Herbi API

A Django REST API for classifying and managing vegetarian/vegan food conversations using AI-powered classification.

🍃 What is Herbi?

Herbi is an intelligent API that helps classify conversations about food to determine if they indicate vegetarian or vegan dietary preferences. It uses AI models to analyze food-related conversations and extract structured data about food consumption patterns.

✨ Features

• AI-Powered Classification: Uses OpenAI models to classify food conversations
• RESTful API: Clean, documented API endpoints with Swagger UI
• Conversation Simulation: Tools for generating and simulating food-related conversations
• Food Extraction: Extracts structured food data from natural language
• Authentication: Secure user authentication system
• Interactive Documentation: Built-in Swagger UI for API exploration

🚀 Quick Start

Prerequisites

• Python 3.8+
• OpenAI API key
• PostgreSQL (optional, SQLite is used by default)

Installation

1. Clone the repository

   git clone <repository-url>
   cd herbi

2. Install dependencies

   cd herbiapi
   pip install -r requirements.txt

3. Set up environment variables Create a .env.django.dev file in the herbiapi directory:

   OPENAI_SECRET=your_openai_api_key_here

4. Run migrations

   python manage.py migrate

5. Create a superuser (optional)

   python manage.py createsuperuser

6. Start the development server

   python manage.py runserver

📖 API Documentation

Once the server is running, you can access the interactive API documentation:

• Swagger UI: http://localhost:8000/
• ReDoc: http://localhost:8000/redoc/
• Raw Schema: http://localhost:8000/schema/

🔌 API Endpoints

Authentication

• POST /login/ - User login with username and password

Conversations

• GET /conversations/ - List all conversations with extracted food data
• GET /conversations/vegs/ - List only vegetarian/vegan conversations

Admin

• GET /admin/ - Django admin interface

Documentation

• GET / - Swagger UI documentation
• GET /redoc/ - ReDoc documentation
• GET /schema/ - OpenAPI schema

🏗️ Project Structure

herbiapi/
├── chat/                    # Conversation management app
│   ├── models.py           # SimulatedConversation model
│   ├── views.py            # API views
│   ├── serializers.py      # Data serialization
│   └── food_classifiers/   # AI classification logic
├── login/                  # Authentication app
│   ├── models.py           # User models
│   ├── views.py            # Login views
│   └── serializers.py      # Auth serializers
├── utils/                  # Utility modules
│   ├── conversation_simulator.py
│   ├── llm_interface.py
│   └── openai_client.py
├── core/                   # Django settings and configuration
│   ├── settings.py         # Project settings
│   └── urls.py            # URL routing
└── requirements.txt        # Python dependencies

🤖 How It Works

1. Conversation Input: The system accepts food-related conversations
2. AI Classification: Uses OpenAI models to analyze the conversation
3. Food Extraction: Extracts structured food data from the text
4. Diet Classification: Determines if the foods indicate vegetarian/vegan preferences
5. Data Storage: Stores the extracted food data from the classified conversation

🧪 Testing

Run the test suite:

pytest app_directory/tests

🛠️ Development

Code Quality

• Follow PEP 8 style guidelines
• Use type hints where appropriate
• Write docstrings for functions and classes

Adding New Features

1. Create models in the appropriate app
2. Add serializers for API responses
3. Create views with proper documentation
4. Update URL routing
5. Add tests for new functionality

📝 Environment Variables

Variable	Description	Required
OPENAI_SECRET	OpenAI API key for AI classification	Yes