endswith("/google.rpc.RetryInfo"):
# retryDelay is a google.protobuf.Duration string like "30s" or "1.5s".
delay_raw = detail.get("retryDelay")
if isinstance(delay_raw, str) and delay_raw.endswith("s"):
try:
retry_delay_seconds = float(delay_raw[:-1])
except ValueError:
pass
elif isinstance(delay_raw, (int, float)):
retry_delay_seconds = float(delay_raw)
# Fall back to the Retry-After header if the body didn't include RetryInfo.
if retry_delay_seconds is None:
try:
header_val = response.headers.get("Retry-After") or response.headers.get("retry-after")
except Exception:
header_val = None
if header_val:
try:
retry_delay_seconds = float(header_val)
except (TypeError, ValueError):
retry_delay_seconds = None
# Classify the error code. ``code_assist_rate_limited`` stays the default
# for 429s; a more specific reason tag helps downstream callers (e.g. tests,
# logs) without changing the rate_limit classification path.
code = f"code_assist_http_{status}"
if status == 401:
code = "code_assist_unauthorized"
elif status == 429:
code = "code_assist_rate_limited"
if error_reason == "MODEL_CAPACITY_EXHAUSTED":
code = "code_assist_capacity_exhausted"
# Build a human-readable message. Keep the status + a raw-body tail for
# debugging, but lead with a friendlier summary when we recognize the
# Google signal.
model_hint = ""
if isinstance(error_metadata, dict):
model_hint = str(error_metadata.get("model") or error_metadata.get("modelId") or "").strip()
if status == 429 and error_reason == "MODEL_CAPACITY_EXHAUSTED":
target = model_hint or "this Gemini model"
message = (
f"Gemini capacity exhausted for {target} (Google-side throttle, "
f"not a Hermes issue). Try a different Gemini model or set a "
f"fallback_providers entry to a non-Gemini provider."
)
if retry_delay_seconds is not None:
message += f" Google suggests retrying in {retry_delay_seconds:g}s."
elif status == 429 and err_status == "RESOURCE_EXHAUSTED":
message = (
f"Gemini quota exhausted ({err_message or 'RESOURCE_EXHAUSTED'}). "
f"Check /gquota for remaining daily requests."
)
if retry_delay_seconds is not None:
message += f" Retry suggested in {retry_delay_seconds:g}s."
elif status == 404:
# Google returns 404 when a model has been retired or renamed.
target = model_hint or (err_message or "model")
message = (
f"Code Assist 404: {target} is not available at "
f"cloudcode-pa.googleapis.com. It may have been renamed or "
f"retired. Check hermes_cli/models.py for the current list."
)
elif err_message:
# Generic fallback with the parsed message.
message = f"Code Assist HTTP {status} ({err_status or 'error'}): {err_message}"
else:
# Last-ditch fallback — raw body snippet.
message = f"Code Assist returned HTTP {status}: {body_text[:500]}"
return CodeAssistError(
message,
code=code,
status_code=status,
response=response,
retry_after=retry_delay_seconds,
details={
"status": err_status,
"reason": error_reason,
"metadata": error_metadata,
"message": err_message,
},
)
+11 -56
View File
@@ -27,18 +27,10 @@ from typing import Any, Dict, Iterator, List, Optional
import httpx
from agent.bounded_response import read_streaming_error_body
from agent.gemini_schema import sanitize_gemini_tool_parameters
logger = logging.getLogger(__name__)
try:
import hermes_cli as _hermes_cli
_HERMES_VERSION = str(_hermes_cli.__version__)
except Exception:
_HERMES_VERSION = "0.0.0"
DEFAULT_GEMINI_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
# Published max output-token ceiling shared by every current Gemini text model
@@ -49,16 +41,6 @@ DEFAULT_GEMINI_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
GEMINI_DEFAULT_MAX_OUTPUT_TOKENS = 65535
def bare_gemini_model_id(model: str) -> str:
"""Strip Gemini's own provider prefix from an aggregator-style model id."""
name = (model or "").strip()
lowered = name.lower()
for prefix in ("google/", "gemini/"):
if lowered.startswith(prefix):
return name[len(prefix):].strip() or name
return name
def is_native_gemini_base_url(base_url: str) -> bool:
"""Return True when the endpoint speaks Gemini's native REST API."""
normalized = str(base_url or "").strip().rstrip("/").lower()
@@ -106,10 +88,7 @@ def probe_gemini_tier(
url,
params={"key": key},
json=payload,
headers={
"Content-Type": "application/json",
"X-Goog-Api-Client": f"hermes-agent/{_HERMES_VERSION}",
},
headers={"Content-Type": "application/json"},
)
except Exception as exc:
logger.debug("probe_gemini_tier: network error: %s", exc)
@@ -348,26 +327,10 @@ def _build_gemini_contents(messages: List[Dict[str, Any]]) -> tuple[List[Dict[st
if parts:
contents.append({"role": gemini_role, "parts": parts})
# Gemini's generateContent requires strict user/model alternation;
# consecutive same-role contents are rejected with HTTP 400 "Please ensure
# that multiturn requests alternate between user and model". The loop above
# emits one content per source message, so parallel tool calls (N tool
# results become N user functionResponse contents), back-to-back user turns,
# or merged assistant turns would each violate that. Merge adjacent
# same-role contents by concatenating their parts. For parallel calls this
# also produces the grouped multi-functionResponse turn Gemini expects.
merged_contents: List[Dict[str, Any]] = []
for content in contents:
if merged_contents and merged_contents[-1]["role"] == content["role"]:
merged_contents[-1]["parts"].extend(content["parts"])
else:
merged_contents.append(content)
contents = merged_contents
system_instruction = None
joined_system = "\n".join(part for part in system_text_parts if part).strip()
if joined_system:
system_instruction = {"role": "system", "parts": [{"text": joined_system}]}
system_instruction = {"parts": [{"text": joined_system}]}
return contents, system_instruction
@@ -753,17 +716,14 @@ def translate_stream_event(event: Dict[str, Any], model: str, tool_call_indices:
return chunks
def gemini_http_error(
response: httpx.Response, *, body_text: Optional[str] = None
) -> GeminiAPIError:
def gemini_http_error(response: httpx.Response) -> GeminiAPIError:
status = response.status_code
body_text = ""
body_json: Dict[str, Any] = {}
if body_text is None:
try:
body_text = response.text
except Exception:
body_text = ""
body_text = body_text or ""
try:
body_text = response.text
except Exception:
body_text = ""
if body_text:
try:
parsed = json.loads(body_text)
@@ -911,11 +871,7 @@ class GeminiNativeClient:
"Content-Type": "application/json",
"Accept": "application/json",
"x-goog-api-key": self.api_key,
# Include Hermes client context following Gemini's partner
# integration guidance.
# See https://ai.google.dev/gemini-api/docs/partner-integration
"User-Agent": f"hermes-agent/{_HERMES_VERSION} (gemini-native)",
"X-Goog-Api-Client": f"hermes-agent/{_HERMES_VERSION}",
"User-Agent": "hermes-agent (gemini-native)",
}
headers.update(self._default_headers)
return headers
@@ -958,7 +914,6 @@ class GeminiNativeClient:
thinking_config=thinking_config,
)
model = bare_gemini_model_id(model)
if stream:
return self._stream_completion(model=model, request=request, timeout=timeout)
@@ -986,8 +941,8 @@ class GeminiNativeClient:
try:
with self._http.stream("POST", url, json=request, headers=stream_headers, timeout=timeout) as response:
if response.status_code != 200:
body_text = read_streaming_error_body(response)
raise gemini_http_error(response, body_text=body_text)
response.read()
raise gemini_http_error(response)
tool_call_indices: Dict[str, Dict[str, Any]] = {}
for event in _iter_sse_events(response):
for chunk in translate_stream_event(event, model, tool_call_indices):
-24
View File
@@ -87,30 +87,6 @@ def sanitize_gemini_schema(schema: Any) -> Dict[str, Any]:
if any(not isinstance(item, str) for item in enum_val):
cleaned.pop("enum", None)
# Gemini validates ``required`` strictly against the same node's
# ``properties`` — GenerateContentRequest fails with HTTP 400
# "...items.required[0]: property is not defined" when a required name
# has no matching property in that node. MCP servers routinely emit
# this shape (e.g. the GitHub remote MCP's array item schemas carry
# ``required`` without ``properties``), and one bad tool schema fails
# the ENTIRE request before any model output. Filter ``required`` to
# names that exist in this node's ``properties`` and drop it when
# nothing valid remains. The tool handler still validates required
# fields at execution time, so this only removes what Gemini couldn't
# accept anyway. (Port of Kilo-Org/kilocode#11955.)
required_val = cleaned.get("required")
if isinstance(required_val, list):
props_val = cleaned.get("properties")
prop_names = set(props_val.keys()) if isinstance(props_val, dict) else set()
valid_required = [
name for name in required_val
if isinstance(name, str) and name in prop_names
]
if not valid_required:
cleaned.pop("required", None)
elif len(valid_required) != len(required_val):
cleaned["required"] = valid_required
return cleaned
+451
View File
@@ -0,0 +1,451 @@
"""Google Code Assist API client — project discovery, onboarding, quota.
The Code Assist API powers Google's official gemini-cli. It sits at
``cloudcode-pa.googleapis.com`` and provides:
- Free tier access (generous daily quota) for personal Google accounts
- Paid tier access via GCP projects with billing / Workspace / Standard / Enterprise
This module handles the control-plane dance needed before inference:
1. ``load_code_assist()`` probe the user's account to learn what tier they're on
and whether a ``cloudaicompanionProject`` is already assigned.
