James RussoandClaude Opus 4.7 6d2569c6bb test(producer): add webm-vp9 distributed regression fixture (#952)
* feat(producer): enable webm in distributed mode via concat-copy

PR 8.2 of the WebM distributed-rendering plan (v1.5 backlog #1; see
DISTRIBUTED-RENDERING-PLAN.md §7.2). Wires libvpx-vp9 webm through the
distributed pipeline now that PR 8.1 proved concat-copy works.

Architectural decision: Path A (concat-copy) — based on PR 8.1's smoke
test result (9/9 tests pass for both yuv420p and yuva420p VP9 streams).
The simpler architecture wins; no re-encode in assemble, no encode-
parallelism loss.

Changes:

- plan.ts:
  - DistributedRenderConfig.format and PlanResult.format now include
    "webm" — type-level acceptance matches the runtime gate.
  - rejectUnsupportedDistributedFormat() no longer trips on webm. HDR
    mp4 remains the only refused configuration.
  - resolveEncoderTriple() returns libvpx-vp9-software + yuva420p +
    preset="good" for format="webm". yuva420p preserves alpha — the
    format's main reason for existing for web delivery.
  - codec= remains rejected for non-mp4 formats (mov is always ProRes
    4444; webm is always libvpx-vp9). The error message lists all four
    distributed-supported formats.
  - FormatNotSupportedInDistributedError docstring updated to reflect
    the new reality (only HDR is unsupported).

- freezePlan.ts: LockedRenderConfig.encoder gains "libvpx-vp9-software".
  Mirrors libx265-software / prores-software / png-sequence in shape;
  the chunk worker reads this discriminant to decide encode args.

- renderChunk.ts: drops the now-incorrect cast that excluded webm from
  buildSyntheticRenderJob's format input; tightens the preset-format
  cast to include webm.

- assemble.ts: docstring + comment updates. The mp4/mov concat-copy
  path is format-agnostic — webm uses the exact same code (applyFaststart
  is a no-op for webm via the existing chunkEncoder.ts gate;
  muxVideoWithAudio already routes webm to libopus audio).

- planFormatBanlist.test.ts: webm-rejection tests removed; replaced with
  "accepts webm" tests + a HDR+webm combo test that verifies HDR is the
  trip regardless of format.

- plan.test.ts: new describe block pins the webm wiring contract:
  format="webm" produces an encoder=libvpx-vp9-software /
  pixelFormat=yuva420p planDir with closedGop=true and gopSize=chunkSize.

- webm-concat-copy.test.ts (smoke): extended with a yuva420p variant
  that proves the alpha pixel format the distributed pipeline actually
  emits also round-trips through concat-copy. 9/9 tests pass locally.

§8 format support matrix in DISTRIBUTED-RENDERING-PLAN.md is intentionally
left unchanged at this PR — it flips to ✓ in PR 8.4 once the end-to-end
fixture (PR 8.3) is green.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(producer): include webm in plan-time needsAlpha + strengthen alpha smoke

PR review feedback from Miguel and Vai on #951 caught a real bug:
`plan.ts`'s `needsAlpha` disjunction excluded `"webm"`, so the plan
stage froze `forceScreenshot: false` into the `LockedRenderConfig`
even though distributed webm uses `yuva420p`. Every chunk worker
captured opaque RGB via BeginFrame (which doesn't preserve alpha on
Linux headless-shell), and libvpx-vp9 encoded uniformly-opaque alpha
that the encoder then dropped — producing un-keyable webm.

Two changes:

1. **plan.ts**: include `"webm"` in `needsAlpha`. Matches the
   in-process renderer's logic at `renderOrchestrator.ts:1469`
   (`const needsAlpha = isWebm || isMov || isPngSequence`); the two
   sites must stay in sync since the distributed pipeline's PSNR
   regression compares against the in-process baseline.

