📄 InvoiceVision

A modern Streamlit application for extracting structured data from invoice images using Qwen 2.5 VL via OpenRouter API.

✨ Features

• 🤖 AI-Powered Extraction - Uses Qwen 2.5 VL model via OpenRouter
• 📱 Modern UI - Responsive design with custom styling
• 📊 Multiple Export Formats - JSON and CSV export options
• 🔧 Configurable - Select which fields to extract
• 🎯 Accurate - Advanced vision model for precise data extraction
• 🔒 Secure - Environment-based API key management

🚀 Quick Start

1. Clone Repository

git clone https://github.com/shagatomte19/InvoiceVision.git
cd InvoiceVision

2. Install Dependencies

pip install -r requirements.txt

3. Configure API Key

Option A: Streamlit Secrets (Recommended)

mkdir .streamlit

Create .streamlit/secrets.toml:

OPENROUTER_API_KEY = "your_openrouter_api_key_here"
OPENROUTER_SITE_URL = "https://github.com/shagatomte19/invoice-ocr-extractor"
OPENROUTER_SITE_NAME = "Invoice OCR Extractor"

Option B: Environment Variable

export OPENROUTER_API_KEY="your_api_key_here"

4. Get OpenRouter API Key

1. Visit OpenRouter.ai
2. Sign up/login
3. Go to API Keys section
4. Create new API key
5. Copy the key

5. Run Application

streamlit run main.py

📁 Project Structure

invoice_ocr_app/
├── main.py                    # Main application entry point
├── requirements.txt           # Python dependencies
├── README.md                  # This file
├── .gitignore                # Git ignore rules
├── .streamlit/
│   └── secrets.toml          # Streamlit secrets (not in repo)
├── config/
│   ├── __init__.py
│   └── settings.py           # Configuration settings
├── api/
│   ├── __init__.py
│   └── openrouter_client.py  # OpenRouter API client
├── utils/
│   ├── __init__.py
│   ├── image_processor.py    # Image processing utilities
│   ├── data_parser.py        # Data parsing and validation
│   └── export_utils.py       # Export functionality
├── ui/
│   ├── __init__.py
│   ├── styles.py             # CSS styles
│   ├── components.py         # Reusable UI components
│   └── layout.py             # Page layout components
└── models/
    ├── __init__.py
    └── invoice_model.py      # Invoice data models

🎯 Usage

1. Start Application: streamlit run main.py
2. Configure API: Enter OpenRouter API key (if not using secrets)
3. Upload Invoice: Select PNG, JPG, or JPEG image
4. Extract Data: Click "Extract Data" button
5. Review Results: View structured data extraction
6. Export: Download as JSON or CSV

🛠️ Configuration

Supported Models

• qwen/qwen2.5-vl-72b-instruct:free (Default, Free tier)
• qwen/qwen2.5-vl-7b-instruct
• qwen/qwen2.5-vl-3b-instruct

Extraction Options

• ✅ Vendor Information (name, address, phone, email)
• ✅ Invoice Details (number, date, due date)
• ✅ Financial Data (subtotal, tax, total)
• ✅ Line Items (description, quantity, price)

🔒 Security

• API keys are never committed to repository
• Uses Streamlit secrets for secure deployment
• Input validation and error handling
• No data stored permanently

🐛 Troubleshooting

API Key Issues:

• Verify OpenRouter API key is valid
• Check API key has sufficient credits
• Ensure proper configuration in secrets.toml

File Upload Issues:

• Supported formats: PNG, JPG, JPEG
• Ensure image quality is good
• Check file size (recommend < 5MB)

Deployment Issues:

• Verify all dependencies in requirements.txt
• Check Python version compatibility (3.8+)
• Ensure .streamlit/secrets.toml is configured

📄 License

MIT License - see LICENSE file for details.

🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'Add amazing feature')
4. Push to branch (git push origin feature/amazing-feature)
5. Open Pull Request

⭐ Support

If you find this project helpful, please give it a star! ⭐

📞 Contact

• GitHub Issues: Report bugs or request features
• Discussions: Community discussions

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Built with ❤️ using Streamlit and Qwen 2.5 VL