Invoice Extraction Streamlit App

A simple Streamlit application that allows users to upload invoice images and extract structured data using LlamaCloud's extraction agent.

Features

• 📄 Upload invoice images (JPG, JPEG, PNG, BMP, TIFF)
• 🔍 Automatic data extraction using LlamaCloud's kaggle_invoice_agent
• 📊 Display extracted data in both JSON and formatted views
• 🎨 Clean, modern UI with progress indicators

Setup

1. Install dependencies:

   pip install -r requirements.txt
   

2. Set up environment variables: Create a .env file in the project root with your LlamaCloud API credentials:

   LLAMA_CLOUD_API_KEY=your_api_key_here
   

3. Run the app:

   streamlit run app.py
   

4. Open your browser: The app will be available at http://localhost:8501

Usage

1. Upload an invoice image using the file uploader
2. Click "Extract Data" to run the extraction
3. View the extracted data in both JSON and formatted formats
4. The sidebar shows configuration details and app information

Configuration

The app uses the following configuration (from sample.py):

• Project ID: 2fef999e-1073-40e6-aeb3-1f3c0e64d99b
• Organization ID: 43b88c8f-e488-46f6-9013-698e3d2e374a
• Agent: kaggle_invoice_agent

File Structure

jerry_invoice_streamlit/
├── app.py              # Main Streamlit application
├── sample.py           # Original sample code
├── requirements.txt    # Python dependencies
├── README.md          # This file
└── .env               # Environment variables (create this)

Troubleshooting

• API Key Issues: Make sure your .env file contains the correct LLAMA_CLOUD_API_KEY
• Import Errors: Ensure all dependencies are installed with pip install -r requirements.txt
• File Upload Issues: Check that your image file is in a supported format