Release v2.0.2-beta

- Add comprehensive explanations for HA Text AI sensor attributes
- Improve readability of README.md documentation
- Provide context and usage details for each sensor attribute
- Translate comments to English with technical clarity

Changes include:
* Detailed descriptions for Model and Provider Information
* Expanded System Status attribute explanations
* Clarified Performance Metrics comments
* Added context for Conversation and Token Usage
* Improved Last Interaction Details descriptions
* Enhanced System Health attribute documentation

.github/workflows/validate.yaml

@@ -0,0 +1,17 @@
+name: Validate
+
+on:
+  push:
+  pull_request:
+  schedule:
+    - cron: "0 0 * * *"
+  workflow_dispatch:
+
+jobs:
+  validate-hacs:
+    runs-on: "ubuntu-latest"
+    steps:
+      - name: HACS validation
+        uses: "hacs/action@main"
+        with:
+          category: "integration"

.gitignore

@@ -1,8 +1,39 @@
+# Python
 __pycache__/
 *.py[cod]
 *$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Home Assistant
+.storage
+.cloud
+.google.token
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+*~
+
+# OS
 .DS_Store
-.env
-.venv
-venv/
-ENV/
+Thumbs.db
+*.psd
+*.zip

CONTRIBUTING.md

@@ -0,0 +1,110 @@
+# 🤝 Contributing Guide
+
+We welcome contributions to the HA Text AI project! This document will help you contribute to the project's development.
+
+## 🌟 How to Contribute
+
+### 1. Preparation
+
+1. Fork the Repository
+   - Go to the repository page on GitHub
+   - Click the "Fork" button in the top right corner
+
+2. Clone Your Fork
+   ```bash
+   git clone https://github.com/YOUR_USERNAME/ha-text-ai.git
+   cd ha-text-ai
+   ```
+
+3. Set Up Remote Repositories
+   ```bash
+   git remote add upstream https://github.com/smkrv/ha-text-ai.git
+   ```
+
+### 2. Creating a Development Branch
+
+```bash
+# Update the main branch
+git checkout main
+git pull upstream main
+
+# Create a new branch for your feature
+git checkout -b feature/short-description-of-changes
+```
+
+### 3. Development
+
+- Follow the project's coding standards
+- Write clean and understandable code
+- Add comments when necessary
+- Create unit tests for new functionality
+
+### 4. Committing Changes
+
+```bash
+# Add modified files
+git add .
+
+# Create a meaningful commit
+git commit -m "Feat: Add [short feature description]"
+```
+
+### 5. Commit Message Style
+
+Use the following prefixes:
+- `Feat:` - new feature
+- `Fix:` - bug fixes
+- `Docs:` - documentation updates
+- `Style:` - formatting changes
+- `Refactor:` - code refactoring
+- `Test:` - adding tests
+- `Chore:` - project maintenance
+
+### 6. Pushing Changes
+
+```bash
+# Push changes to your fork
+git push origin feature/short-description-of-changes
+```
+
+### 7. Creating a Pull Request (PR)
+
+1. Go to your fork on GitHub
+2. Click "New Pull Request"
+3. Select the base branch `main` of the original repository
+4. Fill out the PR description:
+   - Brief description of changes
+   - Motivation for changes
+   - Screenshots (if applicable)
+
+### 8. Review Process
+
+- Project maintainers will review your PR
+- There may be comments and requests for changes
+- After approval, the PR will be merged
+
+## 🛠 Code Requirements
+
+- Follow PEP 8 for Python
+- Write clear and self-documenting code
+- Add type hints
+- Cover code with tests
+
+## 🐛 Found a Bug?
+
+1. Check existing Issues
+2. Create a new Issue with:
+   - Bug description
+   - Reproduction steps
+   - Home Assistant version
+   - Plugin version
+
+## 📜 License
+
+By contributing to the project, you agree to the [project's license](LICENSE).
+
+## 🤔 Questions?
+
+If you have any questions, create an Issue or contact the project maintainers.
+
+**Thank you for your contribution!** 🎉

LICENSE

@@ -19,3 +19,4 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
+ 

README.md

@@ -2,16 +2,27 @@
 
 <div align="center">  
 
-  ![GitHub release](https://img.shields.io/github/release/smkrv/ha-text-ai.svg?style=flat-square) ![GitHub downloads](https://img.shields.io/github/downloads/smkrv/ha-text-ai/total.svg?style=flat-square) ![GitHub stars](https://img.shields.io/github/stars/smkrv/ha-text-ai.svg?style=social) ![GitHub last commit](https://img.shields.io/github/last-commit/smkrv/ha-text-ai.svg?style=flat-square) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT) [![hacs_badge](https://img.shields.io/badge/HACS-Custom-41BDF5.svg?style=flat-square)](https://github.com/hacs/integration)
+![GitHub release](https://img.shields.io/github/release/smkrv/ha-text-ai.svg?style=flat-square) ![GitHub last commit](https://img.shields.io/github/last-commit/smkrv/ha-text-ai.svg?style=flat-square) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT) [![hacs_badge](https://img.shields.io/badge/HACS-Custom-41BDF5.svg?style=flat-square)](https://github.com/hacs/integration) ![/README.md](https://img.shields.io/badge/language-English-green?style=flat-square) ![/README_RU.md](https://img.shields.io/badge/language-Russian-green?style=flat-square) ![](https://img.shields.io/badge/language-Deutch-green?style=flat-square)
 
+  <img src="https://github.com/smkrv/ha-text-ai/blob/524849f6a945ec62c2cf6a6b7ecd9a28b37bf0fa/misc/icons/logo.jpg" alt="HA Text AI" height="160"/>
+
+### Advanced AI Integration for Home Assistant with LLM multi-provider support
 </div>
 
 <p align="center">
 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.
+
 </p>
 
 ---
 
+> [!IMPORTANT]
+> 🚧 ALPHA VERSION 🚧  
+> Expect: potential bugs, frequent changes, incomplete features.  
+> 🤝 Community Driven  
+>
+>  <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>  
+
 ## 🌟 Features
 
 - 🧠 **Multi-Provider AI Integration**:
@@ -19,36 +30,43 @@ Transform your smart home experience with powerful AI assistance powered by mult
   - Anthropic Claude integration
   - Custom API endpoints
   - Flexible model selection
+
 - 💬 **Advanced Language Processing**:
   - Context-aware responses
   - Multi-turn conversations
   - Custom system instructions
   - Natural conversation flow
+
 - 📝 **Enhanced Memory Management**:
   - Persistent conversation history
   - Context-aware responses
   - Customizable history limits
   - Model-specific filtering
+
 - ⚡ **Performance Optimization**:
   - Efficient token usage
   - Smart rate limiting
   - Response caching
   - Request interval control
+
 - 🎯 **Advanced Customization**:
   - Per-request model selection
   - Adjustable parameters
   - Custom system prompts
   - Temperature control
+
 - 🔒 **Enhanced Security**:
   - Secure API key storage
   - Rate limiting protection
   - Error handling
   - Usage monitoring
+
 - 🎨 **Improved User Experience**:
   - Intuitive configuration UI
   - Detailed sensor attributes
   - Rich service interface
   - Model selection UI
+
 - 🔄 **Automation Integration**:
   - Event-driven responses
   - Conditional logic support
@@ -57,25 +75,58 @@ Transform your smart home experience with powerful AI assistance powered by mult
 
 ## 📋 Prerequisites
 
-- Home Assistant 2023.8.0 or newer
-- API key from supported providers:
+- Home Assistant 2024.11 or later
+- Active API key from:
   - OpenAI ([Get key](https://platform.openai.com/account/api-keys))
   - Anthropic ([Get key](https://console.anthropic.com/))
+  - OpenRouter ([Get key](https://openrouter.ai/keys))
 - Python 3.9 or newer
 - Stable internet connection
 
+### Configuration Options
+- API Provider (OpenAI/Anthropic)
+- API Key (provider-specific)
+- Model Selection (flexible, provider-specific models)
+- Temperature (Creativity control, 0.0-2.0)
+- Max Tokens (Response length limit)
+- Request Interval (API call throttling)
+- Custom API Endpoint (optional)
+
+#### ⓘ Potentially Compatible Providers  
+The integration is designed to be flexible and may work with other providers offering OpenAI-compatible APIs:  
+- Groq  
+- Together AI  
+- Perplexity AI  
+- Mistral AI  
+- Google AI  
+- Local AI servers (like Ollama)  
+- Custom OpenAI-compatible endpoints  
+
+#### Additional Notes  
+- Not all providers guarantee full compatibility  
+- Performance may vary between providers  
+- Check individual provider's documentation  
+- Ensure your API key has sufficient credits/quota
+
+#### Provider Compatibility Requirements  
+To be compatible, a provider should support:  
+- OpenAI-like REST API structure  
+- JSON request/response format  
+- Standard authentication method  
+- Similar model parameter handling
+
 ## ⚡ Installation
 
-### HACS Installation (Recommended)  
-1. Open HACS in Home Assistant  
-2. Click on the three dots in the top right corner  
-3. Select "Custom repositories"  
-4. Add `https://github.com/smkrv/ha-text-ai` as Integration  
-5. Click "Add"  
-6. Click on "Integrations" in HACS  
-7. Search for "HA Text AI"  
-8. Click "Download"  
-9. Restart Home Assistant  
+### HACS Installation (Recommended)
+<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>
+1. Open HACS in Home Assistant
+2. Click on "Integrations"
+3. Click "..." in top right corner
+4. Select "Custom repositories"
+5. Add repository URL: `https://github.com/smkrv/ha-text-ai`
+6. Choose "Integration" as category
+7. Click "Download"
+8. Restart Home Assistant
 
 ### Manual Installation
 1. Download the latest release
@@ -92,19 +143,61 @@ Transform your smart home experience with powerful AI assistance powered by mult
 4. Follow the configuration steps
 
 ### Via YAML
+
+### Platform Configuration (Global Settings)
+
 ```yaml
 ha_text_ai:
-  api_key: !secret ai_api_key
-  model: gpt-3.5-turbo  # or claude-3-sonnet
-  temperature: 0.7
-  max_tokens: 1000
-  request_interval: 1.0
-  api_endpoint: https://api.openai.com/v1  # optional, for custom endpoints
-  system_prompt: |
+  api_provider: openai  # Required
+  api_key: !secret ai_api_key  # Required
+  model: gpt-4o-mini  # Strongly recommended
+  temperature: 0.7  # Optional
+  max_tokens: 1000  # Optional
+  request_interval: 1.0  # Optional
+  api_endpoint: https://api.openai.com/v1  # Required
+  system_prompt: |  # Optional
     You are a home automation expert assistant.
     Focus on practical and efficient solutions.
 ```
 
+### Sensor Configuration
+
+```yaml
+sensor:
+  - platform: ha_text_ai
+    name: "My AI Assistant"  # Required, unique identifier
+    api_provider: openai  # Optional (inherits from platform)
+    model: "gpt-4o-mini"  # Optional
+    temperature: 0.7  # Optional
+    max_tokens: 1000  # Optional
+```
+
+### 📋 Configuration Parameters
+
+#### Platform Configuration
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `api_provider` | String | ✅ | - | AI service provider (openai, anthropic) |
+| `api_key` | String | ✅ | - | Authentication key for AI service |
+| `model` | String | ⚠️ | Provider default | Strongly recommended: Specific AI model to use. If not specified, the provider's default model will be used |
+| `temperature` | Float | ❌ | 0.7 | Response creativity level (0.0-2.0) |
+| `max_tokens` | Integer | ❌ | 1000 | Maximum response length |
+| `request_interval` | Float | ❌ | 1.0 | Delay between API requests |
+| `api_endpoint` | URL | ⚠️ | Provider default | Custom API endpoint |
+| `system_prompt` | String | ❌ | - | Default context for AI interactions |
+
+#### Sensor Configuration
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `platform` | String | ✅ | - | Must be `ha_text_ai` |
+| `name` | String | ✅ | - | Unique sensor identifier |
+| `api_provider` | String | ❌ | Platform setting | Override global provider |
+| `model` | String | ⚠️ | Platform setting | Recommended: Override global model. If not specified, uses platform or provider default |
+| `temperature` | Float | ❌ | Platform setting | Override global temperature |
+| `max_tokens` | Integer | ❌ | Platform setting | Override global max tokens |
+
 ## 🛠️ Available Services
 
 ### ask_question
@@ -115,6 +208,7 @@ data:
   model: "claude-3-sonnet"  # optional
   temperature: 0.5  # optional
   max_tokens: 500  # optional
+  context_messages: 10  #optional, number of previous messages to include in context, default: 5
   system_prompt: "You are a sleep optimization expert"  # optional
 ```
 
@@ -140,38 +234,171 @@ service: ha_text_ai.clear_history
 service: ha_text_ai.get_history
 data:
   limit: 5  # optional
-  filter_model: "gpt-4"  # optional
+  filter_model: "gpt-4o"  # optional
 ```
 
+### 🏷️ HA Text AI Sensor Naming Convention
+
+#### Character Restrictions  
+- Only lowercase letters (a-z)  
+- Numbers (0-9)  
+- Underscore (_)  
+- Maximum length: 50 characters (including `ha_text_ai_` prefix (14 characters)
+
+#### Sensor Name Structure
+```yaml
+# Always starts with 'sensor.ha_text_ai_'
+# You define only the part after the underscore
+sensor.ha_text_ai_YOUR_UNIQUE_SUFFIX
+
+# Examples:
+sensor.ha_text_ai_gpt      # GPT-based sensor
+sensor.ha_text_ai_claude   # Claude-based sensor
+sensor.ha_text_ai_gpt   # Custom suffix
+```
+
+#### Response Retrieval
+```yaml
+# Use your specific sensor name
+{{ state_attr('sensor.ha_text_ai_gpt', 'response') }}
+```
+
+#### Practical Usage
+```yaml
+automation:
+  - alias: "AI Response with Custom Sensor"
+    action:
+      - service: ha_text_ai.ask_question
+        data:
+          question: "Home automation advice"
+      - service: notify.mobile
+        data:
+          message: >
+            AI Tip:
+            {{ state_attr('sensor.ha_text_ai_gpt', 'response') }}
+```
+
+### 💡 Naming Rules
+- Prefix is always `sensor.ha_text_ai_`
+- Add your unique identifier after the underscore
+- Use lowercase
+- No spaces allowed
+- Keep it descriptive but concise
+
+### 🔍 HA Text AI Sensor Attributes
+
+#### Model and Provider Information
+```yaml
+# Name of the AI model currently in use (e.g., latest version of GPT)  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Model') }}           # gpt-4o  
+
+# Service provider for the AI model (determines API endpoint and authentication)  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Api provider') }}    # openai  
+
+# Previous or alternative model configuration  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Last model') }}      # gpt-4o
+```
+
+#### System Status
+```yaml
+# Current operational readiness of the AI service API  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Api status') }}      # ready  
+
+# Indicates if a request is currently being processed  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Is processing') }}   # false  
+
+# Shows if the API has hit its request rate limit  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Is rate limited') }} # false  
+
+# Status of the specific API endpoint being used  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Endpoint status') }} # ready
+```
+
+#### Performance Metrics
+```yaml
+# Total number of successfully completed API requests  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Successful requests') }}   # 0  
+
+# Number of API requests that encountered errors  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Failed requests') }}       # 0  
+
+# Mean time taken to receive a response from the AI service  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Average latency') }}       # 0  
+
+# Maximum time taken for a single request-response cycle  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Max latency') }}           # 0
+```
+
+#### Conversation and Token Usage
+```yaml
+# Number of previous interactions stored in conversation context  
+{{ state_attr('sensor.ha_text_ai_gpt', 'History size') }}          # 0  
+
+# Total number of tokens used across all interactions  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Total tokens') }}          # 0  
+
+# Tokens used in the input prompts  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Prompt tokens') }}         # 0  
+
+# Tokens used in the AI's generated responses  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Completion tokens') }}     # 0
+```
+
+#### Last Interaction Details
+```yaml
+# Most recent complete response generated by the AI service  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Response') }}        # Last AI response  
+
+# The most recently processed user query or prompt  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Question') }}        # Last asked question  
+
+# Precise moment when the last interaction occurred (useful for tracking and logging)  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Last timestamp') }}  # Timestamp
+```
+
+#### System Health
+```yaml
+# Cumulative count of all errors encountered during AI service interactions  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Total errors') }}    # 0  
+
+# Indicates if the AI service is currently undergoing scheduled or emergency maintenance  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Is maintenance') }}  # false  
+
+# Total continuous operational time of the AI service (in hours or days)  
+{{ state_attr('sensor.ha_text_ai_gpt', 'Uptime') }}          # 547,58
+```
+
+### 💡 Pro Tips
+- Always check attribute existence
+- Use these attributes for monitoring and automation
+- Some values might be 0 or empty initially
+
+
 ## 📘 FAQ
 
 **Q: Which AI providers are supported?**
-
 A: Currently OpenAI (GPT models) and Anthropic (Claude models) are supported, with more providers planned.
 
 **Q: How can I reduce API costs?**
-
 A: Use GPT-3.5-Turbo or Claude-3-Sonnet for most queries, implement caching, and optimize token usage.
 
-**Q: Can I use custom models?**
+**Q: Are there limitations on the number of requests?**
+A: Depends on your API provider's plan. We recommend monitoring usage and implementing request throttling via `request_interval` configuration.
 
+**Q: Can I use custom models?**
 A: Yes, you can configure custom endpoints and use any compatible model by specifying it in the configuration.
 
 **Q: How do I switch between different AI providers?**
-
 A: Simply change the model parameter in your configuration or service calls to use the desired provider's model.
 
 **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, 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.
 
-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.
+**Q: How do context messages work?**
+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.
 
 ## 🤝 Contributing
 
@@ -187,11 +414,27 @@ Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md).
 
 MIT License - see [LICENSE](LICENSE) for details.
 