2. ``onboard_user()`` if the user hasn't been onboarded yet (new account, fresh
free tier, etc.), call this with the chosen tier + project id. Supports LRO
polling for slow provisioning.
3. ``retrieve_user_quota()`` fetch the ``buckets[]`` array showing remaining
quota per model, used by the ``/gquota`` slash command.
VPC-SC handling: enterprise accounts under a VPC Service Controls perimeter
will get ``SECURITY_POLICY_VIOLATED`` on ``load_code_assist``. We catch this
and force the account to ``standard-tier`` so the call chain still succeeds.
Derived from opencode-gemini-auth (MIT) and clawdbot/extensions/google. The
request/response shapes are specific to Google's internal Code Assist API,
documented nowhere public we copy them from the reference implementations.
"""
from __future__ import annotations
import json
import logging
import time
import urllib.error
import urllib.request
import uuid
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
logger = logging.getLogger(__name__)
# =============================================================================
# Constants
# =============================================================================
CODE_ASSIST_ENDPOINT = "https://cloudcode-pa.googleapis.com"
# Fallback endpoints tried when prod returns an error during project discovery
FALLBACK_ENDPOINTS = [
"https://daily-cloudcode-pa.sandbox.googleapis.com",
"https://autopush-cloudcode-pa.sandbox.googleapis.com",
]
# Tier identifiers that Google's API uses
FREE_TIER_ID = "free-tier"
LEGACY_TIER_ID = "legacy-tier"
STANDARD_TIER_ID = "standard-tier"
# Default HTTP headers matching gemini-cli's fingerprint.
# Google may reject unrecognized User-Agents on these internal endpoints.
_GEMINI_CLI_USER_AGENT = "google-api-nodejs-client/9.15.1 (gzip)"
_X_GOOG_API_CLIENT = "gl-node/24.0.0"
_DEFAULT_REQUEST_TIMEOUT = 30.0
_ONBOARDING_POLL_ATTEMPTS = 12
_ONBOARDING_POLL_INTERVAL_SECONDS = 5.0
class CodeAssistError(RuntimeError):
"""Exception raised by the Code Assist (``cloudcode-pa``) integration.
Carries HTTP status / response / retry-after metadata so the agent's
``error_classifier._extract_status_code`` and the main loop's Retry-After
handling (which walks ``error.response.headers``) pick up the right
signals. Without these, 429s from the OAuth path look like opaque
``RuntimeError`` and skip the rate-limit path.
"""
def __init__(
self,
message: str,
*,
code: str = "code_assist_error",
status_code: Optional[int] = None,
response: Any = None,
retry_after: Optional[float] = None,
details: Optional[Dict[str, Any]] = None,
) -> None:
super().__init__(message)
self.code = code
# ``status_code`` is picked up by ``agent.error_classifier._extract_status_code``
# so a 429 from Code Assist classifies as FailoverReason.rate_limit and
# triggers the main loop's fallback_providers chain the same way SDK
# errors do.
self.status_code = status_code
# ``response`` is the underlying ``httpx.Response`` (or a shim with a
# ``.headers`` mapping and ``.json()`` method). The main loop reads
# ``error.response.headers["Retry-After"]`` to honor Google's retry
# hints when the backend throttles us.
self.response = response
# Parsed ``Retry-After`` seconds (kept separately for convenience —
# Google returns retry hints in both the header and the error body's
# ``google.rpc.RetryInfo`` details, and we pick whichever we found).
self.retry_after = retry_after
# Parsed structured error details from the Google error envelope
# (e.g. ``{"reason": "MODEL_CAPACITY_EXHAUSTED", "status": "RESOURCE_EXHAUSTED"}``).
# Useful for logging and for tests that want to assert on specifics.
self.details = details or {}
class ProjectIdRequiredError(CodeAssistError):
def __init__(self, message: str = "GCP project id required for this tier") -> None:
super().__init__(message, code="code_assist_project_id_required")
# =============================================================================
# HTTP primitive (auth via Bearer token passed per-call)
# =============================================================================
def _build_headers(access_token: str, *, user_agent_model: str = "") -> Dict[str, str]:
ua = _GEMINI_CLI_USER_AGENT
if user_agent_model:
ua = f"{ua} model/{user_agent_model}"
return {
"Content-Type": "application/json",
"Accept": "application/json",
"Authorization": f"Bearer {access_token}",
"User-Agent": ua,
"X-Goog-Api-Client": _X_GOOG_API_CLIENT,
"x-activity-request-id": str(uuid.uuid4()),
}
def _client_metadata() -> Dict[str, str]:
"""Match Google's gemini-cli exactly — unrecognized metadata may be rejected."""
return {
"ideType": "IDE_UNSPECIFIED",
"platform": "PLATFORM_UNSPECIFIED",
"pluginType": "GEMINI",
}
def _post_json(
url: str,
body: Dict[str, Any],
access_token: str,
*,
timeout: float = _DEFAULT_REQUEST_TIMEOUT,
user_agent_model: str = "",
) -> Dict[str, Any]:
data = json.dumps(body).encode("utf-8")
request = urllib.request.Request(
url, data=data, method="POST",
headers=_build_headers(access_token, user_agent_model=user_agent_model),
)
try:
with urllib.request.urlopen(request, timeout=timeout) as response:
raw = response.read().decode("utf-8", errors="replace")
return json.loads(raw) if raw else {}
except urllib.error.HTTPError as exc:
detail = ""
try:
detail = exc.read().decode("utf-8", errors="replace")
except Exception:
pass
# Special case: VPC-SC violation should be distinguishable
if _is_vpc_sc_violation(detail):
raise CodeAssistError(
f"VPC-SC policy violation: {detail}",
code="code_assist_vpc_sc",
) from exc
raise CodeAssistError(
f"Code Assist HTTP {exc.code}: {detail or exc.reason}",
code=f"code_assist_http_{exc.code}",
) from exc
except urllib.error.URLError as exc:
raise CodeAssistError(
f"Code Assist request failed: {exc}",
code="code_assist_network_error",
) from exc
def _is_vpc_sc_violation(body: str) -> bool:
"""Detect a VPC Service Controls violation from a response body."""
if not body:
return False
try:
parsed = json.loads(body)
except (json.JSONDecodeError, ValueError):
return "SECURITY_POLICY_VIOLATED" in body
# Walk the nested error structure Google uses
error = parsed.get("error") if isinstance(parsed, dict) else None
if not isinstance(error, dict):
return False
details = error.get("details") or []
if isinstance(details, list):
for item in details:
if isinstance(item, dict):
reason = item.get("reason") or ""
if reason == "SECURITY_POLICY_VIOLATED":
return True
msg = str(error.get("message", ""))
return "SECURITY_POLICY_VIOLATED" in msg
# =============================================================================
# load_code_assist — discovers current tier + assigned project
# =============================================================================
@dataclass
class CodeAssistProjectInfo:
"""Result from ``load_code_assist``."""
current_tier_id: str = ""
cloudaicompanion_project: str = "" # Google-managed project (free tier)
allowed_tiers: List[str] = field(default_factory=list)
raw: Dict[str, Any] = field(default_factory=dict)
def load_code_assist(
access_token: str,
*,
project_id: str = "",
user_agent_model: str = "",
) -> CodeAssistProjectInfo:
"""Call ``POST /v1internal:loadCodeAssist`` with prod → sandbox fallback.
Returns whatever tier + project info Google reports. On VPC-SC violations,
returns a synthetic ``standard-tier`` result so the chain can continue.
"""
body: Dict[str, Any] = {
"metadata": {
"duetProject": project_id,
**_client_metadata(),
},
}
if project_id:
body["cloudaicompanionProject"] = project_id
endpoints = [CODE_ASSIST_ENDPOINT] + FALLBACK_ENDPOINTS
last_err: Optional[Exception] = None
for endpoint in endpoints:
url = f"{endpoint}/v1internal:loadCodeAssist"
try:
resp = _post_json(url, body, access_token, user_agent_model=user_agent_model)
return _parse_load_response(resp)
except CodeAssistError as exc:
if exc.code == "code_assist_vpc_sc":
logger.info("VPC-SC violation on %s — defaulting to standard-tier", endpoint)
return CodeAssistProjectInfo(
current_tier_id=STANDARD_TIER_ID,
cloudaicompanion_project=project_id,
)
last_err = exc
logger.warning("loadCodeAssist failed on %s: %s", endpoint, exc)
continue
if last_err:
raise last_err
return CodeAssistProjectInfo()
def _parse_load_response(resp: Dict[str, Any]) -> CodeAssistProjectInfo:
current_tier = resp.get("currentTier") or {}
tier_id = str(current_tier.get("id") or "") if isinstance(current_tier, dict) else ""
project = str(resp.get("cloudaicompanionProject") or "")
allowed = resp.get("allowedTiers") or []
allowed_ids: List[str] = []
if isinstance(allowed, list):
for t in allowed:
if isinstance(t, dict):
tid = str(t.get("id") or "")
if tid:
allowed_ids.append(tid)
return CodeAssistProjectInfo(
current_tier_id=tier_id,
cloudaicompanion_project=project,
allowed_tiers=allowed_ids,
raw=resp,
)
# =============================================================================
# onboard_user — provisions a new user on a tier (with LRO polling)
# =============================================================================
def onboard_user(
access_token: str,
*,
tier_id: str,
project_id: str = "",
user_agent_model: str = "",
) -> Dict[str, Any]:
"""Call ``POST /v1internal:onboardUser`` to provision the user.
