RAG-webapp

Retrieval Augmented Generation web application using flask as a web framework, chromadb as the vector database and langchain.

Features

• Modify a vector database by
  • adding new documents either by typing them or by uploading .pdf files
  • deleting rows by ID
  • updating rows by ID
• Query the database through a large language model like gpt-3.5-turbo and ask it to
  • summarize your loaded documents

Notes

The project includes docker configuration files for building a multi-container Docker application which includes the flask server and the chromadb server, the chromadb client is set to be created in the chromadb container like this:

client  =  chromadb.HttpClient(host="chromadb-container", port=8000)