mirror of
https://github.com/andrewyng/openworker.git
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Rohit C Prasad
979badbd3c
Normalized TokenUsage (input/output/cache split) captured in every provider's stream and complete paths, persisted as an assistant-message sidecar and sent on the assistant_message event; matrix gains verified context-window sizes.
227 lines
11 KiB
Python
227 lines
11 KiB
Python
"""The curated model matrix — the only models we actively suggest, label, and vouch for.
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Keyed by the FULL routed id, exactly as the ProviderRouter receives it — including reseller
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"ugly names" like ``together:zai-org/GLM-5.2`` (bare ids route to the OpenAI default). Each
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entry carries the UI display label and the model's capabilities, making this the single
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source of truth the capability probe and the GUI's pickers read from.
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Deliberately SMALL (owner call, 2026-07-04): current-generation, agent-capable (tool-calling)
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models only. It is not user-editable — users can still add any custom model string, which
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falls back to the conservative heuristics in ``capabilities.py`` at their own risk of
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degraded results. Ids verified against vendor/reseller catalogs on 2026-07-04; refresh the
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reseller rows when catalogs rotate (they rename on every model generation).
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Context windows (``context_window``, tokens) feed the GUI's context-fill meter. Entries
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where the vendor spec wasn't re-checked stay ``None`` — the meter simply hides rather than
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showing a made-up denominator. Values entered 2026-07-28 from vendor docs; verify alongside
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the id refresh.
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Resellers: Together + Fireworks + OpenRouter. TODO: add Groq entries here AND its
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descriptor in ``registry.py`` once the current provider surface is tested — deliberately
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deferred to bound how much needs verifying at once.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Optional
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from .base import ModelCapabilities
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_AGENTIC = ModelCapabilities(
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tools=True, vision=False, parallel_tool_calls=True, streaming=True
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)
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# The native three (OpenAI, Anthropic, Gemini) all take PDFs directly; every
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# OpenAI-compatible vendor and reseller in the matrix does not (their chat APIs have
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# no inline file part — checked 2026-07-17), so those fall back via pdf_support.py.
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_AGENTIC_VISION = ModelCapabilities(
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tools=True, vision=True, pdf=True, parallel_tool_calls=True, streaming=True
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)
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@dataclass(frozen=True)
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class ModelEntry:
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label: str # UI display name, e.g. "GLM-5.2 · via Together"
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caps: ModelCapabilities = _AGENTIC
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# Max context length in tokens (prompt side), for the GUI's context-fill meter.
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# None = not verified against the vendor spec yet; the meter hides.
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context_window: Optional[int] = None
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MATRIX: dict[str, ModelEntry] = {
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# -- first-party ------------------------------------------------------------
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# GPT-5.6 (2026-07-09): number = generation, Sol/Terra/Luna = capability tiers.
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# Bare "gpt-5.6" aliases to Sol server-side; we list the explicit tier ids only.
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# Rolling out — accounts without access get a friendly error (providers/errors.py).
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"gpt-5.6-sol": ModelEntry("GPT-5.6 Sol · OpenAI", _AGENTIC_VISION, 400_000),
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"gpt-5.6-terra": ModelEntry("GPT-5.6 Terra · OpenAI", _AGENTIC_VISION, 400_000),
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"gpt-5.6-luna": ModelEntry("GPT-5.6 Luna · OpenAI", _AGENTIC_VISION, 400_000),
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"gpt-5.5": ModelEntry("GPT-5.5 · OpenAI", _AGENTIC_VISION, 400_000),
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# Fable 5 (2026-06-09) is GA; its Mythos 5 sibling is approved-orgs-only, so it
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# stays out of a picker meant for the public.
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"anthropic:claude-fable-5": ModelEntry(
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"Claude Fable 5 · Anthropic", _AGENTIC_VISION, 1_000_000
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),
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"anthropic:claude-opus-4-8": ModelEntry(
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"Claude Opus 4.8 · Anthropic", _AGENTIC_VISION, 200_000
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),
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"anthropic:claude-sonnet-4-6": ModelEntry(
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"Claude Sonnet 4.6 · Anthropic", _AGENTIC_VISION, 200_000
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),
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"anthropic:claude-haiku-4-5": ModelEntry(
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"Claude Haiku 4.5 · Anthropic", _AGENTIC_VISION, 200_000
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),
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# Gemini 3 (thought signatures required in tool loops — carried via the `_gemini`
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# message sidecar, see gemini_provider.py; ids from the vendor catalog 2026-07-22).
