Files
langchain/libs/core
William FH 32bbe99efc chore: Support tool runtime injection when custom args schema is prov… (#33999)
Support injection of injected args (like `InjectedToolCallId`,
`ToolRuntime`) when an `args_schema` is specified that doesn't contain
said args.

This allows for pydantic validation of other args while retaining the
ability to inject langchain specific arguments.

fixes https://github.com/langchain-ai/langchain/issues/33646
fixes https://github.com/langchain-ai/langchain/issues/31688

Taking a deep dive here reminded me that we definitely need to revisit
our internal tooling logic, but I don't think we should do that in this
PR.

---------

Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>
Co-authored-by: Sydney Runkle <sydneymarierunkle@gmail.com>
2025-11-18 17:09:59 +00:00
..
2025-05-15 15:43:57 -04:00
2025-11-14 11:51:27 -05:00
2025-11-14 11:51:27 -05:00

🦜🍎 LangChain Core

PyPI - Version PyPI - License PyPI - Downloads Twitter

Looking for the JS/TS version? Check out LangChain.js.

To help you ship LangChain apps to production faster, check out LangSmith. LangSmith is a unified developer platform for building, testing, and monitoring LLM applications.

Quick Install

pip install langchain-core

🤔 What is this?

LangChain Core contains the base abstractions that power the LangChain ecosystem.

These abstractions are designed to be as modular and simple as possible.

The benefit of having these abstractions is that any provider can implement the required interface and then easily be used in the rest of the LangChain ecosystem.

⛰️ Why build on top of LangChain Core?

The LangChain ecosystem is built on top of langchain-core. Some of the benefits:

  • Modularity: We've designed Core around abstractions that are independent of each other, and not tied to any specific model provider.
  • Stability: We are committed to a stable versioning scheme, and will communicate any breaking changes with advance notice and version bumps.
  • Battle-tested: Core components have the largest install base in the LLM ecosystem, and are used in production by many companies.

📖 Documentation

For full documentation, see the API reference. For conceptual guides, tutorials, and examples on using LangChain, see the LangChain Docs.

📕 Releases & Versioning

See our Releases and Versioning policies.

💁 Contributing

As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.

For detailed information on how to contribute, see the Contributing Guide.