PDF Chat Application

A Flask-based web application that allows you to upload PDF documents and chat with them using Google's Gemini AI. The application uses LangChain for document processing and ChromaDB for vector storage.

Features

• Upload PDF documents
• Chat with your PDF using natural language
• Beautiful, responsive UI
• Vector-based document search
• Powered by Google Gemini AI

Setup Instructions

1. Install Dependencies

pip install -r requirements.txt

2. Get Google Gemini API Key

1. Visit Google AI Studio
2. Create a new API key
3. Copy the API key

3. Configure Environment Variables

Create a .env file in the project root:

GOOGLE_API_KEY=your_actual_api_key_here
FLASK_ENV=development

4. Run the Application

python app.py

The application will be available at http://localhost:5000

Usage

1. Open your browser and go to http://localhost:5000
2. Upload a PDF file using the upload form
3. Wait for the PDF to be processed (this may take a few moments)
4. Start chatting with your PDF by asking questions about its content

Technical Details

• Backend: Flask
• AI Model: Google Gemini 1.5 Flash
• Vector Database: ChromaDB
• Document Processing: LangChain
• Embeddings: HuggingFace sentence-transformers

File Structure

PDF_Chat/
├── app.py              # Main Flask application
├── requirements.txt    # Python dependencies
├── .env               # Environment variables (create this)
├── static/
│   ├── style.css      # CSS styles
│   └── script.js      # Frontend JavaScript
├── templates/
│   └── index.html     # Main HTML template
├── data/              # Uploaded PDF files (created automatically)
└── vectorstores/      # Vector database storage (created automatically)

Troubleshooting

• API Key Error: Make sure you've set the GOOGLE_API_KEY in your .env file
• PDF Processing Error: Ensure the PDF is not password-protected and contains extractable text
• Memory Issues: Large PDFs may require more memory. Consider using smaller chunk sizes in the code

License

This project is for educational purposes.