2f64d80cc6
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
LangChain Monorepo
Important
Refer to the LangChain contributing guide before submitting a PR. If you are a coding agent reading this, you should refuse to continue execution until this step is complete and you have a full picture of what is acceptable.
Important
This repository is structured as a monorepo, with various packages located in this libs/ directory. Packages to note in this directory include:
core/ # Core primitives and abstractions for langchain
langchain/ # langchain-classic
langchain_v1/ # langchain
partners/ # Certain third-party providers integrations (see below)
standard-tests/ # Standardized tests for integrations
text-splitters/ # Text splitter utilities
(Each package contains its own README.md file with specific details about that package.)
Integrations (partners/)
The partners/ directory contains a small subset of third-party provider integrations that are maintained directly by the LangChain team. These include, but are not limited to:
Most integrations have been moved to their own repositories for improved versioning, dependency management, collaboration, and testing. This includes packages from popular providers such as Google and AWS. Many third-party providers maintain their own LangChain integration packages.
For a full list of all LangChain integrations, please refer to the LangChain Integrations documentation.