Release v2.0.0-alpha

Validate HACS
2026-07-22 15:14:01 +08:00 · 2024-11-26 14:02:37 +03:00 · 2024-11-26 13:16:10 +03:00 · 2024-11-26 02:08:55 +03:00 · 2024-11-26 02:04:23 +03:00 · 2024-11-26 01:20:08 +03:00
25 changed files with 2476 additions and 898 deletions
@@ -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"
@@ -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
@@ -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!** 🎉
@@ -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.
+ 
@@ -1,73 +1,132 @@
 # 🤖 HA Text AI for Home Assistant

-<div align="center">
+<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-Default-orange.svg?style=flat-square)](https://github.com/hacs/integration)
-[![Community Forum](https://img.shields.io/badge/Community-Forum-blue.svg?style=flat-square)](https://community.home-assistant.io/t/ha-text-ai-integration)
+![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)

+  <img src="https://github.com/smkrv/ha-text-ai/blob/3e3ec45b195c92989434fde40ae110027f4ea124/misc/icons/icon.png" alt="HA Text AI" width="140"/>
+
+### Advanced AI Integration for Home Assistant with multi-provider support
 </div>

 <p align="center">
-Transform your smart home experience with powerful AI assistance powered by OpenAI's GPT models. Get intelligent responses, automate complex scenarios, and enhance your home automation with natural language processing.
+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

- 🧠 **Advanced AI Integration**:
-  - Support for latest GPT models
+- 🧠 **Multi-Provider AI Integration**:
+  - Support for OpenAI GPT models
+  - Anthropic Claude integration
+  - Custom API endpoints
+  - Flexible model selection
+
+- 💬 **Advanced Language Processing**:
  - Context-aware responses
  - Multi-turn conversations
- 💬 **Natural Language Control**:
-  - Control devices using everyday language
-  - Get detailed explanations and recommendations
+  - Custom system instructions
  - Natural conversation flow
- 📝 **Smart Memory Management**:
+
+- 📝 **Enhanced Memory Management**:
  - Persistent conversation history
  - Context-aware responses
  - Customizable history limits
- ⚡ **Performance Optimized**:
+  - Model-specific filtering
+
+- ⚡ **Performance Optimization**:
  - Efficient token usage
-  - Rate limit handling
+  - Smart rate limiting
  - Response caching
+  - Request interval control
+
 - 🎯 **Advanced Customization**:
-  - Adjustable response parameters
+  - Per-request model selection
+  - Adjustable parameters
  - Custom system prompts
-  - Model selection per request
+  - Temperature control
+
 - 🔒 **Enhanced Security**:
  - Secure API key storage
  - Rate limiting protection
  - Error handling
- 🎨 **User Experience**:
+  - 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
  - Template compatibility
+  - Model-specific automation

 ## 📋 Prerequisites

- Home Assistant 2023.8.0 or newer
- OpenAI API key ([Get one here](https://platform.openai.com/account/api-keys))
+- Home Assistant 2023.11 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)
+<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 the "+" button
-3. Search for "HA Text AI"
-4. Click "Install"
-5. Restart 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
@@ -86,12 +145,16 @@ Transform your smart home experience with powerful AI assistance powered by Open
 ### Via YAML
 ```yaml
 ha_text_ai:
-  api_key: !secret openai_api_key
-  model: gpt-3.5-turbo
+  api_provider: openai  # or anthropic
+  api_key: !secret ai_api_key
+  model: gpt-4o-mini
  temperature: 0.7
  max_tokens: 1000
  request_interval: 1.0
-  api_endpoint: https://api.openai.com/v1  # optional
+  api_endpoint: https://api.openai.com/v1  # optional, for custom endpoints
+  system_prompt: |
+    You are a home automation expert assistant.
+    Focus on practical and efficient solutions.
 ```

 ## 🛠️ Available Services
@@ -101,9 +164,11 @@ ha_text_ai:
 service: ha_text_ai.ask_question
 data:
  question: "What's the optimal temperature for sleeping?"
-  model: "gpt-4o"  # optional
+  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
 ```

 ### set_system_prompt
@@ -128,115 +193,135 @@ service: ha_text_ai.clear_history
 service: ha_text_ai.get_history
 data:
  limit: 5  # optional
+  filter_model: "gpt-4o"  # optional
 ```

