Transform your smart home experience with powerful AI assistance powered by OpenAI's GPT models. Get intelligent responses, automate complex scenarios, and enhance your home automation with natural language processing.
--- ## ๐ Features - ๐ง **Advanced AI Integration**: - Support for latest GPT models - Context-aware responses - Multi-turn conversations - ๐ฌ **Natural Language Control**: - Control devices using everyday language - Get detailed explanations and recommendations - Natural conversation flow - ๐ **Smart Memory Management**: - Persistent conversation history - Context-aware responses - Customizable history limits - โก **Performance Optimized**: - Efficient token usage - Rate limit handling - Response caching - ๐ฏ **Advanced Customization**: - Adjustable response parameters - Custom system prompts - Model selection per request - ๐ **Enhanced Security**: - Secure API key storage - Rate limiting protection - Error handling - ๐จ **User Experience**: - Intuitive configuration UI - Detailed sensor attributes - Rich service interface - ๐ **Automation Integration**: - Event-driven responses - Conditional logic support - Template compatibility ## ๐ Prerequisites - Home Assistant 2023.8.0 or newer - OpenAI API key ([Get one here](https://platform.openai.com/account/api-keys)) - Python 3.9 or newer - Stable internet connection ## โก Installation ### HACS Installation (Recommended) 1. Open HACS in Home Assistant 2. Click the "+" button 3. Search for "HA Text AI" 4. Click "Install" 5. Restart Home Assistant ### Manual Installation 1. Download the latest release 2. Extract and copy `custom_components/ha_text_ai` to your `custom_components` directory 3. Restart Home Assistant 4. Add configuration via UI or YAML ## โ๏ธ Configuration ### Via UI (Recommended) 1. Go to Settings โ Devices & Services 2. Click "Add Integration" 3. Search for "HA Text AI" 4. Follow the configuration steps ### Via YAML ```yaml ha_text_ai: api_key: !secret openai_api_key model: gpt-3.5-turbo temperature: 0.7 max_tokens: 1000 request_interval: 1.0 api_endpoint: https://api.openai.com/v1 # optional ``` ## ๐ ๏ธ Available Services ### ask_question ```yaml service: ha_text_ai.ask_question data: question: "What's the optimal temperature for sleeping?" model: "gpt-4o" # optional temperature: 0.5 # optional max_tokens: 500 # optional ``` ### set_system_prompt ```yaml service: ha_text_ai.set_system_prompt data: prompt: | You are a home automation expert focused on: 1. Energy efficiency 2. Comfort optimization 3. Security considerations Provide practical, actionable advice. ``` ### clear_history ```yaml service: ha_text_ai.clear_history ``` ### get_history ```yaml service: ha_text_ai.get_history data: limit: 5 # optional ``` ## ๐ง Advanced Examples ### Smart Energy Management ```yaml automation: alias: "AI Energy Optimization" trigger: platform: time_pattern hours: "/2" action: - service: ha_text_ai.ask_question data: question: > Current power usage: {{ states('sensor.total_power') }}W Temperature: {{ states('sensor.indoor_temperature') }}ยฐC Time: {{ now().strftime('%H:%M') }} Occupancy: {{ states('binary_sensor.occupancy') }} Analyze current energy usage and suggest optimizations considering comfort and efficiency. temperature: 0.3 max_tokens: 200 - service: notify.mobile_app data: message: "{{ states.sensor.ha_text_ai.attributes.response }}" ``` ### Contextual Lighting Control ```yaml automation: alias: "AI Lighting Assistant" trigger: platform: state entity_id: binary_sensor.motion variables: context: > Time: {{ now().strftime('%H:%M') }} Light Level: {{ states('sensor.illuminance') }} Room: {{ trigger.to_state.attributes.room }} Activity: {{ states('input_select.current_activity') }} Weather: {{ states('weather.home') }} action: - service: ha_text_ai.ask_question data: question: > Based on this context: {{ context }} Suggest optimal lighting settings for current conditions. model: gpt-3.5-turbo temperature: 0.4 - service: scene.turn_on data: entity_id: > {{ states.sensor.ha_text_ai.attributes.response | regex_findall('scene\.[a-z_]+') | first }} ``` ## ๐ Performance Optimization ### Token Usage - Use focused system prompts - Implement response caching - Clear history periodically - Monitor token usage ### Response Time - Adjust request_interval - Use faster models for simple queries - Implement timeout handling - Cache frequent responses ### Memory Management - Set appropriate history limits - Clear unused contexts - Monitor memory usage - Use efficient data structures ## โ Troubleshooting ### API Issues - Verify API key validity - Check rate limits - Monitor usage quotas - Test endpoint accessibility ### Performance Issues - Reduce max_tokens - Increase request_interval - Clear conversation history - Check network connectivity ### Integration Issues - Verify HA version compatibility - Check component dependencies - Review log files - Update configuration ## ๐ FAQ **Q: How can I reduce API costs?** A: Use GPT-3.5-Turbo for most queries, implement caching, and optimize token usage. **Q: Is my data secure?** A: Yes, API keys are stored securely and data is transmitted via encrypted connections. **Q: Can I use custom models?** A: Yes, configure custom endpoints and models via configuration options. ## ๐ค Contributing Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md). 1. Fork the repository 2. Create feature branch (`git checkout -b feature/Enhancement`) 3. Commit changes (`git commit -m 'Add Enhancement'`) 4. Push branch (`git push origin feature/Enhancement`) 5. Open Pull Request ## ๐ License MIT License - see [LICENSE](LICENSE) for details. ---