For paid tiers, ``project_id`` is REQUIRED (raises ProjectIdRequiredError).
For free tiers, ``project_id`` is optional Google will assign one.
Returns the final operation response. Polls ``/v1internal/<name>`` for up
to ``_ONBOARDING_POLL_ATTEMPTS`` × ``_ONBOARDING_POLL_INTERVAL_SECONDS``
(default: 12 × 5s = 1 min).
"""
if tier_id != FREE_TIER_ID and tier_id != LEGACY_TIER_ID and not project_id:
raise ProjectIdRequiredError(
f"Tier {tier_id!r} requires a GCP project id. "
"Set HERMES_GEMINI_PROJECT_ID or GOOGLE_CLOUD_PROJECT."
)
body: Dict[str, Any] = {
"tierId": tier_id,
"metadata": _client_metadata(),
}
if project_id:
body["cloudaicompanionProject"] = project_id
endpoint = CODE_ASSIST_ENDPOINT
url = f"{endpoint}/v1internal:onboardUser"
resp = _post_json(url, body, access_token, user_agent_model=user_agent_model)
# Poll if LRO (long-running operation)
if not resp.get("done"):
op_name = resp.get("name", "")
if not op_name:
return resp
for attempt in range(_ONBOARDING_POLL_ATTEMPTS):
time.sleep(_ONBOARDING_POLL_INTERVAL_SECONDS)
poll_url = f"{endpoint}/v1internal/{op_name}"
try:
poll_resp = _post_json(poll_url, {}, access_token, user_agent_model=user_agent_model)
except CodeAssistError as exc:
logger.warning("Onboarding poll attempt %d failed: %s", attempt + 1, exc)
continue
if poll_resp.get("done"):
return poll_resp
logger.warning("Onboarding did not complete within %d attempts", _ONBOARDING_POLL_ATTEMPTS)
return resp
# =============================================================================
# retrieve_user_quota — for /gquota
# =============================================================================
@dataclass
class QuotaBucket:
model_id: str
token_type: str = ""
remaining_fraction: float = 0.0
reset_time_iso: str = ""
raw: Dict[str, Any] = field(default_factory=dict)
def retrieve_user_quota(
access_token: str,
*,
project_id: str = "",
user_agent_model: str = "",
) -> List[QuotaBucket]:
"""Call ``POST /v1internal:retrieveUserQuota`` and parse ``buckets[]``."""
body: Dict[str, Any] = {}
if project_id:
body["project"] = project_id
url = f"{CODE_ASSIST_ENDPOINT}/v1internal:retrieveUserQuota"
resp = _post_json(url, body, access_token, user_agent_model=user_agent_model)
raw_buckets = resp.get("buckets") or []
buckets: List[QuotaBucket] = []
if not isinstance(raw_buckets, list):
return buckets
for b in raw_buckets:
if not isinstance(b, dict):
continue
buckets.append(QuotaBucket(
model_id=str(b.get("modelId") or ""),
token_type=str(b.get("tokenType") or ""),
remaining_fraction=float(b.get("remainingFraction") or 0.0),
reset_time_iso=str(b.get("resetTime") or ""),
raw=b,
))
return buckets
# =============================================================================
# Project context resolution
# =============================================================================
@dataclass
class ProjectContext:
"""Resolved state for a given OAuth session."""
project_id: str = "" # effective project id sent on requests
managed_project_id: str = "" # Google-assigned project (free tier)
tier_id: str = ""
source: str = "" # "env", "config", "discovered", "onboarded"
def resolve_project_context(
access_token: str,
*,
configured_project_id: str = "",
env_project_id: str = "",
user_agent_model: str = "",
) -> ProjectContext:
"""Figure out what project id + tier to use for requests.
Priority:
1. If configured_project_id or env_project_id is set, use that directly
and short-circuit (no discovery needed).
2. Otherwise call loadCodeAssist to see what Google says.
3. If no tier assigned yet, onboard the user (free tier default).
"""
# Short-circuit: caller provided a project id
if configured_project_id:
return ProjectContext(
project_id=configured_project_id,
tier_id=STANDARD_TIER_ID, # assume paid since they specified one
source="config",
)
if env_project_id:
return ProjectContext(
project_id=env_project_id,
tier_id=STANDARD_TIER_ID,
source="env",
)
# Discover via loadCodeAssist
info = load_code_assist(access_token, user_agent_model=user_agent_model)
effective_project = info.cloudaicompanion_project
tier = info.current_tier_id
if not tier:
# User hasn't been onboarded — provision them on free tier
onboard_resp = onboard_user(
access_token,
tier_id=FREE_TIER_ID,
project_id="",
user_agent_model=user_agent_model,
)
# Re-parse from the onboard response
response_body = onboard_resp.get("response") or {}
if isinstance(response_body, dict):
effective_project = (
effective_project
or str(response_body.get("cloudaicompanionProject") or "")
)
tier = FREE_TIER_ID
source = "onboarded"
else:
source = "discovered"
return ProjectContext(
project_id=effective_project,
managed_project_id=effective_project if tier == FREE_TIER_ID else "",
tier_id=tier,
source=source,
)
File diff suppressed because it is too large Load Diff
+5 -74
View File
@@ -11,18 +11,6 @@ Providers live in ``<repo>/plugins/image_gen/<name>/`` (built-in, auto-loaded
as ``kind: backend``) or ``~/.hermes/plugins/image_gen/<name>/`` (user, opt-in
via ``plugins.enabled``).
Unified surface
---------------
One tool ``image_generate`` covers **text-to-image** and
**image-to-image / image editing**. The router is the presence of
``image_url`` (and/or ``reference_image_urls``): if any source image is
provided, the provider routes to its image-to-image / edit endpoint; if
omitted, the provider routes to text-to-image. Users pick one **model**
(e.g. nano-banana-pro, gpt-image-2, grok-imagine-image); the provider
handles which underlying endpoint to hit. This mirrors the ``video_gen``
provider design (``agent/video_gen_provider.py``) so the two surfaces
stay learnable together.
Response shape
--------------
All providers return a dict that :func:`success_response` / :func:`error_response`
@@ -33,7 +21,6 @@ produce. The tool wrapper JSON-serializes it. Keys:
model str provider-specific model identifier
prompt str echoed prompt
aspect_ratio str "landscape" | "square" | "portrait"
modality str "text" | "image" (which mode was used)
provider str provider name (for diagnostics)
error str only when success=False
error_type str only when success=False
@@ -140,51 +127,19 @@ class ImageGenProvider(abc.ABC):
return models[0].get("id")
return None
def capabilities(self) -> Dict[str, Any]:
"""Return what this provider supports.
Returned dict (all keys optional)::
{
"modalities": ["text", "image"], # which inputs the backend accepts
"max_reference_images": 9, # cap for reference_image_urls
}
``modalities`` declares whether the active backend/model supports
text-to-image (``"text"``), image-to-image / editing (``"image"``),
or both. The tool layer surfaces this in the dynamic schema so the
model knows when ``image_url`` is honored. Used by ``hermes tools``
for the picker too. Default: text-only (backward compatible a
provider that doesn't override this advertises text-to-image only).
"""
return {
"modalities": ["text"],
"max_reference_images": 0,
}
@abc.abstractmethod
def generate(
self,
prompt: str,
aspect_ratio: str = DEFAULT_ASPECT_RATIO,
*,
image_url: Optional[str] = None,
reference_image_urls: Optional[List[str]] = None,
**kwargs: Any,
) -> Dict[str, Any]:
"""Generate an image from a text prompt, or edit/transform a source image.
Routing: if ``image_url`` (or any ``reference_image_urls``) is
provided, the provider should route to its image-to-image / edit
endpoint; otherwise text-to-image. ``image_url`` is the primary
source image to edit; ``reference_image_urls`` are additional
style/composition references (provider clamps to its declared
``max_reference_images``).
"""Generate an image.
Implementations should return the dict from :func:`success_response`
or :func:`error_response`. ``kwargs`` may contain forward-compat
parameters future versions of the schema will expose
implementations MUST ignore unknown keys (no TypeError).
parameters future versions of the schema will expose implementations
should ignore unknown keys.
"""
@@ -207,26 +162,6 @@ def resolve_aspect_ratio(value: Optional[str]) -> str:
return DEFAULT_ASPECT_RATIO
def normalize_reference_images(value: Any) -> Optional[List[str]]:
"""Coerce a reference-image argument into a clean list of URL/path strings.
Accepts a single string or a list; strips blanks and whitespace. Returns
``None`` when nothing usable remains so providers can treat "no refs" as a
single sentinel.
"""
if value is None:
return None
if isinstance(value, str):
value = [value]
if not isinstance(value, (list, tuple)):
return None
out: List[str] = []
for item in value:
if isinstance(item, str) and item.strip():
out.append(item.strip())
return out or None
def _images_cache_dir() -> Path:
"""Return ``$HERMES_HOME/cache/images/``, creating parents as needed."""
from hermes_constants import get_hermes_home
@@ -345,16 +280,13 @@ def success_response(
prompt: str,
aspect_ratio: str,
provider: str,
modality: str = "text",
extra: Optional[Dict[str, Any]] = None,
) -> Dict[str, Any]:
"""Build a uniform success response dict.
