RAG QA

Description

RAG-QA is a free, containerised question-answer framework that allows you to ask questions to your documents in an intuitive way.

This app uses a method called retrieval augmented generation (RAG) to retrieve information that is relevant to your question from your uploaded document. It then uses a large language model (LLM) to answer the question with the retrieved context.

The current implementation uses the following components:

• LLM: Google Gemini Pro
• Embedding Model: all-MiniLM-L6-v2
• Vector Database: Chroma DB
• Frontend: Streamlit
• Backend: FastAPI

Demo

This demo shows the app answering a question related to Alphabet Inc’s Q3 financial result from 2023. Notice the app frontend is shown on the left; the logs are shown on the upper right; the PDF report is shown on the bottom left.