2. **Smoke test (yuva420p describe)**: source frames now use a real
   alpha gradient (`geq=a='X*255/W'` on top of `testsrc2`) instead of
   `testsrc2 + format=rgba` which was uniformly opaque. The decode-
   pix_fmt assertion is dropped (ffprobe reports `yuv420p` for
   VP9-with-alpha because the alpha lives in a Matroska
   `BlockAdditional` sidecar) and replaced with two stronger checks:
   - `TAG:ALPHA_MODE=1` is present on the stream — proves the
     encoder was actually configured for alpha
   - alpha plane variance after `-c:v libvpx-vp9 -i ... -pix_fmt rgba
     -vf extractplanes=a,signalstats` — proves the alpha sub-stream
     round-trips through concat-copy with spatially-varying content,
     not uniform/dropped alpha
   - decode-test gate is now exit-code-only (was `exitCode || stderr`
     which would flake on chatty ffmpeg `-v error` builds emitting
     non-fatal DTS/container notes)

These checks would have caught the `needsAlpha` bug before review.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(aws-lambda): widen narrow format types to include webm

CI on PR #951 was failing at typecheck/build because the producer's
`DistributedRenderConfig.format` widened to include webm in this PR
but the aws-lambda package's narrow `"mp4" | "mov" | "png-sequence"`
type literals in `events.ts`, `handler.ts`, and `validateConfig.ts`
hadn't kept up. `renderToLambda.ts:87` passed `config.format` (now
including webm) into a parameter typed against the narrow union,
producing TS2345.

This widening originally landed in PR #952 (test fixture PR) but
needs to be atomic with the producer's widening here to keep each
PR independently typecheck-clean.

Also refactor `formatExtension` from a switch dispatch to a
`Record<DistributedFormat, string>` lookup. Adding the webm case
tipped the switch's CRAP to the 30.0 fallow threshold; the lookup
table drops cyclomatic from 5 to 1 with the same compile-time
exhaustiveness guarantee (TS errors on missing entries when
`DistributedFormat` adds a new format). The runtime
`_exhaustive: never` throw was only protecting against a string
slipping past TS; `validateConfig.ts`'s `ALLOWED_FORMATS` already
gates untrusted input at the SDK boundary.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* test(producer): add webm-vp9 distributed regression fixture

PR 8.3 of the WebM distributed-rendering plan (v1.5 backlog #1; see
DISTRIBUTED-RENDERING-PLAN.md §7.2). End-to-end regression coverage for
the webm distributed path PRs 8.1 and 8.2 wired up.

Adds packages/producer/tests/distributed/webm-vp9/ matching the
mp4-h264-sdr fixture pattern: a 2-second composition (60 frames @ 30fps)
with text, a crossfade across the frame-30 chunk seam, and a continuous
icon rotation — exercises chunk-boundary continuity for both display
contents and VP9 closed-GOP alpha encoding. `chunkSize: 15` produces 4
chunks so 3 seams are tested, and the crossfade straddles the middle
seam to surface alpha-plane discontinuities introduced by alt-ref drift.

Baseline regenerated inside Dockerfile.test via
`bun run --cwd packages/producer docker:test:update webm-vp9`. Runs in:

  - in-process mode: byte-identical match against baseline ✓
  - distributed-simulated mode: PSNR 56.88-63.49 dB across 100
    checkpoints, well above the 30 dB threshold ✓

Wiring updates required to let webm flow through the harness:

- regression-harness-distributed.ts:
  - checkDistributedSupport() no longer rejects webm. HDR mp4 + NTSC
    fps + non-{24,30,60} fps remain rejected.
  - RunDistributedSimulatedInput.format widened to include webm.
  - Docstring + comments updated.

- regression-harness-distributed.test.ts: webm-rejection test replaced
  with "accepts format=webm" test.

- regression-harness.ts: the now-incorrect format cast at the
  distributed-input call site is dropped; comment about why webm was
  excluded is replaced with "webm is now distributed-supported".

