🍳 Recipe AI Chatbot

A sophisticated AI-powered recipe chatbot built with TypeScript, Node.js, Azure OpenAI, and Langchain. The bot specializes in providing detailed cooking recipes with step-by-step instructions, ingredient lists, cooking times, and helpful tips.

✨ Features

🤖 AI-Powered: Uses Azure OpenAI (O1-Mini) for intelligent recipe generation
🔧 Langchain Integration: Built with Langchain for robust AI workflow management
📝 Detailed Recipes: Provides comprehensive recipes with:
- Complete ingredient lists with measurements
- Step-by-step cooking instructions
- Cooking times and temperatures
- Difficulty levels and serving sizes
- Helpful cooking tips
💬 Conversation Logging: All interactions are logged to trace files for analysis
🎨 Clean UI: Simple, responsive web interface
🚀 TypeScript: Type-safe development with full TypeScript support
📱 Responsive Design: Works seamlessly on desktop and mobile devices

🏗️ Tech Stack

Backend: Node.js, Express.js, TypeScript
AI Integration: Azure OpenAI, Langchain
Frontend: Vanilla HTML5, CSS3, JavaScript
Development: ts-node, nodemon
Environment: dotenv for configuration

📁 Project Structure

recipe-ai-chatbot/
├── src/
│   └── server.ts          # Main TypeScript server
├── public/
│   └── index.html         # Frontend interface
├── logs/                  # Conversation logs (auto-created)
├── dist/                  # Compiled JavaScript (auto-created)
├── .env.example           # Environment variables template
├── package.json           # Dependencies and scripts
├── tsconfig.json          # TypeScript configuration
└── README.md              # This file

🚀 Quick Start

Prerequisites

Node.js 18+ and npm 8+
Azure OpenAI account with O1-Mini deployment
Git (for cloning)

Installation

Clone the repository

git clone https://github.com/YOUR_USERNAME/recipe-ai-chatbot.git
cd recipe-ai-chatbot

Install dependencies
```
npm install
```

Configure environment variables

# Copy the example file
cp .env.example .env

# Edit .env with your Azure OpenAI credentials
nano .env  # or use your preferred editor

Set up your Azure OpenAI credentials in .env

AZURE_OPENAI_API_KEY=your_api_key_here
AZURE_OPENAI_INSTANCE_NAME=your_instance_name
AZURE_OPENAI_DEPLOYMENT_NAME=o1-mini
AZURE_OPENAI_API_VERSION=2024-02-15-preview
PORT=3000

Run the application

# Development mode (recommended)
npm run dev

# Or production build
npm run build && npm start

Open your browser
```
http://localhost:3000
```

🎯 Usage Examples

Try these example prompts in the chat interface:

"Give me a recipe for homemade pasta"
"How to make chocolate chip cookies?"
"I want to cook something with chicken and rice"
"Show me an easy vegetarian dinner recipe"
"What can I make with tomatoes and cheese?"

🔧 Available Scripts

npm run dev      # Development mode with auto-reload
npm run build    # Compile TypeScript to JavaScript
npm start        # Run production server
npm run watch    # Development with file watching
npm run clean    # Remove compiled files

📊 API Endpoints

POST /api/chat

Send a message to the AI chatbot.

Request:

{
  "message": "Give me a recipe for homemade pasta",
  "sessionId": "optional_session_id"
}

Response:

{
  "response": "Here's a detailed recipe for homemade pasta...",
  "sessionId": "session_12345_abcdef",
  "timestamp": "2024-08-07T10:30:00.000Z"
}

GET /api/history/:sessionId

Retrieve conversation history for a specific session.

GET /api/health

Check server health status and active sessions.

🔒 Security & Privacy

All sensitive data is protected via environment variables
API keys and credentials are never committed to the repository
Conversation logs are stored locally and can be configured
No personal data is sent to external services beyond Azure OpenAI

🛠️ Development

Adding New Features

The modular architecture makes it easy to extend:

New API endpoints: Add routes in setupRoutes() method
Additional logging: Extend the TraceLog interface
UI enhancements: Modify the frontend JavaScript class
AI model changes: Update the initializeChatModel() method

Code Structure

server.ts: Main backend logic, API routes, AI integration
index.html: Complete frontend with HTML, CSS, and JavaScript
package.json: Dependencies and build scripts
tsconfig.json: TypeScript compiler configuration

📝 Environment Variables

Required environment variables (create these in your .env file):

| Variable | Description | Example | |----------|-------------|---------| | AZURE_OPENAI_API_KEY | Your Azure OpenAI API key | abc123def456... | | AZURE_OPENAI_INSTANCE_NAME | Azure OpenAI resource name | my-openai-resource | | AZURE_OPENAI_DEPLOYMENT_NAME | Model deployment name | o1-mini | | AZURE_OPENAI_API_VERSION | API version | 2024-02-15-preview | | PORT | Server port (optional) | 3000 |

🐛 Troubleshooting

Common Issues

1. "OpenAI API key not found" error

Verify your .env file exists and contains all required variables
Check that your Azure OpenAI deployment is active

2. "Port already in use" error

Change the PORT in your .env file
Or stop other services using port 3000

3. TypeScript compilation errors

Run npm run clean then npm run build
Ensure TypeScript is installed: npm install -g typescript

4. Connection to Azure OpenAI fails

Verify your deployment name matches exactly what's in Azure OpenAI Studio
Check your instance name and API version

Debug Mode

Enable debug logging by setting:

NODE_ENV=development

📋 Contributing

Fork the repository
Create a feature branch: git checkout -b feature-name
Make your changes and test thoroughly
Commit your changes: git commit -m 'Add feature-name'
Push to your branch: git push origin feature-name
Submit a pull request

📄 License

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

🙏 Acknowledgments

Built with Langchain for AI orchestration
Powered by Azure OpenAI
UI inspired by modern chat interfaces

📞 Support

If you encounter any issues:

Check the troubleshooting section
Review the Azure OpenAI documentation
Open an issue in this repository
Check the console logs for detailed error messages

Happy Cooking! 👨‍🍳👩‍🍳