Feature/pdf chat rag 298

[satyajit-patel]

Closes: #298

RAG-based PDF Chat Feature Implementation
I have implemented a comprehensive RAG (Retrieval-Augmented Generation) based PDF chat system that allows users to upload PDF documents and interact with their content through natural language queries. Here are the key additions and changes:

Working Video 📷

Demo Video: RAG PDF Chat Feature Demo

🚀 New Features Added:

• PDF Upload Interface: Streamlit-based file uploader supporting PDF documents
• Document Processing Pipeline:
  • PDF text extraction using PyPDFLoader
  • Intelligent text chunking with RecursiveCharacterTextSplitter (1000 chars with 100 overlap)
  • Document embedding generation using Google Generative AI embeddings
• Vector Database Integration: FAISS vector store for efficient similarity search
• AI-Powered Chat Interface:
  • Integration with Groq's Llama-3.1-8b-instant model
  • Context-aware responses using retrieved document chunks
  • MMR (Maximal Marginal Relevance) search for diverse results
• Session Management: Streamlit session state for maintaining chat context
• Error Handling: Comprehensive error handling for API keys, file processing, and chat responses

📁 Files Added/Modified:

• chatWithYourPDF.py - Main application file
• .env.example - Environment variable template
• requirements.txt - Updated dependencies

• Bug fix
• New feature
• Code style update (formatting, local variables)
• Documentation update
• Database update

Note to reviewers 📄

Future Enhancements Ready:

• Multi-document chat support
• Chat history persistence
• Advanced filtering options
• Export conversation functionality

[github-actions]

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[Avdhesh-Varshney]

LGTM 👍

[Avdhesh-Varshney]

Perfect ✅