PDF RAG Application

A full-stack PDF document query system that allows users to upload PDF documents and query their content using AI-powered semantic search. Built with FastAPI backend and React frontend.

🚀 Features

• PDF Upload & Processing: Securely upload PDF documents for processing
• Semantic Search: Query documents using natural language
• AI-Powered Responses: Get accurate, contextual answers from your documents
• Vector Embeddings: Uses OpenAI embeddings for intelligent document chunking
• PostgreSQL with pgvector: Efficient similarity search capabilities
• Modern UI: Clean, responsive interface built with React and Tailwind CSS

🏗️ Architecture

• Backend: FastAPI with Python
• Frontend: React with TypeScript and Vite
• Database: PostgreSQL with pgvector extension
• AI/ML: OpenAI API for embeddings and text generation
• Styling: Tailwind CSS with custom design system

📋 Prerequisites

• Python 3.10+
• Node.js 18+
• PostgreSQL 14+ with pgvector extension
• OpenAI API key

🛠️ Installation & Setup

1. Clone the Repository

git clone <repository-url>
cd pdf-rag

2. Backend Setup

Navigate to backend directory

cd backend

Create Python virtual environment

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Environment configuration

1. Copy the sample environment file:

cp sample.env .env

2. Edit .env file with your configuration:

# Database
DATABASE_URL=postgresql://username:password@localhost:5432/pdf_rag_db

# OpenAI
OPENAI_API_KEY=your_openai_api_key_here

# App Settings
ENVIRONMENT=development
LOG_LEVEL=INFO

Database setup

1. Create PostgreSQL database:

CREATE DATABASE pdf_rag_db;

2. Install pgvector extension:

CREATE EXTENSION vector;

Run the backend

# From backend directory
python main.py

The backend will be available at http://localhost:8000

3. Frontend Setup

Navigate to frontend directory

cd frontend

Install dependencies

npm install
# or using bun
bun install

Environment configuration

Create .env file in frontend directory:

VITE_API_BASE_URL=http://localhost:8000

Run the frontend

npm run dev
# or using bun
bun dev

The frontend will be available at http://localhost:8080

🐳 Docker Setup (Alternative)

You can also run the application using Docker:

# Build and run with docker-compose
docker-compose up --build

This will start both backend and frontend services with the database.

🔧 Development

Backend Development

• API documentation: http://localhost:8000/docs
• Health check: http://localhost:8000/api/v1/health
• Statistics: http://localhost:8000/api/v1/stats

Frontend Development

• Built with Vite for fast hot reloading
• Tailwind CSS for styling
• TypeScript for type safety
• React Query for API state management

Key Backend Files

• backend/app/main.py - FastAPI application entry point
• backend/app/routes/routes.py - API routes definition
• backend/app/controller/controller.py - Business logic controllers
• backend/app/services/db_interaction.py - Database operations

Key Frontend Files

• frontend/src/App.tsx - Main application component
• frontend/src/pages/Index.tsx - Main page
• frontend/src/components/PDFUpload.tsx - PDF upload component

📡 API Endpoints

• POST /api/v1/ingest - Upload and process PDF documents
• POST /api/v1/query - Query documents with natural language
• GET /api/v1/health - Health check endpoint
• GET /api/v1/stats - System statistics

🎨 UI Components

The frontend uses a custom design system with:

• Responsive layout
• Dark theme optimized
• Custom gradients and animations
• Accessible components built with Radix UI

🧪 Testing

Backend Testing

cd backend
python -m pytest

Frontend Testing

cd frontend
npm test

🚀 Production Deployment

1. Set environment variables for production
2. Configure PostgreSQL with proper security settings
3. Set up reverse proxy (nginx recommended)
4. Enable SSL/TLS certificates
5. Configure CORS settings appropriately

📝 Environment Variables

Backend

• DATABASE_URL - PostgreSQL connection string
• OPENAI_API_KEY - OpenAI API key for embeddings
• ENVIRONMENT - deployment environment (development/production)
• LOG_LEVEL - logging level

Frontend

• VITE_API_BASE_URL - Backend API base URL

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

📄 License

This project is licensed under the MIT License.