README.md

metadata

title: 📚 RAG-based PDF Query Application
emoji: 📚
colorFrom: purple
colorTo: blue
sdk: streamlit
sdk_version: 1.42.0
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

📚 RAG-based PDF Query Application

This application leverages Retrieval-Augmented Generation (RAG) to enable users to ask questions about a PDF document. The PDF is processed and split into chunks, which are then indexed and used to find the most relevant information when the user submits a query.

Features

• Upload a PDF and ask questions based on its contents.
• PDF is processed using PyMuPDF and text is split into chunks.
• FAISS is used to create an index for quick retrieval of relevant text chunks.
• The application uses the Groq API for generating answers based on the retrieved context.

How it works

1. Upload a PDF document.
2. The application extracts text from the PDF and splits it into smaller chunks.
3. A FAISS index is built using embeddings of these chunks.
4. When you submit a query, the system retrieves the most relevant chunks and sends them to the Groq API to generate an answer.