-## 🔧 Advanced Examples
+### 🏷️ HA Text AI Sensor Naming Convention

-### Smart Energy Management
+#### 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 Energy Optimization"
-  trigger:
-    platform: time_pattern
-    hours: "/2"
-  action:
-    - service: ha_text_ai.ask_question
-      data:
-        question: >
-          Current power usage: {{ states('sensor.total_power') }}W
-          Temperature: {{ states('sensor.indoor_temperature') }}°C
-          Time: {{ now().strftime('%H:%M') }}
-          Occupancy: {{ states('binary_sensor.occupancy') }}
-
-          Analyze current energy usage and suggest optimizations
-          considering comfort and efficiency.
-        temperature: 0.3
-        max_tokens: 200
-    - service: notify.mobile_app
-      data:
-        message: "{{ states.sensor.ha_text_ai.attributes.response }}"
+  - 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') }}
 ```

-### Contextual Lighting Control
+### 💡 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
-automation:
-  alias: "AI Lighting Assistant"
-  trigger:
-    platform: state
-    entity_id: binary_sensor.motion
-  variables:
-    context: >
-      Time: {{ now().strftime('%H:%M') }}
-      Light Level: {{ states('sensor.illuminance') }}
-      Room: {{ trigger.to_state.attributes.room }}
-      Activity: {{ states('input_select.current_activity') }}
-      Weather: {{ states('weather.home') }}
-  action:
-    - service: ha_text_ai.ask_question
-      data:
-        question: >
-          Based on this context:
-          {{ context }}
-
-          Suggest optimal lighting settings for current conditions.
-        model: gpt-3.5-turbo
-        temperature: 0.4
-    - service: scene.turn_on
-      data:
-        entity_id: >
-          {{ states.sensor.ha_text_ai.attributes.response | regex_findall('scene\.[a-z_]+') | first }}
+# Model details
+{{ state_attr('sensor.ha_text_ai_gpt', 'Model') }}           # gpt-4o
+{{ state_attr('sensor.ha_text_ai_gpt', 'Api provider') }}    # openai
+{{ state_attr('sensor.ha_text_ai_gpt', 'Last model') }}      # gpt-4o
 ```

-## 📊 Performance Optimization
+#### System Status
+```yaml
+# Operational status
+{{ state_attr('sensor.ha_text_ai_gpt', 'Api status') }}      # ready
+{{ state_attr('sensor.ha_text_ai_gpt', 'Is processing') }}   # false
+{{ state_attr('sensor.ha_text_ai_gpt', 'Is rate limited') }} # false
+{{ state_attr('sensor.ha_text_ai_gpt', 'Endpoint status') }} # ready
+```

-### Token Usage
- Use focused system prompts
- Implement response caching
- Clear history periodically
- Monitor token usage
+#### Performance Metrics
+```yaml
+# Request and performance statistics
+{{ state_attr('sensor.ha_text_ai_gpt', 'Successful requests') }}   # 0
+{{ state_attr('sensor.ha_text_ai_gpt', 'Failed requests') }}       # 0
+{{ state_attr('sensor.ha_text_ai_gpt', 'Average latency') }}       # 0
+{{ state_attr('sensor.ha_text_ai_gpt', 'Max latency') }}           # 0
+```

-### Response Time
- Adjust request_interval
- Use faster models for simple queries
- Implement timeout handling
- Cache frequent responses
+#### Conversation and Token Usage
+```yaml
+# Conversation and token details
+{{ state_attr('sensor.ha_text_ai_gpt', 'History size') }}          # 0
+{{ state_attr('sensor.ha_text_ai_gpt', 'Total tokens') }}          # 0
+{{ state_attr('sensor.ha_text_ai_gpt', 'Prompt tokens') }}         # 0
+{{ state_attr('sensor.ha_text_ai_gpt', 'Completion tokens') }}     # 0
+```

-### Memory Management
- Set appropriate history limits
- Clear unused contexts
- Monitor memory usage
- Use efficient data structures
+#### Last Interaction Details
+```yaml
+# Last interaction information
+{{ state_attr('sensor.ha_text_ai_gpt', 'Response') }}        # Last AI response
+{{ state_attr('sensor.ha_text_ai_gpt', 'Question') }}        # Last asked question
+{{ state_attr('sensor.ha_text_ai_gpt', 'Last timestamp') }}  # Timestamp
+```

-## ❗ Troubleshooting
+#### System Health
+```yaml
+# System health and maintenance
+{{ state_attr('sensor.ha_text_ai_gpt', 'Total errors') }}    # 0
+{{ state_attr('sensor.ha_text_ai_gpt', 'Is maintenance') }}  # false
+{{ state_attr('sensor.ha_text_ai_gpt', 'Uptime') }}          # 547,58
+```

-### API Issues
- Verify API key validity
- Check rate limits
- Monitor usage quotas
- Test endpoint accessibility
+### 💡 Pro Tips
+- Always check attribute existence
+- Use these attributes for monitoring and automation
+- Some values might be 0 or empty initially

-### Performance Issues
- Reduce max_tokens
- Increase request_interval
- Clear conversation history
- Check network connectivity
-
-### Integration Issues
- Verify HA version compatibility
- Check component dependencies
- Review log files
- Update configuration

 ## 📘 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: 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, API keys are stored securely and data is transmitted via encrypted connections.
+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.

-**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

@@ -252,11 +337,27 @@ 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)

@@ -1,14 +1,24 @@
 """The HA Text AI integration."""
+from __future__ import annotations
+
 import logging
-from typing import Any
+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
-from homeassistant.core import HomeAssistant
-from homeassistant.exceptions import ConfigEntryNotReady
-from homeassistant.helpers import aiohttp_client
+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,
@@ -17,88 +27,269 @@ 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,
+    DEFAULT_CONTEXT_MESSAGES,
+    API_TIMEOUT,
+    SERVICE_ASK_QUESTION,
+    SERVICE_CLEAR_HISTORY,
+    SERVICE_GET_HISTORY,
+    SERVICE_SET_SYSTEM_PROMPT,
 )

 _LOGGER = logging.getLogger(__name__)

 CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)

