ca7790f895
## Description Fixed `BaseCallbackManager.merge()` method to correctly preserve the distinction between `handlers` and `inheritable_handlers` during merge operations. Previously, the merge method was using `add_handler()` which incorrectly added handlers to both lists when `inherit=True`, causing cross-contamination between regular and inheritable handlers. The fix directly passes the combined handler lists to the constructor instead of using `add_handler()`, ensuring proper separation is maintained. ## Issue Fixes #32028 ## Dependencies None ## Testing - Modified existing test `test_merge_preserves_handler_distinction()` to verify handlers remain properly separated after merge ## Checklist - [x] **Breaking Changes**: No breaking changes - only fixes incorrect behavior - [x] **Type Hints**: All functions have complete type annotations - [x] **Tests**: Fix is fully tested with existing unit test - [x] **Security**: No security implications - [x] **Documentation**: No documentation changes needed - bug fix only - [x] **Code Quality**: Passes lint and format checks - [x] **Commit Message**: Follows Conventional Commits format --------- Co-authored-by: Mason Daugherty <mason@langchain.dev>
🦜🍎️ LangChain Core
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.