730a3676f8
**Description:** *Closes #[33883](https://github.com/langchain-ai/langchain/issues/33883)* Chat model cache keys are generated by serializing messages via `dumps(messages)`. The optional `BaseMessage.id` field (a UUID used solely for tracing/threading) is included in this serialization, causing functionally identical messages to produce different cache keys. This results in repeated API calls, cache bloat, and degraded performance in production workloads (e.g., agents, RAG chains, long conversations). This change normalizes messages **only for cache key generation** by stripping the nonsemantic `id` field using Pydantic V2’s `model_copy(update={"id": None})`. The normalization is applied in both synchronous and asynchronous cache paths (`_generate_with_cache` / `_agenerate_with_cache`) immediately before `dumps()`. ```python normalized_messages = [ msg.model_copy(update={"id": None}) if getattr(msg, "id", None) is not None else msg for msg in messages ] prompt = dumps(normalized_messages) --------- Co-authored-by: Mason Daugherty <mason@langchain.dev> Co-authored-by: Mason Daugherty <github@mdrxy.com>
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.