brdata-rag-tools 0.1.3

Improve development of retrieval augmented generation (RAG) applications at the BR AI + Automation Lab.

rag-tools-library

Library to support common tasks in retrieval augmented generation (RAG).

This library is in a very early stage and all the documentation is AI generated.

Tutorial and Documentation

You find a brief tutorial and the documentation under br-data.github.io/rag-tools-library.

Roadmap

• Add Google Bison to available LLMs
• Add an offline database alternative
  • FAISS and SQLite
• Allow users to register their own LLMs
• Allow users to register their own Embedding models
• Support Semantic Scholar endpoint to generate embeddings for scientific papers.
• Support chat functionality; e.g. let the user give feedback on the result to the LLM.

Deployment

Run the build_and_deploy.sh script in the root folder. Once prompted for the username, pass __token__ and the pypi API token you've received. If you don't have an API token and feel like you should, feel free to contact the maintainers.

Contact

Marco Lehner

[e-mail]