#NOTE: This project is still way in beta, hardly working, feel free to help me work on this.

Supply-bot

Supply-bot is an AI-powered inventory management system that leverages GPT models to provide intelligent inventory analysis, demand prediction, and optimization recommendations.

Features

• Intelligent Inventory Analysis: Analyze inventory patterns and predict demand using AI
• Data Processing: Support for multiple data formats (CSV, Excel, JSON)
• Demand Prediction: AI-powered forecasting for optimal stock levels
• Inventory Search: Intelligent search functionality for inventory items
• Comprehensive Reporting: Generate detailed inventory reports and insights
• Fine-tuning Capabilities: Customize the AI model with your specific inventory data

Installation

1. Clone the repository:

git clone https://github.com/Kthecodeer2/Supply-bot.git
cd Supply-bot

2. Create a virtual environment (recommended):

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

3. Install dependencies:

pip install -r requirements.txt

4. Create a .env file in the project root with your OpenAI API key and a random secret key:

OPENAI_API_KEY=your_api_key_here
Secret-Key=Key-Goes-Here

Usage

1. Start the Flask application:

python app.py

2. Access the web interface at http://localhost:5000

3. Upload your inventory data in one of the supported formats (CSV, Excel, or JSON)

4. Use the interface to:

   • Process and analyze inventory data
   • Generate demand predictions
   • Search inventory items
   • Generate comprehensive reports

Data Processing

The system supports three types of data:

• Transactions: Historical transaction data
• Products: Product catalog information
• Sales: Sales data and trends

Dependencies

• Flask 3.0.2
• Pandas 2.2.1
• NumPy 1.26.4
• scikit-learn 1.4.1
• Matplotlib 3.8.3
• OpenAI API 1.12
• And other dependencies listed in requirements.txt

Project Structure

Supply-bot/
├── app.py              # Main Flask application
├── gpt_model.py        # GPT model implementation
├── requirements.txt    # Project dependencies
├── .env               # Environment variables
├── training_data/     # Directory for training data
├── templates/         # Flask templates
└── instance/          # Database instance

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

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