-async def async_setup(hass: HomeAssistant, config: dict[str, Any]) -> bool:
+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"): 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,
+})
+
+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 provider == API_PROVIDER_ANTHROPIC:
+            check_url = f"{endpoint}/v1/models"
+        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 in [200, 404]:
+                    return True
+                elif response.status == 401:
+                    raise ConfigEntryNotReady("Invalid API key")
+                elif response.status == 429:
+                    _LOGGER.warning("Rate limit exceeded during API check")
+                    return False
+                else:
+                    _LOGGER.error("API check failed with status: %d", response.status)
+                    return False
+    except Exception as ex:
+        _LOGGER.error("API check error: %s", str(ex))
+        return False
+
 async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
    """Set up HA Text AI from a config entry."""
    try:
-        session = aiohttp_client.async_get_clientsession(hass)
+        if CONF_API_PROVIDER not in entry.data:
+            _LOGGER.error("API provider not specified")
+            raise ConfigEntryNotReady("API provider is required")

-        coordinator = HATextAICoordinator(
-            hass,
-            api_key=entry.data[CONF_API_KEY],
-            endpoint=entry.data.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT),
-            model=entry.data.get(CONF_MODEL, DEFAULT_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),
+        session = aiohttp_client.async_get_clientsession(hass)
+        api_provider = entry.data.get(CONF_API_PROVIDER)
+        model = entry.data.get(CONF_MODEL, DEFAULT_MODEL)
+        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]
+        instance_name = entry.data.get(CONF_NAME, entry.entry_id)
+        is_anthropic = api_provider == API_PROVIDER_ANTHROPIC
+
+        headers = {
+            "Content-Type": "application/json",
+            "Accept": "application/json"
+        }
+
+        if is_anthropic:
+            headers["x-api-key"] = api_key
+            headers["anthropic-version"] = "2023-06-01"
+        else:
+            headers["Authorization"] = f"Bearer {api_key}"
+
+        if not await async_check_api(session, endpoint, headers, api_provider):
+            raise ConfigEntryNotReady("API connection failed")
+
+        _LOGGER.debug("Creating API client for %s with endpoint %s", api_provider, endpoint)
+
+        api_client = APIClient(
            session=session,
+            endpoint=endpoint,
+            headers=headers,
+            api_provider=api_provider,
+            model=model,
        )

-        try:
-            await coordinator.async_config_entry_first_refresh()
-        except Exception as refresh_ex:
-            _LOGGER.error("Failed to refresh coordinator: %s", str(refresh_ex))
-            return False
+        coordinator = HATextAICoordinator(
+            hass=hass,
+            client=api_client,
+            model=model,
+            update_interval=entry.data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL),
+            instance_name=instance_name,
+            max_tokens=entry.data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
+            temperature=entry.data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
+            is_anthropic=is_anthropic,
+            context_messages=entry.data.get(
+                CONF_CONTEXT_MESSAGES,
+                DEFAULT_CONTEXT_MESSAGES
+            ),
+        )

-        if not coordinator.last_update_success:
-            _LOGGER.error("Failed to communicate with OpenAI API")
-            return False
+        coordinator.data = coordinator._initial_state.copy()
+        _LOGGER.debug(f"Initial state set for coordinator {instance_name}")

+        await coordinator.async_config_entry_first_refresh()
+
+        hass.data.setdefault(DOMAIN, {})
        hass.data[DOMAIN][entry.entry_id] = coordinator

-        try:
-            await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)
-        except Exception as setup_ex:
-            _LOGGER.error("Failed to setup platforms: %s", str(setup_ex))
-            return False
+        await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)

        _LOGGER.info(
-            "Successfully set up HA Text AI with model: %s",
-            entry.data.get(CONF_MODEL, DEFAULT_MODEL)
+            "Successfully set up %s instance '%s' with model %s",
+            api_provider,
+            instance_name,
+            model
        )

        return True

    except Exception as ex:
-        _LOGGER.exception("Unexpected error setting up entry: %s", str(ex))
-        return False
+        _LOGGER.exception("Setup error: %s", str(ex))
+        raise ConfigEntryNotReady(f"Setup error: {str(ex)}") from ex

 async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
    """Unload a config entry."""
    try:
-        if entry.entry_id not in hass.data.get(DOMAIN, {}):
-            return True
+        if entry.entry_id in hass.data[DOMAIN]:
+            coordinator = hass.data[DOMAIN][entry.entry_id]
+
+            if hasattr(coordinator.client, 'shutdown'):
+                await coordinator.client.shutdown()