``image`` may be an HTTP URL or an absolute filesystem path (for b64
providers like OpenAI). ``modality`` is ``"text"`` (text-to-image) or
``"image"`` (image-to-image / editing) indicates which endpoint was
actually hit, useful for diagnostics. Callers that need to pass through
additional backend-specific fields can supply ``extra``.
providers like OpenAI). Callers that need to pass through additional
backend-specific fields can supply ``extra``.
"""
payload: Dict[str, Any] = {
"success": True,
@@ -362,7 +294,6 @@ def success_response(
"model": model,
"prompt": prompt,
"aspect_ratio": aspect_ratio,
"modality": modality,
"provider": provider,
}
if extra:
+27 -254
View File
@@ -17,17 +17,13 @@ It reads ``agent.image_input_mode`` from config.yaml (``auto`` | ``native``
| ``text``, default ``auto``) and the active model's capability metadata.
In ``auto`` mode:
- If the active model reports ``supports_vision=True`` (via config
override or models.dev metadata), we attach natively vision-capable
main models should always see the original pixels, even when an
auxiliary vision backend is configured. That auxiliary backend then
acts as a *fallback* for sessions whose main model can't take images.
- Otherwise, if the user has explicitly configured ``auxiliary.vision``
(provider/model/base_url not ``auto``/empty), we route through the
text pipeline so the auxiliary vision backend can describe the image
for the text-only main model.
- Otherwise (non-vision model, no explicit override), we fall back to
text via the default vision_analyze flow.
- If the user has explicitly configured ``auxiliary.vision.provider``
(i.e. not ``auto`` and not empty), we assume they want the text pipeline
regardless of the main model they've opted in to a specific vision
backend for a reason (cost, quality, local-only, etc.).
- Otherwise, if the active model reports ``supports_vision=True`` in its
models.dev metadata, we attach natively.
- Otherwise (non-vision model, no explicit override), we fall back to text.
This keeps ``vision_analyze`` surfaced as a tool in every session skills
and agent flows that chain it (browser screenshots, deeper inspection of
@@ -189,8 +185,7 @@ def _supports_vision_override(
2. ``providers.<provider>.models.<model>.supports_vision``
(named custom providers ``provider`` may be the runtime-resolved
value ``"custom"`` and/or the user-declared name under
``model.provider``; both are tried. For ``custom:<name>`` syntax,
the stripped ``<name>`` is also tried as a provider key.)
``model.provider``; both are tried)
Returns None when no override is set, so the caller falls through to
models.dev. Returns False explicitly only when the user wrote a
@@ -210,16 +205,11 @@ def _supports_vision_override(
# get rewritten to provider="custom" at runtime
# (hermes_cli/runtime_provider.py:_resolve_named_custom_runtime), so the
# config still holds the user-declared name under model.provider. Try
# both as candidate provider keys, plus the stripped suffix from
# "custom:<name>" (where <name> is the key under providers:).
# both as candidate provider keys.
config_provider = str(model_cfg.get("provider") or "").strip()
# Extract the stripped name from "custom:<name>" if present
stripped_suffix = ""
if config_provider.startswith("custom:"):
stripped_suffix = config_provider[len("custom:"):]
providers_raw = cfg.get("providers")
providers_cfg: Dict[str, Any] = providers_raw if isinstance(providers_raw, dict) else {}
for p in dict.fromkeys(filter(None, (provider, config_provider, stripped_suffix))):
for p in dict.fromkeys(filter(None, (provider, config_provider))):
entry_raw = providers_cfg.get(p)
entry: Dict[str, Any] = entry_raw if isinstance(entry_raw, dict) else {}
models_raw = entry.get("models")
@@ -261,80 +251,6 @@ def _supports_vision_override(
return None
def _resolve_inference_base_url(
cfg: Optional[Dict[str, Any]],
provider: str,
) -> str:
"""Best-effort base URL for the active inference provider."""
try:
from agent.auxiliary_client import _runtime_main_value
runtime = str(_runtime_main_value("base_url") or "").strip()
runtime_provider = str(_runtime_main_value("provider") or "").strip().lower()
requested_provider = str(provider or "").strip().lower()
if runtime and (not requested_provider or requested_provider == runtime_provider):
return runtime
except Exception:
pass
if not isinstance(cfg, dict):
return ""
model_cfg_raw = cfg.get("model")
model_cfg: Dict[str, Any] = model_cfg_raw if isinstance(model_cfg_raw, dict) else {}
base_url = str(model_cfg.get("base_url") or "").strip()
if base_url:
return base_url
config_provider = str(model_cfg.get("provider") or "").strip()
candidate_names: set[str] = set()
for p in filter(None, (provider, config_provider)):
candidate_names.add(p)
if p.lower().startswith("custom:"):
candidate_names.add(p.split(":", 1)[1])
else:
candidate_names.add(f"custom:{p}")
providers_cfg = cfg.get("providers")
if isinstance(providers_cfg, dict):
for name in candidate_names:
entry = providers_cfg.get(name)
if isinstance(entry, dict):
bu = str(entry.get("base_url") or "").strip()
if bu:
return bu
custom_providers = cfg.get("custom_providers")
if isinstance(custom_providers, list):
lowered = {n.lower() for n in candidate_names}
for entry_raw in custom_providers:
if not isinstance(entry_raw, dict):
continue
entry_name = str(entry_raw.get("name") or "").strip()
if entry_name not in candidate_names and entry_name.lower() not in lowered:
continue
bu = str(entry_raw.get("base_url") or "").strip()
if bu:
return bu
return ""
def _should_probe_ollama_vision(provider: str, base_url: str) -> bool:
"""True when the active provider likely fronts a local Ollama server."""
p = (provider or "").strip().lower()
if p == "ollama":
return True
if not base_url:
return False
try:
from agent.model_metadata import detect_local_server_type
return detect_local_server_type(base_url) == "ollama"
except Exception:
return False
def _coerce_mode(raw: Any) -> str:
"""Normalize a config value into one of the valid modes."""
if not isinstance(raw, str):
@@ -348,10 +264,8 @@ def _coerce_mode(raw: Any) -> str:
def _explicit_aux_vision_override(cfg: Optional[Dict[str, Any]]) -> bool:
"""True when the user configured a specific auxiliary vision backend.
An explicit override means the user has a dedicated vision backend
available; it's used as a *fallback* when the main model can't take
images natively. In ``auto`` mode, native vision on a vision-capable
main model still wins over this fallback see issue #29135.
An explicit override means the user *wants* the text pipeline (they're
paying for a dedicated vision model), so we don't silently bypass it.
"""
if not isinstance(cfg, dict):
return False
@@ -388,33 +302,15 @@ def _lookup_supports_vision(
return override
if not provider or not model:
return None
caps = None
try:
from agent.models_dev import get_model_capabilities
caps = get_model_capabilities(provider, model)
except Exception as exc: # pragma: no cover - defensive
logger.debug("image_routing: caps lookup failed for %s:%s%s", provider, model, exc)
if caps is not None:
return bool(caps.supports_vision)
base_url = _resolve_inference_base_url(cfg, provider)
if not base_url and (provider or "").strip().lower() == "ollama":
base_url = "http://localhost:11434/v1"
if _should_probe_ollama_vision(provider, base_url):
try:
from agent.model_metadata import query_ollama_supports_vision
ollama_vision = query_ollama_supports_vision(model, base_url)
if ollama_vision is not None:
return ollama_vision
except Exception as exc: # pragma: no cover - defensive
logger.debug(
"image_routing: ollama vision probe failed for %s:%s%s",
provider,
model,
exc,
)
return None
return None
if caps is None:
return None
return bool(caps.supports_vision)
def decide_image_input_mode(
@@ -440,15 +336,13 @@ def decide_image_input_mode(
if mode_cfg == "text":
return "text"
# auto: prefer native vision when the main model supports it. An
# explicit auxiliary.vision config acts as a *fallback* for text-only
# main models — it should not preempt native vision on a model that
# can natively inspect the pixels (issue #29135).
# auto
if _explicit_aux_vision_override(cfg):
return "text"
supports = _lookup_supports_vision(provider, model, cfg)
if supports is True:
return "native"
if _explicit_aux_vision_override(cfg):
return "text"
return "text"
@@ -494,98 +388,14 @@ def _sniff_mime_from_bytes(raw: bytes) -> Optional[str]:
# BMP: "BM"
if raw.startswith(b"BM"):
return "image/bmp"
# ISO-BMFF family (HEIC/HEIF/AVIF): bytes 4..8 == 'ftyp', major brand at 8..12
if len(raw) >= 12 and raw[4:8] == b"ftyp":
brand = raw[8:12]
if brand in {b"avif", b"avis"}:
return "image/avif"
if brand in {
b"heic", b"heix", b"hevc", b"hevx",
b"mif1", b"msf1", b"heim", b"heis",
}:
return "image/heic"
# TIFF: II*\0 (little-endian) or MM\0* (big-endian)
if raw[:4] in {b"II*\x00", b"MM\x00*"}:
return "image/tiff"
# ICO: 00 00 01 00 (reserved=0, type=1=icon)
if raw[:4] == b"\x00\x00\x01\x00":
return "image/x-icon"
# SVG: text-based, look for an <svg tag near the start (skip BOM/whitespace)
head = raw[:512].lstrip().lower()
if head.startswith(b"<?xml") or head.startswith(b"<svg"):
if b"<svg" in head:
return "image/svg+xml"
# HEIC/HEIF: ftypheic / ftypheix / ftypmif1 / ftypmsf1 etc.
if len(raw) >= 12 and raw[4:8] == b"ftyp" and raw[8:12] in {
b"heic", b"heix", b"hevc", b"hevx", b"mif1", b"msf1", b"heim", b"heis",
}:
return "image/heic"
return None
# Formats every major vision provider (Anthropic, OpenAI, Gemini, Bedrock)
# accepts natively. Anything outside this set has to be transcoded to PNG
# before we declare media_type, otherwise the provider returns HTTP 400
# ("Could not process image" / "Unsupported image media type") and the
# whole turn fails with no salvage path.
#
# Discord (and a few other chat platforms) freely accept attachments in
# formats outside this set -- AVIF screenshots from Chromium, HEIC from
# iPhones, TIFF from scanners, BMP from old Windows tools, ICO -- so users
# do hit this in practice. SVG is vector and Pillow cannot rasterize it;
# it is skipped (logged) rather than transcoded.
_UNIVERSALLY_SUPPORTED_MIMES = frozenset({
"image/png", "image/jpeg", "image/gif", "image/webp",
})
def _transcode_to_png(raw: bytes) -> Optional[bytes]:
"""Decode arbitrary image bytes with Pillow and re-encode as PNG.