- regression-harness-lambda-local-types.ts: RunLambdaLocalInput.format
  widened to include webm so lambda-local mode can also exercise webm
  fixtures end-to-end.

- aws-lambda webm support (Path A through the Lambda handler):
  - formatExtension.ts: DistributedFormat gains "webm" → ".webm" case.
  - events.ts: RenderChunkEvent / AssembleEvent / PlanLambdaResult
    Format widened to include webm.
  - sdk/validateConfig.ts: ALLOWED_FORMATS gains "webm".
  - handler.ts: downloadChunkObjects format param widened.

The Lambda handler delegates to the producer's assemble() primitive
which PR 8.2 already taught to handle webm (concat-copy + applyFaststart
no-op + muxVideoWithAudio with libopus); no Lambda-side rendering
changes are needed beyond the type/validation surfaces above.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs(aws-lambda): drop stale webm rejection from validateConfig docblock

PR #952 review nit (Miguel): the validateConfig.ts file-header comment
still claimed the SDK rejects webm, but the runtime check no longer
does (ALLOWED_FORMATS now includes 'webm'). Update the docblock to
reflect that only force-hdr remains an SDK-side rejection.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* ci(regression): add webm-vp9 to shard-3 + refactor formatExtension

Three follow-ups bundled together (Vai's review feedback on PR #952
plus the fallow audit finding that surfaced when the webm case was
added):

1. **Wire webm-vp9 into CI regression.** The fixture was added in this
   PR but never appeared in any `.github/workflows/regression.yml`
   shard's args allowlist, so the regression harness's positional-args
   gate skipped it in CI. Append `webm-vp9` to shard-3 (which already
   carries `mp4-h264-sdr` + `webm-transparency`) so the fixture runs.

2. **Fix stale "four hard gates" prose in checkDistributedSupport
   docstring.** Earlier in the stack I removed the webm bullet but
   didn't update the count. Two gates remain (fps + hdr).

3. **Refactor `formatExtension` from switch to lookup table.** Adding
   the webm case made the switch dispatch's CRAP score hit 30.0
   (cyclomatic = 5, plus the function's small body). Replaced with a
   `Record<DistributedFormat, string>` lookup, which:
   - drops cyclomatic from 5 → 1,
   - keeps exhaustiveness enforcement at compile time (TS errors if
     a new format gets added to `DistributedFormat` without a
     matching key in the Record literal),
   - drops the runtime `_exhaustive: never` throw, which was only
     guarding against an arbitrary string slipping past TS — a
     caller-side concern, not this function's job.

   The function now reads as a table lookup, which matches what it
   actually does, and the fallow audit now reports zero new
   complexity findings (down from 1).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-19 03:13:30 -04:00
2026-05-18 20:07:08 +00:00
2026-03-21 22:43:56 -07:00

HyperFrames

npm version npm downloads License Node.js Discord

Write HTML. Render video. Built for agents.

HyperFrames demo — HTML code on the left transforms into a rendered video on the right

Hyperframes is an open-source video rendering framework that lets you create, preview, and render HTML-based video compositions — with first-class support for AI agents.

Quick Start

Install the HyperFrames skills, then describe the video you want:

npx skills add heygen-com/hyperframes

This teaches your agent (Claude Code, Cursor, Gemini CLI, Codex) how to write correct compositions, GSAP timelines, Tailwind v4 browser-runtime styles, and first-party adapter animations. In Claude Code, the skills register as slash commands — invoke /hyperframes to author compositions, /hyperframes-cli for the dev-loop commands (init, lint, preview, render), /hyperframes-media for asset preprocessing (TTS, transcription, background removal), /tailwind for init --tailwind projects, /gsap for timeline animation help, or the adapter skills (/animejs, /css-animations, /lottie, /three, /waapi) when a composition uses those runtimes.

For Claude Design, open docs/guides/claude-design-hyperframes.md on GitHub and click the download button (↓) to save it, then attach the file to your Claude Design chat. It produces a valid first draft; refine in any AI coding agent. See the Claude Design guide.

