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
• Embedding-backed Search: Semantic retrieval ranks products by meaning before the AI responds
• 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

1. Create a virtual environment (recommended):

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

1. Install dependencies:

pip install -r requirements.txt

1. 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
SUPPLYBOT_EMBEDDING_MODEL=google/gemini-embedding-2
Secret-Key=Key-Goes-Here
DATABASE_URL=sqlite:///inventory.db

cd frontend
npm install

Usage

1. Start the Flask backend application:

python app.py

Start the frontend:

cd frontend
npm run dev

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

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

3. Use the interface to:

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

The search layer now uses the cloud embedding model google/gemini-embedding-2 for semantic ranking, and it automatically falls back to recomputing any legacy stored vectors that no longer match the current embedding shape.

Data Processing

The system supports three types of data:

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

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.