-        unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
-        if unload_ok:
-            coordinator = hass.data[DOMAIN].pop(entry.entry_id)
            await coordinator.async_shutdown()
+            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_reload_entry(hass: HomeAssistant, entry: ConfigEntry) -> None:
-    """Reload config entry."""
-    try:
-        await async_unload_entry(hass, entry)
-        await async_setup_entry(hass, entry)
-    except Exception as ex:
-        _LOGGER.exception("Error reloading entry: %s", str(ex))
@@ -0,0 +1,180 @@
+"""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."""
+        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:
+                        if response.status != 200:
+                            error_data = await response.json()
+                            raise HomeAssistantError(f"API error: {error_data}")
+                        return await response.json()
+            except asyncio.TimeoutError:
+                if attempt == API_RETRY_COUNT - 1:
+                    raise HomeAssistantError("API request timed out")
+                await asyncio.sleep(1 * (attempt + 1))
+            except Exception as e:
+                if attempt == API_RETRY_COUNT - 1:
+                    raise
+                _LOGGER.warning("API request failed, retrying: %s", str(e))
+                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"
+
+        # Convert messages to Anthropic format
+        system_prompt = next(
+            (msg["content"] for msg in messages if msg["role"] == "system"),
+            None
+        )
+        conversation = [msg for msg in messages if msg["role"] != "system"]
+
+        payload = {
+            "model": model,
+            "messages": conversation,
+            "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"]
+            }
+        }
@@ -1,19 +1,14 @@
 """Config flow for HA text AI integration."""
-from typing import Any, Dict, Optional, Tuple
-import voluptuous as vol
-import ssl
-import certifi
-import asyncio
-from async_timeout import timeout
-import aiohttp
-from urllib.parse import urlparse
+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 openai import AsyncOpenAI
-from openai import OpenAIError, APIError, APIConnectionError, AuthenticationError, RateLimitError
+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,
@@ -22,261 +17,231 @@ 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,
 )

-import logging
 _LOGGER = logging.getLogger(__name__)

-# Create SSL context at module level
-SSL_CONTEXT = ssl.create_default_context(cafile=certifi.where())
-
-STEP_USER_DATA_SCHEMA = vol.Schema({
-    vol.Required(CONF_API_KEY): str,
-    vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): str,
-    vol.Optional(
-        CONF_TEMPERATURE,
-        default=DEFAULT_TEMPERATURE
-    ): vol.All(
-        vol.Coerce(float),
-        vol.Range(min=0, max=2)
-    ),
-    vol.Optional(
-        CONF_MAX_TOKENS,
-        default=DEFAULT_MAX_TOKENS
-    ): vol.All(
-        vol.Coerce(int),
-        vol.Range(min=1, max=4096)
-    ),
-    vol.Optional(CONF_API_ENDPOINT, default=DEFAULT_API_ENDPOINT): str,
-    vol.Optional(
-        CONF_REQUEST_INTERVAL,
-        default=DEFAULT_REQUEST_INTERVAL
-    ): vol.All(
-        vol.Coerce(float),
-        vol.Range(min=0.1)
-    ),
-})
-
-async def validate_endpoint(endpoint: str) -> Tuple[bool, str]:
-    """Validate API endpoint accessibility."""
-    try:
-        parsed_url = urlparse(endpoint)
-        if parsed_url.scheme not in ('http', 'https'):
-            return False, "invalid_endpoint_scheme"
-
-        connector = aiohttp.TCPConnector(ssl=SSL_CONTEXT)
-        async with timeout(5):
-            async with aiohttp.ClientSession(connector=connector) as session:
-                async with session.get(endpoint) as response:
-                    if response.status != 200:
-                        return False, "endpoint_not_available"
-        return True, ""
-    except Exception as e:
-        _LOGGER.error("Error validating endpoint: %s", str(e))
-        return False, "endpoint_error"
-
-async def validate_api_connection(
-    api_key: str,
-    endpoint: str,
-    model: str,
-    retry_count: int = 3,
-    retry_delay: float = 1.0
-) -> Tuple[bool, str, list]:
-    """Validate API connection with improved retry logic."""
-    # Validate endpoint first
-    endpoint_valid, endpoint_error = await validate_endpoint(endpoint)
-    if not endpoint_valid:
-        return False, endpoint_error, []
-
-    connector = aiohttp.TCPConnector(ssl=SSL_CONTEXT)
-    async with aiohttp.ClientSession(connector=connector) as session:
-        for attempt in range(retry_count):
-            try:
-                async with timeout(10):
-                    client = AsyncOpenAI(
-                        api_key=api_key,
-                        base_url=endpoint,
-                        http_client=session
-                    )
-
-                    models = await client.models.list()
-                    model_ids = [model.id for model in models.data]
-
-                    if model not in model_ids:
-                        _LOGGER.warning(
-                            "Model %s not found in available models: %s",
-                            model,
-                            ", ".join(model_ids)
-                        )
-                        return False, "invalid_model", model_ids
-                    return True, "", model_ids
-
-            except asyncio.TimeoutError:
-                _LOGGER.warning(
-                    "Timeout during API validation (attempt %d/%d)",
-                    attempt + 1,
-                    retry_count
-                )
-                if attempt == retry_count - 1:
-                    return False, "timeout", []
-                await asyncio.sleep(retry_delay)
-
-            except AuthenticationError as err:
-                _LOGGER.error("Authentication error: %s", str(err))
-                return False, "invalid_auth", []
-
-            except RateLimitError as err:
-                _LOGGER.error("Rate limit exceeded: %s", str(err))
-                return False, "rate_limit", []
-
-            except APIConnectionError as err:
-                _LOGGER.error("API connection error: %s", str(err))
-                return False, "cannot_connect", []
-
-            except APIError as err:
-                _LOGGER.error("API error: %s", str(err))
-                return False, "api_error", []
-
-            except Exception as err:
-                _LOGGER.exception("Unexpected error during validation: %s", str(err))
-                return False, "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
-    ) -> Dict[str, Any]:
+    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:
-                # Validate URL format
-                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
-                    )
+                    ),
+                })
+            )

