Fireworks's chat completions endpoint rejects unknown fields on tool
message content blocks — specifically the `id` key that LangChain
auto-generates on `TextContentBlock`. Add
`_sanitize_chat_completions_content` to strip those extra keys before
the payload hits the wire, preventing `Extra inputs are not permitted`
errors on tool message round-trips.
Add a `service_tier` init kwarg to `ChatFireworks`, mirroring the field
on `ChatOpenAI`. Forwards to the Fireworks chat completions API when
set, and echoes the response's tier back onto `response_metadata` and
`llm_output` so callbacks and consumers can read what the server
actually applied.
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
🤖 Generated by the `refresh_model_profiles` workflow.
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
## Summary
`langchain_fireworks._convert_message_to_dict` ships LangChain canonical
v0/v1 multimodal content blocks (e.g. `{"type": "image", "base64": ...,
"mime_type": ...}`) on the wire unchanged. Fireworks' OpenAI-compatible
chat completions API rejects the unknown `base64`/`mime_type` keys and
the list shape on roles that expect a string, returning HTTP 422 — so
any image upload, including via tools that return image content blocks,
fails for Kimi K2.6 and other Fireworks vision models.
This change mirrors
`langchain_openai.chat_models.base._format_message_content`:
- Walk `content` blocks.
- Drop block types the chat-completions wire doesn't carry (`tool_use`,
`thinking`, `reasoning_content`, `function_call`,
`code_interpreter_call`).
- Detect v0/v1 multimodal data blocks via
`langchain_core.messages.is_data_content_block`, and translate them via
`convert_to_openai_data_block(..., api="chat/completions")`.
- Strings and non-list content pass through unchanged.
Applied in the `ChatMessage`, `HumanMessage`, `SystemMessage`, and
`ToolMessage` paths of `_convert_message_to_dict`. `AIMessage` already
routes through `_convert_from_v1_to_chat_completions` for v1 output and
assistant content is text-only on the way out, so it is left untouched.
## Why this approach
Fireworks is OpenAI-compatible. The canonical → OpenAI translator
already exists in `langchain_core.messages.block_translators.openai` and
is the same one `langchain-openai` uses. Reusing it (rather than
inventing a Fireworks-specific translator) gives:
- v0 (`source_type`-based) and v1 (`base64`/`url`-based) data block
coverage for free.
- Consistent behavior with `langchain-openai` for image, file, and any
future canonical data block.
- A small, focused diff (≈30 lines of new code, plus tests).
## Test plan
- [x] `make test` passes (64/64 unit tests, including 9 new ones for the
new helper and translation paths).
- [x] `make lint` passes (ruff check, ruff format, mypy, lint_imports).
- [ ] End-to-end: image upload to a Kimi K2.6 (Fireworks) agent
translates to `{"type": "image_url", "image_url": {"url":
"data:image/png;base64,..."}}` on the wire and the model returns a
coherent description (validated locally against
`langchain-fireworks==1.0.0` site-packages with the same patch).
---------
Co-authored-by: murugand23 <murugand23@users.noreply.github.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
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Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
`ChatFireworks.max_retries` silently did nothing. The old code assigned
the value to a `ChatCompletionV2` sub-object rather than the base
client, and the pinned Fireworks SDK (0.13.0–0.19.20) never honors its
own `_max_retries` attribute on the base client either. Since the
Stainless-generated 1.x SDK that does implement retries is still
pre-release (1.0.1a63 at time of writing), retry responsibility is
ported to the LangChain side until the pin can be bumped.
Populate `usage_metadata` on streaming responses. Newer Fireworks models
(e.g. Kimi K2 slugs) require an explicit
`stream_options.include_usage=True` opt-in and return token counts in a
final empty-`choices` chunk; the chunk was previously `continue`-d past,
so streaming usage silently came back as `None`.
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
🤖 Generated by the `refresh_model_profiles` workflow.
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
🤖 Generated by the `refresh_model_profiles` workflow.
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
🤖 Generated by the `refresh_model_profiles` workflow.
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
🤖 Generated by the `refresh_model_profiles` workflow.
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
Automated refresh of model profile data for all in-monorepo partner
integrations via `langchain-profiles refresh`.
🤖 Generated by the `refresh_model_profiles` workflow.
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
PR #35788 added 7 new fields to the `langchain-profiles` CLI output
(`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`) but didn't update `ModelProfile` in
`langchain-core`. Partner packages like `langchain-aws` that set
`extra="forbid"` on their Pydantic models hit `extra_forbidden`
validation errors when Pydantic encountered undeclared TypedDict keys at
construction time. This adds the missing fields, makes `ModelProfile`
forward-compatible, provides a base-class hook so partners can stop
duplicating model-profile validator boilerplate, migrates all in-repo
partners to the new hook, and adds runtime + CI-time warnings for schema
drift.
