Files
langchain/libs/core
Varun Chawla a5f22e7cb1 chore(core): clean up docstring mismatch and redundant logic in langchain-core (#35064)
## Description

Fixes #35046

Two minor cleanups in `langchain-core`:

1. **Fix docstring mismatch in `mustache.render()`**: The docstring
incorrectly documented `partials_path` and `partials_ext` parameters
that do not exist in the function signature. These were likely carried
over from the original
[chevron](https://github.com/noahmorrison/chevron) library but were
never part of this adapted implementation.

2. **Remove redundant logic in `Blob.from_path()`**: The expression
`mimetypes.guess_type(path)[0] if guess_type else None` had a redundant
`if guess_type` ternary since the outer condition `if mime_type is None
and guess_type:` already guarantees `guess_type` is `True` at that
point. Simplified to just `mimetypes.guess_type(path)[0]`.

## AI Disclaimer

An AI coding assistant was used to help identify and implement these
changes.
2026-02-10 12:25:50 -05:00
..
2026-01-26 18:05:37 -08:00
2026-02-04 16:16:52 -05:00
2026-02-10 09:40:26 -05:00
2026-01-23 23:07:48 -05:00
2026-02-10 09:40:26 -05:00

🦜🍎 LangChain Core

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

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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. You can also chat with the docs using Chat LangChain.

📕 Releases & Versioning

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💁 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.