💬 ContextAI - Intelligent Document Assistant

A production-ready Retrieval-Augmented Generation (RAG) application built with FastAPI, React, and LangChain. ContextAI transforms how you interact with documents through intelligent conversation and streaming responses.

🚀 Features

• 📄 PDF Document Upload & Processing: Upload and process PDF documents for Q&A
• 🧠 Conversational Memory: Maintains context across conversations using history-aware retrieval
• ⚡ Streaming Responses: Real-time typewriter effect like ChatGPT
• 🎯 Intelligent Question Reformulation: Automatically reformulates follow-up questions based on chat history
• 🔍 Vector Search: Uses FAISS for efficient semantic search
• 🌐 Modern Tech Stack: FastAPI backend, React frontend with TypeScript

🛠️ Tech Stack

Backend

• FastAPI - Modern Python web framework
• LangChain - LLM orchestration and RAG implementation
• Groq - Fast LLM inference
• FAISS - Vector database for document search
• HuggingFace - Embeddings model

Frontend

• React 19 - Modern React with hooks
• TypeScript - Type-safe development
• Vite - Fast development and build tool
• Tailwind CSS - Utility-first CSS framework

🏃‍♂️ Quick Start

Backend Setup

cd backend
python -m venv venv
source venv/bin/activate  # Windows: .\venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env  # Add your GROQ_API_KEY
python main.py

Frontend Setup

cd frontend
npm install
npm run dev

🔧 Key Implementation Highlights

Conversational Memory

• Implements history-aware retrieval for context preservation
• Automatically reformulates vague questions ("what's the first one about?")
• Maintains conversation flow across multiple exchanges

Streaming Architecture

• Server-Sent Events (SSE) for real-time response streaming
• Dual endpoints: /chat (instant) and /chat/stream (typewriter effect)
• Smooth user experience with progressive content loading

Production Features

• Environment-based configuration
• CORS security settings
• Error handling and logging
• Scalable deployment setup

🌟 Demo

🚀 Live Demo | 📚 API Docs

Note: Free tier services may take 30 seconds to wake up from sleep. This is normal for portfolio projects.

Current Status: Groq API is experiencing temporary outages (Nov 18, 2025). The application architecture and deployment are fully functional - this demonstrates real-world API reliability considerations.

📁 Project Structure

├── backend/
│   ├── main.py              # FastAPI application
│   ├── requirements.txt     # Python dependencies
│   └── .env.example        # Environment template
└── frontend/
    ├── src/
    │   ├── components/     # React components
    │   ├── hooks/         # Custom hooks
    │   └── api/          # API client
    └── package.json      # Node dependencies

🚀 Deployment

Deployed on Render (Free Tier):

• Backend: Web Service with Python runtime
• Frontend: Static Site with automatic builds
• Features: Auto-deployments from GitHub, built-in SSL, environment variables

Quick Deploy to Render:

1. Fork this repository
2. Connect to Render.com
3. Deploy backend as Web Service (backend directory)
4. Deploy frontend as Static Site (frontend directory)
5. Add environment variables (GROQ_API_KEY)

📝 License

MIT License - feel free to use for your projects!

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Built by Faraz Mirza - Showcasing modern RAG implementation with conversational AI