## Changes
### `langchain-core`
- Add `__pydantic_config__ = ConfigDict(extra="allow")` to
`ModelProfile` so unknown profile keys pass Pydantic validation even on
models with `extra="forbid"` — forward-compatibility for when the CLI
schema evolves ahead of core
- Declare the 7 missing fields on `ModelProfile`: `name`, `status`,
`release_date`, `last_updated`, `open_weights` (metadata) and
`attachment`, `temperature` (capabilities)
- Add `_warn_unknown_profile_keys()` in `model_profile.py` — emits a
`UserWarning` when a profile dict contains keys not in `ModelProfile`,
suggesting a core upgrade. Wrapped in a bare `except` so introspection
failures never crash model construction
- Add `BaseChatModel._resolve_model_profile()` hook that returns `None`
by default. Partners can override this single method instead of
redefining the full `_set_model_profile` validator — the base validator
calls it automatically
- Add `BaseChatModel._check_profile_keys` as a separate
`model_validator` that calls `_warn_unknown_profile_keys`. Uses a
distinct method name so partner overrides of `_set_model_profile` don't
inadvertently suppress the check
### `langchain-profiles` CLI
- Add `_warn_undeclared_profile_keys()` to the CLI (`cli.py`), called
after merging augmentations in `refresh()` — warns at profile-generation
time (not just runtime) when emitted keys aren't declared in
`ModelProfile`. Gracefully skips if `langchain-core` isn't installed
- Add guard test
`test_model_data_to_profile_keys_subset_of_model_profile` in
model-profiles — feeds a fully-populated model dict to
`_model_data_to_profile()` and asserts every emitted key exists in
`ModelProfile.__annotations__`. CI fails before any release if someone
adds a CLI field without updating the TypedDict
### Partner packages
- Migrate all 10 in-repo partners to the `_resolve_model_profile()`
hook, replacing duplicated `@model_validator` / `_set_model_profile`
overrides: anthropic, deepseek, fireworks, groq, huggingface, mistralai,
openai (base + azure), openrouter, perplexity, xai
- Anthropic retains custom logic (context-1m beta → `max_input_tokens`
override); all others reduce to a one-liner
- Add `pr_lint.yml` scope for the new `model-profiles` package
Extract additional fields from models.dev into `_model_data_to_profile`:
`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`
Move the model profile refresh logic from an inline bash script in the
GitHub Actions workflow into a `make refresh-profiles` target in
`libs/model-profiles/Makefile`. This makes it runnable locally with a
single command and keeps the provider map in one place instead of
duplicated between CI and developer docs.
Add a `model` property to `ChatFireworks`, `ChatGroq`, and
`ChatOpenRouter` that returns `model_name`. These partners use
Pydantic's `Field(alias="model")` on `model_name`, which means
`instance.model` doesn't work as a read accessor after construction — it
raises an `AttributeError` or returns the field descriptor. `ChatOpenAI`
already has this property; this brings the remaining in-repo partners to
parity.
- Sort model profiles alphabetically by model ID (the top-level
`_PROFILES` dictionary keys, e.g. `claude-3-5-haiku-20241022`,
`gpt-4o-mini`) before writing `_profiles.py`, so that regenerating
profiles only shows actual data changes in diffs — not random reordering
from the models.dev API response order
- Regenerate all 10 partner profile files with the new sorted ordering
- Add `text_inputs` and `text_outputs` fields to `ModelProfile`
- Regenerate `_profiles.py` for all providers
## Why
models.dev data includes `'text'` as both an input and output modality,
but we didn't capture it.
models.dev broadly contains models without text input (Whisper/ASR) and
without text output (image generators, TTS).
Without this, downstream consumers can't filter on model text support
(e.g. preventing users from passing text input to an audio-only model).
---
We'd need to also run for Google, AWS and cut releases for all to
propagate
Extract strict from kwargs and pass it to convert_to_openai_tool when
converting tools. This ensures that when strict is provided, it's
properly used during tool conversion and removed from kwargs before
calling the parent bind method.
Also extract reasoning_content from API responses and store it in
additional_kwargs for AIMessage objects.
Fixes https://github.com/langchain-ai/langchain/issues/34341 and
https://github.com/langchain-ai/langchain/issues/34342
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Ensures proper reStructuredText formatting by adding the required blank
line before closing docstring quotes, which resolves the "Block quote
ends without a blank line; unexpected unindent" warning.