Returns None if Pillow isn't installed or can't decode the input
(rare formats, corrupted bytes, missing optional decoder plugin for
HEIC/AVIF, or vector formats like SVG). Caller falls back to skipping
the image so the rest of the turn still works.
HEIC/HEIF and AVIF need optional Pillow plugins; we try to register
them on demand and swallow ImportError so a missing plugin just
looks like 'Pillow can't decode this' rather than crashing.
"""
try:
from PIL import Image
except ImportError:
logger.info(
"image_routing: Pillow not installed; cannot transcode "
"non-standard image format to PNG. Install with `pip install Pillow` "
"(and `pillow-heif` / `pillow-avif-plugin` for those formats)."
)
return None
# Optional plugin registration. Silent on failure: an unsupported
# format will just fall through to Image.open raising below.
try:
import pillow_heif # type: ignore
pillow_heif.register_heif_opener()
except Exception:
pass
try:
import pillow_avif # type: ignore # noqa: F401 -- registers AVIF on import
except Exception:
pass
try:
from io import BytesIO
with Image.open(BytesIO(raw)) as im:
# Pick an output mode PNG can serialise. Anything other than
# the standard set gets normalised to RGBA so transparency is
# preserved where the source had it.
if im.mode not in {"RGB", "RGBA", "L", "LA", "P"}:
im = im.convert("RGBA")
buf = BytesIO()
im.save(buf, format="PNG", optimize=False)
return buf.getvalue()
except Exception as exc:
logger.info(
"image_routing: Pillow could not transcode image to PNG -- %s", exc
)
return None
def _guess_mime(path: Path, raw: Optional[bytes] = None) -> str:
"""Return image MIME type for *path*.
@@ -621,52 +431,15 @@ def _file_to_data_url(path: Path) -> Optional[str]:
accept large images (OpenAI 49 MB+, Gemini 100 MB) don't pay a silent
quality tax just because one other provider is stricter.
Format compatibility IS handled here: if the sniffed MIME isn't one
of ``_UNIVERSALLY_SUPPORTED_MIMES`` (i.e. it's something like AVIF,
HEIC, BMP, TIFF, or ICO that some providers reject outright), we
transcode to PNG with Pillow before declaring media_type. This fixes
the user-visible "Could not process image" HTTP 400 from Anthropic on
Discord-attached AVIF/HEIC/BMP files.
Returns None if the file can't be read OR if the format isn't
universally supported AND Pillow can't transcode it (Pillow missing,
HEIC/AVIF plugin missing, vector format like SVG, corrupt bytes). The
caller reports those paths in ``skipped`` and the rest of the turn
proceeds.
Returns None only if the file can't be read (missing, permission
denied, etc.); the caller reports those paths in ``skipped``.
"""
try:
from agent.file_safety import raise_if_read_blocked
raise_if_read_blocked(str(path))
except ValueError as exc:
logger.warning("image_routing: blocked local image attachment %s -- %s", path, exc)
return None
except Exception:
# Keep attachment routing best-effort if the guard itself is unavailable.
pass
try:
raw = path.read_bytes()
except Exception as exc:
logger.warning("image_routing: failed to read %s%s", path, exc)
return None
mime = _guess_mime(path, raw=raw)
if mime not in _UNIVERSALLY_SUPPORTED_MIMES:
transcoded = _transcode_to_png(raw)
if transcoded is None:
logger.warning(
"image_routing: %s is %s which is not accepted by all major "
"vision providers and could not be transcoded to PNG; "
"skipping this attachment.",
path, mime,
)
return None
logger.info(
"image_routing: transcoded %s (%s) -> image/png for provider compatibility",
path.name, mime,
)
raw = transcoded
mime = "image/png"
b64 = base64.b64encode(raw).decode("ascii")
return f"data:{mime};base64,{b64}"
+23 -194
View File
@@ -17,7 +17,6 @@ Usage:
"""
import json
import sqlite3
import time
from collections import Counter, defaultdict
from datetime import datetime
@@ -142,8 +141,8 @@ class InsightsEngine:
}
# Compute insights
models = self._compute_model_breakdown(sessions, cutoff, source)
overview = self._compute_overview(sessions, message_stats, models)
overview = self._compute_overview(sessions, message_stats)
models = self._compute_model_breakdown(sessions)
platforms = self._compute_platform_breakdown(sessions)
tools = self._compute_tool_breakdown(tool_usage)
skills = self._compute_skill_breakdown(skill_usage)
@@ -173,7 +172,7 @@ class InsightsEngine:
"message_count, tool_call_count, input_tokens, output_tokens, "
"cache_read_tokens, cache_write_tokens, billing_provider, "
"billing_base_url, billing_mode, estimated_cost_usd, "
"actual_cost_usd, cost_status, cost_source, api_call_count")
"actual_cost_usd, cost_status, cost_source")
# Pre-computed query strings — f-string evaluated once at class definition,
# not at runtime, so no user-controlled value can alter the query structure.
@@ -400,12 +399,7 @@ class InsightsEngine:
# Computation
# =========================================================================
def _compute_overview(
self,
sessions: List[Dict],
message_stats: Dict,
models: Optional[List[Dict]] = None,
) -> Dict:
def _compute_overview(self, sessions: List[Dict], message_stats: Dict) -> Dict:
"""Compute high-level overview statistics."""
total_input = sum(s.get("input_tokens") or 0 for s in sessions)
total_output = sum(s.get("output_tokens") or 0 for s in sessions)
@@ -437,21 +431,6 @@ class InsightsEngine:
else:
models_without_pricing.add(display)
if models:
total_cost = sum(float(m.get("cost") or 0.0) for m in models)
# Token totals likewise: the per-model breakdown includes
# auxiliary usage rows (vision/compression/titles — task
# dimension in session_model_usage, #23270) plus reconciled
# residuals, while the sessions counters carry main-loop usage
# only. Summing the breakdown keeps overview totals consistent
# with the per-model table and stops `hermes insights`
# undercounting aux spend (#58592, #9979).
total_input = sum(int(m.get("input_tokens") or 0) for m in models)
total_output = sum(int(m.get("output_tokens") or 0) for m in models)
total_cache_read = sum(int(m.get("cache_read_tokens") or 0) for m in models)
total_cache_write = sum(int(m.get("cache_write_tokens") or 0) for m in models)
total_tokens = total_input + total_output + total_cache_read + total_cache_write
# Session duration stats (guard against negative durations from clock drift)
durations = []
for s in sessions:
@@ -494,189 +473,39 @@ class InsightsEngine:
"included_cost_sessions": included_cost_sessions,
}
_GET_MODEL_USAGE_WITH_SOURCE = (
"SELECT u.session_id, u.model, u.billing_provider, u.billing_base_url,"
" u.api_call_count, u.input_tokens, u.output_tokens,"
" u.cache_read_tokens, u.cache_write_tokens, u.reasoning_tokens,"
" u.estimated_cost_usd, u.actual_cost_usd, u.cost_status,"
" u.cost_source, u.billing_mode"
" FROM session_model_usage u"
" JOIN sessions s ON s.id = u.session_id"
" WHERE s.started_at >= ? AND s.source = ?"
)
_GET_MODEL_USAGE_ALL = (
"SELECT u.session_id, u.model, u.billing_provider, u.billing_base_url,"
" u.api_call_count, u.input_tokens, u.output_tokens,"
" u.cache_read_tokens, u.cache_write_tokens, u.reasoning_tokens,"
" u.estimated_cost_usd, u.actual_cost_usd, u.cost_status,"
" u.cost_source, u.billing_mode"
" FROM session_model_usage u"
" JOIN sessions s ON s.id = u.session_id"
" WHERE s.started_at >= ?"
)
def _get_model_usage(self, cutoff: float, source: str = None) -> List[Dict]:
"""Fetch per-model usage rows within the window (issue #51607).
Returns an empty list when the table is missing (e.g. a DB opened by
older code that never created it) so the caller can fall back to the
per-session aggregate.
