mirror of
https://github.com/smkrv/ha-text-ai.git
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395 lines
13 KiB
Markdown
395 lines
13 KiB
Markdown
# 🤖 HA Text AI for Home Assistant
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<div align="center">
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  [](https://opensource.org/licenses/MIT) [](https://github.com/hacs/integration)   
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<img src="https://github.com/smkrv/ha-text-ai/blob/524849f6a945ec62c2cf6a6b7ecd9a28b37bf0fa/misc/icons/logo.jpg" alt="HA Text AI" width="98%"/>
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### Advanced AI Integration for Home Assistant with LLM multi-provider support
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</div>
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<p align="center">
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Transform your smart home experience with powerful AI assistance powered by multiple AI providers including OpenAI GPT and Anthropic Claude models. Get intelligent responses, automate complex scenarios, and enhance your home automation with advanced natural language processing.
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</p>
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---
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> [!IMPORTANT]
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> 🚧 ALPHA VERSION 🚧
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> Expect: potential bugs, frequent changes, incomplete features.
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> 🤝 Community Driven
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>
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> <a href="https://community.home-assistant.io/t/ha-text-ai-transforming-home-automation-with-multi-provider-language-models/799741"><img src="https://img.shields.io/badge/Community-blue?style=for-the-badge&logo=homeassistant&logoColor=white&color=03a9f4"/></a>
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## 🌟 Features
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- 🧠 **Multi-Provider AI Integration**:
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- Support for OpenAI GPT models
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- Anthropic Claude integration
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- Custom API endpoints
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- Flexible model selection
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- 💬 **Advanced Language Processing**:
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- Context-aware responses
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- Multi-turn conversations
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- Custom system instructions
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- Natural conversation flow
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- 📝 **Enhanced Memory Management**:
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- Persistent conversation history
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- Context-aware responses
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- Customizable history limits
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- Model-specific filtering
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- ⚡ **Performance Optimization**:
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- Efficient token usage
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- Smart rate limiting
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- Response caching
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- Request interval control
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- 🎯 **Advanced Customization**:
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- Per-request model selection
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- Adjustable parameters
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- Custom system prompts
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- Temperature control
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- 🔒 **Enhanced Security**:
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- Secure API key storage
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- Rate limiting protection
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- Error handling
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- Usage monitoring
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- 🎨 **Improved User Experience**:
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- Intuitive configuration UI
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- Detailed sensor attributes
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- Rich service interface
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- Model selection UI
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- 🔄 **Automation Integration**:
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- Event-driven responses
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- Conditional logic support
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- Template compatibility
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- Model-specific automation
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## 📋 Prerequisites
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- Home Assistant 2024.11 or later
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- Active API key from:
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- OpenAI ([Get key](https://platform.openai.com/account/api-keys))
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- Anthropic ([Get key](https://console.anthropic.com/))
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- OpenRouter ([Get key](https://openrouter.ai/keys))
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- Python 3.9 or newer
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- Stable internet connection
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### Configuration Options
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- API Provider (OpenAI/Anthropic)
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- API Key (provider-specific)
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- Model Selection (flexible, provider-specific models)
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- Temperature (Creativity control, 0.0-2.0)
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- Max Tokens (Response length limit)
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- Request Interval (API call throttling)
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- Custom API Endpoint (optional)
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#### ⓘ Potentially Compatible Providers
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The integration is designed to be flexible and may work with other providers offering OpenAI-compatible APIs:
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- Groq
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- Together AI
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- Perplexity AI
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- Mistral AI
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- Google AI
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- Local AI servers (like Ollama)
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- Custom OpenAI-compatible endpoints
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#### Additional Notes
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- Not all providers guarantee full compatibility
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- Performance may vary between providers
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- Check individual provider's documentation
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- Ensure your API key has sufficient credits/quota
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#### Provider Compatibility Requirements
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To be compatible, a provider should support:
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- OpenAI-like REST API structure
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- JSON request/response format
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- Standard authentication method
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- Similar model parameter handling
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## ⚡ Installation
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### HACS Installation (Recommended)
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<a href="https://my.home-assistant.io/redirect/hacs_repository/?owner=smkrv&repository=ha-text-ai&category=Integration"><img src="https://my.home-assistant.io/badges/hacs_repository.svg" width="170" height="auto"></a>
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1. Open HACS in Home Assistant
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2. Click on "Integrations"
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3. Click "..." in top right corner
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4. Select "Custom repositories"
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5. Add repository URL: `https://github.com/smkrv/ha-text-ai`
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6. Choose "Integration" as category
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7. Click "Download"
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8. Restart Home Assistant
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### Manual Installation
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1. Download the latest release
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2. Extract and copy `custom_components/ha_text_ai` to your `custom_components` directory
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3. Restart Home Assistant
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4. Add configuration via UI or YAML
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## ⚙️ Configuration
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### Via UI (Recommended)
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1. Go to Settings → Devices & Services
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2. Click "Add Integration"
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3. Search for "HA Text AI"
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4. Follow the configuration steps
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### Via YAML
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```yaml
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ha_text_ai:
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api_provider: openai # or anthropic
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api_key: !secret ai_api_key
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model: gpt-4o-mini
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temperature: 0.7
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max_tokens: 1000
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request_interval: 1.0
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api_endpoint: https://api.openai.com/v1 # optional, for custom endpoints
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system_prompt: |
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You are a home automation expert assistant.