+## 💡 Support the Project
+
+The best support is:
+- Sharing feedback
+- Contributing ideas
+- Recommending to friends
+- Reporting issues
+- Star the repository
+
+If you want to say thanks financially, you can send a small token of appreciation in USDT:
+
+**USDT Wallet (TRC10/TRC20):**
+`TXC9zYHYPfWUGi4Sv4R1ctTBGScXXQk5HZ`
+
+*Open-source is built by community passion!* 🚀
+
 ---
 
 <div align="center">
 
-Made with ❤️ for the Home Assistant Community
+Made with ❤️ and Claude 3.5 Sonnet for the Home Assistant Community
 
 [Report Bug](https://github.com/smkrv/ha-text-ai/issues) · [Request Feature](https://github.com/smkrv/ha-text-ai/issues)
 

custom_components/ha_text_ai/__init__.py

@@ -1,20 +1,24 @@
 """The HA Text AI integration."""
-import logging
-from typing import Any, Dict, Optional
-import asyncio
-import voluptuous as vol
-import json
-from datetime import datetime
+from __future__ import annotations
 
-from homeassistant.config_entries import ConfigEntry
-from homeassistant.const import CONF_API_KEY
-from homeassistant.core import HomeAssistant, ServiceCall, callback
-from homeassistant.exceptions import ConfigEntryNotReady, HomeAssistantError
-from homeassistant.helpers import aiohttp_client
-from homeassistant.helpers import config_validation as cv
+import logging
+import os
+import shutil
+from datetime import datetime, timedelta
+from typing import Any, Dict
+
+import voluptuous as vol
 from async_timeout import timeout
 
+from homeassistant.config_entries import ConfigEntry
+from homeassistant.const import CONF_API_KEY, CONF_NAME, Platform
+from homeassistant.core import HomeAssistant, ServiceCall
+from homeassistant.exceptions import ConfigEntryNotReady, HomeAssistantError
+from homeassistant.helpers import config_validation as cv
+from homeassistant.helpers import aiohttp_client
+
 from .coordinator import HATextAICoordinator
+from .api_client import APIClient
 from .const import (
     DOMAIN,
     PLATFORMS,
@@ -23,75 +27,163 @@ from .const import (
     CONF_MAX_TOKENS,
     CONF_API_ENDPOINT,
     CONF_REQUEST_INTERVAL,
+    CONF_API_PROVIDER,
+    CONF_CONTEXT_MESSAGES,
+    API_PROVIDER_OPENAI,
+    API_PROVIDER_ANTHROPIC,
     DEFAULT_MODEL,
     DEFAULT_TEMPERATURE,
     DEFAULT_MAX_TOKENS,
-    DEFAULT_API_ENDPOINT,
+    DEFAULT_OPENAI_ENDPOINT,
+    DEFAULT_ANTHROPIC_ENDPOINT,
     DEFAULT_REQUEST_INTERVAL,
-    API_VERSION,
-    API_MODELS_PATH,
-    API_CHAT_PATH,
+    DEFAULT_CONTEXT_MESSAGES,
     API_TIMEOUT,
-    API_RETRY_COUNT,
-    API_BACKOFF_FACTOR,
-    LOGGER_NAME,
-    STATE_ERROR,
-    STATE_READY,
-    STATE_PROCESSING,
-    STATE_RATE_LIMITED,
-    STATE_MAINTENANCE,
-    STATE_DISCONNECTED,
-    STATE_RETRYING,
-    STATE_QUEUED,
-    STATE_UPDATING,
-    SUPPORTED_MODELS,
-    EVENT_RESPONSE_RECEIVED,
-    EVENT_ERROR_OCCURRED,
-    EVENT_STATE_CHANGED,
+    SERVICE_ASK_QUESTION,
+    SERVICE_CLEAR_HISTORY,
+    SERVICE_GET_HISTORY,
+    SERVICE_SET_SYSTEM_PROMPT,
+    DEFAULT_MAX_HISTORY,
+    CONF_MAX_HISTORY_SIZE,
 )
 
-_LOGGER = logging.getLogger(LOGGER_NAME)
+_LOGGER = logging.getLogger(__name__)
 
 CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)
 
-# Service validation schemas
 SERVICE_SCHEMA_ASK_QUESTION = vol.Schema({
+    vol.Required("instance"): cv.string,
     vol.Required("question"): cv.string,
     vol.Optional("system_prompt"): cv.string,
-    vol.Optional("model"): vol.In(SUPPORTED_MODELS),
-    vol.Optional("temperature"): vol.All(
-        vol.Coerce(float), vol.Range(min=0, max=2)
-    ),
-    vol.Optional("max_tokens"): vol.All(
-        vol.Coerce(int), vol.Range(min=1, max=4096)
-    ),
-    vol.Optional("priority"): vol.Boolean,
-})
-
-SERVICE_SCHEMA_GET_HISTORY = vol.Schema({
-    vol.Optional("limit", default=10): vol.All(
-        vol.Coerce(int), vol.Range(min=1, max=100)
-    ),
-    vol.Optional("filter_model"): vol.In(SUPPORTED_MODELS),
-    vol.Optional("start_date"): cv.datetime,
-    vol.Optional("include_metadata"): vol.Boolean,
+    vol.Optional("model"): cv.string,
+    vol.Optional("temperature"): cv.positive_float,
+    vol.Optional("max_tokens"): cv.positive_int,
+    vol.Optional("context_messages"): cv.positive_int,
 })
 
 SERVICE_SCHEMA_SET_SYSTEM_PROMPT = vol.Schema({
+    vol.Required("instance"): cv.string,
     vol.Required("prompt"): cv.string,
 })
 
-async def async_check_api(session, endpoint: str, headers: dict, is_anthropic: bool = False) -> bool:
+SERVICE_SCHEMA_GET_HISTORY = vol.Schema({
+    vol.Required("instance"): cv.string,
+    vol.Optional("limit"): cv.positive_int,
+    vol.Optional("filter_model"): cv.string,
+})
+
+def get_coordinator_by_instance(hass: HomeAssistant, instance: str) -> HATextAICoordinator:
+    """Get coordinator by instance name."""
+    if instance.startswith("sensor."):
+        instance = instance.replace("sensor.ha_text_ai_", "", 1)
+
+    for entry_id, coord in hass.data[DOMAIN].items():
+        if isinstance(coord, HATextAICoordinator) and coord.instance_name.lower() == instance.lower():
+            return coord
+
+    raise HomeAssistantError(f"Instance {instance} not found")
+
+async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
+    """Set up the HA Text AI component."""
+    hass.data.setdefault(DOMAIN, {})
+
+    try:
+        source = os.path.join(os.path.dirname(__file__), 'icons', 'icon.svg')
+        dest_dir = os.path.join(hass.config.path('www'), 'icons')
+        os.makedirs(dest_dir, exist_ok=True)
+        dest = os.path.join(dest_dir, 'icon.png')
+        if not os.path.exists(dest):
+            shutil.copyfile(source, dest)
+    except Exception as ex:
+        _LOGGER.warning("Failed to copy custom icon: %s", str(ex))
+
+    async def async_ask_question(call: ServiceCall) -> None:
+        """Handle ask_question service."""
+        try:
+            coordinator = get_coordinator_by_instance(hass, call.data["instance"])
+            await coordinator.async_ask_question(
+                question=call.data["question"],
+                model=call.data.get("model"),
+                temperature=call.data.get("temperature"),
+                max_tokens=call.data.get("max_tokens"),
+                system_prompt=call.data.get("system_prompt"),
+                context_messages=call.data.get("context_messages"),
+            )
+        except Exception as err:
+            _LOGGER.error("Error asking question: %s", str(err))
+            raise HomeAssistantError(f"Failed to process question: {str(err)}")
+
+    async def async_clear_history(call: ServiceCall) -> None:
+        """Handle clear_history service."""
+        try:
+            coordinator = get_coordinator_by_instance(hass, call.data["instance"])
+            await coordinator.async_clear_history()
+        except Exception as err:
+            _LOGGER.error("Error clearing history: %s", str(err))
+            raise HomeAssistantError(f"Failed to clear history: {str(err)}")
+
+    async def async_get_history(call: ServiceCall) -> list:
+        """Handle get_history service."""
+        try:
+            coordinator = get_coordinator_by_instance(hass, call.data["instance"])
+            return await coordinator.async_get_history(
+                limit=call.data.get("limit"),
+                filter_model=call.data.get("filter_model")
+            )
+        except Exception as err:
+            _LOGGER.error("Error getting history: %s", str(err))
+            raise HomeAssistantError(f"Failed to get history: {str(err)}")
+
+    async def async_set_system_prompt(call: ServiceCall) -> None:
+        """Handle set_system_prompt service."""
+        try:
+            coordinator = get_coordinator_by_instance(hass, call.data["instance"])
+            await coordinator.async_set_system_prompt(call.data["prompt"])
+        except Exception as err:
+            _LOGGER.error("Error setting system prompt: %s", str(err))
+            raise HomeAssistantError(f"Failed to set system prompt: {str(err)}")
+
+    hass.services.async_register(
+        DOMAIN,
+        SERVICE_ASK_QUESTION,
+        async_ask_question,
+        schema=SERVICE_SCHEMA_ASK_QUESTION
+    )
+
+    hass.services.async_register(
+        DOMAIN,
+        SERVICE_CLEAR_HISTORY,
+        async_clear_history,
+        schema=vol.Schema({vol.Required("instance"): cv.string})
+    )
+
+    hass.services.async_register(
+        DOMAIN,
+        SERVICE_GET_HISTORY,
+        async_get_history,
+        schema=SERVICE_SCHEMA_GET_HISTORY
+    )
+
+    hass.services.async_register(
+        DOMAIN,
+        SERVICE_SET_SYSTEM_PROMPT,
+        async_set_system_prompt,
+        schema=SERVICE_SCHEMA_SET_SYSTEM_PROMPT
+    )
+
+    return True
+
+async def async_check_api(session, endpoint: str, headers: dict, provider: str) -> bool:
     """Check API availability for different providers."""
     try:
-        if is_anthropic:
+        if provider == API_PROVIDER_ANTHROPIC:
             check_url = f"{endpoint}/v1/models"
-        else:
-            check_url = f"{endpoint}/{API_VERSION}/{API_MODELS_PATH}"
+        else:  # OpenAI
+            check_url = f"{endpoint}/models"
 
         async with timeout(API_TIMEOUT):
             async with session.get(check_url, headers=headers) as response:
-                if response.status == 200:
+                if response.status in [200, 404]:
                     return True
                 elif response.status == 401:
                     raise ConfigEntryNotReady("Invalid API key")
@@ -105,32 +197,33 @@ async def async_check_api(session, endpoint: str, headers: dict, is_anthropic: b
         _LOGGER.error("API check error: %s", str(ex))
         return False
 
-async def async_setup(hass: HomeAssistant, config: dict[str, Any]) -> bool:
-    """Set up the HA Text AI component."""
-    hass.data.setdefault(DOMAIN, {
-        "coordinators": {},
-        "metrics": {
-            "total_requests": 0,
-            "total_tokens": 0,
-            "errors": {},
-            "model_usage": {},
-        }
-    })
-    return True
-
 async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
     """Set up HA Text AI from a config entry."""
+    _LOGGER.debug(f"Setting up HA Text AI entry: {entry.data}")
+
     try:
+        if CONF_API_PROVIDER not in entry.data:
+            _LOGGER.error("API provider not specified")
+            raise ConfigEntryNotReady("API provider is required")
+
+        # Get configuration
         session = aiohttp_client.async_get_clientsession(hass)
-
-        # Determine API type based on model
+        api_provider = entry.data.get(CONF_API_PROVIDER)
         model = entry.data.get(CONF_MODEL, DEFAULT_MODEL)
-        is_anthropic = any(model.startswith("claude") for model in SUPPORTED_MODELS)
-
+        endpoint = entry.data.get(
+            CONF_API_ENDPOINT,
+            DEFAULT_OPENAI_ENDPOINT if api_provider == API_PROVIDER_OPENAI
+            else DEFAULT_ANTHROPIC_ENDPOINT
+        ).rstrip('/')
         api_key = entry.data[CONF_API_KEY]
-        endpoint = entry.data.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT).rstrip('/')
+        instance_name = entry.data.get(CONF_NAME, entry.entry_id)
+        request_interval = entry.data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)
+        max_tokens = entry.data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS)
+        temperature = entry.data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)
+        max_history_size = entry.data.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
+        context_messages = entry.data.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
+        is_anthropic = api_provider == API_PROVIDER_ANTHROPIC
 
-        # Configure headers based on API type
         headers = {
             "Content-Type": "application/json",
             "Accept": "application/json"
@@ -142,234 +235,65 @@ async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
         else:
             headers["Authorization"] = f"Bearer {api_key}"
 
-        # Check API with retries
-        for attempt in range(API_RETRY_COUNT):
-            if await async_check_api(session, endpoint, headers, is_anthropic):
-                break
-            if attempt < API_RETRY_COUNT - 1:
-                delay = API_BACKOFF_FACTOR * (2 ** attempt)
-                await asyncio.sleep(delay)
-            else:
-                raise ConfigEntryNotReady("Failed to connect to API")
+        if not await async_check_api(session, endpoint, headers, api_provider):
+            raise ConfigEntryNotReady("API connection failed")
 
-        # Create and initialize coordinator
-        coordinator = HATextAICoordinator(
-            hass,
-            api_key=api_key,
-            endpoint=endpoint,
-            model=model,
-            temperature=entry.data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
-            max_tokens=entry.data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
-            request_interval=entry.data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL),
+        _LOGGER.debug("Creating API client for %s with endpoint %s", api_provider, endpoint)
+
+        api_client = APIClient(
             session=session,
-            is_anthropic=is_anthropic
+            endpoint=endpoint,
+            headers=headers,
+            api_provider=api_provider,
+            model=model,
         )
 
-        # Initialize coordinator
-        await coordinator.async_config_entry_first_refresh()
+        coordinator = HATextAICoordinator(
+            hass=hass,
+            client=api_client,
+            model=model,
+            update_interval=request_interval,
+            instance_name=instance_name,
+            max_tokens=max_tokens,
+            temperature=temperature,
+            max_history_size=max_history_size,
+            context_messages=context_messages,
+            is_anthropic=is_anthropic,
+        )
 
-        # Check coordinator status
-        if coordinator.endpoint_status == "auth_error":
-            raise ConfigEntryNotReady("Authentication failed")
-        elif coordinator.endpoint_status == "rate_limited":
-            _LOGGER.warning("API rate limited during setup")
-        elif coordinator.endpoint_status == "maintenance":
-            raise ConfigEntryNotReady("API is in maintenance mode")
-        elif coordinator.endpoint_status == "error":
-            raise ConfigEntryNotReady("API error during setup")
-        elif not coordinator.last_update_success:
-            raise ConfigEntryNotReady("Failed to initialize coordinator")
+        _LOGGER.debug(f"Created coordinator for {instance_name}")
 
+        # Store coordinator
+        hass.data.setdefault(DOMAIN, {})
         hass.data[DOMAIN][entry.entry_id] = coordinator
 
+        _LOGGER.debug(f"Stored coordinator in hass.data[{DOMAIN}][{entry.entry_id}]")
+
+        # Set up platforms
         await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)
 
-        # Register event handlers
-        @callback
-        def handle_state_change(event):
-            """Handle state changes."""
-            if event.data.get("entity_id").startswith(f"{DOMAIN}."):
-                _LOGGER.debug("State changed: %s", event.data)
-
-        hass.bus.async_listen(EVENT_STATE_CHANGED, handle_state_change)
-
-        # Register services
-        async def async_ask_question(call: ServiceCall) -> None:
-            """Handle the ask_question service call."""
-            question = call.data.get("question", "")
-            if not question:
-                _LOGGER.error("No question provided in service call")
-                return
-
-            request_params = {}
-            for param in ["system_prompt", "model", "temperature", "max_tokens"]:
-                if param in call.data:
-                    request_params[param] = call.data[param]
-
-            try:
-                await coordinator.async_ask_question(question, **request_params)
-            except Exception as err:
-                _LOGGER.error("Error asking question: %s", str(err))
-
-        async def async_clear_history(call: ServiceCall) -> None:
-            """Handle the clear_history service call."""
-            try:
-                coordinator._responses.clear()
-                await coordinator.async_refresh()
-                _LOGGER.info("History cleared successfully")
-            except Exception as err:
-                _LOGGER.error("Error clearing history: %s", str(err))
-
-        async def async_get_history(call: ServiceCall) -> dict:
-            """Handle the get_history service call."""
-            try:
-                limit = min(int(call.data.get("limit", 10)), 100)
-                filter_model = str(call.data.get("filter_model", ""))
-                start_date = call.data.get("start_date")
-                include_metadata = call.data.get("include_metadata", False)
-
-                responses = coordinator._responses
-                metrics = {
-                    "total_requests": coordinator.request_count,
-                    "total_tokens": coordinator.tokens_used,
-                    "api_version": coordinator.api_version,
-                    "endpoint_status": coordinator.endpoint_status,
-                    "error_count": coordinator.error_count
-                }
-
-                filtered_responses = responses.copy()
-
-                if filter_model:
-                    filtered_responses = {
-                        k: v for k, v in filtered_responses.items()
-                        if v.get("model") == filter_model
-                    }
-
-                if start_date:
-                    filtered_responses = {
-                        k: v for k, v in filtered_responses.items()
-                        if v.get("timestamp") >= start_date
-                    }
-
-                if not include_metadata:
-                    filtered_responses = {
-                        k: {
-                            "question": v["question"],
-                            "response": v["response"],
-                            "timestamp": v["timestamp"]
-                        } for k, v in filtered_responses.items()
-                    }
-
-                sorted_responses = dict(
-                    sorted(
-                        filtered_responses.items(),
-                        key=lambda x: x[1]["timestamp"],
-                        reverse=True
-                    )[:limit]
-                )
-
-                return {
-                    "metrics": metrics,
-                    "responses": sorted_responses
-                }
-            except Exception as err:
-                _LOGGER.error("Error getting history: %s", str(err))
-                return {}
-
-        async def async_set_system_prompt(call: ServiceCall) -> None:
-            """Handle the set_system_prompt service call."""
-            try:
-                prompt = str(call.data.get("prompt", "")).strip()
-                if prompt:
-                    coordinator.system_prompt = prompt
-                    _LOGGER.info("System prompt updated successfully")
-                else:
-                    _LOGGER.error("Empty prompt provided")
-            except Exception as err:
-                _LOGGER.error("Error setting system prompt: %s", str(err))
-
-        # Register services with validation
-        hass.services.async_register(
-            DOMAIN,
-            "ask_question",
-            async_ask_question,
-            schema=SERVICE_SCHEMA_ASK_QUESTION
-        )
-
-        hass.services.async_register(
-            DOMAIN,
-            "clear_history",
-            async_clear_history
-        )
-
-        hass.services.async_register(
-            DOMAIN,
-            "get_history",
-            async_get_history,
-            schema=SERVICE_SCHEMA_GET_HISTORY
-        )
-
-        hass.services.async_register(
-            DOMAIN,
-            "set_system_prompt",
-            async_set_system_prompt,
-            schema=SERVICE_SCHEMA_SET_SYSTEM_PROMPT
-        )
-
-        _LOGGER.info(
-            "Successfully set up HA Text AI with model: %s",
-            entry.data.get(CONF_MODEL, DEFAULT_MODEL)
-        )
+        _LOGGER.debug(f"Setup completed for {instance_name}")
 
         return True
 
-    except Exception as ex:
-        _LOGGER.exception("Setup error: %s", str(ex))
-        raise ConfigEntryNotReady from ex
+    except Exception as err:
+        _LOGGER.exception(f"Error setting up HA Text AI: {err}")
+        raise
 
 async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
     """Unload a config entry."""
     try:
-        coordinator = hass.data[DOMAIN].get(entry.entry_id)
-        if coordinator:
-            # Clear queue and history
-            coordinator._responses.clear()
-            while not coordinator._question_queue.empty():
-                try:
-                    coordinator._question_queue.get_nowait()
-                    coordinator._question_queue.task_done()
-                except Exception:
-                    pass
+        if entry.entry_id in hass.data[DOMAIN]:
+            coordinator = hass.data[DOMAIN][entry.entry_id]
+
+            if hasattr(coordinator.client, 'shutdown'):
+                await coordinator.client.shutdown()
 
