Python AI Console

A smart home assistant powered by Azure OpenAI and Semantic Kernel that can control lights through natural language commands.

Features

• Natural language processing for smart home control
• Light control functionality (turn on/off lights in specific rooms)
• Conversational AI interface using Azure OpenAI
• Function calling capabilities with Semantic Kernel

Prerequisites

• Python 3.8 or higher
• Azure OpenAI account and API key
• pip (Python package installer)

Quick Setup

1. Clone the repository

git clone https://github.com/BachEndDeveloper/python-ai-console.git
cd python-ai-console

2. Create a virtual environment (recommended)

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Configure environment variables

cp .env.example .env

Edit the .env file with your Azure OpenAI credentials:

• AZURE_OPENAI_API_KEY: Your Azure OpenAI API key
• AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpoint URL
• AZURE_OPENAI_DEPLOYMENT_NAME: Your deployment name (e.g., "gpt-4")

5. Run the application

python main.py

Usage

Once the application is running, you can interact with it using natural language:

User > Turn on the lights in the living room
Assistant > The lights in the living room have been turned on.

User > Turn off the bedroom lights
Assistant > The lights in the bedroom have been turned off.

User > exit

Project Structure

python-ai-console/
├── main.py              # Main application entry point
├── requirements.txt     # Python dependencies
├── .env.example        # Environment variables template
├── .gitignore          # Git ignore rules
└── README.md           # This file

Development

Code Style

This project uses:

• black for code formatting
• flake8 for linting
• isort for import sorting

Run formatting:

black main.py
isort main.py
flake8 main.py

Testing

Run tests using pytest:

pytest

Configuration

The application can be configured through environment variables or by directly editing the configuration in main.py.

Key Configuration Options

• Azure OpenAI Deployment: Change the deployment_name parameter
• Logging Level: Modify the logging configuration in the main() function
• Plugin Functions: Add new functions to the LightsPlugin class

Troubleshooting

Common Issues

1. Authentication Error: Ensure your Azure OpenAI API key and endpoint are correct
2. Module Not Found: Make sure you've activated your virtual environment and installed dependencies
3. Connection Error: Check your internet connection and Azure service status

Getting Help

• Check the Semantic Kernel documentation
• Review Azure OpenAI service documentation
• Create an issue in this repository

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

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