This is a simple Retrieval Augmented Generation app (RAG) with a full-fledged user interface!
- Document Upload: Users can upload PDF files up to 3145728B (~3MB) containing information for analysis.
- Google Gemini Pro: Leveraging Google's latest LLM with 2 million token contexts to craft responses and embeddings.
- State-of-the-art UI: Can't go wrong with React + Bootstrap
- HTTPS: Deployed on a VPS with a valid SSL certificate
- Server: Langchain, FastAPI, Redis
- Client: React, Bootstrap
- Clone the repository
- Make sure you are on the branch
main
- cd into it
- Add GOOGLE_API_KEY and REDIS_URL as variables in the
back_end/.env
- Google Gemini: https://ai.google.dev/gemini-api
- Redis: https://redis.io/
docker compose up
- Create the app itself :D
- PDF reader
- RAG chain with context and chat history
- REST api endpoints
- React app client
- Better PDF parser
- Scale vectorstore
- Agents with self-evaluating mechanism instead of current chain
- Improve processing time + Add support for larger file
-
Deploy on VercelFile too large - Deploy on a VPS with
nginx
andpm2
- Use
WebSocket
for faster conversation response rate - Site reliability engineering (eta soon)
- Phong Pham
- Trung Nguyen