-            # Close connection
             await coordinator.async_shutdown()
-
-        # Remove services
-        for service in ["ask_question", "clear_history", "get_history", "set_system_prompt"]:
-            hass.services.async_remove(DOMAIN, service)
-
-        unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
-        if unload_ok:
             hass.data[DOMAIN].pop(entry.entry_id)
 
-        return unload_ok
+        return await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
 
     except Exception as ex:
         _LOGGER.exception("Error unloading entry: %s", str(ex))
         return False
-
-async def async_migrate_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
-    """Migrate old entry."""
-    _LOGGER.debug("Migrating from version %s", entry.version)
-
-    if entry.version == 1:
-        new = {**entry.data}
-
-        # Migrate settings
-        if CONF_MODEL in new and new[CONF_MODEL] not in SUPPORTED_MODELS:
-            new[CONF_MODEL] = DEFAULT_MODEL
-
-        entry.version = 2
-        hass.config_entries.async_update_entry(entry, data=new)
-
-    return True

custom_components/ha_text_ai/api_client.py

@@ -0,0 +1,200 @@
+"""API Client for HA Text AI."""
+import logging
+import asyncio
+from typing import Any, Dict, List, Optional
+from aiohttp import ClientSession, ClientTimeout
+from async_timeout import timeout
+
+from homeassistant.core import HomeAssistant
+from homeassistant.exceptions import HomeAssistantError
+from .const import (
+    API_TIMEOUT,
+    API_RETRY_COUNT,
+    API_PROVIDER_ANTHROPIC,
+    MIN_TEMPERATURE,
+    MAX_TEMPERATURE,
+    MIN_MAX_TOKENS,
+    MAX_MAX_TOKENS,
+)
+
+_LOGGER = logging.getLogger(__name__)
+
+
+class APIClient:
+    """API Client for OpenAI and Anthropic."""
+
+    def __init__(
+        self,
+        session: ClientSession,
+        endpoint: str,
+        headers: Dict[str, str],
+        api_provider: str,
+        model: str,
+    ) -> None:
+        """Initialize API client."""
+        self.session = session
+        self.endpoint = endpoint
+        self.headers = headers
+        self.api_provider = api_provider
+        self.model = model
+        self.timeout = ClientTimeout(total=API_TIMEOUT)
+
+    def _validate_parameters(
+        self,
+        temperature: float,
+        max_tokens: int,
+    ) -> None:
+        """Validate API parameters."""
+        if not MIN_TEMPERATURE <= temperature <= MAX_TEMPERATURE:
+            raise ValueError(
+                f"Temperature must be between {MIN_TEMPERATURE} and {MAX_TEMPERATURE}"
+            )
+        if not MIN_MAX_TOKENS <= max_tokens <= MAX_MAX_TOKENS:
+            raise ValueError(
+                f"Max tokens must be between {MIN_MAX_TOKENS} and {MAX_MAX_TOKENS}"
+            )
+
+    async def _make_request(
+        self,
+        url: str,
+        payload: Dict[str, Any],
+    ) -> Dict[str, Any]:
+        """Make API request with retry logic."""
+        _LOGGER.debug(f"API Request: URL={url}, Payload={payload}")
+        for attempt in range(API_RETRY_COUNT):
+            try:
+                async with timeout(API_TIMEOUT):
+                    async with self.session.post(
+                        url,
+                        json=payload,
+                        headers=self.headers,
+                        timeout=self.timeout,
+                    ) as response:
+                        _LOGGER.debug(f"Response status: {response.status}")
+                        if response.status != 200:
+                            error_data = await response.json()
+                            _LOGGER.error(f"API error: {error_data}")
+                            raise HomeAssistantError(f"API error: {error_data}")
+                        return await response.json()
+            except asyncio.TimeoutError:
+                _LOGGER.warning(f"Timeout on attempt {attempt + 1}")
+                if attempt == API_RETRY_COUNT - 1:
+                    raise HomeAssistantError("API request timed out")
+                await asyncio.sleep(1 * (attempt + 1))
+            except Exception as e:
+                _LOGGER.warning(f"API request failed on attempt {attempt + 1}: {str(e)}")
+                if attempt == API_RETRY_COUNT - 1:
+                    raise
+                await asyncio.sleep(1 * (attempt + 1))
+
+    async def create(
+        self,
+        model: str,
+        messages: List[Dict[str, str]],
+        temperature: float,
+        max_tokens: int,
+    ) -> Dict[str, Any]:
+        """Create completion using appropriate API."""
+        try:
+            self._validate_parameters(temperature, max_tokens)
+
+            if self.api_provider == API_PROVIDER_ANTHROPIC:
+                return await self._create_anthropic_completion(
+                    model, messages, temperature, max_tokens
+                )
+            else:
+                return await self._create_openai_completion(
+                    model, messages, temperature, max_tokens
+                )
+        except Exception as e:
+            _LOGGER.error("API request failed: %s", str(e))
+            raise HomeAssistantError(f"API request failed: {str(e)}")
+
+    async def _create_openai_completion(
+        self,
+        model: str,
+        messages: List[Dict[str, str]],
+        temperature: float,
+        max_tokens: int,
+    ) -> Dict[str, Any]:
+        """Create completion using OpenAI API."""
+        url = f"{self.endpoint}/chat/completions"
+        payload = {
+            "model": model,
+            "messages": messages,
+            "temperature": temperature,
+            "max_tokens": max_tokens,
+        }
+
+        data = await self._make_request(url, payload)
+        return {
+            "choices": [
+                {
+                    "message": {"content": data["choices"][0]["message"]["content"]},
+                }
+            ],
+            "usage": {
+                "prompt_tokens": data["usage"]["prompt_tokens"],
+                "completion_tokens": data["usage"]["completion_tokens"],
+                "total_tokens": data["usage"]["total_tokens"],
+            },
+        }
+
+    async def _create_anthropic_completion(
+        self,
+        model: str,
+        messages: List[Dict[str, str]],
+        temperature: float,
+        max_tokens: int,
+    ) -> Dict[str, Any]:
+        """Create completion using Anthropic API."""
+        url = f"{self.endpoint}/v1/messages"
+
+        system_prompt = None
+        filtered_messages = []
+        for msg in messages:
+            if msg['role'] == 'system':
+                if system_prompt is None:
+                    system_prompt = msg['content']
+                else:
+                    system_prompt += f" {msg['content']}"
+            else:
+                filtered_messages.append(msg)
+
+        payload = {
+            "model": model,
+            "messages": filtered_messages,
+            "max_tokens": max_tokens,
+            "temperature": temperature,
+        }
+
+        if system_prompt:
+            payload["system"] = system_prompt
+
+        data = await self._make_request(url, payload)
+        return {
+            "choices": [
+                {
+                    "message": {"content": data["content"][0]["text"]},
+                }
+            ],
+            "usage": {
+                "prompt_tokens": data["usage"]["input_tokens"],
+                "completion_tokens": data["usage"]["output_tokens"],
+                "total_tokens": data["usage"]["input_tokens"] + data["usage"]["output_tokens"],
+            },
+        }
+
+    async def check_connection(self) -> bool:
+        """Check API connection."""
+        try:
+            await self._make_request(self.endpoint, {"test": "connection"})
+            return True
+        except Exception as e:
+            _LOGGER.error(f"Connection check failed: {str(e)}")
+            return False
+
+    async def shutdown(self) -> None:
+        """Shutdown API client."""
+        _LOGGER.debug("Shutting down API client")
+        await self.session.close()

custom_components/ha_text_ai/config_flow.py

@@ -1,17 +1,14 @@
 """Config flow for HA text AI integration."""
-from typing import Any, Dict, Optional, Tuple
-import voluptuous as vol
-import asyncio
-import aiohttp
-from async_timeout import timeout
-from urllib.parse import urlparse, urljoin
+import logging
+from typing import Any, Dict, Optional
 
+import voluptuous as vol
 from homeassistant import config_entries
-from homeassistant.const import CONF_API_KEY
-import homeassistant.helpers.config_validation as cv
+from homeassistant.const import CONF_API_KEY, CONF_NAME
 from homeassistant.core import callback
 from homeassistant.data_entry_flow import FlowResult
 from homeassistant.helpers.aiohttp_client import async_get_clientsession
+from homeassistant.helpers import selector
 
 from .const import (
     DOMAIN,
@@ -20,269 +17,326 @@ from .const import (
     CONF_MAX_TOKENS,
     CONF_API_ENDPOINT,
     CONF_REQUEST_INTERVAL,
+    CONF_API_PROVIDER,
+    CONF_CONTEXT_MESSAGES,
+    API_PROVIDER_OPENAI,
+    API_PROVIDER_ANTHROPIC,
+    API_PROVIDERS,
     DEFAULT_MODEL,
     DEFAULT_TEMPERATURE,
     DEFAULT_MAX_TOKENS,
-    DEFAULT_API_ENDPOINT,
     DEFAULT_REQUEST_INTERVAL,
+    DEFAULT_OPENAI_ENDPOINT,
+    DEFAULT_ANTHROPIC_ENDPOINT,
+    DEFAULT_CONTEXT_MESSAGES,
     MIN_TEMPERATURE,
     MAX_TEMPERATURE,
     MIN_MAX_TOKENS,
     MAX_MAX_TOKENS,
     MIN_REQUEST_INTERVAL,
-    API_VERSION,
-    API_MODELS_PATH,
-    ERROR_INVALID_API_KEY,
-    ERROR_CANNOT_CONNECT,
-    ERROR_UNKNOWN,
-    ERROR_INVALID_MODEL,
-    ERROR_RATE_LIMIT,
-    ERROR_API_ERROR,
-    ERROR_TIMEOUT,
+    DEFAULT_NAME_PREFIX,
+    DEFAULT_MAX_HISTORY,
+    CONF_MAX_HISTORY_SIZE,
 )
 
-import logging
 _LOGGER = logging.getLogger(__name__)
 
-STEP_USER_DATA_SCHEMA = vol.Schema(
-    {
-        vol.Required(CONF_API_KEY): cv.string,
-        vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): cv.string,
-        vol.Optional(
-            CONF_TEMPERATURE,
-            default=DEFAULT_TEMPERATURE
-        ): vol.All(
-            vol.Coerce(float),
-            vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
-        ),
-        vol.Optional(
-            CONF_MAX_TOKENS,
-            default=DEFAULT_MAX_TOKENS
-        ): vol.All(
-            vol.Coerce(int),
-            vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
-        ),
-        vol.Optional(
-            CONF_API_ENDPOINT,
-            default=DEFAULT_API_ENDPOINT
-        ): cv.string,
-        vol.Optional(
-            CONF_REQUEST_INTERVAL,
-            default=DEFAULT_REQUEST_INTERVAL
-        ): vol.All(
-            vol.Coerce(float),
-            vol.Range(min=MIN_REQUEST_INTERVAL)
-        ),
-    }
-)
 
-async def validate_api_connection(
-    hass,
-    api_key: str,
-    endpoint: str,
-    model: str,
-    retry_count: int = 3,
-    retry_delay: float = 1.0
-) -> Tuple[bool, str, list]:
-    """Validate API connection with retry logic."""
-    session = async_get_clientsession(hass)
-    headers = {
-        "Authorization": f"Bearer {api_key}",
-        "Content-Type": "application/json; charset=utf-8",
-        "Accept": "application/json; charset=utf-8",
-        "Accept-Charset": "utf-8"
-    }
+def normalize_name(name: str) -> str:
+    """Normalize name to conform to HA naming convention using underscores."""
+    normalized = ''.join(c if c.isalnum() or c == '_' else '_' for c in name)
+    normalized = '_'.join(filter(None, normalized.split('_')))
+    return normalized.lower()
 
-    base_url = endpoint.rstrip('/')
-    if not base_url.endswith(f"/{API_VERSION}"):
-        base_url = f"{base_url}/{API_VERSION}"
-
-    models_url = f"{base_url}/{API_MODELS_PATH}"
-    _LOGGER.debug("Attempting to connect to: %s", models_url)
-
-    for attempt in range(retry_count):
-        try:
-            async with timeout(10):
-                async with session.get(models_url, headers=headers) as response:
-                    if response.status == 200:
-                        data = await response.json()
-                        model_ids = [m["id"] for m in data.get("data", [])]
-
-                        _LOGGER.debug("Available models: %s", ", ".join(model_ids))
-
-                        if model not in model_ids:
-                            _LOGGER.warning(
-                                "Model %s not found in available models: %s",
-                                model,
-                                ", ".join(model_ids)
-                            )
-                            return False, ERROR_INVALID_MODEL, model_ids
-                        return True, "", model_ids
-
-                    elif response.status == 401:
-                        _LOGGER.error("Authentication failed")
-                        return False, ERROR_INVALID_API_KEY, []
-
-                    elif response.status == 429:
-                        _LOGGER.error("Rate limit exceeded")
-                        return False, ERROR_RATE_LIMIT, []
-
-                    else:
-                        response_text = await response.text()
-                        _LOGGER.error(
-                            "API error: %s - %s",
-                            response.status,
-                            response_text
-                        )
-                        return False, ERROR_API_ERROR, []
-
-        except asyncio.TimeoutError:
-            _LOGGER.warning(
-                "Timeout during API validation (attempt %d/%d)",
-                attempt + 1,
-                retry_count
-            )
-            if attempt == retry_count - 1:
-                return False, ERROR_TIMEOUT, []
-            await asyncio.sleep(retry_delay)
-
-        except aiohttp.ClientError as err:
-            _LOGGER.error("Connection error: %s", str(err))
-            return False, ERROR_CANNOT_CONNECT, []
-
-        except Exception as err:
-            _LOGGER.exception("Unexpected error during validation: %s", str(err))
-            return False, ERROR_UNKNOWN, []
-
-    return False, ERROR_UNKNOWN, []
 
 class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
     """Handle a config flow for HA text AI."""
 
