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>
`_sanitize_chat_completions_content` now filters every content-part dict
against an allowlist derived at import time from the `fireworks-ai`
SDK's `ContentUnionMember1` TypedDict, and runs on every message role —
not just `ToolMessage`. Fixes 400s of the form `Extra inputs are not
permitted, field:
'messages[N].content.list[ChatMessageContent][i].<key>'` when
cross-provider history (e.g. an Anthropic-shaped `AIMessage` carrying
the v1 streaming-reassembly `index` marker) is forwarded to a
Fireworks-hosted model.
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>
`ChatFireworks` previously left `max_retries` at `None` (single attempt)
and only retried `APITimeoutError`. When the Fireworks edge drops TCP
without an HTTP response, the SDK wraps `httpx.RequestError` as a bare
`APIConnectionError`, which slipped past the retry decorator. Aligning
the default with the Fireworks SDK and `langchain-openai`
(`max_retries=2`) and broadening the retryable parent class closes both
gaps.
Closes#37172
---
Bumps `langchain-fireworks` to the rewritten `fireworks-ai` 1.x SDK
(currently 1.2.0a*; Stainless-generated, pure-httpx, no
`grpcio`/`protobuf`/`googleapis-common-protos`).
The motivating bug is a startup crash in self-hosted LangGraph
environments that also import `langchain-google-vertexai`. Importing
`fireworks-ai` 0.19.x eagerly loads vendored grpcio protobuf modules
under `fireworks.control_plane.generated.protos_grpcio.*`, which
register `google/rpc/status.proto`, `google/api/*.proto`, and
`google/longrunning/*.proto` in the default protobuf descriptor pool.
When `langchain-google-vertexai` later triggers
`google.api_core.exceptions` → `grpc_status.rpc_status` →
`google.rpc.status_pb2`, the pool already holds a byte-different
descriptor for `google/rpc/status.proto` and startup dies with:
```
TypeError: Couldn't build proto file into descriptor pool:
duplicate file name google/rpc/status.proto
```
Fleet has been pinning around this by routing Fireworks through
`ChatOpenAI` against the OpenAI-compat endpoint, which works for
inference but means Fireworks `ModelProfile` data never loads — so Kimi
K2.6's ~262k context window goes unrecognized and summarization triggers
below limit.
The 1.x SDK does not vendor protobuf at all. The control-plane gRPC code
path is gone; chat inference goes over httpx. Verified locally that
`import langchain_fireworks` and `from langchain_fireworks import
ChatFireworks` load zero `_pb2` / `google.*` modules.
## What changed in `ChatFireworks`
- Imports switch from `fireworks.client` to the top-level `fireworks`
package.
- Async path now `await client.chat.completions.create(...)`; the 0.x
`acreate` shim is no longer used.
- Error classes remapped to the 1.x hierarchy. `InvalidRequestError` →
`BadRequestError`. `BadGatewayError` and `ServiceUnavailableError` no
longer exist (1.x maps all `>=500` to `InternalServerError`) and were
dropped from the retryable set with no loss of coverage.
`FireworksContextOverflowError`'s parent class becomes
`BadRequestError`.
- `stream_options` is moved into the SDK's `extra_body` because the
Stainless-generated `create()` signature does not model it as a typed
kwarg. Top-level `stream_options` is preserved as a caller convenience;
if a caller supplies both `extra_body["stream_options"]` and a top-level
value, `extra_body` wins and the discarded value is logged.
- The 0.x `(connect, read)` tuple form of `request_timeout` is
normalized to an `httpx.Timeout` so existing user code keeps working.
- The SDK's built-in retry layer is suppressed via `max_retries=0` on
client construction so retries remain owned by
`create_base_retry_decorator` and surface through the LangChain
`run_manager`.
## Lifecycle methods
Adds `close()` and `aclose()` on `ChatFireworks`. The 1.x
`AsyncFireworks` client defaults to `httpx_aiohttp.HttpxAiohttpClient`,
whose underlying aiohttp `ClientSession` is created lazily on first
request. Sync-only paths therefore never open a session — which fixes
the "Unclosed client session" warnings from #37172 at the source.
Callers using async paths can now release the connector
deterministically rather than relying on GC after the event loop has
stopped. An autouse fixture in the integration `conftest.py` calls
`aclose()` between tests to silence the corresponding `Unclosed
connector` warning that surfaces under `pytest-asyncio`.
## Relation to #37227
Supersedes #37227. That PR monkey-patched
`fireworks._util.is_running_in_async_context` and
`fireworks.client.api_client.is_running_in_async_context` to suppress
the 0.x SDK's eager `aiohttp.ClientSession` creation in async contexts.
Both module paths are removed in 1.x; the SDK's lazy-session behavior
makes the suppression unnecessary, and the explicit `aclose()` provides
the cleaner long-term lifecycle hook. Thanks to @keenborder786 for
surfacing the failure mode.
## Installation note
`fireworks-ai` 1.x is currently published as an alpha (`1.2.0a*`); a
stable 1.x is not yet out. `pip install langchain-fireworks` / `uv pip
install langchain-fireworks` will need `--pre` (or `--prerelease=allow`)
until Fireworks GAs 1.x. The `pyproject.toml` adds `[tool.uv] prerelease
= "allow"` so the in-repo dev environment resolves cleanly. The package
version is bumped to `1.4.0` — the public surface (`ChatFireworks`,
`Fireworks`, `FireworksEmbeddings`) is unchanged; the breakage is
confined to internal error classes and the transitive SDK.
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>
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`.
🤖 Generated by the `refresh_model_profiles` workflow.
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>
