InvoiceGPT

InvoiceGPT is an intelligent invoice processing solution that leverages GPT-4 Vision for advanced OCR capabilities, allowing automated extraction and interpretation of invoice data. Built with Streamlit, it offers a user-friendly interface for managing financial documents with AI-powered insights.

Features

• Advanced OCR Processing: Utilizes GPT-4 Vision to accurately extract data from any invoice format
• Secure Storage: Automated storage of processed data in Amazon S3 and AWS RDS (MySQL)
• Data Security: Implements Google Authentication and robust data isolation
• Natural Language Querying: AI-powered chatbot interface using LangChain and GPT-4
• Smart Auto-Splitting: Intelligent categorization of invoice items across PDF and image formats
• Analytics Dashboard: Advanced tools for financial data analysis and insights

Technology Stack

• Frontend: Streamlit
• AI/ML: GPT-4 Vision, GPT-4o-mini, LangChain
• Storage: Amazon S3, AWS RDS (MySQL)
• Authentication: Google Auth
• OCR: GPT-4 Vision

Installation

1. Clone the repository:

git clone https://github.com/yourusername/invoicegpt.git
cd invoicegpt

2. Install required dependencies:

pip install -r requirements.txt

3. Set up Google OAuth 2.0:

• Go to the Google Cloud Console
• Create a new project or select an existing one
• Enable the Google OAuth2 API
• Go to Credentials > Create Credentials > OAuth Client ID
• Configure the OAuth consent screen
• Create OAuth 2.0 Client ID (Web application type)
• Download the client configuration JSON file
• Rename it to google_creds.json and place it in the root directory

3. Set up environment variables:

# Create a .env file with the following variables
AWS_ACCESS_KEY_ID=your_access_key
AWS_SECRET_ACCESS_KEY=your_secret_key
OPENAI_API_KEY=your_openai_api_key
GOOGLE_CLIENT_ID=your_google_client_id
GOOGLE_CLIENT_SECRET=your_google_client_secret

Usage

1. Start the application:

streamlit run main.py

2. Access the application through your web browser at http://localhost:8501

3. Log in using your Google account

4. Upload invoices through the user interface

5. Use the chatbot interface to query your invoice data using natural language

Project Structure

invoicegpt/
├── .streamlit/           # Streamlit configuration files
├── database_files/       # Database related files and schemas
├── images/              # Application icons and images
├── navigation_pages/    # Streamlit page navigation files
├── utilities/           # Utility functions and helpers
├── .gitignore          # Git ignore configuration
├── README.md           # Project documentation
├── requirements.txt    # Python dependencies
└── main.py             # Main application entry point

Key Features Explained

Store Invoices

• Centralized document storage
• Secure cloud backup
• Easy access and organization

Smart Processing

• Advanced OCR technology
• Automated data extraction
• Intelligent interpretation

Auto-Splitting

• Automatic item categorization
• Support for multiple formats
• Precise allocation of items

User-Friendly Interface

• Intuitive design
• Accessible to all skill levels
• Streamlined workflow

AI Querying

• Natural language processing
• Instant response generation
• Detailed financial insights

Data Insights

• Advanced analytics tools
• Custom reporting
• Business intelligence features

Security

InvoiceGPT prioritizes data security through:

• Secure Google Authentication
• Data isolation
• AWS S3 encrypted storage
• Secure database connections

Contributing

1. Fork the repository
2. Create a new branch (git checkout -b feature/improvement)
3. Commit your changes (git commit -am 'Add new feature')
4. Push to the branch (git push origin feature/improvement)
5. Create a Pull Request

License

This project is licensed under the MIT License

Support

For support, please open an issue in the GitHub repository.