     VERSION = 1
 
-    async def async_step_user(
-        self,
-        user_input: Optional[Dict[str, Any]] = None
-    ) -> FlowResult:
+    def __init__(self) -> None:
+        """Initialize flow."""
+        self._errors = {}
+        self._data = {}
+        self._provider = None
+
+    async def async_step_user(self, user_input: Optional[Dict[str, Any]] = None) -> FlowResult:
         """Handle the initial step."""
-        errors: Dict[str, str] = {}
-
-        if user_input is not None:
-            try:
-                endpoint = user_input.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT)
-                try:
-                    result = urlparse(endpoint)
-                    if not all([result.scheme, result.netloc]):
-                        errors["base"] = "invalid_url_format"
-                        return self.async_show_form(
-                            step_id="user",
-                            data_schema=STEP_USER_DATA_SCHEMA,
-                            errors=errors
+        if user_input is None:
+            return self.async_show_form(
+                step_id="user",
+                data_schema=vol.Schema({
+                    vol.Required(CONF_API_PROVIDER): selector.SelectSelector(
+                        selector.SelectSelectorConfig(
+                            options=API_PROVIDERS,
+                            translation_key="api_provider"
                         )
-                except Exception as e:
-                    _LOGGER.error("URL parsing error: %s", str(e))
-                    errors["base"] = "invalid_url_format"
-                    return self.async_show_form(
-                        step_id="user",
-                        data_schema=STEP_USER_DATA_SCHEMA,
-                        errors=errors
-                    )
+                    ),
+                })
+            )
 
-                validated_input = STEP_USER_DATA_SCHEMA(user_input)
+        self._provider = user_input[CONF_API_PROVIDER]
+        return await self.async_step_provider()
 
-                is_valid, error_code, available_models = await validate_api_connection(
-                    self.hass,
-                    validated_input[CONF_API_KEY],
-                    endpoint,
-                    validated_input[CONF_MODEL]
+    async def async_step_provider(self, user_input: Optional[Dict[str, Any]] = None) -> FlowResult:
+        """Handle provider configuration step."""
+        self._errors = {}
+
+        if user_input is None:
+            default_endpoint = (
+                DEFAULT_OPENAI_ENDPOINT if self._provider == API_PROVIDER_OPENAI
+                else DEFAULT_ANTHROPIC_ENDPOINT
+            )
+
+            return self.async_show_form(
+                step_id="provider",
+                data_schema=vol.Schema({
+                    vol.Required(CONF_NAME, default="my_assistant"): str,
+                    vol.Required(CONF_API_KEY): str,
+                    vol.Required(CONF_MODEL, default=DEFAULT_MODEL): str,
+                    vol.Required(CONF_API_ENDPOINT, default=default_endpoint): str,
+                    vol.Optional(CONF_TEMPERATURE, default=DEFAULT_TEMPERATURE): vol.All(
+                        vol.Coerce(float),
+                        vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
+                    ),
+                    vol.Optional(CONF_MAX_TOKENS, default=DEFAULT_MAX_TOKENS): vol.All(
+                        vol.Coerce(int),
+                        vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
+                    ),
+                    vol.Optional(CONF_REQUEST_INTERVAL, default=DEFAULT_REQUEST_INTERVAL): vol.All(
+                        vol.Coerce(float),
+                        vol.Range(min=MIN_REQUEST_INTERVAL)
+                    ),
+                    vol.Optional(
+                        CONF_CONTEXT_MESSAGES,
+                        default=DEFAULT_CONTEXT_MESSAGES
+                    ): vol.All(
+                        vol.Coerce(int),
+                        vol.Range(min=1, max=20)
+                    ),
+                    vol.Optional(
+                        CONF_MAX_HISTORY_SIZE,
+                        default=DEFAULT_MAX_HISTORY
+                    ): vol.All(
+                        vol.Coerce(int),
+                        vol.Range(min=1, max=100)
+                    ),
+                })
+            )
+
+        input_copy = user_input.copy()
+
+        try:
+            normalized_name = self._validate_and_normalize_name(input_copy[CONF_NAME])
+            input_copy[CONF_NAME] = normalized_name
+        except ValueError as e:
+            return self.async_show_form(
+                step_id="provider",
+                data_schema=vol.Schema({
+                    vol.Required(CONF_NAME, default=input_copy[CONF_NAME]): str,
+                    vol.Required(CONF_API_KEY, default=input_copy[CONF_API_KEY]): str,
+                    vol.Required(CONF_MODEL, default=input_copy[CONF_MODEL]): str,
+                    vol.Required(CONF_API_ENDPOINT, default=input_copy[CONF_API_ENDPOINT]): str,
+                    vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All(
+                        vol.Coerce(float),
+                        vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
+                    ),
+                }),
+                errors={"name": str(e)}
+            )
+
+        try:
+            if not await self._async_validate_api(input_copy):
+                return self.async_show_form(
+                    step_id="provider",
+                    data_schema=vol.Schema({
+                    }),
+                    errors=self._errors
                 )
+        except Exception as e:
+            return self.async_show_form(
+                step_id="provider",
+                data_schema=vol.Schema({
+                }),
+                errors={"base": str(e)}
+            )
 
-                if is_valid:
-                    await self.async_set_unique_id(validated_input[CONF_API_KEY])
-                    self._abort_if_unique_id_configured()
+        return await self._create_entry(input_copy)
 
-                    return self.async_create_entry(
-                        title="HA Text AI",
-                        data=validated_input
-                    )
+    def _validate_and_normalize_name(self, name: str) -> str:
+        """
+        Validate and normalize name with detailed error handling.
 
-                errors["base"] = error_code
-                if error_code == ERROR_INVALID_MODEL:
-                    _LOGGER.warning(
-                        "Selected model %s not found in available models: %s",
-                        validated_input[CONF_MODEL],
-                        ", ".join(available_models)
-                    )
+        Raises:
+            ValueError: If name is invalid
 
-            except vol.Invalid as err:
-                _LOGGER.error("Validation error: %s", str(err))
-                errors["base"] = "invalid_input"
+        Returns:
+            Normalized name
+        """
+        if not name:
+            raise ValueError("empty")
 
-        return self.async_show_form(
-            step_id="user",
-            data_schema=STEP_USER_DATA_SCHEMA,
-            errors=errors,
-            description_placeholders={
-                "default_model": DEFAULT_MODEL,
-                "default_endpoint": DEFAULT_API_ENDPOINT,
+        name = name.strip()
+        normalized = ''.join(
+            c if c.isalnum() or c in ' _' else '_'  # Only allow underscores
+            for c in name
+        )
+
+        normalized = normalized.replace(' ', '_').lower()
+
+        for entry in self._async_current_entries():
+            if entry.data.get(CONF_NAME, "") == normalized:
+                raise ValueError("name_exists")
+
+        normalized = normalized[:50]
+
+        if not normalized:
+            raise ValueError("empty")
+
+        return normalized
+
+    async def _async_validate_api(self, user_input: Dict[str, Any]) -> bool:
+        """Validate API connection."""
+        try:
+            session = async_get_clientsession(self.hass)
+            headers = self._get_api_headers(user_input)
+            endpoint = user_input[CONF_API_ENDPOINT].rstrip('/')
+
+            check_url = (
+                f"{endpoint}/v1/models" if self._provider == API_PROVIDER_ANTHROPIC
+                else f"{endpoint}/models"
+            )
+
+            async with session.get(check_url, headers=headers) as response:
+                if response.status == 401:
+                    self._errors["base"] = "invalid_auth"
+                    return False
+                elif response.status not in [200, 404]:
+                    self._errors["base"] = "cannot_connect"
+                    return False
+                return True
+
+        except Exception as err:
+            _LOGGER.error("API validation error: %s", str(err))
+            self._errors["base"] = "cannot_connect"
+            return False
+
+    def _get_api_headers(self, user_input: Dict[str, Any]) -> Dict[str, str]:
+        """Get API headers based on provider."""
+        api_key = user_input[CONF_API_KEY]
+
+        if self._provider == API_PROVIDER_ANTHROPIC:
+            return {
+                "x-api-key": api_key,
+                "anthropic-version": "2023-06-01",
+                "Content-Type": "application/json"
             }
+        return {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json"
+        }
+
+    async def _create_entry(self, user_input: Dict[str, Any]) -> FlowResult:
+        """Create the config entry with comprehensive data preservation."""
+        instance_name = user_input[CONF_NAME]
+        normalized_name = normalize_name(instance_name)
+
+        unique_id = f"{DOMAIN}_{normalized_name}_{self._provider}".lower()
+
+        entry_data = {
+            CONF_API_PROVIDER: self._provider,
+            CONF_NAME: instance_name,
+            "normalized_name": normalized_name,
+            CONF_API_KEY: user_input.get(CONF_API_KEY),
+            CONF_API_ENDPOINT: user_input.get(CONF_API_ENDPOINT),
+            "unique_id": unique_id,
+            CONF_MODEL: user_input.get(CONF_MODEL, DEFAULT_MODEL),
+            CONF_TEMPERATURE: user_input.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
+            CONF_MAX_TOKENS: user_input.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
+            CONF_REQUEST_INTERVAL: user_input.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL),
+            CONF_CONTEXT_MESSAGES: user_input.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES),
+            CONF_MAX_HISTORY_SIZE: user_input.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY),
+        }
+
+        for key, value in user_input.items():
+            if key not in entry_data:
+                entry_data[key] = value
+
+        _LOGGER.debug(f"Creating config entry with data: {entry_data}")
+
+        return self.async_create_entry(
+            title=instance_name,
+            data=entry_data
         )
 
     @staticmethod
     @callback
-    def async_get_options_flow(
-        config_entry: config_entries.ConfigEntry,
-    ) -> config_entries.OptionsFlow:
+    def async_get_options_flow(config_entry: config_entries.ConfigEntry) -> config_entries.OptionsFlow:
         """Get the options flow for this handler."""
         return OptionsFlowHandler(config_entry)
 
+
 class OptionsFlowHandler(config_entries.OptionsFlow):
-    """Handle options flow for HA text AI."""
+    """Handle options flow."""
 
     def __init__(self, config_entry: config_entries.ConfigEntry) -> None:
         """Initialize options flow."""
         self.config_entry = config_entry
 
-    async def async_step_init(
-        self,
-        user_input: Optional[Dict[str, Any]] = None
-    ) -> FlowResult:
-        """Handle options flow."""
+    async def async_step_init(self, user_input: Optional[Dict[str, Any]] = None) -> FlowResult:
+        """Manage the options."""
         if user_input is not None:
             return self.async_create_entry(title="", data=user_input)
 
-        options_schema = vol.Schema({
-            vol.Optional(
-                CONF_TEMPERATURE,
-                default=self.config_entry.options.get(
-                    CONF_TEMPERATURE, DEFAULT_TEMPERATURE
-                ),
-            ): vol.All(
-                vol.Coerce(float),
-                vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
-            ),
-            vol.Optional(
-                CONF_MAX_TOKENS,
-                default=self.config_entry.options.get(
-                    CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS
-                ),
-            ): vol.All(
-                vol.Coerce(int),
-                vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
-            ),
-            vol.Optional(
-                CONF_REQUEST_INTERVAL,
-                default=self.config_entry.options.get(
-                    CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL
-                ),
-            ): vol.All(
-                vol.Coerce(float),
-                vol.Range(min=MIN_REQUEST_INTERVAL)
-            ),
-        })
+        current_data = {**self.config_entry.data, **self.config_entry.options}
 
         return self.async_show_form(
             step_id="init",
-            data_schema=options_schema,
+            data_schema=vol.Schema({
+                vol.Optional(
+                    CONF_MODEL,
+                    default=current_data.get(CONF_MODEL, DEFAULT_MODEL)
+                ): str,
+                vol.Optional(
+                    CONF_TEMPERATURE,
+                    default=current_data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)
+                ): vol.All(
+                    vol.Coerce(float),
+                    vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
+                ),
+                vol.Optional(
+                    CONF_MAX_TOKENS,
+                    default=current_data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS)
+                ): vol.All(
+                    vol.Coerce(int),
+                    vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
+                ),
+                vol.Optional(
+                    CONF_REQUEST_INTERVAL,
+                    default=current_data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)
+                ): vol.All(
+                    vol.Coerce(float),
+                    vol.Range(min=MIN_REQUEST_INTERVAL)
+                ),
+                vol.Optional(
+                    CONF_CONTEXT_MESSAGES,
+                    default=current_data.get(
+                        CONF_CONTEXT_MESSAGES,
+                        DEFAULT_CONTEXT_MESSAGES
+                    )
+                ): vol.All(
+                    vol.Coerce(int),
+                    vol.Range(min=1, max=20)
+                ),
+                vol.Optional(
+                    CONF_MAX_HISTORY_SIZE,
+                    default=current_data.get(
+                        CONF_MAX_HISTORY_SIZE,
+                        DEFAULT_MAX_HISTORY
+                    )
+                ): vol.All(
+                    vol.Coerce(int),
+                    vol.Range(min=1, max=100)
+                ),
+            })
         )

custom_components/ha_text_ai/const.py

@@ -1,10 +1,26 @@
 """Constants for the HA text AI integration."""
 from typing import Final
-from homeassistant.const import Platform
+import voluptuous as vol
+from homeassistant.const import Platform, CONF_API_KEY, CONF_NAME
+from homeassistant.helpers import config_validation as cv
 
 # Domain and platforms
 DOMAIN: Final = "ha_text_ai"
-PLATFORMS: Final = [Platform.SENSOR]
+PLATFORMS: list[str] = ["sensor"]
+
+# Provider configuration
+CONF_API_PROVIDER: Final = "api_provider"
+API_PROVIDER_OPENAI: Final = "openai"
+API_PROVIDER_ANTHROPIC: Final = "anthropic"
+
+API_PROVIDERS: Final = [
+    API_PROVIDER_OPENAI,
+    API_PROVIDER_ANTHROPIC
+]
+
+# Default endpoints
+DEFAULT_OPENAI_ENDPOINT: Final = "https://api.openai.com/v1"
+DEFAULT_ANTHROPIC_ENDPOINT: Final = "https://api.anthropic.com"
 
 # Configuration constants
 CONF_MODEL: Final = "model"
@@ -12,28 +28,21 @@ CONF_TEMPERATURE: Final = "temperature"
 CONF_MAX_TOKENS: Final = "max_tokens"
 CONF_API_ENDPOINT: Final = "api_endpoint"
 CONF_REQUEST_INTERVAL: Final = "request_interval"
-
-# Model constants
-SUPPORTED_MODELS: Final = [
-    "gpt-3.5-turbo",
-    "gpt-3.5-turbo-16k",
-    "gpt-4",
-    "gpt-4-32k",
-    "gpt-4-1106-preview",
-    "claude-3-sonnet",
-    "claude-3-opus"
-]
+CONF_INSTANCE: Final = "instance"
+CONF_MAX_HISTORY_SIZE: Final = "max_history_size"  # Correct constant name
+CONF_IS_ANTHROPIC: Final = "is_anthropic"
+CONF_CONTEXT_MESSAGES: Final = "context_messages"
 
 # Default values
-DEFAULT_MODEL: Final = "gpt-3.5-turbo"
+DEFAULT_MODEL: Final = "gpt-4o-mini"
 DEFAULT_TEMPERATURE: Final = 0.1
 DEFAULT_MAX_TOKENS: Final = 1000
-DEFAULT_API_ENDPOINT: Final = "https://api.openai.com"
 DEFAULT_REQUEST_INTERVAL: Final = 1.0
 DEFAULT_TIMEOUT: Final = 30
-DEFAULT_QUEUE_SIZE: Final = 100
-DEFAULT_HISTORY_LIMIT: Final = 50
-DEFAULT_RETRY_COUNT: Final = 3
+DEFAULT_MAX_HISTORY: Final = 50
+DEFAULT_NAME: Final = "HA Text AI"
+DEFAULT_NAME_PREFIX = "ha_text_ai"
+DEFAULT_CONTEXT_MESSAGES: Final = 5
 
 # Parameter constraints
 MIN_TEMPERATURE: Final = 0.0
@@ -41,25 +50,11 @@ MAX_TEMPERATURE: Final = 2.0
 MIN_MAX_TOKENS: Final = 1
 MAX_MAX_TOKENS: Final = 4096
 MIN_REQUEST_INTERVAL: Final = 0.1
-MIN_TIMEOUT: Final = 5
-MAX_TIMEOUT: Final = 120
-MAX_PROMPT_LENGTH: Final = 1000
-MAX_HISTORY_LIMIT: Final = 100
+MAX_REQUEST_INTERVAL: Final = 60.0
 
 # API constants
-API_VERSION: Final = "v1"
-API_MODELS_PATH: Final = "models"
-API_CHAT_PATH: Final = "chat/completions"
 API_TIMEOUT: Final = 30
 API_RETRY_COUNT: Final = 3
-API_BACKOFF_FACTOR: Final = 1.5
-API_MAX_RETRIES: Final = 3
-
-# History constants
-HISTORY_FILTER_MODEL: Final = "filter_model"
-HISTORY_FILTER_DATE: Final = "start_date"
-HISTORY_SORT_ORDER: Final = "sort_order"
-HISTORY_INCLUDE_METADATA: Final = "include_metadata"
 
 # Service names
 SERVICE_ASK_QUESTION: Final = "ask_question"
@@ -67,33 +62,48 @@ SERVICE_CLEAR_HISTORY: Final = "clear_history"
 SERVICE_GET_HISTORY: Final = "get_history"
 SERVICE_SET_SYSTEM_PROMPT: Final = "set_system_prompt"
 
-# Service descriptions
-SERVICE_ASK_QUESTION_DESCRIPTION: Final = "Ask a question to the AI model"
-SERVICE_CLEAR_HISTORY_DESCRIPTION: Final = "Clear conversation history"
-SERVICE_GET_HISTORY_DESCRIPTION: Final = "Get conversation history"
-SERVICE_SET_SYSTEM_PROMPT_DESCRIPTION: Final = "Set system prompt for AI model"
-
 # Attribute keys
 ATTR_QUESTION: Final = "question"
 ATTR_RESPONSE: Final = "response"
-ATTR_LAST_UPDATED: Final = "last_updated"
+ATTR_INSTANCE: Final = "instance"
 ATTR_MODEL: Final = "model"
 ATTR_TEMPERATURE: Final = "temperature"
 ATTR_MAX_TOKENS: Final = "max_tokens"
-ATTR_TOTAL_RESPONSES: Final = "total_responses"
 ATTR_SYSTEM_PROMPT: Final = "system_prompt"
-ATTR_RESPONSE_TIME: Final = "response_time"
-ATTR_QUEUE_SIZE: Final = "queue_size"
 ATTR_API_STATUS: Final = "api_status"
 ATTR_ERROR_COUNT: Final = "error_count"
+ATTR_CONVERSATION_HISTORY: Final = "conversation_history"
+
+# Sensor attributes
+ATTR_TOTAL_RESPONSES: Final = "total_responses"
+ATTR_TOTAL_ERRORS: Final = "total_errors"
+ATTR_AVG_RESPONSE_TIME: Final = "average_response_time"
+ATTR_LAST_REQUEST_TIME: Final = "last_request_time"
 ATTR_LAST_ERROR: Final = "last_error"
+ATTR_IS_PROCESSING: Final = "is_processing"
+ATTR_IS_RATE_LIMITED: Final = "is_rate_limited"
+ATTR_IS_MAINTENANCE: Final = "is_maintenance"
 ATTR_API_VERSION: Final = "api_version"
 ATTR_ENDPOINT_STATUS: Final = "endpoint_status"
-ATTR_REQUEST_COUNT: Final = "request_count"
-ATTR_TOKENS_USED: Final = "tokens_used"
-ATTR_RETRY_COUNT: Final = "retry_count"
-ATTR_QUEUE_POSITION: Final = "queue_position"
-ATTR_ESTIMATED_WAIT: Final = "estimated_wait"
+ATTR_PERFORMANCE_METRICS: Final = "performance_metrics"
+ATTR_HISTORY_SIZE: Final = "history_size"
+ATTR_UPTIME: Final = "uptime"
+ATTR_API_PROVIDER: Final = "api_provider"
+ATTR_METRICS: Final = "metrics"
+ATTR_STATE: Final = "state"
+ATTR_LAST_RESPONSE: Final = "last_response"
+ATTR_ERROR: Final = "error"
+ATTR_TIMESTAMP: Final = "timestamp"
+
+# Sensor metrics
+METRIC_TOTAL_TOKENS: Final = "total_tokens"
+METRIC_PROMPT_TOKENS: Final = "prompt_tokens"
+METRIC_COMPLETION_TOKENS: Final = "completion_tokens"
+METRIC_SUCCESSFUL_REQUESTS: Final = "successful_requests"
+METRIC_FAILED_REQUESTS: Final = "failed_requests"
+METRIC_AVERAGE_LATENCY: Final = "average_latency"
+METRIC_MAX_LATENCY: Final = "max_latency"
+METRIC_MIN_LATENCY: Final = "min_latency"
 