For Codex specifically, the same skills are also exposed as an OpenAI Codex plugin — sparse-install just the plugin surface:

codex plugin marketplace add heygen-com/hyperframes --sparse .codex-plugin --sparse skills --sparse assets

For Claude Code, the repo also ships a Claude Code plugin manifest: test it locally with claude --plugin-dir .. The manifest intentionally omits skills because Claude Code auto-discovers the root skills/ directory by convention, and for marketplace submission use the title HyperFrames by HeyGen plus the black/white icon assets at assets/claude-code-icon-dark.svg and assets/claude-code-icon-light.svg for the two theme slots. For Cursor, the same skills are packaged as a Cursor plugin — install from the Cursor Marketplace, or sideload by cloning this repo and pointing Settings → Plugins → Load unpacked at the repo root.

Try it: example prompts

Copy any of these into your agent to get started. The /hyperframes prefix loads the skill context explicitly so you get correct output the first time.

Cold start — describe what you want:

Using /hyperframes, create a 10-second product intro with a fade-in title, a background video, and background music.

Warm start — turn existing context into a video:

Take a look at this GitHub repo https://github.com/heygen-com/hyperframes and explain its uses and architecture to me using /hyperframes.

Summarize the attached PDF into a 45-second pitch video using /hyperframes.

Turn this CSV into an animated bar chart race using /hyperframes.

Format-specific:

Make a 9:16 TikTok-style hook video about [topic] using /hyperframes, with bouncy captions synced to a TTS narration.

Iterate — talk to the agent like a video editor:

Make the title 2x bigger, swap to dark mode, and add a fade-out at the end.

Add a lower third at 0:03 with my name and title.

The agent handles scaffolding, animation, and rendering. See the prompting guide for more patterns.

Option 2: Start a project manually

npx hyperframes init my-video
cd my-video
npx hyperframes preview      # preview in browser (live reload)
npx hyperframes render       # render to MP4

hyperframes init installs skills automatically, so you can hand off to your AI agent at any point.

Requirements: Node.js >= 22, FFmpeg

Why Hyperframes?

  • HTML-native — compositions are HTML files with data attributes. No React, no proprietary DSL.
  • AI-first — agents already speak HTML. The CLI is non-interactive by default, designed for agent-driven workflows.
  • Deterministic rendering — same input = identical output. Built for automated pipelines.
  • Frame Adapter pattern — bring your own animation runtime (GSAP, Lottie, CSS, Three.js).

Hyperframes vs Remotion

Hyperframes is inspired by Remotion — we used Remotion at HeyGen in production, learned a ton from it, and kept attribution comments in the source for the patterns it pioneered (Chrome launch flags, image2pipe → FFmpeg streaming, frame buffering). Both tools drive headless Chrome and both are deterministic. They differ on one decision: what the primary author writes. Remotion's bet is React components; Hyperframes' bet is HTML.

Hyperframes Remotion
Authoring HTML + CSS + GSAP React components (TSX)
Build step None; index.html plays as-is Required (bundler)
Library-clock animations (GSAP, Anime.js, Motion One) Seekable, frame-accurate Plays at wall-clock during render
Arbitrary HTML / CSS passthrough Paste and animate Rewrite as JSX
Distributed rendering Single-machine today Lambda, production-ready

Licensing: fully open source vs source-available

Hyperframes is completely open source under Apache 2.0 — an OSI-approved license. Use it commercially at any scale, with no per-render fees, no seat caps, no company-size thresholds.

Remotion is source-available, not open source. The code is on GitHub under a custom Remotion License that requires a paid company license above small-team thresholds. It's a great product with a real team behind it — but if open-source licensing matters to you (OSI compliance, redistribution rights, no per-use fees), that's a first-order decision point.

Full write-up with benchmarks, an honest list of where each tool wins, and a GSAP side-by-side: Hyperframes vs Remotion guide.

