BiteBase Intelligence

BiteBase Intelligence is a comprehensive restaurant market analytics platform that empowers restaurant businesses with data-driven insights and decision-making tools. The platform combines AI-powered analytics with practical business intelligence to help restaurants optimize their operations, understand market trends, and make informed strategic decisions.

Features

Market Analysis

• Competitor Analysis: Track and analyze competitor performance, menu offerings, and customer reviews
• Location Intelligence: Interactive maps and spatial analysis for optimal restaurant location selection
• Foot Traffic Analysis: Monitor and analyze customer traffic patterns and peak hours

Menu Optimization

• Performance Analytics: Track menu item performance, popularity, and profitability
• AI-Powered Recommendations: Get data-driven suggestions for menu improvements
• Cost Analysis: Monitor ingredient costs and profit margins

Supply Chain Management

• Inventory Optimization: Smart inventory tracking and reorder recommendations
• Supplier Management: Track supplier performance and optimize relationships
• Waste Reduction: Monitor and analyze food waste to improve efficiency

Customer Insights

• Sentiment Analysis: Analyze customer feedback and reviews
• Trend Analysis: Identify emerging customer preferences and market trends
• Satisfaction Metrics: Track and improve customer satisfaction scores

Tech Stack

Frontend

• React with TypeScript
• Tailwind CSS for styling
• i18next for internationalization
• Chart.js for data visualization

Backend

• Python FastAPI
• PostgreSQL database
• Langflow for AI workflow orchestration
• Pydantic for data validation

AI/ML Components

• Sentiment Analysis
• Topic Modeling
• Time Series Forecasting
• Natural Language Processing

Getting Started

Prerequisites

• Node.js (v16 or higher)
• Python (v3.9 or higher)
• Docker and Docker Compose
• Git

Installation

1. Clone the repository:

git clone https://github.com/yourusername/bitebase-intelligence.git
cd bitebase-intelligence

2. Set up the backend:

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

3. Set up the frontend:

cd frontend
npm install

4. Configure environment variables:

cp .env.example .env
# Edit .env with your configuration

5. Start the development environment:

# From the project root
./deployment/dev.sh

The application will be available at:

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000
• API Documentation: http://localhost:8000/docs

Development

Running Tests

# Backend tests
cd backend
pytest

# Frontend tests
cd frontend
npm test

Code Style

• Backend: Follow PEP 8 guidelines
• Frontend: ESLint and Prettier configurations provided

Contributing

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

Deployment

Production Setup

./deployment/prod.sh

Environment Variables

Required environment variables are documented in .env.example.

License

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

Support

For support, please contact:

• Email: support@bitebase.com
• Documentation: docs.bitebase.com
• Issue Tracker: GitHub Issues

Acknowledgments

• Thanks to all contributors who have helped shape this project
• Special thanks to the open-source community for their invaluable tools and libraries