 # Error messages
 ERROR_INVALID_API_KEY: Final = "invalid_api_key"
@@ -104,81 +114,89 @@ ERROR_RATE_LIMIT: Final = "rate_limit_exceeded"
 ERROR_CONTEXT_LENGTH: Final = "context_length_exceeded"
 ERROR_API_ERROR: Final = "api_error"
 ERROR_TIMEOUT: Final = "timeout_error"
-ERROR_QUEUE_FULL: Final = "queue_full"
-ERROR_INVALID_PROMPT: Final = "invalid_prompt"
-ERROR_INVALID_PARAMETERS: Final = "invalid_parameters"
-ERROR_SERVICE_UNAVAILABLE: Final = "service_unavailable"
-
-# Configuration descriptions
-CONF_MODEL_DESCRIPTION: Final = "AI model to use for responses"
-CONF_TEMPERATURE_DESCRIPTION: Final = "Temperature for response generation (0-2)"
-CONF_MAX_TOKENS_DESCRIPTION: Final = "Maximum tokens in response (1-4096)"
-CONF_API_ENDPOINT_DESCRIPTION: Final = "API endpoint URL"
-CONF_REQUEST_INTERVAL_DESCRIPTION: Final = "Minimum time between API requests (seconds)"
-
-# Entity attributes descriptions
-ATTR_QUESTION_DESCRIPTION: Final = "Last question asked"
-ATTR_RESPONSE_DESCRIPTION: Final = "Last response received"
-ATTR_LAST_UPDATED_DESCRIPTION: Final = "Time of last update"
-ATTR_MODEL_DESCRIPTION: Final = "Current AI model in use"
-ATTR_TEMPERATURE_DESCRIPTION: Final = "Current temperature setting"
-ATTR_MAX_TOKENS_DESCRIPTION: Final = "Current max tokens setting"
-ATTR_TOTAL_RESPONSES_DESCRIPTION: Final = "Total number of responses"
-ATTR_SYSTEM_PROMPT_DESCRIPTION: Final = "Current system prompt"
-ATTR_RESPONSE_TIME_DESCRIPTION: Final = "Time taken for last response"
-ATTR_QUEUE_SIZE_DESCRIPTION: Final = "Current size of question queue"
-ATTR_API_STATUS_DESCRIPTION: Final = "Current API connection status"
-ATTR_ERROR_COUNT_DESCRIPTION: Final = "Total number of errors"
-ATTR_LAST_ERROR_DESCRIPTION: Final = "Last error message"
-ATTR_API_VERSION_DESCRIPTION: Final = "Current API version"
-ATTR_ENDPOINT_STATUS_DESCRIPTION: Final = "Current endpoint status"
-ATTR_REQUEST_COUNT_DESCRIPTION: Final = "Total number of API requests"
-ATTR_TOKENS_USED_DESCRIPTION: Final = "Total tokens used"
+ERROR_INVALID_INSTANCE: Final = "invalid_instance"
+ERROR_NAME_EXISTS: Final = "name_exists"
 
 # Entity attributes
-ENTITY_NAME: Final = "HA Text AI"
 ENTITY_ICON: Final = "mdi:robot"
 ENTITY_ICON_ERROR: Final = "mdi:robot-dead"
 ENTITY_ICON_PROCESSING: Final = "mdi:robot-excited"
-ENTITY_ICON_OFFLINE: Final = "mdi:robot-off"
-ENTITY_ICON_QUEUE: Final = "mdi:robot-confused"
-
-# Translation keys
-TRANSLATION_KEY_CONFIG: Final = "config"
-TRANSLATION_KEY_OPTIONS: Final = "options"
-TRANSLATION_KEY_ERROR: Final = "error"
-TRANSLATION_KEY_STATE: Final = "state"
-TRANSLATION_KEY_SERVICES: Final = "services"
 
 # State attributes
 STATE_READY: Final = "ready"
 STATE_PROCESSING: Final = "processing"
 STATE_ERROR: Final = "error"
-STATE_DISCONNECTED: Final = "disconnected"
-STATE_RATE_LIMITED: Final = "rate_limited"
 STATE_INITIALIZING: Final = "initializing"
 STATE_MAINTENANCE: Final = "maintenance"
-STATE_RETRYING: Final = "retrying"
-STATE_QUEUED: Final = "queued"
-STATE_UPDATING: Final = "updating"
-
-# Logging
-LOGGER_NAME: Final = "custom_components.ha_text_ai"
-LOG_LEVEL_DEFAULT: Final = "INFO"
-
-# Queue constants
-QUEUE_TIMEOUT: Final = 5
-QUEUE_MAX_SIZE: Final = 100
-
-# Service schema constants
-SCHEMA_QUESTION: Final = "question"
-SCHEMA_MODEL: Final = "model"
-SCHEMA_TEMPERATURE: Final = "temperature"
-SCHEMA_MAX_TOKENS: Final = "max_tokens"
-SCHEMA_PROMPT: Final = "prompt"
-SCHEMA_LIMIT: Final = "limit"
+STATE_RATE_LIMITED: Final = "rate_limited"
+STATE_DISCONNECTED: Final = "disconnected"
 
 # Event names
 EVENT_RESPONSE_RECEIVED: Final = f"{DOMAIN}_response_received"
 EVENT_ERROR_OCCURRED: Final = f"{DOMAIN}_error_occurred"
 EVENT_STATE_CHANGED: Final = f"{DOMAIN}_state_changed"
+
+# Service schema constants
+SERVICE_SCHEMA_ASK_QUESTION = vol.Schema({
+    vol.Required(CONF_INSTANCE): cv.string,
+    vol.Required("question"): cv.string,
+    vol.Optional("system_prompt"): cv.string,
+    vol.Optional("model"): cv.string,
+    vol.Optional("temperature"): vol.All(
+        vol.Coerce(float),
+        vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
+    ),
+    vol.Optional("max_tokens"): vol.All(
+        vol.Coerce(int),
+        vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
+    ),
+    vol.Optional("context_messages"): vol.All(
+        vol.Coerce(int),
+        vol.Range(min=1, max=20)
+    )
+})
+
+SERVICE_SCHEMA_SET_SYSTEM_PROMPT = vol.Schema({
+    vol.Required(CONF_INSTANCE): cv.string,
+    vol.Required("prompt"): cv.string
+})
+
+SERVICE_SCHEMA_GET_HISTORY = vol.Schema({
+    vol.Required(CONF_INSTANCE): cv.string,
+    vol.Optional("limit", default=10): vol.All(
+        vol.Coerce(int),
+        vol.Range(min=1, max=100),
+    ),
+    vol.Optional("filter_model"): cv.string
+})
+
+# Configuration schema
+CONFIG_SCHEMA = vol.Schema({
+    DOMAIN: vol.Schema({
+        vol.Required(CONF_NAME): cv.string,
+        vol.Required(CONF_API_KEY): cv.string,
+        vol.Required(CONF_API_PROVIDER): vol.In(API_PROVIDERS),
+        vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): cv.string,
+        vol.Optional(CONF_TEMPERATURE, default=DEFAULT_TEMPERATURE): vol.All(
+            vol.Coerce(float),
+            vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
+        ),
+        vol.Optional(CONF_MAX_TOKENS, default=DEFAULT_MAX_TOKENS): vol.All(
+            vol.Coerce(int),
+            vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
+        ),
+        vol.Optional(CONF_API_ENDPOINT): cv.string,
+        vol.Optional(CONF_REQUEST_INTERVAL, default=DEFAULT_REQUEST_INTERVAL): vol.All(
+            vol.Coerce(float),
+            vol.Range(min=MIN_REQUEST_INTERVAL, max=MAX_REQUEST_INTERVAL)
+        ),
+        vol.Optional(CONF_MAX_HISTORY_SIZE, default=DEFAULT_MAX_HISTORY): vol.All(  # Correct usage
+            vol.Coerce(int),
+            vol.Range(min=1, max=100),
+        ),
+        vol.Optional(CONF_CONTEXT_MESSAGES, default=DEFAULT_CONTEXT_MESSAGES): vol.All(
+            vol.Coerce(int),
+            vol.Range(min=1, max=20)
+        )
+    })
+}, extra=vol.ALLOW_EXTRA)

custom_components/ha_text_ai/manifest.json

@@ -1,42 +1,28 @@
 {
   "domain": "ha_text_ai",
   "name": "HA Text AI",
+  "after_dependencies": ["http"],
+  "bluetooth": [],
   "codeowners": ["@smkrv"],
   "config_flow": true,
   "dependencies": [],
   "documentation": "https://github.com/smkrv/ha-text-ai",
-  "homepage": "https://github.com/smkrv/ha-text-ai",
+  "integration_type": "service",
   "iot_class": "cloud_polling",
   "issue_tracker": "https://github.com/smkrv/ha-text-ai/issues",
+  "loggers": ["custom_components.ha_text_ai"],
+  "mqtt": [],
+  "quality_scale": "silver",
   "requirements": [
     "openai>=1.12.0",
     "anthropic>=0.8.0",
     "aiohttp>=3.8.0",
-    "async-timeout>=4.0.0"
+    "async-timeout>=4.0.0",
+    "certifi>=2024.2.2"
   ],
-  "version": "2.0.0",
-  "homeassistant": "2024.1.0",
-  "quality_scale": "silver",
-  "integration_type": "service",
-  "translations": [
-    "en"
-  ],
-  "zeroconf": [],
+  "single_config_entry": false,
   "ssdp": [],
   "usb": [],
-  "bluetooth": [],
-  "mqtt": [],
-  "loggers": ["custom_components.ha_text_ai"],
-  "after_dependencies": ["http"],
-  "title": "Text AI Assistant",
-  "description": "AI-powered text assistant supporting multiple models including GPT and Claude",
-  "render_readme": true,
-  "tags": [
-    "ai",
-    "automation",
-    "chat",
-    "assistant",
-    "openai",
-    "claude"
-  ]
+  "version": "2.0.2-alpha",
+  "zeroconf": []
 }

custom_components/ha_text_ai/sensor.py

@@ -1,70 +1,101 @@
-"""Sensor platform for HA text AI."""
-from datetime import datetime
+"""Sensor platform for HA Text AI."""
 import logging
-from typing import Any, Dict, Optional
+import math
+from typing import Any, Dict
 
 from homeassistant.components.sensor import (
     SensorEntity,
-    SensorStateClass,
-    SensorDeviceClass,
+    SensorEntityDescription,
 )
 from homeassistant.config_entries import ConfigEntry
 from homeassistant.core import HomeAssistant
+from homeassistant.helpers.device_registry import DeviceInfo
 from homeassistant.helpers.entity_platform import AddEntitiesCallback
 from homeassistant.helpers.typing import StateType
 from homeassistant.helpers.update_coordinator import CoordinatorEntity
 from homeassistant.util import dt as dt_util
+from homeassistant.util import slugify
 
 from .const import (
     DOMAIN,
-    ATTR_QUESTION,
-    ATTR_RESPONSE,
-    ATTR_LAST_UPDATED,
-    ATTR_MODEL,
-    ATTR_TEMPERATURE,
-    ATTR_MAX_TOKENS,
+    CONF_MODEL,
+    CONF_API_PROVIDER,
     ATTR_TOTAL_RESPONSES,
-    ATTR_SYSTEM_PROMPT,
-    ATTR_QUEUE_SIZE,
-    ATTR_API_STATUS,
-    ATTR_ERROR_COUNT,
+    ATTR_TOTAL_ERRORS,
+    ATTR_AVG_RESPONSE_TIME,
+    ATTR_LAST_REQUEST_TIME,
     ATTR_LAST_ERROR,
-    ATTR_RESPONSE_TIME,
+    ATTR_IS_PROCESSING,
+    ATTR_IS_RATE_LIMITED,
+    ATTR_IS_MAINTENANCE,
     ATTR_API_VERSION,
     ATTR_ENDPOINT_STATUS,
-    ATTR_REQUEST_COUNT,
-    ATTR_TOKENS_USED,
-    ENTITY_ICON,
-    ENTITY_ICON_ERROR,
-    ENTITY_ICON_PROCESSING,
+    ATTR_PERFORMANCE_METRICS,
+    ATTR_HISTORY_SIZE,
+    ATTR_UPTIME,
+    ATTR_API_PROVIDER,
+    ATTR_MODEL,
+    ATTR_SYSTEM_PROMPT,
+    ATTR_API_STATUS,
+    ATTR_RESPONSE,
+    ATTR_QUESTION,
+    ATTR_CONVERSATION_HISTORY,
+    METRIC_TOTAL_TOKENS,
+    METRIC_PROMPT_TOKENS,
+    METRIC_COMPLETION_TOKENS,
+    METRIC_SUCCESSFUL_REQUESTS,
+    METRIC_FAILED_REQUESTS,
+    METRIC_AVERAGE_LATENCY,
+    METRIC_MAX_LATENCY,
+    METRIC_MIN_LATENCY,
     STATE_READY,
     STATE_PROCESSING,
     STATE_ERROR,
-    STATE_DISCONNECTED,
-    STATE_RATE_LIMITED,
     STATE_INITIALIZING,
     STATE_MAINTENANCE,
+    STATE_RATE_LIMITED,
+    STATE_DISCONNECTED,
+    ENTITY_ICON,
+    ENTITY_ICON_ERROR,
+    ENTITY_ICON_PROCESSING,
+    DEFAULT_NAME_PREFIX,
+    CONF_MAX_HISTORY_SIZE,
 )
+
 from .coordinator import HATextAICoordinator
 
 _LOGGER = logging.getLogger(__name__)
 
+
 async def async_setup_entry(
     hass: HomeAssistant,
     entry: ConfigEntry,
     async_add_entities: AddEntitiesCallback,
 ) -> None:
-    """Set up the HA text AI sensor."""
-    coordinator = hass.data[DOMAIN][entry.entry_id]
-    async_add_entities([HATextAISensor(coordinator, entry)], True)
+    """Set up the HA Text AI sensor."""
+    _LOGGER.debug(f"Starting sensor setup for entry: {entry.entry_id}")
 
+    try:
+        coordinator = hass.data[DOMAIN][entry.entry_id]
+        _LOGGER.debug(f"Found coordinator for entry {entry.entry_id}")
+
+        instance_name = coordinator.instance_name
+        _LOGGER.debug(f"Setting up sensor with instance: {instance_name}")
+
+        sensor = HATextAISensor(coordinator, entry)
+        _LOGGER.debug(f"Created sensor instance: {sensor.entity_id}")
+
+        async_add_entities([sensor], True)
+        _LOGGER.debug(f"Added sensor entity: {sensor.entity_id}")
+
+    except Exception as err:
+        _LOGGER.exception(f"Error setting up sensor: {err}")
+        raise
 
 class HATextAISensor(CoordinatorEntity, SensorEntity):
-    """HA text AI Sensor."""
+    """HA Text AI Sensor."""
 
