dde2012b83
Closes https://github.com/langchain-ai/langchain/issues/33956 * Making `ModelRequest` generic on `ContextT` and `ResponseT` so that we can thread type information through to `wrap_model_call` * Making builtin middlewares generic on `ContextT` and `ResponseT` so their context and response types can be inferred from the `create_agent` signature See new tests that verify backwards compatibility (for cases where folks use custom middleware that wasn't parametrized). This fixes: 1. Lack of access to context and response types in `wrap_model_call` 2. Lack of cohesion between middleware context + response types with those specified in `create_agent` See examples below: ### Type-safe context and response access ```python class MyMiddleware(AgentMiddleware[AgentState[AnalysisResult], UserContext, AnalysisResult]): def wrap_model_call( self, request: ModelRequest[UserContext], handler: Callable[[ModelRequest[UserContext]], ModelResponse[AnalysisResult]], ) -> ModelResponse[AnalysisResult]: # ✅ Now type-safe: IDE knows user_id exists and is str user_id: str = request.runtime.context["user_id"] # ❌ mypy error: "session_id" doesn't exist on UserContext request.runtime.context["session_id"] response = handler(request) if response.structured_response is not None: # ✅ Now type-safe: IDE knows sentiment exists and is str sentiment: str = response.structured_response.sentiment # ❌ mypy error: "summary" doesn't exist on AnalysisResult response.structured_response.summary return response ``` ### Mismatched middleware/schema caught at `create_agent` ```python class SessionMiddleware(AgentMiddleware[AgentState[Any], SessionContext, Any]): ... # ❌ mypy error: SessionMiddleware expects SessionContext, not UserContext create_agent( model=model, middleware=[SessionMiddleware()], context_schema=UserContext, # mismatch! ) class AnalysisMiddleware(AgentMiddleware[AgentState[AnalysisResult], ContextT, AnalysisResult]): ... # ❌ mypy error: AnalysisMiddleware expects AnalysisResult, not SummaryResult create_agent( model=model, middleware=[AnalysisMiddleware()], response_format=SummaryResult, # mismatch! ) ```
Packages
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.