-                # Validate input data
-                user_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(
-                    user_input[CONF_API_KEY],
-                    endpoint,
-                    user_input[CONF_MODEL]
-                )
+    async def async_step_provider(self, user_input: Optional[Dict[str, Any]] = None) -> FlowResult:
+        """Handle provider configuration step."""
+        if user_input is None:
+            default_endpoint = (
+                DEFAULT_OPENAI_ENDPOINT if self._provider == API_PROVIDER_OPENAI
+                else DEFAULT_ANTHROPIC_ENDPOINT
+            )

-                if is_valid:
-                    await self.async_set_unique_id(user_input[CONF_API_KEY])
-                    self._abort_if_unique_id_configured()
+            suggested_name = f"HA Text AI {len(self._async_current_entries()) + 1}"

-                    return self.async_create_entry(
-                        title="HA text AI",
-                        data=user_input
-                    )
+            return self.async_show_form(
+                step_id="provider",
+                data_schema=vol.Schema({
+                    vol.Required(CONF_NAME, default=suggested_name): 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)
+                    ),
+                }),
+                errors=self._errors
+            )

-                errors["base"] = error_code
-                if error_code == "invalid_model":
-                    _LOGGER.warning(
-                        "Selected model %s not found in available models: %s",
-                        user_input[CONF_MODEL],
-                        ", ".join(available_models)
-                    )
+        instance_name = user_input[CONF_NAME]
+        await self._async_validate_name(instance_name)
+        if self._errors:
+            return await self.async_step_provider()

-            except vol.Invalid as err:
-                _LOGGER.error("Validation error: %s", str(err))
-                errors["base"] = "invalid_input"
+        if not await self._async_validate_api(user_input):
+            return await self.async_step_provider()

-        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,
+        return await self._create_entry(user_input)
+
+    async def _async_validate_name(self, name: str) -> bool:
+        """Validate that the name is unique."""
+        for entry in self._async_current_entries():
+            if entry.data.get(CONF_NAME) == name:
+                self._errors["name"] = "name_exists"
+                return False
+        return True
+
+    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."""
+        instance_name = user_input[CONF_NAME]
+        unique_id = f"{DOMAIN}_{instance_name}_{self._provider}".lower().replace(" ", "_")
+
+        return self.async_create_entry(
+            title=instance_name,
+            data={
+                CONF_API_PROVIDER: self._provider,
+                CONF_NAME: instance_name,
+                **user_input,
+                "unique_id": unique_id,
+                CONF_CONTEXT_MESSAGES: user_input.get(
+                CONF_CONTEXT_MESSAGES,
+                DEFAULT_CONTEXT_MESSAGES)
+        }
        )

    @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
-    ) -> Dict[str, Any]:
-        """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
-                ),
-                description={"suggested_value": DEFAULT_TEMPERATURE},
-            ): vol.All(
-                vol.Coerce(float),
-                vol.Range(min=0, max=2)
-            ),
-            vol.Optional(
-                CONF_MAX_TOKENS,
-                default=self.config_entry.options.get(
-                    CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS
-                ),
-                description={"suggested_value": DEFAULT_MAX_TOKENS},
-            ): vol.All(
-                vol.Coerce(int),
-                vol.Range(min=1, max=4096)
-            ),
-            vol.Optional(
-                CONF_REQUEST_INTERVAL,
-                default=self.config_entry.options.get(
-                    CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL
-                ),
-                description={"suggested_value": DEFAULT_REQUEST_INTERVAL},
-            ): vol.All(
-                vol.Coerce(float),
-                vol.Range(min=0.1)
-            ),
-        })
+        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)
+                ),
+            })
        )
@@ -1,27 +1,47 @@
 """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]

+# 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"
 CONF_TEMPERATURE: Final = "temperature"
 CONF_MAX_TOKENS: Final = "max_tokens"
 CONF_API_ENDPOINT: Final = "api_endpoint"
 CONF_REQUEST_INTERVAL: Final = "request_interval"
+CONF_INSTANCE: Final = "instance"
+CONF_MAX_HISTORY_SIZE: Final = "max_history_size"
+CONF_IS_ANTHROPIC: Final = "is_anthropic"
+CONF_CONTEXT_MESSAGES: Final = "context_messages"

 # Default values
-DEFAULT_MODEL: Final = "gpt-3.5-turbo"
-DEFAULT_TEMPERATURE: Final = 0.7
+DEFAULT_MODEL: Final = "gpt-4o-mini"
+DEFAULT_TEMPERATURE: Final = 0.1
 DEFAULT_MAX_TOKENS: Final = 1000
-DEFAULT_API_ENDPOINT: Final = "https://api.openai.com/v1"
 DEFAULT_REQUEST_INTERVAL: Final = 1.0
 DEFAULT_TIMEOUT: Final = 30
-DEFAULT_QUEUE_SIZE: Final = 100
-DEFAULT_HISTORY_LIMIT: Final = 50
+DEFAULT_MAX_HISTORY: Final = 50
+DEFAULT_NAME: Final = "HA Text AI"
+DEFAULT_CONTEXT_MESSAGES: Final = 5