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"gemini:gemini-3.1-pro-preview": ModelEntry(
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"Gemini 3.1 Pro · Google", _AGENTIC_VISION, 1_048_576
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),
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"gemini:gemini-3.6-flash": ModelEntry(
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"Gemini 3.6 Flash · Google", _AGENTIC_VISION, 1_048_576
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),
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"gemini:gemini-2.5-pro": ModelEntry(
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"Gemini 2.5 Pro · Google", _AGENTIC_VISION, 1_048_576
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),
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"gemini:gemini-2.5-flash": ModelEntry(
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"Gemini 2.5 Flash · Google", _AGENTIC_VISION, 1_048_576
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),
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# -- direct OpenAI-compatible vendors ----------------------------------------
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# Muse Spark (Meta Model API, public preview 2026-07-09): multimodal + tools via
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# their OpenAI-compat surface. Vision yes; PDFs unverified over compat — falls
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# back via pdf_support.py like the other compat vendors.
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"meta:muse-spark-1.1": ModelEntry(
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"Muse Spark 1.1 · Meta",
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ModelCapabilities(
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tools=True, vision=True, parallel_tool_calls=True, streaming=True
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),
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),
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"zai:glm-5.2": ModelEntry("GLM-5.2 · Z AI", _AGENTIC, 128_000),
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"deepseek:deepseek-v4-flash": ModelEntry(
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"DeepSeek V4 Flash · DeepSeek", _AGENTIC, 128_000
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),
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"deepseek:deepseek-v4-pro": ModelEntry(
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"DeepSeek V4 Pro · DeepSeek", _AGENTIC, 128_000
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),
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"kimi:kimi-k2.6": ModelEntry("Kimi K2.6 · Moonshot", _AGENTIC, 256_000),
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"minimax:MiniMax-M2.5": ModelEntry("MiniMax M2.5 · MiniMax"),
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"qwen:qwen3-max": ModelEntry("Qwen3 Max · Alibaba", _AGENTIC, 256_000),
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"xai:grok-4.3": ModelEntry("Grok 4.3 · xAI", _AGENTIC, 256_000),
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"mistral:mistral-large-latest": ModelEntry(
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"Mistral Large · Mistral", _AGENTIC, 128_000
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),
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# -- resellers (their model namespaces, verbatim) -----------------------------
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"together:thinkingmachines/Inkling": ModelEntry("Inkling · via Together"),
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"together:zai-org/GLM-5.2": ModelEntry("GLM-5.2 · via Together", _AGENTIC, 128_000),
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# Kimi K3 (2026-07-16) is not on Together yet — weights land ~07-27; revisit then.
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"together:moonshotai/Kimi-K2.7-Code": ModelEntry(
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"Kimi K2.7 Code · via Together", _AGENTIC, 256_000
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),
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"together:moonshotai/Kimi-K2.6": ModelEntry(
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"Kimi K2.6 · via Together", _AGENTIC, 256_000
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),
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"together:deepseek-ai/DeepSeek-V4-Pro": ModelEntry(
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"DeepSeek V4 Pro · via Together", _AGENTIC, 128_000
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),
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"together:meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8": ModelEntry(
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"Llama 4 Maverick · via Together", _AGENTIC, 1_000_000
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),
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"fireworks:accounts/fireworks/models/glm-5p2": ModelEntry(
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"GLM-5.2 · via Fireworks", _AGENTIC, 128_000
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),
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"fireworks:accounts/fireworks/models/kimi-k2p6": ModelEntry(
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"Kimi K2.6 · via Fireworks", _AGENTIC, 256_000
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),
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"fireworks:accounts/fireworks/models/deepseek-v4-pro": ModelEntry(
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"DeepSeek V4 Pro · via Fireworks", _AGENTIC, 128_000
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),
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"fireworks:accounts/fireworks/models/llama4-maverick-instruct-basic": ModelEntry(
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"Llama 4 Maverick · via Fireworks", _AGENTIC, 1_000_000
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),
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# OpenRouter slugs are lowercase `<lab>/<model>` (checked against their catalog
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# 2026-07-25); same labs as above, one key for all of them.