"""
try:
if source:
cursor = self._conn.execute(
self._GET_MODEL_USAGE_WITH_SOURCE, (cutoff, source)
)
else:
cursor = self._conn.execute(self._GET_MODEL_USAGE_ALL, (cutoff,))
return [dict(row) for row in cursor.fetchall()]
except sqlite3.OperationalError:
return []
def _compute_model_breakdown(
self, sessions: List[Dict], cutoff: float, source: str = None
) -> List[Dict]:
"""Break down token usage and cost by model.
Tokens and cost are attributed per model from session_model_usage, so a
session that switched models mid-flight (via ``/model``) splits across
every model it used instead of dumping everything on the initial model
(issue #51607). Sessions without per-model rows — e.g. data written
before this table existed and not yet backfilled fall back to their
single recorded (model, billing_provider) aggregate so nothing is lost.
Tool calls aren't tied to a specific API invocation, so they stay
attributed to the session's recorded model.
"""
def _compute_model_breakdown(self, sessions: List[Dict]) -> List[Dict]:
"""Break down usage by model."""
model_data = defaultdict(lambda: {
"sessions": set(), "input_tokens": 0, "output_tokens": 0,
"sessions": 0, "input_tokens": 0, "output_tokens": 0,
"cache_read_tokens": 0, "cache_write_tokens": 0,
"reasoning_tokens": 0, "total_tokens": 0, "api_calls": 0,
"tool_calls": 0, "cost": 0.0, "actual_cost": 0.0,
"total_tokens": 0, "tool_calls": 0, "cost": 0.0,
})
def _accumulate(model, provider, base_url, session_id, inp, out,
cache_read, cache_write, reasoning, *,
stored_cost=None, actual_cost=None, cost_status=None):
model = model or "unknown"
for s in sessions:
model = s.get("model") or "unknown"
# Normalize: strip provider prefix for display
display_model = model.split("/")[-1] if "/" in model else model
d: Dict[str, Any] = model_data[display_model]
d["sessions"].add(session_id)
d = model_data[display_model]
d["sessions"] += 1
inp = s.get("input_tokens") or 0
out = s.get("output_tokens") or 0
cache_read = s.get("cache_read_tokens") or 0
cache_write = s.get("cache_write_tokens") or 0
d["input_tokens"] += inp
d["output_tokens"] += out
d["cache_read_tokens"] += cache_read
d["cache_write_tokens"] += cache_write
d["reasoning_tokens"] += reasoning
d["total_tokens"] += inp + out + cache_read + cache_write
if stored_cost is None:
estimate, status = _estimate_cost(
model, inp, out,
cache_read_tokens=cache_read, cache_write_tokens=cache_write,
provider=provider or None, base_url=base_url,
)
else:
estimate = float(stored_cost or 0.0)
status = cost_status or "unknown"
d["tool_calls"] += s.get("tool_call_count") or 0
estimate, status = _estimate_cost(s)
d["cost"] += estimate
d["actual_cost"] += float(actual_cost or 0.0)
d["has_pricing"] = has_known_pricing(model, s.get("billing_provider"), s.get("billing_base_url"))
d["cost_status"] = status
if has_known_pricing(model, provider or None, base_url):
d["has_pricing"] = True
else:
d.setdefault("has_pricing", False)
return display_model
usage_rows = self._get_model_usage(cutoff, source)
usage_totals = defaultdict(lambda: {
"input_tokens": 0, "output_tokens": 0, "cache_read_tokens": 0,
"cache_write_tokens": 0, "reasoning_tokens": 0,
"api_call_count": 0, "estimated_cost_usd": 0.0,
"actual_cost_usd": 0.0,
})
for r in usage_rows:
totals: Dict[str, Any] = usage_totals[r["session_id"]]
for key in (
"input_tokens", "output_tokens", "cache_read_tokens",
"cache_write_tokens", "reasoning_tokens", "api_call_count",
):
totals[key] += r[key] or 0
totals["estimated_cost_usd"] += r["estimated_cost_usd"] or 0.0
totals["actual_cost_usd"] += r["actual_cost_usd"] or 0.0
d = _accumulate(
r["model"], r["billing_provider"], r.get("billing_base_url"),
r["session_id"], r["input_tokens"] or 0, r["output_tokens"] or 0,
r["cache_read_tokens"] or 0, r["cache_write_tokens"] or 0,
r["reasoning_tokens"] or 0,
stored_cost=(
r["estimated_cost_usd"]
if r.get("cost_status") or r.get("cost_source")
else None
),
actual_cost=r["actual_cost_usd"],
cost_status=r.get("cost_status"),
)
model_data[d]["api_calls"] += r["api_call_count"] or 0
# Reconcile against the aggregate row. This covers legacy sessions,
# interrupted migrations, and absolute cumulative updates without
# double-counting already-attributed route deltas.
for s in sessions:
totals = usage_totals[s["id"]]
inp = max(0, (s.get("input_tokens") or 0) - totals["input_tokens"])
out = max(0, (s.get("output_tokens") or 0) - totals["output_tokens"])
cache_read = max(
0, (s.get("cache_read_tokens") or 0) - totals["cache_read_tokens"]
)
cache_write = max(
0, (s.get("cache_write_tokens") or 0) - totals["cache_write_tokens"]
)
residual_cost = max(
0.0, float(s.get("estimated_cost_usd") or 0.0)
- totals["estimated_cost_usd"],
)
residual_actual = max(
0.0, float(s.get("actual_cost_usd") or 0.0)
- totals["actual_cost_usd"],
)
residual_calls = max(
0, (s.get("api_call_count") or 0) - totals["api_call_count"]
)
if not (
inp or out or cache_read or cache_write or residual_cost
or residual_actual or residual_calls
):
continue
d = _accumulate(
s.get("model"), s.get("billing_provider"),
s.get("billing_base_url"), s["id"],
inp, out, cache_read, cache_write, 0,
stored_cost=residual_cost,
actual_cost=residual_actual,
cost_status=s.get("cost_status"),
)
residual_bucket: Dict[str, Any] = model_data[d]
residual_bucket["api_calls"] += residual_calls
# Tool calls are attributed by the session's recorded model.
for s in sessions:
tool_calls = s.get("tool_call_count") or 0
if not tool_calls:
continue
model = s.get("model") or "unknown"
display_model = model.split("/")[-1] if "/" in model else model
model_data[display_model]["tool_calls"] += tool_calls
result = []
for model, data in model_data.items():
entry = {"model": model, **data}
entry["sessions"] = len(data["sessions"])
# Models that surfaced only via tool-call attribution (no token
# rows) won't have these set by _accumulate — default them so the
# output shape is uniform for downstream/JSON consumers.
entry.setdefault("has_pricing", False)
entry.setdefault("cost_status", "unknown")
result.append(entry)
result = [
{"model": model, **data}
for model, data in model_data.items()
]
# Sort by tokens first, fall back to session count when tokens are 0
result.sort(key=lambda x: (x["total_tokens"], x["sessions"]), reverse=True)
return result
-108
View File
@@ -1,108 +0,0 @@
"""Turn-end guard for kanban workers.
Kanban workers must end with ``kanban_complete`` or ``kanban_block``. Models
(especially GLM / Qwen families) sometimes narrate the next step
("Let me write the report now") and stop with ``finish_reason=stop`` and no
tool calls. Hermes treats that as a clean exit ``rc=0`` dispatcher
``protocol_violation``.
This module is policy-only: when a kanban worker tries to finish without a
terminal board tool, return a bounded synthetic nudge so the conversation
loop continues instead of exiting.
"""
from __future__ import annotations
import os
from typing import Any, Iterable, Optional
_TERMINAL_KANBAN_TOOLS = frozenset({"kanban_complete", "kanban_block"})
_DEFAULT_MAX_ATTEMPTS = 2
def kanban_stop_nudge_enabled() -> bool:
"""Return whether the kanban stop-guard is active for this process.
On when ``HERMES_KANBAN_TASK`` is set (dispatcher-spawned worker), unless
``HERMES_KANBAN_STOP_NUDGE`` explicitly disables it.
"""
env = os.environ.get("HERMES_KANBAN_STOP_NUDGE")
if env is not None and env.strip().lower() in {"0", "false", "no", "off"}:
return False
task = (os.environ.get("HERMES_KANBAN_TASK") or "").strip()
return bool(task)
def _tool_call_name(tc: Any) -> str:
if isinstance(tc, dict):
fn = tc.get("function")
if isinstance(fn, dict):
return str(fn.get("name") or "")
return str(tc.get("name") or "")
fn = getattr(tc, "function", None)
if fn is not None:
return str(getattr(fn, "name", "") or "")
return str(getattr(tc, "name", "") or "")
def session_called_kanban_terminal(messages: Iterable[dict] | None) -> bool:
"""True if this conversation already invoked a terminal kanban tool."""
if not messages:
return False
for msg in messages:
if not isinstance(msg, dict):
continue
role = msg.get("role")
if role == "assistant":
for tc in msg.get("tool_calls") or []:
if _tool_call_name(tc) in _TERMINAL_KANBAN_TOOLS:
return True
elif role == "tool":
name = str(msg.get("name") or "")
if name in _TERMINAL_KANBAN_TOOLS:
return True
return False
def build_kanban_stop_nudge(
*,
messages: Iterable[dict] | None = None,
attempts: int = 0,
max_attempts: int = _DEFAULT_MAX_ATTEMPTS,
task_id: Optional[str] = None,
) -> Optional[str]:
"""Return a synthetic follow-up when a kanban worker exits without a terminal tool.