 # Parameter constraints
 MIN_TEMPERATURE: Final = 0.0
@@ -29,8 +49,11 @@ 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_REQUEST_INTERVAL: Final = 60.0
+
+# API constants
+API_TIMEOUT: Final = 30
+API_RETRY_COUNT: Final = 3

 # Service names
 SERVICE_ASK_QUESTION: Final = "ask_question"
@@ -38,26 +61,48 @@ 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_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"
@@ -68,74 +113,89 @@ 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"
-
-# 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"
+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"

-# 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"
-
-# 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
-
-# API constants
-API_TIMEOUT: Final = 30
-API_RETRY_COUNT: Final = 3
-API_BACKOFF_FACTOR: Final = 1.5
-
-# 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_MAINTENANCE: Final = "maintenance"
+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(
+            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)
@@ -1,194 +1,377 @@
-"""Data coordinator for HA text AI."""
-import asyncio
+"""The HA Text AI coordinator."""
+from __future__ import annotations
+
 import logging
-from datetime import timedelta
-from typing import Any, Dict, Optional
+from datetime import datetime, timedelta
+from typing import Any, Dict, List, Optional

-from openai import AsyncOpenAI, APIError, AuthenticationError, RateLimitError
 from homeassistant.core import HomeAssistant
 from homeassistant.helpers.update_coordinator import DataUpdateCoordinator
-import async_timeout
+from homeassistant.util import dt as dt_util
+from homeassistant.exceptions import HomeAssistantError

-from .const import DOMAIN
+from .const import (
+    DOMAIN,
+    STATE_READY,
+    STATE_PROCESSING,
+    STATE_ERROR,
+    STATE_RATE_LIMITED,
+    STATE_MAINTENANCE,
+    DEFAULT_MAX_TOKENS,
+    DEFAULT_TEMPERATURE,
+    DEFAULT_MAX_HISTORY,
+    DEFAULT_CONTEXT_MESSAGES,
+)

 _LOGGER = logging.getLogger(__name__)

 class HATextAICoordinator(DataUpdateCoordinator):
-    """Class to manage fetching data from the API."""
-
    def __init__(
        self,
        hass: HomeAssistant,
-        api_key: str,
-        endpoint: str,
+        client: Any,
        model: str,
-        temperature: float,
-        max_tokens: int,
-        request_interval: float,
-        session: Optional[Any] = None,
+        update_interval: int,
+        instance_name: str,
+        max_tokens: int = DEFAULT_MAX_TOKENS,
+        temperature: float = DEFAULT_TEMPERATURE,
+        max_history_size: int = DEFAULT_MAX_HISTORY,
+        context_messages: int = DEFAULT_CONTEXT_MESSAGES,
+        is_anthropic: bool = False,
    ) -> None:
-        """Initialize."""
+        """Initialize coordinator."""
+        self.instance_name = instance_name
+        self.hass = hass
+        self.client = client
+        self.model = model
+        self.temperature = temperature
+        self.max_tokens = max_tokens
+        self.max_history_size = max_history_size
+        self.is_anthropic = is_anthropic
+
+        # Initialize with default state
+        self._initial_state = {
+            "state": STATE_READY,
+            "metrics": {
+                "total_tokens": 0,
+                "prompt_tokens": 0,
+                "completion_tokens": 0,
+                "successful_requests": 0,
+                "failed_requests": 0,
+                "total_errors": 0,
+                "average_latency": 0,
+                "max_latency": 0,
+                "min_latency": float('inf'),
+            },
+            "last_response": {
+                "timestamp": dt_util.utcnow().isoformat(),
+                "question": "",
+                "response": "",
+                "model": model,
+                "instance": instance_name,
+                "error": None
+            },
+            "is_processing": False,
+            "is_rate_limited": False,
+            "is_maintenance": False,
+            "endpoint_status": "ready",
+            "uptime": 0,
+            "system_prompt": None,
+            "history_size": 0,
+            "conversation_history": [],
+        }
+
+        update_interval_td = timedelta(seconds=update_interval)
+
        super().__init__(
            hass,
            _LOGGER,
-            name=DOMAIN,
-            update_interval=timedelta(seconds=request_interval),
+            name=instance_name,
+            update_interval=update_interval_td,
        )

-        self._validate_params(api_key, temperature, max_tokens)
+        # Register instance
+        self.hass.data.setdefault(DOMAIN, {})
+        self.hass.data[DOMAIN][instance_name] = self
+        self.context_messages = context_messages

-        self.api_key = api_key
-        self.endpoint = endpoint
-        self.model = model
-        self.temperature = float(temperature)
-        self.max_tokens = int(max_tokens)
-        self._question_queue = asyncio.Queue()
-        self._responses: Dict[str, Any] = {}
-        self.system_prompt: Optional[str] = None
-        self._is_ready = False
-        self._error_count = 0
-        self._MAX_ERRORS = 3
+        self._system_prompt = None
+        self._conversation_history = []
+        self._performance_metrics = self._initial_state["metrics"].copy()
+        self._is_processing = False
+        self._is_rate_limited = False
+        self._is_maintenance = False
+        self.endpoint_status = "ready"
+        self.last_response = self._initial_state["last_response"].copy()
+        self._start_time = dt_util.utcnow()