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Focus on practical and efficient solutions.
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```
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## 🛠️ Available Services
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### ask_question
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```yaml
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service: ha_text_ai.ask_question
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data:
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question: "What's the optimal temperature for sleeping?"
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model: "claude-3-sonnet" # optional
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temperature: 0.5 # optional
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max_tokens: 500 # optional
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context_messages: 10 #optional, number of previous messages to include in context, default: 5
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system_prompt: "You are a sleep optimization expert" # optional
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```
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### set_system_prompt
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```yaml
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service: ha_text_ai.set_system_prompt
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data:
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prompt: |
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You are a home automation expert focused on:
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1. Energy efficiency
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2. Comfort optimization
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3. Security considerations
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Provide practical, actionable advice.
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```
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### clear_history
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```yaml
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service: ha_text_ai.clear_history
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```
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### get_history
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```yaml
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service: ha_text_ai.get_history
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data:
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limit: 5 # optional
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filter_model: "gpt-4o" # optional
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```
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### 🏷️ HA Text AI Sensor Naming Convention
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#### Sensor Name Structure
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```yaml
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# Always starts with 'sensor.ha_text_ai_'
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# You define only the part after the underscore
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sensor.ha_text_ai_YOUR_UNIQUE_SUFFIX
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# Examples:
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sensor.ha_text_ai_gpt # GPT-based sensor
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sensor.ha_text_ai_claude # Claude-based sensor
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sensor.ha_text_ai_gpt # Custom suffix
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```
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#### Response Retrieval
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```yaml
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# Use your specific sensor name
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{{ state_attr('sensor.ha_text_ai_gpt', 'response') }}
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```
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#### Practical Usage
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```yaml
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automation:
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- alias: "AI Response with Custom Sensor"
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action:
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- service: ha_text_ai.ask_question
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data:
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question: "Home automation advice"
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- service: notify.mobile
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data:
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message: >
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AI Tip:
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{{ state_attr('sensor.ha_text_ai_gpt', 'response') }}
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```
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### 💡 Naming Rules
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- Prefix is always `sensor.ha_text_ai_`
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- Add your unique identifier after the underscore
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- Use lowercase
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- No spaces allowed
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- Keep it descriptive but concise
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### 🔍 HA Text AI Sensor Attributes
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#### Model and Provider Information
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```yaml
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# Name of the AI model currently in use (e.g., latest version of GPT)
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{{ state_attr('sensor.ha_text_ai_gpt', 'Model') }} # gpt-4o
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# Service provider for the AI model (determines API endpoint and authentication)
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{{ state_attr('sensor.ha_text_ai_gpt', 'Api provider') }} # openai
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# Previous or alternative model configuration
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{{ state_attr('sensor.ha_text_ai_gpt', 'Last model') }} # gpt-4o
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```
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#### System Status
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```yaml
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# Current operational readiness of the AI service API
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{{ state_attr('sensor.ha_text_ai_gpt', 'Api status') }} # ready
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# Indicates if a request is currently being processed
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{{ state_attr('sensor.ha_text_ai_gpt', 'Is processing') }} # false
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# Shows if the API has hit its request rate limit
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{{ state_attr('sensor.ha_text_ai_gpt', 'Is rate limited') }} # false
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# Status of the specific API endpoint being used
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{{ state_attr('sensor.ha_text_ai_gpt', 'Endpoint status') }} # ready
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```
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#### Performance Metrics
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```yaml
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# Total number of successfully completed API requests
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{{ state_attr('sensor.ha_text_ai_gpt', 'Successful requests') }} # 0
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# Number of API requests that encountered errors
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{{ state_attr('sensor.ha_text_ai_gpt', 'Failed requests') }} # 0
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# Mean time taken to receive a response from the AI service