Returns ``None`` when the guard should not fire (not a kanban worker,
already completed/blocked, or nudge budget exhausted).
"""
if not kanban_stop_nudge_enabled():
return None
if attempts >= max_attempts:
return None
if session_called_kanban_terminal(messages):
return None
tid = (task_id or os.environ.get("HERMES_KANBAN_TASK") or "").strip() or "this task"
return (
"[System: You are a Hermes kanban worker. A plain-text reply is NOT a "
"terminal state for the board.\n\n"
f"Task `{tid}` is still `running`. Ending now without a board tool "
"causes a protocol violation (clean exit with no "
"`kanban_complete` / `kanban_block`).\n\n"
"Do this immediately in your next response — do not narrate intent:\n"
"1. Finish any remaining deliverable (write the required file(s) now).\n"
"2. Call `kanban_complete(summary=..., artifacts=[...])` if the work "
"is done, OR `kanban_block(reason=...)` if you are blocked.\n\n"
"Never end a turn with only a promise of future action. Repeated "
"protocol violations will block this task and require manual intervention.]"
)
__all__ = [
"build_kanban_stop_nudge",
"kanban_stop_nudge_enabled",
"session_called_kanban_terminal",
]
-150
View File
@@ -1,150 +0,0 @@
#!/usr/bin/env python3
"""``/learn`` — build the standards-guided prompt that turns whatever the user
described into a reusable skill.
``/learn`` is open-ended. The user can point it at anything they can describe:
a directory of code, an API doc URL, a workflow they just walked the agent
through in this conversation, or pasted notes. This module builds ONE prompt
that instructs the live agent to:
1. Gather the sources the user named, using the tools it already has
(``read_file`` / ``search_files`` for dirs, ``web_extract`` for URLs, the
current conversation for "what I just did", the user's text for pasted
material).
2. Author a single ``SKILL.md`` via ``skill_manage`` that follows the Hermes
skill-authoring standards (description <=60 chars, the modern section
order, Hermes-tool framing, no invented commands).
There is no separate distillation engine and no model-tool footprint: the
agent does the work with its existing toolset, so this works identically on
local, Docker, and remote terminal backends. Every surface (CLI ``/learn``,
gateway ``/learn``, the dashboard "Learn a skill" panel) calls
:func:`build_learn_prompt` and feeds the result to the agent as a normal turn.
"""
from __future__ import annotations
# The house-style rules, distilled from AGENTS.md "Skill authoring standards
# (HARDLINE)" and the hermes-agent-dev new-skill salvage reference. Embedded in
# the prompt so the agent authors skills the way a maintainer would by hand.
_AUTHORING_STANDARDS = """\
Follow the Hermes skill-authoring standards exactly. These are the same
HARDLINE rules a maintainer enforces in review:
Frontmatter:
- name: lowercase-hyphenated, <=64 chars, no spaces.
- description: ONE sentence, **<=60 characters**, ends with a period. State the
capability, not the implementation. No marketing words (powerful,
comprehensive, seamless, advanced, robust). Do NOT repeat the skill name. If
the description contains a colon, wrap the whole value in double quotes.
This is the most-violated rule and it is NOT cosmetic: the system-prompt
skill index truncates the description to 60 chars and loads it every
session, so anything past char 60 is silently cut and never routes. After
you write the description, COUNT the characters; if it is over 60, cut it
down before saving do not ship a sentence and hope.
Good (<=60): `Search arXiv papers by keyword, author, or ID.`
Bad (123): `A comprehensive skill that lets the agent search arXiv for
academic papers using keywords, authors, and categories.`
- version: 0.1.0
- author: always the literal value `Hermes`. NEVER fill it from the host
environment the OS/login username (e.g. the `user=` line in your
environment hints), git config, or any identity you can probe must not be
written. Skills get shared and published, so an environment-derived name is
a privacy leak the user never opted into; the skill names itself as Hermes.
- platforms: declare `[macos]`, `[linux]`, and/or `[windows]` IF the skill
uses OS-bound primitives (osascript/apt/systemctl => the matching OS; /proc,
os.setsid, signal.SIGKILL => linux; fcntl/termios => POSIX). Prefer fixing it
cross-platform first (tempfile.gettempdir(), pathlib.Path, psutil); gate only
when the dependency is genuinely platform-bound. Omit the field for portable
skills.
- metadata.hermes.tags: a few Capitalized, Relevant, Tags.
Body section order (omit a section only if it genuinely has no content):
1. "# <Human Title>" then a 2-3 sentence intro: what it does, what it does NOT
do, and the key dependency stance (e.g. "stdlib only").
2. "## When to Use" bullet list of concrete trigger phrases.
3. "## Prerequisites" exact env vars, install steps, credentials.
4. "## How to Run" the canonical invocation, framed through Hermes tools.
5. "## Quick Reference" a flat command/endpoint list, no narration.
6. "## Procedure" numbered steps with copy-paste-exact commands.
7. "## Pitfalls" known limits, rate limits, things that look broken but aren't.
8. "## Verification" a single command/check that proves the skill worked.
Hermes-tool framing (this is what makes it a skill, not shell docs):
- Frame running scripts as "invoke through the `terminal` tool".
- Reference Hermes tools by name in backticks: `terminal`, `read_file`,
`write_file`, `search_files`, `patch`, `web_extract`, `web_search`,
`vision_analyze`, `browser_navigate`, `delegate_task`, `image_generate`,
`text_to_speech`, `cronjob`, `memory`, `skill_view`, `execute_code`.
- Do NOT name shell utilities the agent already has wrapped: say `read_file`
not cat/head/tail, `search_files` not grep/rg/find/ls, `patch` not sed/awk,
`web_extract` not curl-to-scrape, `write_file` not echo>file or heredocs.
- Third-party CLIs (ffmpeg, gh, an SDK) are fine inside a script file, but the
prose still frames them as "invoke through the `terminal` tool". If the
skill needs an MCP server, name it and document its setup in Prerequisites.
Quality bar:
- Prefer exact commands, endpoint URLs, function signatures, and config keys
that appear VERBATIM in the source. NEVER invent flags, paths, or APIs if
you didn't see it in the source, don't write it.
- Keep it tight and scannable: ~100 lines for a simple skill, ~200 for a
complex one. Don't re-paste the source docs.
- Don't write a router/index/hub skill that only points at other skills.
- Larger scripts/parsers belong in a `scripts/` file (add via
`skill_manage` write_file), referenced from SKILL.md by relative path not
inlined for the agent to re-type every run. References go in `references/`,
templates in `templates/`."""
def build_learn_prompt(user_request: str) -> str:
"""Build the agent prompt for an open-ended ``/learn`` request.
Args:
user_request: the free-text the user gave after ``/learn`` a
description of the workflow, paths, URLs, or "what I just did".
Returns:
A complete instruction the agent runs as a normal turn. The agent
gathers the described sources with its existing tools and authors the
skill via ``skill_manage``.
"""
req = (user_request or "").strip()
if not req:
req = (
"the workflow we just went through in this conversation — review "
"the steps taken and distill them into a reusable skill"
)
return (
"[/learn] The user wants you to learn a reusable skill from the "
"request below, and save it.\n\n"
f"THE REQUEST:\n{req}\n\n"
"The request is open-ended and may mix two kinds of content, in any "
"order: SOURCES to gather (directories, file paths, URLs, \"what we "
"just did\", pasted notes) AND REQUIREMENTS that shape the skill "
"(what to focus on, what to leave out, scope, naming, the angle to "
"take). Treat EVERY part of the request as load-bearing. In "
"particular, prose that comes after a path or link is NOT incidental "
"— it is the user telling you what they want from that source. A "
"request like `<url> focus on the auth flow, skip the deprecated "
"endpoints` means: gather the URL AND honor \"focus on auth, skip "
"deprecated\" as authoring requirements. Never fetch the first source "
"and ignore the rest.\n\n"
"Do this:\n"
"1. Gather every source the user named, using the tools you already "
"have — `read_file`/`search_files` for local files or directories, "
"`web_extract` for URLs, the current conversation history if they "
"referred to something you just did, and the text they pasted as-is. "
"If the request is ambiguous about scope, make a reasonable choice "
"and note it; do not stall.\n"
"1b. Apply every requirement, focus, and constraint in the request to "
"the skill you author — these govern what the SKILL.md covers and "
"emphasizes, not just which sources you read.\n"
"2. Author ONE SKILL.md and save it with the `skill_manage` tool "
"(action=\"create\"). Pick a sensible category. If the procedure needs "
"a non-trivial script, add it under the skill's `scripts/` with "
"`skill_manage` write_file and reference it by relative path.\n\n"
f"{_AUTHORING_STANDARDS}\n\n"
"When done, tell the user the skill name, its category, and a "
"one-line summary of what it captured."
)
-328
View File
@@ -1,328 +0,0 @@
"""Assemble the "learning made visible" graph for desktop.
This graph is intentionally scoped to what a user actually learns over time:
- non-base, learned/profile skills (agent-created or used),
- memory chunks from ``MEMORY.md`` / ``USER.md`` as first-class nodes.
Skill links come from declared ``related_skills``. Memory-to-skill links are
derived from lexical overlap so the graph can answer "which learned skills are
connected to the things I remember?".
