90280d1f58
## Summary This PR fixes several bugs and improves the example code in `BaseChatMessageHistory` docstring that would prevent it from working correctly. ### Bugs Fixed - **Critical bug**: Fixed `json.dump(messages, f)` → `json.dump(serialized, f)` - was using wrong variable - **NameError**: Fixed bare variable references to use `self.storage_path` and `self.session_id` - **Missing imports**: Added required imports (`json`, `os`, message converters) to make example runnable ### Improvements - Added missing type hints following project standards (`messages() -> list[BaseMessage]`, `clear() -> None`) - Added robust error handling with `FileNotFoundError` exception handling - Added directory creation with `os.makedirs(exist_ok=True)` to prevent path errors - Improved performance: `json.load(f)` instead of `json.loads(f.read())` - Added explicit UTF-8 encoding to all file operations - Updated stores.py to use modern union syntax (`int | None` vs `Optional[int]`) ### Test Plan - [x] Code passes linting (`ruff check`) - [x] Example code now has all required imports and proper syntax - [x] Fixed variable references prevent runtime errors - [x] Follows project's type annotation standards The example code in the docstring is now fully functional and follows LangChain's coding standards. --------- Co-authored-by: sadiqkhzn <sadiqkhzn@users.noreply.github.com>
🦜🍎️ LangChain Core
Quick Install
pip install langchain-core
What is it?
LangChain Core contains the base abstractions that power the 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.
For full documentation see the API reference.
⛰️ 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.
1️⃣ Core Interface: Runnables
The concept of a Runnable is central to LangChain Core – it is the interface that most LangChain Core components implement, giving them
- A common invocation interface (
invoke(),batch(),stream(), etc.) - Built-in utilities for retries, fallbacks, schemas and runtime configurability
- Easy deployment with LangGraph
For more check out the Runnable docs. Examples of components that implement the interface include: Chat Models, Tools, Retrievers, and Output Parsers.
📕 Releases & Versioning
As langchain-core contains the base abstractions and runtime for the whole LangChain ecosystem, we will communicate any breaking changes with advance notice and version bumps. The exception for this is anything in langchain_core.beta. The reason for langchain_core.beta is that given the rate of change of the field, being able to move quickly is still a priority, and this module is our attempt to do so.
Minor version increases will occur for:
- Breaking changes for any public interfaces NOT in
langchain_core.beta
Patch version increases will occur for:
- Bug fixes
- New features
- Any changes to private interfaces
- Any changes to
langchain_core.beta
💁 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.