-    _attr_has_entity_name = True
-    _attr_state_class = SensorStateClass.MEASUREMENT
-    _attr_device_class = SensorDeviceClass.TIMESTAMP
+    coordinator: HATextAICoordinator
 
     def __init__(
         self,
@@ -72,164 +103,230 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
         config_entry: ConfigEntry,
     ) -> None:
         """Initialize the sensor."""
+        _LOGGER.debug(f"Initializing sensor with config entry: {config_entry.data}")
+
         super().__init__(coordinator)
+
         self._config_entry = config_entry
+        self._instance_name = coordinator.instance_name
+        self._normalized_name = coordinator.normalized_name
+
+        _LOGGER.debug(f"Instance name: {self._instance_name}")
+        _LOGGER.debug(f"Normalized name: {self._normalized_name}")
+
+        self._conversation_history = []
+        self._system_prompt = None
+
+        self._attr_name = f"HA Text AI {self._instance_name}"
+        self.entity_id = f"sensor.ha_text_ai_{self._normalized_name}"
         self._attr_unique_id = f"{config_entry.entry_id}"
-        self._attr_name = "Last Response"
-        self._attr_suggested_display_precision = 0
+
+        _LOGGER.debug(f"Created sensor with entity_id: {self.entity_id}")
+        _LOGGER.debug(f"Sensor name: {self._attr_name}")
+        _LOGGER.debug(f"Unique ID: {self._attr_unique_id}")
+
+        self.entity_description = SensorEntityDescription(
+            key=f"ha_text_ai_{self._normalized_name.lower()}",
+            entity_registry_enabled_default=True,
+        )
+
+        self._current_state = STATE_INITIALIZING
         self._error_count = 0
         self._last_error = None
-        self._state = STATE_INITIALIZING
-        self._attr_device_info = {
-            "identifiers": {(DOMAIN, self._attr_unique_id)},
-            "name": "HA Text AI",
-            "manufacturer": "Community",
-            "model": coordinator.model,
-            "sw_version": coordinator.api_version,
-        }
+        self._last_update = None
+        self._is_processing = False
+        self._last_response = {}
+        self._metrics = {}
 
-    @property
-    def icon(self) -> str:
-        """Return the icon based on the current state."""
-        if self._state == STATE_PROCESSING:
-            return ENTITY_ICON_PROCESSING
-        elif self._state in [STATE_ERROR, STATE_DISCONNECTED, STATE_RATE_LIMITED]:
-            return ENTITY_ICON_ERROR
-        return ENTITY_ICON
+        model = config_entry.data.get(CONF_MODEL, "Unknown")
+        api_provider = config_entry.data.get(CONF_API_PROVIDER, "Unknown")
 
-    @property
-    def state(self) -> StateType:
-        """Return the state of the sensor."""
-        if not self.coordinator.data or not self.coordinator.last_update_success:
-            return None
+        self._attr_device_info = DeviceInfo(
+            identifiers={(DOMAIN, self._attr_unique_id)},
+            name=self._attr_name,
+            manufacturer="Community",
+            model=f"{model} ({api_provider} provider)",
+            sw_version="1.0.0",
+        )
 
-        try:
-            if self.coordinator.data and isinstance(self.coordinator.data, dict):
-                last_update = self.coordinator.data.get("last_update")
-                if isinstance(last_update, datetime):
-                    return dt_util.as_local(last_update)
-                return last_update
-            return None
-        except Exception as err:
-            _LOGGER.error("Error getting state: %s", err, exc_info=True)
-            return None
-
-    @property
-    def extra_state_attributes(self) -> Dict[str, Any]:
-        """Return entity specific state attributes."""
-        attributes = {
-            ATTR_TOTAL_RESPONSES: 0,
-            ATTR_MODEL: self.coordinator.model,
-            ATTR_TEMPERATURE: self.coordinator.temperature,
-            ATTR_MAX_TOKENS: self.coordinator.max_tokens,
-            ATTR_SYSTEM_PROMPT: self.coordinator.system_prompt,
-            ATTR_QUEUE_SIZE: self.coordinator._question_queue.qsize(),
-            ATTR_API_STATUS: self._state,
-            ATTR_ERROR_COUNT: self._error_count,
-            ATTR_LAST_ERROR: self._last_error,
-            ATTR_API_VERSION: self.coordinator.api_version,
-            ATTR_ENDPOINT_STATUS: self.coordinator.endpoint_status,
-            ATTR_REQUEST_COUNT: self.coordinator.request_count,
-            ATTR_TOKENS_USED: self.coordinator.tokens_used,
-        }
-
-        if not self.coordinator.data:
-            return attributes
-
-        try:
-            history = list(self.coordinator._responses.items())
-            if history:
-                last_question, last_data = history[-1]
-
-                if isinstance(last_data, dict):
-                    last_response = last_data.get("response", "")
-                    last_updated = last_data.get("timestamp") or self.coordinator.data.get("last_update")
-                    response_time = last_data.get("response_time")
-
-                    model = last_data.get("model", self.coordinator.model)
-                    temperature = last_data.get("temperature", self.coordinator.temperature)
-                    max_tokens = last_data.get("max_tokens", self.coordinator.max_tokens)
-                    error = last_data.get("error")
-
-                    if error:
-                        self._last_error = error
-                        self._state = STATE_ERROR
-                else:
-                    last_response = str(last_data)
-                    last_updated = self.coordinator.data.get("last_update")
-                    response_time = None
-                    model = self.coordinator.model
-                    temperature = self.coordinator.temperature
-                    max_tokens = self.coordinator.max_tokens
-
-                if isinstance(last_updated, datetime):
-                    last_updated = dt_util.as_local(last_updated)
-
-                attributes.update({
-                    ATTR_QUESTION: last_question,
-                    ATTR_RESPONSE: last_response,
-                    ATTR_LAST_UPDATED: last_updated,
-                    ATTR_TOTAL_RESPONSES: len(history),
-                    ATTR_MODEL: model,
-                    ATTR_TEMPERATURE: temperature,
-                    ATTR_MAX_TOKENS: max_tokens,
-                })
-
-                if response_time is not None:
-                    attributes[ATTR_RESPONSE_TIME] = response_time
-
-            return attributes
-
-        except Exception as err:
-            _LOGGER.error("Error getting attributes: %s", err, exc_info=True)
-            self._error_count += 1
-            self._last_error = str(err)
-            self._state = STATE_ERROR
-            return attributes
+        _LOGGER.debug(
+            f"Initialized sensor: {self.entity_id} for instance: {self._instance_name}"
+        )
 
     @property
     def available(self) -> bool:
         """Return if entity is available."""
-        return self.coordinator.last_update_success
+        return (
+            self.coordinator.last_update_success
+            and self.coordinator.data is not None
+            and self._current_state != STATE_DISCONNECTED
+        )
+
+    def _sanitize_value(self, value: Any) -> Any:
+        """Sanitize values for JSON serialization."""
+        if isinstance(value, float):
+            if math.isinf(value) or math.isnan(value):
+                return None
+        return value
+
+    def _sanitize_attributes(self, attributes: Dict[str, Any]) -> Dict[str, Any]:
+        """Sanitize all attributes for JSON serialization."""
+        return {
+            key: self._sanitize_value(value)
+            for key, value in attributes.items()
+            if value is not None
+        }
+
+    @property
+    def native_value(self) -> StateType:
+        """Return the native value of the sensor."""
+        if not self.coordinator.last_update_success or not self.coordinator.data:
+            self._current_state = STATE_DISCONNECTED
+            return self._current_state
+
+        status = self.coordinator.data.get("state", STATE_READY)
+        self._current_state = status
+        return status
+
+    @property
+    def icon(self) -> str:
+        """Return the icon based on the current state."""
+        if self._current_state == STATE_ERROR:
+            return ENTITY_ICON_ERROR
+        elif self._current_state == STATE_PROCESSING:
+            return ENTITY_ICON_PROCESSING
+        return ENTITY_ICON
+
+    @property
+    def extra_state_attributes(self) -> Dict[str, Any]:
+        """Return entity specific state attributes."""
+        if not self.coordinator.data:
+            return {}
+
+        try:
+            data = self.coordinator.data
+            attributes = {
+                ATTR_MODEL: self._config_entry.data.get(CONF_MODEL, "Unknown"),
+                ATTR_API_PROVIDER: self._config_entry.data.get(
+                    CONF_API_PROVIDER, "Unknown"
+                ),
+                ATTR_API_STATUS: self._current_state,
+                ATTR_TOTAL_ERRORS: self._error_count,
+                ATTR_LAST_ERROR: self._last_error,
+                "instance_name": self._instance_name,
+                "normalized_name": self._normalized_name,
+                ATTR_SYSTEM_PROMPT: data.get("system_prompt"),
+                ATTR_IS_PROCESSING: data.get("is_processing", False),
+                ATTR_IS_RATE_LIMITED: data.get("is_rate_limited", False),
+                ATTR_IS_MAINTENANCE: data.get("is_maintenance", False),
+                ATTR_ENDPOINT_STATUS: data.get("endpoint_status", "unknown"),
+                ATTR_UPTIME: data.get("uptime", 0),
+                ATTR_HISTORY_SIZE: data.get("history_size", 0),
+                ATTR_CONVERSATION_HISTORY: data.get("conversation_history", []),
+            }
+
+            # Add metrics
+            metrics = data.get("metrics", {})
+            if isinstance(metrics, dict):
+                self._metrics = metrics
+                attributes.update(
+                    {
+                        METRIC_TOTAL_TOKENS: metrics.get("total_tokens", 0),
+                        METRIC_PROMPT_TOKENS: metrics.get("prompt_tokens", 0),
+                        METRIC_COMPLETION_TOKENS: metrics.get("completion_tokens", 0),
+                        METRIC_SUCCESSFUL_REQUESTS: metrics.get(
+                            "successful_requests", 0
+                        ),
+                        METRIC_FAILED_REQUESTS: metrics.get("failed_requests", 0),
+                        METRIC_AVERAGE_LATENCY: metrics.get("average_latency", 0),
+                        METRIC_MAX_LATENCY: metrics.get("max_latency", 0),
+                        METRIC_MIN_LATENCY: metrics.get("min_latency", float("inf")),
+                    }
+                )
+
+            # Add last response
+            last_response = data.get("last_response", {})
+            if isinstance(last_response, dict):
+                self._last_response = last_response
+                attributes.update(
+                    {
+                        ATTR_RESPONSE: last_response.get("response", ""),
+                        ATTR_QUESTION: last_response.get("question", ""),
+                        "last_model": last_response.get("model", ""),
+                        "last_timestamp": last_response.get("timestamp", ""),
+                        "last_error": last_response.get("error"),
+                    }
+                )
+
+            # Add performance metrics if available
+            if ATTR_PERFORMANCE_METRICS in data:
+                attributes[ATTR_PERFORMANCE_METRICS] = data[
+                    ATTR_PERFORMANCE_METRICS
+                ]
+
+            # Add API version if available
+            if ATTR_API_VERSION in data:
+                attributes[ATTR_API_VERSION] = data[ATTR_API_VERSION]
+
+            return self._sanitize_attributes(attributes)
+
+        except Exception as err:
+            _LOGGER.error("Error preparing attributes: %s", err, exc_info=True)
+            return {}
 
     async def async_added_to_hass(self) -> None:
         """When entity is added to hass."""
         await super().async_added_to_hass()
         self._handle_coordinator_update()
-        self._state = STATE_READY
+        _LOGGER.debug(f"Entity {self.entity_id} added to Home Assistant")
 
     def _handle_coordinator_update(self) -> None:
         """Handle updated data from the coordinator."""
         try:
-            if self.coordinator.data:
-                if self.coordinator._is_ready:
-                    if self.coordinator._is_processing:
-                        self._state = STATE_PROCESSING
-                    elif self.coordinator._is_rate_limited:
-                        self._state = STATE_RATE_LIMITED
-                    elif self.coordinator._is_maintenance:
-                        self._state = STATE_MAINTENANCE
-                    else:
-                        self._state = STATE_READY
-                else:
-                    self._state = STATE_DISCONNECTED
-            else:
-                self._state = STATE_DISCONNECTED
+            data = self.coordinator.data
+            if not self.coordinator.last_update_success or not data:
+                self._current_state = STATE_DISCONNECTED
+                _LOGGER.warning(f"No data available for {self.entity_id}")
+                self.async_write_ha_state()
+                return
 
-            # Обновляем счетчик ошибок только если статус изменился на ошибку
-            if self._state == STATE_ERROR:
+            self._is_processing = data.get("is_processing", False)
+
+            # Update conversation history and system prompt
+            self._conversation_history = data.get("conversation_history", [])
+            self._system_prompt = data.get("system_prompt")
+
+            # Update state based on conditions
+            if self._is_processing:
+                self._current_state = STATE_PROCESSING
+            elif data.get("is_rate_limited"):
+                self._current_state = STATE_RATE_LIMITED
+            elif data.get("is_maintenance"):
+                self._current_state = STATE_MAINTENANCE
+            elif data.get("error"):
+                self._current_state = STATE_ERROR
+                self._last_error = data["error"]
                 self._error_count += 1
+            else:
+                self._current_state = data.get("state", STATE_READY)
+
+            # Update last update timestamp
+            self._last_update = dt_util.utcnow()
+
+            _LOGGER.debug(
+                f"Updated {self.entity_id} state to: {self._current_state} "
+                f"(available: {self.available})"
+            )
 
         except Exception as err:
-            _LOGGER.error("Error handling update: %s", err, exc_info=True)
-            self._error_count += 1
+            self._current_state = STATE_ERROR
             self._last_error = str(err)
-            self._state = STATE_ERROR
+            self._error_count += 1
+            _LOGGER.error(
+                "Error handling update for %s: %s",
+                self.entity_id,
+                err,
+                exc_info=True,
+            )
 
         self.async_write_ha_state()
-
-    async def async_reset_error_count(self) -> None:
-        """Reset the error counter."""
-        self._error_count = 0
-        self._last_error = None
-        self.async_write_ha_state()

custom_components/ha_text_ai/services.yaml

@@ -3,69 +3,55 @@ ask_question:
   description: >-
     Send a question to the AI model and receive a detailed response.
     The response will be stored in the conversation history and can be retrieved later.
-    Response time may vary based on model selection and server load.
-    Supports various AI models with different capabilities and pricing.
   fields:
+    instance:
+      name: Instance
+      description: Name of the HA Text AI instance to use
+      required: true
+      selector:
+        entity:
+          integration: ha_text_ai
+          domain: sensor
+
     question:
       name: Question
-      description: >-
-        Your question or prompt for the AI assistant. Be specific and clear for better results.
-        You can ask about home automation, technical advice, or general questions.
-        For complex queries, consider breaking them into smaller parts.
-        The system will maintain conversation context for follow-up questions.
+      description: Your question or prompt for the AI assistant
       required: true
-      example: |
-        What automations would you recommend for a smart kitchen?
-        Consider energy efficiency, convenience, and integration with:
-        - Smart lighting
-        - Appliance control
-        - Temperature monitoring
-        - Voice commands
       selector:
         text:
           multiline: true
           type: text
 
+    system_prompt:
+      name: System Prompt
+      description: Optional system prompt to set context for this specific question
+      required: false
+      selector:
+        text:
+          multiline: true
+
+    context_messages:
+      name: Context Messages
+      description: Number of previous messages to include in context (1-20)
+      required: false
+      default: 5
+      selector:
+        number:
+          min: 1
+          max: 20
+          step: 1
+          mode: slider
+
     model:
       name: Model
-      description: >-
-        Select an AI model to use (optional, overrides default setting).
-        Different models have different capabilities, context limits, and response characteristics:
-        - GPT-3.5 Turbo: Fast, efficient, good for most tasks
-        - GPT-4: More capable, better reasoning, slower
-        - Claude-3: Advanced capabilities, longer context
-        Note: More capable models may have longer response times and higher API costs.
+      description: "Select AI model to use (optional, overrides default setting)"
       required: false
-      example: "gpt-3.5-turbo"
-      default: "gpt-3.5-turbo"
       selector:
-        select:
-          custom_value: true
-          options:
-            - label: "GPT-3.5 Turbo (Fast & Efficient)"
-              value: "gpt-3.5-turbo"
-            - label: "GPT-3.5 Turbo 16K (Extended)"
-              value: "gpt-3.5-turbo-16k"
-            - label: "GPT-4 (Most Capable)"
-              value: "gpt-4"
-            - label: "GPT-4 32K (Extended Context)"
-              value: "gpt-4-32k"
-            - label: "GPT-4 Turbo (Latest)"
-              value: "gpt-4-1106-preview"
-            - label: "Claude-3 Sonnet (Balanced)"
-              value: "claude-3-sonnet"
-            - label: "Claude-3 Opus (Most Advanced)"
-              value: "claude-3-opus"
-          mode: dropdown
+        text: {}
 
     temperature:
       name: Temperature
-      description: >-
-        Controls response creativity (0.0-2.0):
-        0.0-0.3: Focused, consistent responses (best for technical/factual queries)
-        0.4-0.7: Balanced responses (recommended for most uses)
-        0.8-2.0: More creative, varied responses (best for brainstorming)
-        Note: Higher values may produce less predictable results.
+      description: Controls response creativity (0.0-2.0)
       required: false
       default: 0.7
       selector:
@@ -74,17 +60,10 @@ ask_question:
           max: 2.0
           step: 0.1
           mode: slider
-          unit_of_measurement: ""
 
     max_tokens:
       name: Max Tokens
-      description: >-
-        Maximum length of the response (1-4096 tokens).
-        Recommended ranges:
-        - Short (256-512): Quick answers, status updates
-        - Medium (512-1024): Detailed explanations
-        - Long (1024-4096): Complex analysis
-        Note: Token limits vary by model. Actual length may be shorter.
+      description: Maximum length of the response (1-4096 tokens)
       required: false
       default: 1000
       selector:
@@ -94,42 +73,36 @@ ask_question:
           step: 1
           mode: box
 
