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khoaliamle/Cooking_Tutor

sourceHugging Faceapache-2.0updated 11mo agoView on Hugging Face

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App README

Cooking Tutor Backend

An intelligent cooking assistant that provides personalized recipe guidance, cooking techniques, and culinary tips with multilingual support (English, Vietnamese, Chinese).

🚀 Features

—Smart Recipe Recommendations: Get personalized recipes based on available ingredients
—Multilingual Support: English, Vietnamese (Tiếng Việt), and Chinese (中文)
—Cooking Techniques: Step-by-step guidance for various cooking methods
—Ingredient Substitutions: Smart suggestions for ingredient alternatives
—Dietary Accommodations: Support for various dietary preferences and restrictions
—Web Search Integration: Real-time cooking information from trusted sources
—Memory System: Contextual conversation continuity

🛠️ Technical Stack

—Backend: FastAPI with Python 3.9+
—AI Models: Google Gemini Flash API
—Memory: FAISS + Sentence Transformers for semantic search
—Translation: HuggingFace Transformers (VietAI/envit5-translation, Helsinki-NLP/opus-mt-zh-en)
—Web Search: DuckDuckGo + specialized cooking engines
—Deployment: Docker container on HuggingFace Spaces

🏃‍♂️ Quick Start

The API is automatically deployed and running on HuggingFace Spaces. You can interact with it through the web interface or API endpoints.

API Endpoints

—GET / - Health check
—POST /chat - Main chat endpoint
—GET /health - System health status

Example Usage

python

import requests

# Chat with the cooking tutor
response = requests.post("https://your-space-url.hf.space/chat", json={
    "user_id": "user123",
    "query": "How do I make perfect pasta?",
    "lang": "EN"
})

print(response.json())

🌍 Multilingual Support

The cooking tutor supports three languages:

—English (EN): Full feature support
—Vietnamese (VI): Complete Vietnamese language support
—Chinese (ZH): Simplified Chinese support

🔧 Environment Variables

Required environment variables for deployment:

bash

FlashAPI=your_gemini_api_key

📚 API Documentation

Chat Endpoint

POST /chat

Request body:

json

{
    "user_id": "string",
    "query": "string",
    "lang": "EN|VI|ZH",
    "search_mode": true,
    "video_mode": false,
    "servings": 4,
    "dietary": ["vegetarian"],
    "allergens": ["nuts"],
    "equipment": ["oven", "stovetop"],
    "time_limit_minutes": 30,
    "skill_level": "beginner|intermediate|advanced",
    "cuisine": "italian",
    "structured": false
}

Response:

json

{
    "response": "string",
    "videos": [
        {
            "title": "string",
            "url": "string",
            "thumbnail": "string",
            "source": "string"
        }
    ]
}

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Frontend      │    │   FastAPI        │    │   AI Models     │
│   (Vercel)      │◄──►│   Backend        │◄──►│   (Gemini)      │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                              │
                              ▼
                       ┌──────────────────┐
                       │   Search &       │
                       │   Memory         │
                       │   Systems        │
                       └──────────────────┘

🔍 Search & Memory

—Web Search: Real-time cooking information from multiple sources
—Memory Management: Short-term and long-term memory for conversation context
—Content Processing: Advanced content extraction and summarization
—Citation System: Proper source attribution with inline citations

🚀 Deployment

This space is configured for Docker deployment on HuggingFace Spaces:

—Port: 7860
—Base Image: Python 3.9
—Auto-deploy: Enabled on push to main branch

📄 License

MIT License - see LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.

📞 Support

For support or questions, please open an issue in the repository.