Run as a module to print edge-density stats against real data:
python -m agent.learning_graph
"""
from __future__ import annotations
import json
import re
from dataclasses import dataclass, field
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Optional
from hermes_constants import get_hermes_home
@dataclass
class SkillNode:
name: str
category: str
source: str = "profile"
timestamp: Optional[int] = None
use_count: int = 0
state: str = "active"
created_by: Optional[str] = None
pinned: bool = False
related: list[str] = field(default_factory=list)
def _frontmatter(text: str) -> dict[str, Any]:
try:
from agent.skill_utils import parse_frontmatter
fm, _ = parse_frontmatter(text)
return fm or {}
except Exception:
return {}
def _hermes_meta(fm: dict[str, Any]) -> dict[str, Any]:
"""``metadata.hermes`` as a dict, tolerant of the string-valued frontmatter
that ``parse_frontmatter``'s malformed-YAML fallback produces."""
meta = fm.get("metadata")
hermes = meta.get("hermes") if isinstance(meta, dict) else None
return hermes if isinstance(hermes, dict) else {}
def _related(fm: dict[str, Any]) -> list[str]:
raw = fm.get("related_skills") or _hermes_meta(fm).get("related_skills")
if isinstance(raw, list):
return [str(r).strip() for r in raw if str(r).strip()]
if isinstance(raw, str):
return [r.strip() for r in raw.strip("[]").split(",") if r.strip()]
return []
def _category(fm: dict[str, Any], skill_md: Path) -> str:
cat = fm.get("category") or _hermes_meta(fm).get("category")
if cat:
return str(cat)
# …/skills/<category>/<skill>/SKILL.md
parts = skill_md.parts
return parts[-3] if len(parts) >= 3 else "general"
def _iter_skill_files(roots: list[tuple[str, Path]]):
for source, root in roots:
if root.exists():
for path in root.rglob("SKILL.md"):
yield source, path
def _load_usage() -> dict[str, dict[str, Any]]:
try:
from tools.skill_usage import load_usage
return load_usage()
except Exception:
path = get_hermes_home() / "skills" / ".usage.json"
try:
return json.loads(path.read_text(encoding="utf-8"))
except Exception:
return {}
def _to_int_ts(value: Any) -> Optional[int]:
try:
if value is None:
return None
if isinstance(value, (int, float)):
return int(value)
s = str(value).strip()
if not s:
return None
try:
return int(float(s))
except ValueError:
parsed = datetime.fromisoformat(s.replace("Z", "+00:00"))
if parsed.tzinfo is None:
parsed = parsed.replace(tzinfo=timezone.utc)
return int(parsed.timestamp())
except Exception:
return None
def _usage_timestamp(rec: dict[str, Any]) -> Optional[int]:
for key in ("last_activity_at", "last_used_at", "last_viewed_at", "last_patched_at", "created_at"):
ts = _to_int_ts(rec.get(key))
if ts is not None:
return ts
return None
def build_skill_nodes(skill_roots: list[tuple[str, Path]]) -> dict[str, SkillNode]:
usage = _load_usage()
nodes: dict[str, SkillNode] = {}
for source, skill_md in _iter_skill_files(skill_roots):
if any(p in {".archive", ".hub", "node_modules", ".git"} for p in skill_md.parts):
continue
try:
fm = _frontmatter(skill_md.read_text(encoding="utf-8")[:4000])
except OSError:
continue
name = str(fm.get("name") or skill_md.parent.name).strip()
if not name or name in nodes:
continue
rec = usage.get(name, {})
last_activity = _usage_timestamp(rec)
file_ts = _to_int_ts(skill_md.stat().st_mtime)
nodes[name] = SkillNode(
name=name,
category=_category(fm, skill_md),
source=source,
timestamp=last_activity or file_ts,
use_count=int(rec.get("use_count", 0) or 0),
state=str(rec.get("state", "active") or "active"),
created_by=rec.get("created_by"),
pinned=bool(rec.get("pinned", False)),
related=_related(fm),
)
return nodes
def build_edges(nodes: dict[str, SkillNode]) -> list[tuple[str, str]]:
"""Undirected related_skills edges where BOTH endpoints exist (deduped)."""
seen: set[tuple[str, str]] = set()
edges: list[tuple[str, str]] = []
for node in nodes.values():
for target in node.related:
if target in nodes and target != node.name:
a, b = sorted((node.name, target))
key = (a, b)
if key not in seen:
seen.add(key)
edges.append(key)
return edges
def density_stats(nodes: dict[str, SkillNode], edges: list[tuple[str, str]]) -> dict[str, Any]:
linked: set[str] = set()
for a, b in edges:
linked.add(a)
linked.add(b)
cats: dict[str, int] = {}
for n in nodes.values():
cats[n.category] = cats.get(n.category, 0) + 1
n = len(nodes) or 1
return {
"nodes": len(nodes),
"related_edges": len(edges),
"edges_per_node": round(len(edges) / n, 3),
"linked_nodes": len(linked),
"isolated_pct": round(100 * (n - len(linked)) / n, 1),
"categories": len(cats),
"agent_created": sum(1 for x in nodes.values() if x.created_by == "agent"),
"used": sum(1 for x in nodes.values() if x.use_count > 0),
"top_categories": sorted(cats.items(), key=lambda kv: -kv[1])[:8],
}
def _memory_cards() -> list[dict[str, Any]]:
"""Freeform memory as readable cards.
``MEMORY.md`` / ``USER.md`` are prose split on bare ``§`` separators; each
chunk becomes one card. Every chunk is surfaced the graph shows everything.
"""
base = get_hermes_home() / "memories"
cards: list[dict[str, Any]] = []
for fname, source in (("MEMORY.md", "memory"), ("USER.md", "profile")):
path = base / fname
try:
text = path.read_text(encoding="utf-8").strip()
file_ts = _to_int_ts(path.stat().st_mtime)
except OSError:
continue
for chunk_idx, chunk in enumerate(c.strip() for c in text.split("\n§\n")):
if not chunk:
continue
first = chunk.splitlines()[0].strip().lstrip("# ").strip()
cards.append(
{
"source": source,
"timestamp": file_ts + chunk_idx if file_ts is not None else None,
"title": (first[:80] + "") if len(first) > 80 else first,
"body": chunk[:1200],
}
)
return cards
def _tokenize(text: str) -> set[str]:
return {t for t in re.split(r"[^a-z0-9]+", text.lower()) if len(t) >= 3}
def _memory_skill_edges(memory_cards: list[dict[str, Any]], skills: list[SkillNode]) -> list[tuple[str, str]]:
edges: list[tuple[str, str]] = []
skill_meta = [(s, _tokenize(s.name), s.name.lower()) for s in skills]
for idx, card in enumerate(memory_cards):
mem_id = f"memory:{card['source']}:{idx}"
text = f"{card.get('title', '')}\n{card.get('body', '')}".lower()
text_tokens = _tokenize(text)
scored: list[tuple[int, str]] = []
for skill, tokens, skill_name_lower in skill_meta:
score = 0
if skill_name_lower in text:
score += 6
score += len(tokens & text_tokens)
if score > 0:
scored.append((score, skill.name))
scored.sort(key=lambda x: (-x[0], x[1]))
for _, skill_name in scored[:4]:
edges.append((mem_id, skill_name))
return edges
def _skill_roots() -> list[tuple[str, Path]]:
repo = Path(__file__).resolve().parent.parent
home_skills = get_hermes_home() / "skills"
return [("base", repo / "skills"), ("profile", home_skills)]
def build_learning_graph() -> dict[str, Any]:
"""Full payload for the desktop learning panel.
Focus on what is profile-learned and actionable:
- skills that are NOT base-installed and show real learning signal
(agent-created or used),
- memory chunks as first-class graph nodes connected to those learned skills.
"""
all_skills = build_skill_nodes(_skill_roots())
learned_skills = {
name: node
for name, node in all_skills.items()
if node.source != "base" and (node.created_by == "agent" or node.use_count > 0)
}
skill_edges = build_edges(learned_skills)
memory_cards = _memory_cards()
memory_edges = _memory_skill_edges(memory_cards, list(learned_skills.values()))
edges = skill_edges + memory_edges
clusters: dict[str, int] = {}
for node in learned_skills.values():
clusters[node.category] = clusters.get(node.category, 0) + 1
if memory_cards:
clusters["memory"] = len(memory_cards)
graph_nodes = [
{
"id": n.name,
"label": n.name,
"kind": "skill",
"timestamp": n.timestamp,
"category": n.category,
"useCount": n.use_count,
"state": n.state,
"createdBy": n.created_by,
"pinned": n.pinned,
}
for n in learned_skills.values()
]
for i, card in enumerate(memory_cards):
graph_nodes.append(
{
"id": f"memory:{card['source']}:{i}",
"label": card["title"],
"kind": "memory",
"memorySource": card["source"],
"timestamp": card.get("timestamp"),
"category": "memory",
"useCount": 0,
"state": "active",
"createdBy": "memory",
"pinned": False,
}
)
return {
"nodes": graph_nodes,
"edges": [{"source": a, "target": b} for a, b in edges],
"clusters": [
{"category": c, "count": n}
for c, n in sorted(clusters.items(), key=lambda kv: -kv[1])
],
"memory": memory_cards,
"stats": {
**density_stats(learned_skills, skill_edges),
"memory_nodes": len(memory_cards),
"memory_skill_edges": len(memory_edges),
"learned_skills": len(learned_skills),
},
}
if __name__ == "__main__":
nodes = build_skill_nodes(_skill_roots())
print(json.dumps(density_stats(nodes, build_edges(nodes)), indent=2))

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