645b077c30
Stash the OpenAI function description dict on the BaseTool instance under `tool.__dict__["_openai_function_dict"]`. BaseTool.__setattr__ already pops `tool_call_schema` and `args` when `args_schema`, `description`, or `name` change; extend the invalidation set to include the new key so the cache matches the schema caching lifecycle. Previously, every call to `convert_to_openai_tool(tool)` re-ran `schema.model_json_schema()` on the cached tool_call_schema pydantic model, rebuilding the full JSON-schema tree on every model invocation. Summarization middleware's `count_tokens_approximately` (called twice per model call) plus the prompt-caching middleware's `bind_tools` meant three fresh schema generations per model call × 15-ish tools × 500 model calls in a 100-turn agent run — tens of seconds of pydantic work that's identical every time. With this cache the first call pays the schema-gen cost once per tool; all subsequent calls are a dict lookup. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.