AI Document Assistant

An intelligent document assistant that allows users to chat with their documents using state-of-the-art language models. Built with FastAPI, React, and LangChain.

Features

• 📄 Document Processing: Support for PDF, DOCX, CSV, and JSON files
• 💬 Interactive Chat: Natural conversation with your documents
• 🔍 Smart Search: Semantic search across all uploaded documents
• 📊 Source Citations: Automatic citation of sources in responses
• 💾 Persistent Conversations: Chat history preserved between sessions
• 📥 Export Functionality: Export conversations as PDF or TXT

Tech Stack

Backend

• FastAPI
• LangChain
• Ollama (DeepSeek model)
• ChromaDB
• ReportLab
• Python 3.11+

Frontend

• React
• Material-UI
• Axios
• React Markdown
• React Syntax Highlighter

Local Development Setup

Prerequisites

1. Install Python 3.11 or higher
2. Install Node.js 18 or higher
3. Install Ollama from ollama.ai
4. Pull the DeepSeek model:

   ollama pull deepseek-r1:32b

Backend Setup

1. Clone the repository:

   git clone https://github.com/yourusername/ai-doc-assistant.git
   cd ai-doc-assistant

2. Create and activate a virtual environment:

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

3. Install dependencies:

   pip install -r requirements.txt

4. Create necessary directories:

   mkdir -p uploads exports vectordb/conversations

5. Start the backend server:

   uvicorn main:app --reload --port 8000

Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm start

The application will be available at http://localhost:3000

Production Deployment

Backend Deployment

1. Set up a Linux server (Ubuntu 20.04+ recommended)

2. Install system dependencies:

   sudo apt update
   sudo apt install python3.11 python3.11-venv nginx

3. Install Ollama:

   curl -fsSL https://ollama.ai/install.sh | sh

4. Pull the DeepSeek model:

   ollama pull deepseek-r1:32b

5. Clone and set up the application:

   git clone https://github.com/yourusername/ai-doc-assistant.git
   cd ai-doc-assistant
   python3.11 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt

6. Create a systemd service for Ollama:

   sudo nano /etc/systemd/system/ollama.service

   Add the following content:

   [Unit]
   Description=Ollama Service
   After=network.target
   
   [Service]
   Type=simple
   User=root
   ExecStart=/usr/bin/ollama serve
   Restart=always
   
   [Install]
   WantedBy=multi-user.target

7. Create a systemd service for the FastAPI application:

   sudo nano /etc/systemd/system/aidoc.service

   Add the following content:

   [Unit]
   Description=AI Document Assistant
   After=network.target
   
   [Service]
   User=ubuntu
   WorkingDirectory=/path/to/ai-doc-assistant
   Environment="PATH=/path/to/ai-doc-assistant/venv/bin"
   ExecStart=/path/to/ai-doc-assistant/venv/bin/uvicorn main:app --host 0.0.0.0 --port 8000
   Restart=always
   
   [Install]
   WantedBy=multi-user.target

8. Configure Nginx:

   sudo nano /etc/nginx/sites-available/aidoc

   Add the following content:

   server {
       listen 80;
       server_name your_domain.com;
   
       location / {
           root /path/to/ai-doc-assistant/frontend/build;
           try_files $uri $uri/ /index.html;
       }
   
       location /api {
           proxy_pass http://localhost:8000;
           proxy_http_version 1.1;
           proxy_set_header Upgrade $http_upgrade;
           proxy_set_header Connection 'upgrade';
           proxy_set_header Host $host;
           proxy_cache_bypass $http_upgrade;
       }
   }

9. Enable and start services:

   sudo ln -s /etc/nginx/sites-available/aidoc /etc/nginx/sites-enabled/
   sudo systemctl enable nginx
   sudo systemctl enable ollama
   sudo systemctl enable aidoc
   sudo systemctl start nginx
   sudo systemctl start ollama
   sudo systemctl start aidoc

Frontend Deployment

1. Build the frontend:

   cd frontend
   npm install
   npm run build

2. Copy the build files to the server:

   scp -r build/* user@your_server:/path/to/ai-doc-assistant/frontend/build/

Environment Variables

Create a .env file in the root directory:

# Backend
UPLOAD_DIR=uploads
DB_DIR=vectordb
EXPORT_DIR=exports
MAX_UPLOAD_SIZE=10485760  # 10MB

# Frontend
REACT_APP_API_URL=http://localhost:8000

For production, update the REACT_APP_API_URL to your domain.

Security Considerations

1. Set up SSL/TLS using Let's Encrypt:

   sudo apt install certbot python3-certbot-nginx
   sudo certbot --nginx -d your_domain.com

2. Configure firewall:

   sudo ufw allow 80
   sudo ufw allow 443
   sudo ufw allow 22
   sudo ufw enable

3. Set up proper file permissions:

   sudo chown -R ubuntu:ubuntu /path/to/ai-doc-assistant
   chmod -R 755 /path/to/ai-doc-assistant

Maintenance

• Monitor logs:

  sudo journalctl -u ollama -f
  sudo journalctl -u aidoc -f

• Update the application:

  cd /path/to/ai-doc-assistant
  git pull
  source venv/bin/activate
  pip install -r requirements.txt
  sudo systemctl restart aidoc

Troubleshooting

1. Check service status:

   sudo systemctl status ollama
   sudo systemctl status aidoc
   sudo systemctl status nginx

2. Check logs:

   sudo journalctl -u ollama -n 100
   sudo journalctl -u aidoc -n 100
   sudo tail -f /var/log/nginx/error.log

3. Common issues:

   • Port conflicts: Check if ports 8000 and 3000 are free
   • Memory issues: Monitor RAM usage with htop
   • Disk space: Check available space with df -h

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.