-    system_prompt:
-      name: System Prompt
-      description: >-
-        Optional system prompt to set context for this specific question.
-        This will temporarily override the default system prompt.
-        Use this to specify expertise areas, response format, or special instructions.
-      required: false
-      example: "You are a home automation expert focused on energy efficiency and security"
-      selector:
-        text:
-          multiline: true
-
 clear_history:
   name: Clear History
   description: >-
-    Delete all stored questions and responses from the conversation history.
-    This action cannot be undone. Consider using 'get_history' first if you need to backup the data.
-    System prompt settings and configuration will be preserved.
-  fields: {}
+    Delete all stored questions and responses from the conversation history
+  fields:
+    instance:
+      name: Instance
+      description: Name of the HA Text AI instance to clear history for
+      required: true
+      selector:
+        entity:
+          integration: ha_text_ai
+          domain: sensor
 
 get_history:
   name: Get History
-  description: >-
-    Retrieve recent conversation history, including:
-    - Questions and responses
-    - Timestamps and response times
-    - Models used and token counts
-    - Temperature and other settings
-    Results are ordered from newest to oldest.
+  description: Retrieve conversation history with optional filtering and sorting
   fields:
+    instance:
+      name: Instance
+      description: Name of the HA Text AI instance to get history from
+      required: true
+      selector:
+        entity:
+          integration: ha_text_ai
+          domain: sensor
+
     limit:
       name: Limit
-      description: >-
-        Number of most recent conversations to return (1-100).
-        Higher values return more history but may take longer to process.
-        Default: 10 conversations
+      description: Number of conversations to return (1-100)
       required: false
       default: 10
       selector:
@@ -140,66 +113,57 @@ get_history:
           mode: box
 
     filter_model:
-      name: Filter by Model
-      description: >-
-        Only return conversations using a specific AI model.
-        Leave empty to show all models.
+      name: Filter Model
+      description: Filter conversations by specific AI model
       required: false
       selector:
-        select:
-          custom_value: true
-          options:
-            - label: "All Models"
-              value: ""
-            - label: "GPT-3.5 Turbo"
-              value: "gpt-3.5-turbo"
-            - label: "GPT-4"
-              value: "gpt-4"
-            - label: "GPT-4 Turbo"
-              value: "gpt-4-1106-preview"
-            - label: "Claude-3 Sonnet"
-              value: "claude-3-sonnet"
-            - label: "Claude-3 Opus"
-              value: "claude-3-opus"
-          mode: dropdown
+        text:
+          multiline: false
 
     start_date:
       name: Start Date
-      description: >-
-        Optional start date for filtering history.
-        Format: YYYY-MM-DD
+      description: Filter conversations starting from this date/time
       required: false
       selector:
-        datetime:
-          type: date
+        text:
+          multiline: false
+
+    include_metadata:
+      name: Include Metadata
+      description: Include additional information like tokens used, response time, etc.
+      required: false
+      default: false
+      selector:
+        boolean:
+
+    sort_order:
+      name: Sort Order
+      description: Sort order for results (newest or oldest first)
+      required: false
+      default: newest
+      selector:
+        select:
+          options:
+            - newest
+            - oldest
 
 set_system_prompt:
   name: Set System Prompt
-  description: >-
-    Set default system behavior instructions for all future conversations.
-    This defines how the AI should behave and respond to questions.
-    The prompt will be used for all models unless overridden per question.
+  description: Set default system behavior instructions for all future conversations
   fields:
+    instance:
+      name: Instance
+      description: Name of the HA Text AI instance to set system prompt for
+      required: true
+      selector:
+        entity:
+          integration: ha_text_ai
+          domain: sensor
+
     prompt:
       name: System Prompt
-      description: >-
-        Instructions that define how the AI should behave and respond.
-        Be specific about:
-        - Desired expertise and knowledge areas
-        - Response tone and style
-        - Output format preferences
-        - Special handling instructions
-        Maximum length: 1000 characters
+      description: Instructions that define how the AI should behave and respond
       required: true
-      example: |
-        You are a home automation expert assistant. Focus on:
-        1. Practical and efficient solutions
-        2. Energy-saving recommendations
-        3. Integration with popular smart home platforms
-        4. Security and privacy considerations
-        Provide detailed but concise responses with clear steps when applicable.
-        Format complex responses with bullet points or numbered lists.
-        Include warnings about potential risks or limitations.
       selector:
         text:
           multiline: true

custom_components/ha_text_ai/translations/de.json

@@ -0,0 +1,266 @@
+{
+  "config": {
+    "step": {
+      "provider": {
+        "title": "KI-Anbieter auswählen",
+        "description": "Wählen Sie den KI-Dienstanbieter für diese Instanz aus.",
+        "data": {
+          "api_provider": "API-Anbieter",
+          "context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)"
+        }
+      },
+      "user": {
+        "title": "HA Text AI-Instanz konfigurieren",
+        "description": "Richten Sie eine neue KI-Assistenteninstanz mit Ihrem ausgewählten Anbieter ein.",
+        "data": {
+          "name": "Instanzname (z. B. 'GPT-Assistent', 'Claude-Helfer')",
+          "api_key": "API-Schlüssel zur Authentifizierung",
+          "model": "Zu verwendendes KI-Modell",
+          "temperature": "Antwortkreativität (0-2, niedriger = fokussierter)",
+          "max_tokens": "Maximale Antwortlänge (1-4096 Token)",
+          "api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)",
+          "api_provider": "API-Anbieter",
+          "request_interval": "Mindestzeit zwischen Anfragen (0,1-60 Sekunden)",
+          "context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)",
+          "max_history_size": "Maximale Größe des Konversationsverlaufs (1-100)"
+        }
+      }
+    },
+    "error": {
+      "name_exists": "Eine Instanz mit diesem Namen existiert bereits",
+      "invalid_name": "Ungültiger Instanzname",
+      "invalid_auth": "Authentifizierung fehlgeschlagen - überprüfen Sie Ihren API-Schlüssel",
+      "invalid_api_key": "Ungültiger API-Schlüssel - überprüfen Sie Ihre Anmeldedaten",
+      "cannot_connect": "Verbindung zum API-Dienst fehlgeschlagen",
+      "invalid_model": "Das ausgewählte Modell ist nicht verfügbar",
+      "rate_limit": "Ratenlimit überschritten",
+      "context_length": "Kontextlänge überschritten",
+      "rate_limit_exceeded": "API-Ratenlimit überschritten",
+      "maintenance": "Dienst befindet sich in der Wartung",
+      "invalid_response": "Ungültige API-Antwort empfangen",
+      "api_error": "Fehler im API-Dienst aufgetreten",
+      "timeout": "Anfrage ist abgelaufen",
+      "invalid_instance": "Ungültige Instanz angegeben",
+      "unknown": "Es ist ein unerwarteter Fehler aufgetreten",
+      "empty": "Name darf nicht leer sein",
+      "invalid_characters": "Name darf nur Buchstaben, Zahlen, Leerzeichen, Unterstriche und Bindestriche enthalten",
+      "name_too_long": "Name darf maximal 50 Zeichen lang sein"
+    }
+  },
+  "options": {
+    "step": {
+      "init": {
+        "title": "Instanzeinstellungen aktualisieren",
+        "description": "Ändern Sie die Einstellungen für diese KI-Assistenteninstanz.",
+        "data": {
+          "model": "KI-Modell",
+          "temperature": "Antwortkreativität (0-2)",
+          "max_tokens": "Maximale Antwortlänge (1-4096)",
+          "request_interval": "Mindestzeitraum zwischen Anfragen (0,1-60 Sekunden)",
+          "context_messages": "Anzahl der vorherigen Nachrichten, die im Kontext enthalten sein sollen (1-20)",
+          "max_history_size": "Maximale Größe des Konversationsverlaufs (1-100)"
+        }
+      }
+    }
+  },
+  "services": {
+    "ask_question": {
+      "name": "Frage stellen (HA Text AI)",
+      "description": "Senden Sie eine Frage an das KI-Modell und erhalten Sie eine detaillierte Antwort. Die Antwort wird im Konversationsverlauf gespeichert und kann später abgerufen werden.",
+      "fields": {
+        "instance": {
+          "name": "Instanz",
+          "description": "Name der zu verwendenden HA Text AI-Instanz"
+        },
+        "question": {
+          "name": "Frage",
+          "description": "Ihre Frage oder Aufforderung an den KI-Assistenten"
+        },
+        "context_messages": {
+          "name": "Kontextnachrichten",
+          "description": "Anzahl der vorherigen Nachrichten, die im Kontext enthalten sein sollen (1-20)"
+        },
+        "system_prompt": {
+          "name": "Systemprompt",
+          "description": "Optionaler Systemprompt, um den Kontext für diese spezielle Frage festzulegen"
+        },
+        "model": {
+          "name": "Modell",
+          "description": "Wählen Sie das zu verwendende KI-Modell aus (optional, überschreibt die Standardeinstellung)"
+        },
+        "temperature": {
+          "name": "Temperatur",
+          "description": "Steuert die Antwortkreativität (0.0-2.0)"
+        },
+        "max_tokens": {
+          "name": "Max. Token",
+          "description": "Maximale Länge der Antwort (1-4096 Token)"
+        }
+      }
+    },
+    "clear_history": {
+      "name": "Verlauf löschen",
+      "description": "Alle gespeicherten Fragen und Antworten aus dem Konversationsverlauf löschen",
+      "fields": {
+        "instance": {
+          "name": "Instanz",
+          "description": "Name der HA Text AI-Instanz, deren Verlauf gelöscht werden soll"
+        }
+      }
+    },
+    "get_history": {
+      "name": "Verlauf abrufen",
+      "description": "Konversationsverlauf mit optionalem Filtern und Sortieren abrufen",
+      "fields": {
+        "instance": {
+          "name": "Instanz",
+          "description": "Name der HA Text AI-Instanz, von der der Verlauf abgerufen werden soll"
+        },
+        "limit": {
+          "name": "Limit",
+          "description": "Anzahl der zurückzugebenden Konversationen (1-100)"
+        },
+        "filter_model": {
+          "name": "Modell filtern",
+          "description": "Konversationen nach einem bestimmten KI-Modell filtern"
+        },
+        "start_date": {
+          "name": "Startdatum",
+          "description": "Konversationen ab diesem Datum/Uhrzeit filtern"
+        },
+        "include_metadata": {
+          "name": "Metadaten einschließen",
+          "description": "Zusätzliche Informationen wie verwendete Token, Antwortzeit usw. einschließen"
+        },
+        "sort_order": {
+          "name": "Sortierreihenfolge",
+          "description": "Sortierreihenfolge für die Ergebnisse (neueste oder älteste zuerst)"
+        }
+      }
+    },
+    "set_system_prompt": {
+      "name": "Systemprompt festlegen",
+      "description": "Legen Sie Standardanweisungen für das Systemverhalten für alle zukünftigen Konversationen fest",
+      "fields": {
+        "instance": {
+          "name": "Instanz",
+          "description": "Name der HA Text AI-Instanz, für die der Systemprompt festgelegt werden soll"
+        },
+        "prompt": {
+          "name": "Systemprompt",
+          "description": "Anweisungen, die definieren, wie sich die KI verhalten und antworten soll"
+        }
+      }
+    }
+  },
+  "entity": {
+    "sensor": {
+      "ha_text_ai": {
+        "name": "{name}",
+        "state": {
+          "ready": "Bereit",
+          "processing": "Verarbeitung",
+          "error": "Fehler",
+          "disconnected": "Getrennt",
+          "rate_limited": "Ratenlimit",
+          "maintenance": "Wartung",
+          "initializing": "Initialisierung",
+          "retrying": "Wiederholen",
+          "queued": "Warteschlange"
+        },
+        "state_attributes": {
+          "question": {
+            "name": "Letzte Frage"
+          },
+          "response": {
+            "name": "Letzte Antwort"
+          },
+          "model": {
+            "name": "Aktuelles Modell"
+          },
+          "temperature": {
+            "name": "Temperatur"
+          },
+          "max_tokens": {
+            "name": "Max. Token"
+          },
+          "system_prompt": {
+            "name": "Systemprompt"
+          },
+          "response_time": {
+            "name": "Letzte Antwortzeit"
+          },
+          "total_responses": {
+            "name": "Gesamtzahl der Antworten"
+          },
+          "error_count": {
+            "name": "Fehleranzahl"
+          },
+          "last_error": {
+            "name": "Letzter Fehler"
+          },
+          "api_status": {
+            "name": "API-Status"
+          },
+          "tokens_used": {
+            "name": "Verwendete Token insgesamt"
+          },
+          "average_response_time": {
+            "name": "Durchschnittliche Antwortzeit"
+          },
+          "last_request_time": {
+            "name": "Zeitpunkt der letzten Anfrage"
+          },
+          "is_processing": {
+            "name": "Verarbeitungsstatus"
+          },
+          "is_rate_limited": {
+            "name": "Ratenlimit-Status"
+          },
+          "is_maintenance": {
+            "name": "Wartungsstatus"
+          },
+          "api_version": {
+            "name": "API-Version"
+          },
+          "endpoint_status": {
+            "name": "Endpunkt-Status"
+          },
+          "performance_metrics": {
+            "name": "Leistungsmetriken"
+          },
+          "history_size": {
+            "name": "Verlaufsgröße"
+          },
+          "uptime": {
+            "name": "Betriebszeit"
+          },
+          "total_tokens": {
+            "name": "Gesamtzahl der Token"
+          },
+          "prompt_tokens": {
+            "name": "Prompt-Token"
+          },
+          "completion_tokens": {
+            "name": "Completion-Token"
+          },
+          "successful_requests": {
+            "name": "Erfolgreiche Anfragen"
+          },
+          "failed_requests": {
+            "name": "Fehlgeschlagene Anfragen"
+          },
+          "average_latency": {
+            "name": "Durchschnittliche Latenz"
+          },
+          "max_latency": {
+            "name": "Maximale Latenz"
+          },
+          "min_latency": {
+            "name": "Minimale Latenz"
+          }
+        }
+      }
+    }
+  }
+}