-        self.client = AsyncOpenAI(
-            api_key=self.api_key,
-            base_url=self.endpoint,
-            http_client=session,
-        )
-
-    def _validate_params(self, api_key: str, temperature: float, max_tokens: int) -> None:
-        """Validate initialization parameters."""
-        if not api_key:
-            raise ValueError("API key is required")
-        if not isinstance(temperature, (int, float)) or not 0 <= temperature <= 2:
-            raise ValueError("Temperature must be between 0 and 2")
-        if not isinstance(max_tokens, int) or max_tokens < 1:
-            raise ValueError("Max tokens must be a positive integer")
+        _LOGGER.info(f"Initialized HA Text AI coordinator with instance: {instance_name}")

    async def _async_update_data(self) -> Dict[str, Any]:
-        """Update data via OpenAI API."""
-        if self._question_queue.empty():
-            return self._responses
+        """Update data via library."""
+        try:
+            current_state = self._get_current_state()
+            _LOGGER.debug(f"Updating data for {self.instance_name}, current state: {current_state}")
+
+            data = {
+                "state": current_state,
+                "metrics": self._performance_metrics,
+                "last_response": self.last_response,
+                "is_processing": self._is_processing,
+                "is_rate_limited": self._is_rate_limited,
+                "is_maintenance": self._is_maintenance,
+                "endpoint_status": self.endpoint_status,
+                "uptime": (dt_util.utcnow() - self._start_time).total_seconds(),
+                "system_prompt": self._system_prompt,
+                "history_size": len(self._conversation_history),
+                "conversation_history": self._conversation_history,
+            }
+
+            # Validate data
+            if not isinstance(data, dict):
+                raise ValueError("Invalid data format")
+
+            _LOGGER.debug(f"Updated data for {self.instance_name}: {data}")
+            return data
+
+        except Exception as err:
+            _LOGGER.error(f"Error updating data for {self.instance_name}: {err}")
+            return self._initial_state
+
+    async def async_update_ha_state(self) -> None:
+        """Update Home Assistant state."""
+        try:
+            _LOGGER.debug(f"Requesting state update for {self.instance_name}")
+            await self.async_request_refresh()
+
+            # Force update of all entities
+            for entity_id in self.hass.states.async_entity_ids():
+                if entity_id.startswith(f"sensor.ha_text_ai_{self.instance_name}"):
+                    self.hass.states.async_set(entity_id, self._get_current_state())
+
+        except Exception as err:
+            _LOGGER.error(f"Error updating HA state for {self.instance_name}: {err}")
+
+    def _get_current_state(self) -> str:
+        """Get current state based on internal flags."""
+        if self._is_processing:
+            return STATE_PROCESSING
+        elif self._is_rate_limited:
+            return STATE_RATE_LIMITED
+        elif self._is_maintenance:
+            return STATE_MAINTENANCE
+        elif self.last_response.get("error"):
+            return STATE_ERROR
+        return STATE_READY
+
+    def _calculate_context_tokens(self, messages: List[Dict[str, str]]) -> int:
+        try:
+            if self.is_anthropic and hasattr(self.client, 'count_tokens'):
+                return sum(self.client.count_tokens(msg['content']) for msg in messages)
+
+            return sum(len(msg['content']) // 4 for msg in messages)
+        except Exception as e:
+            _LOGGER.warning(f"Error calculating context tokens: {e}")
+        return 0
+
+    async def async_ask_question(
+        self,
+        question: str,
+        model: Optional[str] = None,
+        temperature: Optional[float] = None,
+        max_tokens: Optional[int] = None,
+        system_prompt: Optional[str] = None,
+        context_messages: Optional[int] = None,
+    ) -> dict:
+        """Process a question with optional parameters."""
+        return await self.async_process_question(
+            question, model, temperature, max_tokens, system_prompt, context_messages
+        )
+
+    async def async_process_question(
+        self,
+        question: str,
+        model: Optional[str] = None,
+        temperature: Optional[float] = None,
+        max_tokens: Optional[int] = None,
+        system_prompt: Optional[str] = None,
+        context_messages: Optional[int] = None,
+    ) -> dict:
+        temp_context_messages = context_messages or self.context_messages
+
+        if not question:
+            raise ValueError("Question cannot be empty")
+
+        _LOGGER.debug(f"Processing question for instance {self.instance_name}")

        try:
-            async with async_timeout.timeout(30):
-                question = await self._question_queue.get()
-                try:
-                    response_content = await self._make_api_call(question)
-                    self._responses[question] = {
-                        "question": question,
-                        "response": response_content,
-                        "error": None,
-                        "timestamp": self.hass.loop.time()
-                    }
-                    self._error_count = 0
-                    self._is_ready = True
-                    _LOGGER.debug("Response received for question: %s", question)
+            self._is_processing = True
+            await self.async_update_ha_state()

-                except Exception as err:
-                    self._handle_api_error(question, err)
-                finally:
-                    self._question_queue.task_done()
+            temp_model = model or self.model
+            temp_temperature = temperature or self.temperature
+            temp_max_tokens = max_tokens or self.max_tokens
+            temp_system_prompt = system_prompt or self._system_prompt

