Files
joshy-deshaw bf5385592e core, community: propagate context between threads (#15171)
While using `chain.batch`, the default implementation uses a
`ThreadPoolExecutor` and run the chains in separate threads. An issue
with this approach is that that [the token counting
callback](https://python.langchain.com/docs/modules/callbacks/token_counting)
fails to work as a consequence of the context not being propagated
between threads. This PR adds context propagation to the new threads and
adds some thread synchronization in the OpenAI callback. With this
change, the token counting callback works as intended.

Having the context propagation change would be highly beneficial for
those implementing custom callbacks for similar functionalities as well.

---------

Co-authored-by: Nuno Campos <nuno@langchain.dev>
2023-12-28 14:51:22 -08:00
..
2023-12-17 12:55:49 -08:00

🦜🧑‍🤝‍🧑 LangChain Community

Downloads License: MIT

Quick Install

pip install langchain-community

What is it?

LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application.

For full documentation see the API reference.

LangChain Stack

📕 Releases & Versioning

langchain-community is currently on version 0.0.x

All changes will be accompanied by a patch version increase.

💁 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.