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"openrouter:z-ai/glm-5.2": ModelEntry("GLM-5.2 · via OpenRouter", _AGENTIC, 128_000),
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"openrouter:moonshotai/kimi-k2.6": ModelEntry(
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"Kimi K2.6 · via OpenRouter", _AGENTIC, 256_000
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),
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"openrouter:deepseek/deepseek-v4-pro": ModelEntry(
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"DeepSeek V4 Pro · via OpenRouter", _AGENTIC, 128_000
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),
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"openrouter:meta-llama/llama-4-maverick": ModelEntry(
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"Llama 4 Maverick · via OpenRouter", _AGENTIC, 1_000_000
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),
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# -- cloud accounts (models running in the user's own AWS/GCP) ----------------
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# Bedrock ids carry a family segment (claude/ → native Anthropic path, other/ →
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# Converse) plus AWS's own `-v<n>:<m>` version suffix. Some regions require the
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# `us.`/`eu.` cross-region inference-profile prefix — custom add-model accepts those.
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"bedrock:claude/anthropic.claude-sonnet-4-6-v1:0": ModelEntry(
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"Claude Sonnet 4.6 · AWS Bedrock", _AGENTIC_VISION, 200_000
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),
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"bedrock:claude/anthropic.claude-haiku-4-5-v1:0": ModelEntry(
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"Claude Haiku 4.5 · AWS Bedrock", _AGENTIC_VISION, 200_000
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),
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"bedrock:other/amazon.nova-2-pro-v1:0": ModelEntry(
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"Nova 2 Pro · AWS Bedrock", _AGENTIC, 300_000
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),
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"bedrock:other/meta.llama4-maverick-17b-instruct-v1:0": ModelEntry(
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"Llama 4 Maverick · AWS Bedrock", _AGENTIC, 1_000_000
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),
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"bedrock:other/mistral.mistral-large-3-v1:0": ModelEntry(
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"Mistral Large 3 · AWS Bedrock", _AGENTIC, 128_000
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),
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# Live-verified on Converse 2026-07-26 (complete/stream/tool round trip); asked for
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# two tool calls it emits them one at a time, so parallel stays off.
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"bedrock:other/nvidia.nemotron-super-3-120b": ModelEntry(
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"Nemotron Super 3 120B · AWS Bedrock",
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ModelCapabilities(
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tools=True, vision=False, parallel_tool_calls=False, streaming=True
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),
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),
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# Vertex ids carry a family segment too (gemini/ and claude/ → native paths,
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# openweight/ → the MaaS OpenAI-compat endpoint, keeping the publisher segment).
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"vertex:gemini/gemini-3.1-pro-preview": ModelEntry(
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"Gemini 3.1 Pro · Vertex AI", _AGENTIC_VISION, 1_048_576
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),
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"vertex:gemini/gemini-3.6-flash": ModelEntry(
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"Gemini 3.6 Flash · Vertex AI", _AGENTIC_VISION, 1_048_576
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),
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"vertex:claude/claude-sonnet-4-6": ModelEntry(
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"Claude Sonnet 4.6 · Vertex AI", _AGENTIC_VISION, 200_000
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),
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"vertex:claude/claude-haiku-4-5": ModelEntry(
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"Claude Haiku 4.5 · Vertex AI", _AGENTIC_VISION, 200_000
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),
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"vertex:openweight/meta/llama-4-maverick-17b-128e-instruct-maas": ModelEntry(
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"Llama 4 Maverick · Vertex AI", _AGENTIC, 1_000_000
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),
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"vertex:openweight/qwen/qwen3-coder-480b-a35b-instruct-maas": ModelEntry(
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"Qwen3 Coder · Vertex AI", _AGENTIC, 256_000
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),
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}
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def entry_for(model: str) -> ModelEntry | None:
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return MATRIX.get(model)
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def model_labels() -> dict[str, str]:
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"""Full-id → display-label map, shipped to the GUI so every picker shows human names."""
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return {mid: e.label for mid, e in MATRIX.items()}
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def model_context_windows() -> dict[str, int]:
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"""Full-id → context-window map (verified entries only), for the GUI's fill meter."""
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return {
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mid: e.context_window for mid, e in MATRIX.items() if e.context_window
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}
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def models_for_provider(provider: str) -> list[str]:
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"""BARE model ids (prefix stripped) the matrix curates for a provider — feeds the
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Settings pane's suggestions and the composer picker so both stay in lockstep with the
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matrix. OpenAI entries are stored without a prefix (bare ids route to the OpenAI
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default), so its list is every un-prefixed id."""
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if provider == "openai":
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return [mid for mid in MATRIX if ":" not in mid]
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prefix = provider + ":"
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return [mid[len(prefix) :] for mid in MATRIX if mid.startswith(prefix)]
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