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Inventory Management using GenAI

This project showcases an innovative approach to inventory management by leveraging Generative AI capabilities. It combines a Streamlit web application with a SQLite database and Google's Gemini Pro AI model to provide an intuitive, AI-powered interface for managing product inventories.

Features

  • Natural Language Queries: Ask questions about your inventory in plain English.
  • AI-Powered SQL Generation: Utilizes Google's Gemini Pro to convert natural language to SQL queries.
  • Interactive Dashboard: Visualize inventory data with dynamic charts and graphs.
  • Inventory Modification: Add, remove, or update products using natural language commands or Excel file uploads.
  • Bulk Data Processing: Upload Excel files for batch updates to the inventory.
  • Automated Insights: Products insights generated through the sales and trends
  • Prediction of stocks:Predicts the demand of the products using AI
  • Generate Report:Generates a whole report based the on the database
  • Ploting different parameters through user prompt:This feature helps a Non-technical user to become a potential data analyst and understand the inventory better

Files in the Repository

  1. main.py: The core Streamlit application that handles the user interface and AI interactions.
  2. database.py: Script to initialize and populate the SQLite database with sample product data.

Setup and Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/inventory-management-using-GenAI.git
cd inventory-management-using-GenAI

  2. Install required dependencies:

    pip install -r requirements.txt

  3. Set up your Google API key and Pandas AI API key:

    • Create a .env file in the project root.
    • Add your Google API key: GOOGLE_API_KEY=your_api_key_here
    • Visit www.pandabi.com .Get your Pandas AI API key
    • Add your Pandas AI API key :PANDASAI_API_KEY=your_api_key_here

  4. Initialize the database:

    python database.py

  5. Run the Streamlit app:

    streamlit run main.py

Usage

The application offers three main functionalities:

  1. Ask Questions: Enter natural language queries about the inventory.
  2. View Dashboard: Explore inventory statistics and visualizations.
  3. Modify Inventory: Add, remove, or update products using AI-powered commands or Excel file uploads.

Dependencies

  • streamlit
  • pandas
  • sqlite3
  • python-dotenv
  • google-generativeai
  • plotly
  • faker

Contributing

Contributions to improve the project are welcome. Please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature.
  3. Commit your changes.
  4. Push to the branch.
  5. Create a new Pull Request.

License

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

Acknowledgments

  • Google Gemini Pro for powering the AI capabilities.
  • Streamlit for the web application framework.