Overview
This project aims to create a powerful PDF understanding system capable of:
- Efficiently processing and understanding PDF content
- Providing accurate and informative responses to user queries
- Saving user chat history
Key Features:
- PDF Upload and Processing: Users can upload PDF documents for analysis.
- Natural Language Question-Answering: Users can ask questions about the PDF content, and the system provides relevant answers.
- Advanced Language Model Integration: Leverages state-of-the-art language models for accurate understanding and response generation.
- User-Friendly Interface: Intuitive web interface for easy interaction.
Technology Stack:
- Frontend: React
- Backend: FastAPI
- Authentication: Supabase Authentication
- Database: Firebase Realtime Database, Supabase PostgreSQL Database
- Language Model: meta-llama/Llama-3.2-1B-Instruct(HuggingFace Inference API)
HostedLink : ezPDF