custom_components/ha_text_ai/translations/en.json

@@ -1,147 +1,266 @@
 {
-    "config": {
-        "step": {
-            "user": {
-                "title": "Set up HA Text AI",
-                "description": "Configure your AI integration for various providers (OpenAI, Anthropic, etc.). Different models have different capabilities and pricing.",
-                "data": {
-                    "api_key": "API key for authentication (required)",
-                    "model": "AI model to use (e.g., gpt-3.5-turbo, gpt-4, claude-3-sonnet, claude-3-opus)",
-                    "temperature": "Response creativity (0-2, lower = more focused and consistent)",
-                    "max_tokens": "Maximum response length (1-4096 tokens)",
-                    "api_endpoint": "Custom API endpoint URL (default varies by provider)",
-                    "request_interval": "Minimum time between requests in seconds (min: 0.1)",
-                    "system_prompt": "Default instructions for AI behavior and expertise"
-                }
-            }
-        },
-        "error": {
-            "invalid_auth": "Authentication failed - check your API key",
-            "invalid_api_key": "Invalid API key - please verify your credentials",
-            "cannot_connect": "Connection failed - check endpoint and network status",
-            "invalid_model": "Model unavailable or not supported by the API",
-            "rate_limit": "Rate limit exceeded - please reduce request frequency",
-            "context_length": "Input exceeds maximum context length for model",
-            "api_error": "API service error - check provider status",
-            "timeout": "Request timeout - server not responding",
-            "queue_full": "Request queue full - try again later",
-            "invalid_prompt": "Invalid system prompt format or length",
-            "invalid_url_format": "Invalid API endpoint URL format",
-            "invalid_input": "Invalid configuration parameters",
-            "unknown": "Unexpected error - check logs for details"
+  "config": {
+    "step": {
+      "provider": {
+        "title": "Select AI Provider",
+        "description": "Choose which AI service provider to use for this instance.",
+        "data": {
+          "api_provider": "API Provider",
+          "context_messages": "Number of context messages to retain (1-20)"
         }
-    },
-    "options": {
-        "step": {
-            "init": {
-                "title": "HA Text AI Settings",
-                "description": "Adjust your AI integration parameters and behavior",
-                "data": {
-                    "model": "Select AI model for responses (capabilities vary)",
-                    "temperature": "Response creativity (0-2, affects variation)",
-                    "max_tokens": "Maximum response length in tokens",
-                    "request_interval": "Minimum seconds between requests (rate limiting)",
-                    "system_prompt": "Default AI behavior and expertise instructions",
-                    "timeout": "Request timeout in seconds (default: 30)",
-                    "retry_count": "Number of retry attempts for failed requests",
-                    "queue_size": "Maximum pending requests in queue"
-                }
-            }
+      },
+      "user": {
+        "title": "Configure HA Text AI Instance",
+        "description": "Set up a new AI assistant instance with your selected provider.",
+        "data": {
+          "name": "Instance name (e.g., 'GPT Assistant', 'Claude Helper')",
+          "api_key": "API key for authentication",
+          "model": "AI model to use",
+          "temperature": "Response creativity (0-2, lower = more focused)",
+          "max_tokens": "Maximum response length (1-4096 tokens)",
+          "api_endpoint": "Custom API endpoint URL (optional)",
+          "api_provider": "API Provider",
+          "request_interval": "Minimum time between requests (0.1-60 seconds)",
+          "context_messages": "Number of context messages to retain (1-20)",
+          "max_history_size": "Maximum conversation history size (1-100)"
         }
+      }
     },
-    "services": {
-        "ask_question": {
-            "name": "Ask Question",
-            "description": "Send a question to the AI model and get a detailed response. Supports context awareness for follow-up questions.",
-            "fields": {
-                "question": {
-                    "name": "Question",
-                    "description": "Your question or prompt for the AI model. Be specific for better results."
-                },
-                "system_prompt": {
-                    "name": "System Prompt",
-                    "description": "Optional behavior instructions for this specific question"
-                },
-                "model": {
-                    "name": "Model",
-                    "description": "Optional specific AI model for this request (overrides default)"
-                },
-                "temperature": {
-                    "name": "Temperature",
-                    "description": "Optional creativity setting (0-2, affects response variation)"
-                },
-                "max_tokens": {
-                    "name": "Max Tokens",
-                    "description": "Optional maximum response length (1-4096 tokens)"
-                }
-            }
-        },
-        "clear_history": {
-            "name": "Clear History",
-            "description": "Delete all stored conversation history, responses, and metadata"
-        },
-        "get_history": {
-            "name": "Get History",
-            "description": "Retrieve conversation history with detailed metadata including timestamps",
-            "fields": {
-                "limit": {
-                    "name": "Limit",
-                    "description": "Maximum number of conversations to return (1-100)"
-                },
-                "filter_model": {
-                    "name": "Filter Model",
-                    "description": "Show only responses from a specific model"
-                },
-                "start_date": {
-                    "name": "Start Date",
-                    "description": "Filter conversations from this date (YYYY-MM-DD)"
-                }
-            }
-        },
-        "set_system_prompt": {
-            "name": "Set System Prompt",
-            "description": "Update default AI behavior and expertise instructions",
-            "fields": {
-                "prompt": {
-                    "name": "System Prompt",
-                    "description": "Instructions for AI behavior, expertise, and response style"
-                }
-            }
-        }
-    },
-    "state": {
-        "ready": "Ready for requests",
-        "processing": "Processing request",
-        "error": "Error occurred",
-        "disconnected": "API disconnected",
-        "rate_limited": "Rate limit reached",
-        "initializing": "Starting up",
-        "retrying": "Retrying request",
-        "queued": "Request queued"
-    },
-    "entity": {
-        "sensor": {
-            "status": {
-                "name": "AI Status",
-                "state": {
-                    "ready": "Ready",
-                    "processing": "Processing",
-                    "error": "Error",
-                    "disconnected": "Disconnected",
-                    "rate_limited": "Rate Limited",
-                    "initializing": "Initializing",
-                    "retrying": "Retrying",
-                    "queued": "Queued"
-                }
-            },
-            "last_response": {
-                "name": "Last Response",
-                "state": {
-                    "success": "Success",
-                    "error": "Error",
-                    "timeout": "Timeout"
-                }
-            }
-        }
+    "error": {
+      "name_exists": "An instance with this name already exists",
+      "invalid_name": "Invalid instance name",
+      "invalid_auth": "Authentication failed - check your API key",
+      "invalid_api_key": "Invalid API key - please verify your credentials",
+      "cannot_connect": "Failed to connect to API service",
+      "invalid_model": "Selected model is not available",
+      "rate_limit": "Rate limit exceeded",
+      "context_length": "Context length exceeded",
+      "rate_limit_exceeded": "API rate limit exceeded",
+      "maintenance": "Service is under maintenance",
+      "invalid_response": "Invalid API response received",
+      "api_error": "API service error occurred",
+      "timeout": "Request timed out",
+      "invalid_instance": "Invalid instance specified",
+      "unknown": "Unexpected error occurred",
+      "empty": "Name cannot be empty",
+      "invalid_characters": "Name can only contain letters, numbers, spaces, underscores and hyphens",
+      "name_too_long": "Name must be 50 characters or less"
     }
+  },
+  "options": {
+    "step": {
+      "init": {
+        "title": "Update Instance Settings",
+        "description": "Modify settings for this AI assistant instance.",
+        "data": {
+          "model": "AI model",
+          "temperature": "Response creativity (0-2)",
+          "max_tokens": "Maximum response length (1-4096)",
+          "request_interval": "Minimum request interval (0.1-60 seconds)",
+          "context_messages": "Number of previous messages to include in context (1-20)",
+          "max_history_size": "Maximum conversation history size (1-100)"
+        }
+      }
+    }
+  },
+  "services": {
+    "ask_question": {
+      "name": "Ask Question (HA Text AI)",
+      "description": "Send a question to the AI model and receive a detailed response. The response will be stored in the conversation history and can be retrieved later.",
+      "fields": {
+        "instance": {
+          "name": "Instance",
+          "description": "Name of the HA Text AI instance to use"
+        },
+        "question": {
+          "name": "Question",
+          "description": "Your question or prompt for the AI assistant"
+        },
+        "context_messages": {
+          "name": "Context Messages",
+          "description": "Number of previous messages to include in context (1-20)"
+        },
+        "system_prompt": {
+          "name": "System Prompt",
+          "description": "Optional system prompt to set context for this specific question"
+        },
+        "model": {
+          "name": "Model",
+          "description": "Select AI model to use (optional, overrides default setting)"
+        },
+        "temperature": {
+          "name": "Temperature",
+          "description": "Controls response creativity (0.0-2.0)"
+        },
+        "max_tokens": {
+          "name": "Max Tokens",
+          "description": "Maximum length of the response (1-4096 tokens)"
+        }
+      }
+    },
+    "clear_history": {
+      "name": "Clear History",
+      "description": "Delete all stored questions and responses from the conversation history",
+      "fields": {
+        "instance": {
+          "name": "Instance",
+          "description": "Name of the HA Text AI instance to clear history for"
+        }
+      }
+    },
+    "get_history": {
+      "name": "Get History",
+      "description": "Retrieve conversation history with optional filtering and sorting",
+      "fields": {
+        "instance": {
+          "name": "Instance",
+          "description": "Name of the HA Text AI instance to get history from"
+        },
+        "limit": {
+          "name": "Limit",
+          "description": "Number of conversations to return (1-100)"
+        },
+        "filter_model": {
+          "name": "Filter Model",
+          "description": "Filter conversations by specific AI model"
+        },
+        "start_date": {
+          "name": "Start Date",
+          "description": "Filter conversations starting from this date/time"
+        },
+        "include_metadata": {
+          "name": "Include Metadata",
+          "description": "Include additional information like tokens used, response time, etc."
+        },
+        "sort_order": {
+          "name": "Sort Order",
+          "description": "Sort order for results (newest or oldest first)"
+        }
+      }
+    },
+    "set_system_prompt": {
+      "name": "Set System Prompt",
+      "description": "Set default system behavior instructions for all future conversations",
+      "fields": {
+        "instance": {
+          "name": "Instance",
+          "description": "Name of the HA Text AI instance to set system prompt for"
+        },
+        "prompt": {
+          "name": "System Prompt",
+          "description": "Instructions that define how the AI should behave and respond"
+        }
+      }
+    }
+  },
+  "entity": {
+    "sensor": {
+      "ha_text_ai": {
+        "name": "{name}",
+        "state": {
+          "ready": "Ready",
+          "processing": "Processing",
+          "error": "Error",
+          "disconnected": "Disconnected",
+          "rate_limited": "Rate Limited",
+          "maintenance": "Maintenance",
+          "initializing": "Initializing",
+          "retrying": "Retrying",
+          "queued": "Queued"
+        },
+        "state_attributes": {
+          "question": {
+            "name": "Last Question"
+          },
+          "response": {
+            "name": "Last Response"
+          },
+          "model": {
+            "name": "Current Model"
+          },
+          "temperature": {
+            "name": "Temperature"
+          },
+          "max_tokens": {
+            "name": "Max Tokens"
+          },
+          "system_prompt": {
+            "name": "System Prompt"
+          },
+          "response_time": {
+            "name": "Last Response Time"
+          },
+          "total_responses": {
+            "name": "Total Responses"
+          },
+          "error_count": {
+            "name": "Error Count"
+          },
+          "last_error": {
+            "name": "Last Error"
+          },
+          "api_status": {
+            "name": "API Status"
+          },
+          "tokens_used": {
+            "name": "Total Tokens Used"
+          },
+          "average_response_time": {
+            "name": "Average Response Time"
+          },
+          "last_request_time": {
+            "name": "Last Request Time"
+          },
+          "is_processing": {
+            "name": "Processing Status"
+          },
+          "is_rate_limited": {
+            "name": "Rate Limited Status"
+          },
+          "is_maintenance": {
+            "name": "Maintenance Status"
+          },
+          "api_version": {
+            "name": "API Version"
+          },
+          "endpoint_status": {
+            "name": "Endpoint Status"
+          },
+          "performance_metrics": {
+            "name": "Performance Metrics"
+          },
+          "history_size": {
+            "name": "History Size"
+          },
+          "uptime": {
+            "name": "Uptime"
+          },
+          "total_tokens": {
+            "name": "Total Tokens"
+          },
+          "prompt_tokens": {
+            "name": "Prompt Tokens"
+          },
+          "completion_tokens": {
+            "name": "Completion Tokens"
+          },
+          "successful_requests": {
+            "name": "Successful Requests"
+          },
+          "failed_requests": {
+            "name": "Failed Requests"
+          },
+          "average_latency": {
+            "name": "Average Latency"
+          },
+          "max_latency": {
+            "name": "Maximum Latency"
+          },
+          "min_latency": {
+            "name": "Minimum Latency"
+          }
+        }
+      }
+    }
+  }
 }

custom_components/ha_text_ai/translations/ru.json

@@ -0,0 +1,266 @@
+{
+  "config": {
+    "step": {
+      "provider": {
+        "title": "Выбор поставщика ИИ",
+        "description": "Выберите поставщика услуг ИИ для этой инстанции.",
+        "data": {
+          "api_provider": "Поставщик API",
+          "context_messages": "Количество контекстных сообщений для сохранения (1-20)"
+        }
+      },
+      "user": {
+        "title": "Настройка инстанции HA Text AI",
+        "description": "Настройте новую инстанцию помощника ИИ с выбранным вами поставщиком.",
+        "data": {
+          "name": "Имя инстанции (например, 'GPT Assistant', 'Claude Helper')",
+          "api_key": "API-ключ для аутентификации",
+          "model": "Используемая модель ИИ",
+          "temperature": "Креативность ответа (0-2, чем ниже, тем больше фокусировки)",
+          "max_tokens": "Максимальная длина ответа (1-4096 токенов)",
+          "api_endpoint": "Пользовательский URL-адрес конечной точки API (необязательно)",
+          "api_provider": "Поставщик API",
+          "request_interval": "Минимальное время между запросами (0,1-60 секунд)",
+          "context_messages": "Количество контекстных сообщений для сохранения (1-20)",
+          "max_history_size": "Максимальный размер истории разговора (1-100)"
+        }
+      }
+    },
+    "error": {
+      "name_exists": "Инстанция с таким именем уже существует",
+      "invalid_name": "Некорректное имя инстанции",
+      "invalid_auth": "Аутентификация не удалась - проверьте ваш API-ключ",
+      "invalid_api_key": "Неверный API-ключ - проверьте ваши учетные данные",
+      "cannot_connect": "Не удалось подключиться к службе API",
+      "invalid_model": "Выбранная модель недоступна",
+      "rate_limit": "Превышен лимит запросов",
+      "context_length": "Превышена длина контекста",
+      "rate_limit_exceeded": "Превышен лимит запросов API",
+      "maintenance": "Сервис находится на техническом обслуживании",
+      "invalid_response": "Получен неверный ответ API",
+      "api_error": "Произошла ошибка службы API",
+      "timeout": "Запрос превысил время ожидания",
+      "invalid_instance": "Указана неверная инстанция",
+      "unknown": "Произошла непредвиденная ошибка",
+      "empty": "Имя не может быть пустым",
+      "invalid_characters": "Имя может содержать только буквы, цифры, пробелы, подчеркивания и дефисы",
+      "name_too_long": "Имя должно быть не более 50 символов"
+    }
+  },
+  "options": {
+    "step": {
+      "init": {
+        "title": "Обновление настроек инстанции",
+        "description": "Измените настройки для этой инстанции помощника ИИ.",
+        "data": {
+          "model": "Модель ИИ",
+          "temperature": "Креативность ответа (0-2)",
+          "max_tokens": "Максимальная длина ответа (1-4096)",
+          "request_interval": "Минимальный интервал между запросами (0,1-60 секунд)",
+          "context_messages": "Количество предыдущих сообщений для включения в контекст (1-20)",
+          "max_history_size": "Максимальный размер истории разговора (1-100)"
+        }
+      }
+    }
+  },
+  "services": {
+    "ask_question": {
+      "name": "Задать вопрос (HA Text AI)",
+      "description": "Отправьте вопрос модели ИИ и получите подробный ответ. Ответ будет сохранен в истории разговора и может быть извлечен позже.",
+      "fields": {
+        "instance": {
+          "name": "Инстанция",
+          "description": "Имя используемой инстанции HA Text AI"
+        },
+        "question": {
+          "name": "Вопрос",
+          "description": "Ваш вопрос или запрос к помощнику ИИ"
+        },
+        "context_messages": {
+          "name": "Контекстные сообщения",
+          "description": "Количество предыдущих сообщений для включения в контекст (1-20)"
+        },
+        "system_prompt": {
+          "name": "Системный запрос",
+          "description": "Необязательный системный запрос для установки контекста для этого конкретного вопроса"
+        },
+        "model": {
+          "name": "Модель",
+          "description": "Выберите модель ИИ для использования (необязательно, переопределяет настройку по умолчанию)"
+        },
+        "temperature": {
+          "name": "Температура",
+          "description": "Управляет креативностью ответа (0.0-2.0)"
+        },
+        "max_tokens": {
+          "name": "Макс. токенов",
+          "description": "Максимальная длина ответа (1-4096 токенов)"
+        }
+      }
+    },
+    "clear_history": {
+      "name": "Очистить историю",
+      "description": "Удалить все сохраненные вопросы и ответы из истории разговора",
+      "fields": {
+        "instance": {
+          "name": "Инстанция",
+          "description": "Имя инстанции HA Text AI, для которой нужно очистить историю"
+        }
+      }
+    },
+    "get_history": {
+      "name": "Получить историю",
+      "description": "Извлечь историю разговора с возможностью фильтрации и сортировки",
+      "fields": {
+        "instance": {
+          "name": "Инстанция",
+          "description": "Имя инстанции HA Text AI, из которой нужно получить историю"
+        },
+        "limit": {
+          "name": "Лимит",
+          "description": "Количество разговоров для возврата (1-100)"
+        },
+        "filter_model": {
+          "name": "Фильтр модели",
+          "description": "Фильтрация разговоров по определенной модели ИИ"
+        },
+        "start_date": {
+          "name": "Дата начала",
+          "description": "Фильтрация разговоров, начиная с этой даты/времени"
+        },
+        "include_metadata": {
+          "name": "Включить метаданные",
+          "description": "Включить дополнительную информацию, такую как использованные токены, время ответа и т.д."
+        },
+        "sort_order": {
+          "name": "Порядок сортировки",
+          "description": "Порядок сортировки результатов (самые новые или самые старые)"
+        }
+      }
+    },
+    "set_system_prompt": {
+      "name": "Установить системный запрос",
+      "description": "Установить инструкции по умолчанию для поведения системы для всех будущих разговоров",
+      "fields": {
+        "instance": {
+          "name": "Инстанция",
+          "description": "Имя инстанции HA Text AI, для которой нужно установить системный запрос"
+        },
+        "prompt": {
+          "name": "Системный запрос",
+          "description": "Инструкции, определяющие, как ИИ должен себя вести и отвечать"
+        }
+      }
+    }
+  },
+  "entity": {
+    "sensor": {
+      "ha_text_ai": {
+        "name": "{name}",
+        "state": {
+          "ready": "Готов",
+          "processing": "Обработка",
+          "error": "Ошибка",
+          "disconnected": "Отключен",
+          "rate_limited": "Лимит запросов",
+          "maintenance": "Техническое обслуживание",
+          "initializing": "Инициализация",
+          "retrying": "Повторная попытка",
+          "queued": "В очереди"
+        },
+        "state_attributes": {
+          "question": {
+            "name": "Последний вопрос"
+          },
+          "response": {
+            "name": "Последний ответ"
+          },
+          "model": {
+            "name": "Текущая модель"
+          },
+          "temperature": {
+            "name": "Температура"
+          },
+          "max_tokens": {
+            "name": "Макс. токенов"
+          },
+          "system_prompt": {
+            "name": "Системный запрос"
+          },
+          "response_time": {
+            "name": "Время последнего ответа"
+          },
+          "total_responses": {
+            "name": "Всего ответов"
+          },
+          "error_count": {
+            "name": "Количество ошибок"
+          },
+          "last_error": {
+            "name": "Последняя ошибка"
+          },
+          "api_status": {
+            "name": "Статус API"
+          },
+          "tokens_used": {
+            "name": "Использовано токенов всего"
+          },
+          "average_response_time": {
+            "name": "Среднее время ответа"
+          },
+          "last_request_time": {
+            "name": "Время последнего запроса"
+          },
+          "is_processing": {
+            "name": "Статус обработки"
+          },
+          "is_rate_limited": {
+            "name": "Статус ограничения запросов"
+          },
+          "is_maintenance": {
+            "name": "Статус технического обслуживания"
+          },
+          "api_version": {
+            "name": "Версия API"
+          },
+          "endpoint_status": {
+            "name": "Статус конечной точки"
+          },
+          "performance_metrics": {
+            "name": "Метрики производительности"
+          },
+          "history_size": {
+            "name": "Размер истории"
+          },
+          "uptime": {
+            "name": "Время работы"
+          },
+          "total_tokens": {
+            "name": "Всего токенов"
+          },
+          "prompt_tokens": {
+            "name": "Токены запроса"
+          },
+          "completion_tokens": {
+            "name": "Токены завершения"
+          },
+          "successful_requests": {
+            "name": "Успешных запросов"
+          },
+          "failed_requests": {
+            "name": "Неудачных запросов"
+          },
+          "average_latency": {
+            "name": "Средняя задержка"
+          },
+          "max_latency": {
+            "name": "Максимальная задержка"
+          },
+          "min_latency": {
+            "name": "Минимальная задержка"
+          }
+        }
+      }
+    }
+  }
+}

hacs.json

@@ -1,9 +1,5 @@
 {
   "name": "HA text AI",
   "render_readme": true,
-  "domains": ["sensor"],
-  "homeassistant": "2024.11.0",
-  "icon": "mdi:brain",
-  "version": "2.0.0",
-  "documentation": "https://github.com/smkrv/ha-text-ai"
+  "homeassistant": "2024.11.0"
 }

requirements.txt

@@ -1,3 +0,0 @@
-pytest
-pytest-asyncio
-homeassistant

structure.md

@@ -2,16 +2,24 @@
 ha-text-ai/
 │
 ├── custom_components/
-│   └── ha_text_ai/
-│       ├── __init__.py
-│       ├── config_flow.py
-│       ├── coordinator.py
-│       ├── manifest.json
-│       ├── sensor.py
-│       ├── services.yaml
-│       └── const.py
-│
-└── strings/
-    ├── en.json
-    └── ru.json
+    ├── ha_text_ai/
+    │   ├── __init__.py
+    │   ├── config_flow.py
+    │   ├── coordinator.py
+    │   ├── manifest.json
+    │   ├── sensor.py
+    │   ├── services.yaml
+    │   ├── const.py
+    │   └── api_client.py
+    │
+    ├── translations/
+    │   ├── en.json
+    │   ├── de.json
+    │   └── ru.json
+    │
+    └── icons/
+        ├── icon.png
+        ├── icon@2x.png
+        ├── logo.png
+        └── logo@2x.png
 ```