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
This PR fixes#32234 and improves HuggingFace chat model integration by:
Ensuring ChatHuggingFace inherits key parameters (temperature,
max_tokens, top_p, streaming, etc.) from the underlying LLM when not
explicitly set.
Adding and updating unit tests to verify property inheritance.
No breaking changes; these updates enhance reliability and
maintainability.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Hi there, I'm Célina from 🤗,
This PR introduces support for Hugging Face's serverless Inference
Providers (documentation
[here](https://huggingface.co/docs/inference-providers/index)), allowing
users to specify different providers for chat completion and text
generation tasks.
This PR also removes the usage of `InferenceClient.post()` method in
`HuggingFaceEndpoint`, in favor of the task-specific `text_generation`
method. `InferenceClient.post()` is deprecated and will be removed in
`huggingface_hub v0.31.0`.
---
## Changes made
- bumped the minimum required version of the `huggingface-hub` package
to ensure compatibility with the latest API usage.
- added a `provider` field to `HuggingFaceEndpoint`, enabling users to
select the inference provider (e.g., 'cerebras', 'together',
'fireworks-ai'). Defaults to `hf-inference` (HF Inference API).
- replaced the deprecated `InferenceClient.post()` call in
`HuggingFaceEndpoint` with the task-specific `text_generation` method
for future-proofing, `post()` will be removed in huggingface-hub
v0.31.0.
- updated the `ChatHuggingFace` component:
- added async and streaming support.
- added support for tool calling.
- exposed underlying chat completion parameters for more granular
control.
- Added integration tests for `ChatHuggingFace` and updated the
corresponding unit tests.
✅ All changes are backward compatible.
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Currently `_convert_TGI_message_to_LC_message` replaces `'` in the tool
arguments, so an argument like "It's" will be converted to `It"s` and
could cause a json parser to fail.
---------
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Vadym Barda <vadym@langchain.dev>
supports following UX
```python
class SubTool(TypedDict):
"""Subtool docstring"""
args: Annotated[Dict[str, Any], {}, "this does bar"]
class Tool(TypedDict):
"""Docstring
Args:
arg1: foo
"""
arg1: str
arg2: Union[int, str]
arg3: Optional[List[SubTool]]
arg4: Annotated[Literal["bar", "baz"], ..., "this does foo"]
arg5: Annotated[Optional[float], None]
```
- can parse google style docstring
- can use Annotated to specify default value (second arg)
- can use Annotated to specify arg description (third arg)
- can have nested complex types
Description:
1. partners/HuggingFace module support reading params from env. Not
adjust langchain_community/.../huggingfaceXX modules since they are
deprecated.
2. pydantic 2 @root_validator migration.
Issue: #22448#22819
---------
Co-authored-by: gongwn1 <gongwn1@lenovo.com>
- **Description:** A small fix where I moved the `available_endpoints`
in order to avoid the token error in the below issue. Also I have added
conftest file and updated the `scripy`,`numpy` versions to support newer
python versions in poetry files.
- **Issue:** #22804
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: ccurme <chester.curme@gmail.com>
**Updated ChatHuggingFace doc string as per issue #22296**:
"langchain_huggingface: updated docstring for ChatHuggingFace in
langchain_huggingface to match that of the description (in the appendix)
provided in issue #22296. "
**Issue:** This PR is in response to issue #22296, and more specifically
ChatHuggingFace model. In particular, this PR updates the docstring for
langchain/libs/partners/hugging_face/langchain_huggingface/chat_models/huggingface.py
by adding the following sections: Instantiate, Invoke, Stream, Async,
Tool calling, and Response metadata. I used the template from the
Anthropic implementation and referenced the Appendix of the original
issue post. I also noted that: langchain_community hugging face llms do
not work with langchain_huggingface's ChatHuggingFace model (at least
for me); the .stream(messages) functionality of ChatHuggingFace only
returned a block of response.
---------
Co-authored-by: lucast2021 <lucast2021@headroyce.org>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Added support for using HuggingFacePipeline in
ChatHuggingFace (previously it was only usable with API endpoints,
probably by oversight).
- **Issue:** #19997
- **Dependencies:** none
- **Twitter handle:** none
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
First Pr for the langchain_huggingface partner Package
- Moved some of the hugging face related class from `community` to the
new `partner package`
Still needed :
- Documentation
- Tests
- Support for the new apply_chat_template in `ChatHuggingFace`
- Confirm choice of class to support for embeddings witht he
sentence-transformer team.
cc : @efriis
---------
Co-authored-by: Cyril Kondratenko <kkn1993@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
