Invoice Processing Platform Prototype

A Streamlit-based prototype for processing and extracting information from invoice PDFs.

Setup

1. Create and Activate Virtual Environment:

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

2. Install Dependencies:

   pip install -r requirements.txt

3. Set Up Environment Variables: Create a file named .env in the root directory of the project. Add your API keys to this file in the following format:

   ANTHROPIC_API_KEY=your_anthropic_api_key_here
   # If using AWS Bedrock, you would also set your AWS credentials here or configure them via other standard AWS methods.
   # AWS_ACCESS_KEY_ID=your_aws_access_key_id
   # AWS_SECRET_ACCESS_KEY=your_aws_secret_access_key
   # AWS_SESSION_TOKEN=your_aws_session_token (if using temporary credentials)
   # AWS_DEFAULT_REGION=your_aws_region (e.g., us-east-1)

   Replace your_anthropic_api_key_here with your actual Anthropic API key. The .env file is already in .gitignore to prevent accidental commits of your keys.

4. Run the Application:

   streamlit run app.py

Features

• PDF invoice upload
• Choice of API provider (Anthropic API or AWS Bedrock)
• Automatic extraction of invoice details
• Clean display of extracted information
• Line items table view
• Export functionality for extracted data

Note

This is an early prototype version. The actual LLM-based extraction functionality may require further refinement for accuracy and robustness across different invoice formats.