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{{ state_attr('sensor.ha_text_ai_gpt', 'Average latency') }} # 0
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# Maximum time taken for a single request-response cycle
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{{ state_attr('sensor.ha_text_ai_gpt', 'Max latency') }} # 0
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```
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#### Conversation and Token Usage
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```yaml
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# Number of previous interactions stored in conversation context
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{{ state_attr('sensor.ha_text_ai_gpt', 'History size') }} # 0
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# Total number of tokens used across all interactions
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{{ state_attr('sensor.ha_text_ai_gpt', 'Total tokens') }} # 0
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# Tokens used in the input prompts
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{{ state_attr('sensor.ha_text_ai_gpt', 'Prompt tokens') }} # 0
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# Tokens used in the AI's generated responses
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{{ state_attr('sensor.ha_text_ai_gpt', 'Completion tokens') }} # 0
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```
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#### Last Interaction Details
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```yaml
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# Most recent complete response generated by the AI service
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{{ state_attr('sensor.ha_text_ai_gpt', 'Response') }} # Last AI response
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# The most recently processed user query or prompt
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{{ state_attr('sensor.ha_text_ai_gpt', 'Question') }} # Last asked question
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# Precise moment when the last interaction occurred (useful for tracking and logging)
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{{ state_attr('sensor.ha_text_ai_gpt', 'Last timestamp') }} # Timestamp
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```
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#### System Health
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```yaml
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# Cumulative count of all errors encountered during AI service interactions
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{{ state_attr('sensor.ha_text_ai_gpt', 'Total errors') }} # 0
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# Indicates if the AI service is currently undergoing scheduled or emergency maintenance
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{{ state_attr('sensor.ha_text_ai_gpt', 'Is maintenance') }} # false
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# Total continuous operational time of the AI service (in hours or days)
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{{ state_attr('sensor.ha_text_ai_gpt', 'Uptime') }} # 547,58
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```
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### 💡 Pro Tips
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- Always check attribute existence
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- Use these attributes for monitoring and automation
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- Some values might be 0 or empty initially
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## 📘 FAQ
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**Q: Which AI providers are supported?**
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A: Currently OpenAI (GPT models) and Anthropic (Claude models) are supported, with more providers planned.
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**Q: How can I reduce API costs?**
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A: Use GPT-3.5-Turbo or Claude-3-Sonnet for most queries, implement caching, and optimize token usage.
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**Q: Are there limitations on the number of requests?**
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A: Depends on your API provider's plan. We recommend monitoring usage and implementing request throttling via `request_interval` configuration.
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**Q: Can I use custom models?**
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A: Yes, you can configure custom endpoints and use any compatible model by specifying it in the configuration.
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**Q: How do I switch between different AI providers?**
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A: Simply change the model parameter in your configuration or service calls to use the desired provider's model.
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**Q: How can I reduce API costs?**
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A: Use GPT-3.5-Turbo for most queries, implement caching, and optimize token usage.
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**Q: Is my data secure?**
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A: Yes, your data is secure. The system operates entirely on your local machine, keeping your data under your control. API keys are stored securely and all external communications use encrypted connections.
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**Q: How do context messages work?**
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A: Context messages allow the AI to remember and reference previous conversation history. By default, 5 previous messages are included, but you can customize this from 1 to 20 messages to control the conversation depth and token usage.
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## 🤝 Contributing
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Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md).
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1. Fork the repository
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2. Create feature branch (`git checkout -b feature/Enhancement`)
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3. Commit changes (`git commit -m 'Add Enhancement'`)
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4. Push branch (`git push origin feature/Enhancement`)
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5. Open Pull Request
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## 📝 License
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MIT License - see [LICENSE](LICENSE) for details.
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## 💡 Support the Project
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The best support is:
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- Sharing feedback
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- Contributing ideas
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- Recommending to friends
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- Reporting issues
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- Star the repository
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If you want to say thanks financially, you can send a small token of appreciation in USDT:
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**USDT Wallet (TRC10/TRC20):**
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`TXC9zYHYPfWUGi4Sv4R1ctTBGScXXQk5HZ`
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*Open-source is built by community passion!* 🚀
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---
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<div align="center">
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Made with ❤️ and Claude 3.5 Sonnet for the Home Assistant Community
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[Report Bug](https://github.com/smkrv/ha-text-ai/issues) · [Request Feature](https://github.com/smkrv/ha-text-ai/issues)
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</div>
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