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Examples on how to use LangChain and Ray

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🦜️🔗 LangChain and Ray - repository of examples

© 2023, Anyscale Inc. All Rights Reserved

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Welcome to the LangChain and Ray!

Overview

LangChain and Ray are two Python libraries that are emerging as key components of the modern open source stack for LLMs (OSS LLMs). If you're a Python developer or a machine learning practitioner, these tools can be very helpful in rapidly developing LLM-based applications by making it easier to build and deploy these models.

This repo is as a go-to place for all technical examples and use cases on how to use these two libraries together.

Examples

Example Code Blog Video
Open Source LLM Search Engine github article youtube
Fast and Scalable Embedding Generation github article youtube
Retrival-Based Question Answering System github article youtube

Connect with the Ray community

You can learn and get more involved with the Ray community of developers and researchers:

  • Ray documentation

  • Official Ray site Browse the ecosystem and use this site as a hub to get the information that you need to get going and building with Ray.

  • Join the community on Slack Find friends to discuss your new learnings in our Slack space.

  • Use the discussion board Ask questions, follow topics, and view announcements on this community forum.

  • Join a meetup group Tune in on meet-ups to listen to compelling talks, get to know other users, and meet the team behind Ray.

  • Open an issue Ray is constantly evolving to improve developer experience. Submit feature requests, bug-reports, and get help via GitHub issues.

  • Become a Ray contributor We welcome community contributions to improve our documentation and Ray framework.