How It Works

Define your video as HTML with data attributes:

<div id="stage" data-composition-id="my-video" data-start="0" data-width="1920" data-height="1080">
  <video
    id="clip-1"
    data-start="0"
    data-duration="5"
    data-track-index="0"
    src="intro.mp4"
    muted
    playsinline
  ></video>
  <img
    id="overlay"
    class="clip"
    data-start="2"
    data-duration="3"
    data-track-index="1"
    src="logo.png"
  />
  <audio
    id="bg-music"
    data-start="0"
    data-duration="9"
    data-track-index="2"
    data-volume="0.5"
    src="music.wav"
  ></audio>
</div>

Preview instantly in the browser. Render to MP4 locally or in Docker.

Catalog

50+ ready-to-use blocks and components — social overlays, shader transitions, data visualizations, and cinematic effects:

npx hyperframes add flash-through-white   # shader transition
npx hyperframes add instagram-follow      # social overlay
npx hyperframes add data-chart            # animated chart

Browse the full catalog at hyperframes.heygen.com/catalog.

Documentation

Full documentation at hyperframes.heygen.com/introductionQuickstart | Guides | API Reference | Catalog

Packages

Package Description
hyperframes CLI — create, preview, lint, and render compositions
@hyperframes/core Types, parsers, generators, linter, runtime, frame adapters
@hyperframes/engine Seekable page-to-video capture engine (Puppeteer + FFmpeg)
@hyperframes/producer Full rendering pipeline (capture + encode + audio mix)
@hyperframes/studio Browser-based composition editor UI
@hyperframes/player Embeddable <hyperframes-player> web component
@hyperframes/shader-transitions WebGL shader transitions for compositions

Skills

HyperFrames ships skills that teach AI agents framework-specific patterns that generic docs don't cover.

npx skills add heygen-com/hyperframes
Skill What it teaches
hyperframes HTML composition authoring, captions, TTS, audio-reactive animation, transitions
hyperframes-cli Dev-loop CLI: init, lint, inspect, preview, render, doctor
hyperframes-media Asset preprocessing: tts (Kokoro), transcribe (Whisper), remove-background (u2net) — voice/model/codec selection
hyperframes-registry Block and component installation via hyperframes add
website-to-hyperframes Capture a URL and turn it into a video — full website-to-video pipeline
remotion-to-hyperframes Translate a Remotion (React) composition into a HyperFrames HTML composition
gsap GSAP timelines for HyperFrames: paused registration, deterministic seeking, easing, sequencing, performance
animejs Anime.js animations and timelines registered on window.__hfAnime for deterministic HyperFrames seeking
css-animations CSS keyframe animation patterns that HyperFrames can discover, pause, and seek
lottie lottie-web and dotLottie players registered on window.__hfLottie with local assets and paused playback
three Three.js scenes that render from HyperFrames hf-seek events and window.__hfThreeTime instead of wall-clock time
waapi Web Animations API element.animate() patterns seeked through document.getAnimations()

Contributing

See CONTRIBUTING.md for guidelines.

Cloning the repo

The repo uses Git LFS for golden regression-test baselines under packages/producer/tests/**/output.mp4 (~240 MB of .mp4 files). If you're cloning the full repo for development, install Git LFS first:

# macOS
brew install git-lfs

# Ubuntu/Debian
sudo apt install git-lfs

# Windows
winget install GitHub.GitLFS
# (or install Git for Windows, which bundles Git LFS as an optional component)

# Then (once, per machine)
git lfs install

If you hit git-lfs filter-process: command not found during git clone or npx skills add heygen-com/hyperframes, install Git LFS and retry. You can also skip LFS content if you only need the source files:

GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/heygen-com/hyperframes.git

License

Apache 2.0

S
Description
Write HTML. Render video. Built for agents.
Readme
581 MiB
Languages
TypeScript 86%
JavaScript 9.3%
CSS 4.1%
Shell 0.3%
Python 0.2%