-                return self._responses
+            start_time = dt_util.utcnow()

-        except asyncio.TimeoutError as err:
-            _LOGGER.error("Timeout while processing question")
-            await self._handle_timeout_error()
-            return self._responses
-
-    def _handle_api_error(self, question: str, error: Exception) -> None:
-        """Handle API errors."""
-        self._error_count += 1
-        error_msg = str(error)
-
-        if isinstance(error, AuthenticationError):
-            error_msg = "Authentication failed - invalid API key"
-            self._is_ready = False
-        elif isinstance(error, RateLimitError):
-            error_msg = "Rate limit exceeded"
-        elif isinstance(error, APIError):
-            error_msg = f"API error: {error}"
-
-        self._responses[question] = {
-            "question": question,
-            "response": None,
-            "error": error_msg,
-            "timestamp": self.hass.loop.time()
-        }
-
-        _LOGGER.error("API error (%s): %s", type(error).__name__, error_msg)
-
-        if self._error_count >= self._MAX_ERRORS:
-            _LOGGER.warning(
-                "Multiple errors occurred (%d). Coordinator needs attention.",
-                self._error_count
-            )
-
-    async def _handle_timeout_error(self) -> None:
-        """Handle timeout errors."""
-        self._error_count += 1
-        if not self._question_queue.empty():
-            try:
-                # Clear the queue if we have timeout issues
-                while not self._question_queue.empty():
-                    self._question_queue.get_nowait()
-                    self._question_queue.task_done()
-            except Exception as err:
-                _LOGGER.error("Error clearing question queue: %s", err)
-
-    async def _make_api_call(self, question: str) -> str:
-        """Make API call to OpenAI."""
-        try:
            messages = []
-            if self.system_prompt:
-                messages.append({"role": "system", "content": self.system_prompt})
+            if temp_system_prompt:
+                if self.is_anthropic:
+                    system_content = f"\n\nHuman: {temp_system_prompt}\n\nAssistant: I understand and will follow these instructions."
+                    messages.append({"role": "user", "content": system_content})
+                else:
+                    messages.append({"role": "system", "content": temp_system_prompt})
+
+            # Add conversation history
+            context_history = self._conversation_history[-temp_context_messages:]
+            for entry in context_history:
+                messages.append({"role": "user", "content": entry["question"]})
+                messages.append({"role": "assistant", "content": entry["response"]})
+
            messages.append({"role": "user", "content": question})

-            completion = await self.client.chat.completions.create(
-                model=self.model,
-                messages=messages,
-                temperature=self.temperature,
-                max_tokens=self.max_tokens,
-            )
-            return completion.choices[0].message.content
+            kwargs = {
+                "model": temp_model,
+                "temperature": temp_temperature,
+                "max_tokens": temp_max_tokens,
+                "messages": messages,
+            }
+
+            response = await self.async_process_message(question, **kwargs)
+
+            # Update metrics
+            end_time = dt_util.utcnow()
+            latency = (end_time - start_time).total_seconds()
+            self._update_metrics(latency, response)
+
+            # Update history
+            self._update_history(question, response)
+
+            return response

        except Exception as err:
-            _LOGGER.error("Error in API call: %s", err)
+            self._handle_error(err)
+            raise HomeAssistantError(f"Failed to process question: {err}")
+
+        finally:
+            self._is_processing = False
+            await self.async_update_ha_state()
+
+    async def async_process_message(self, question: str, **kwargs) -> dict:
+        """Process message using the AI client."""
+        try:
+            if self.is_anthropic:
+                response = await self._process_anthropic_message(question, **kwargs)
+            else:
+                response = await self._process_openai_message(question, **kwargs)
+
+            self.last_response = {
+                "timestamp": dt_util.utcnow().isoformat(),
+                "question": question,
+                "response": response["content"],
+                "model": kwargs.get("model", self.model),
+                "instance": self.instance_name,
+                "error": None
+            }
+
+            return response
+
+        except Exception as err:
+            self._handle_error(err)
            raise

-    async def async_ask_question(self, question: str) -> None:
-        """Add question to queue."""
-        if not self._is_ready and self._error_count >= self._MAX_ERRORS:
-            _LOGGER.warning("Coordinator is not ready due to previous errors")
-            return
+    async def _process_anthropic_message(self, question: str, **kwargs) -> dict:
+        """Process message using Anthropic API."""
+        response = await self.client.messages.create(
+            model=kwargs["model"],
+            max_tokens=kwargs["max_tokens"],
+            messages=kwargs["messages"],
+            temperature=kwargs["temperature"],
+        )
+        return {
+            "content": response.content[0].text,
+            "tokens": {
+                "prompt": response.usage.input_tokens,
+                "completion": response.usage.output_tokens,
+                "total": response.usage.input_tokens + response.usage.output_tokens
+            }
+        }

-        await self._question_queue.put(question)
-        await self.async_refresh()
-
-    async def async_shutdown(self) -> None:
-        """Shutdown the coordinator."""
+    async def _process_openai_message(self, question: str, **kwargs) -> dict:
+        """Process message using OpenAI API."""
        try:
-            # Clear the queue
-            while not self._question_queue.empty():
-                self._question_queue.get_nowait()
-                self._question_queue.task_done()
+            response = await self.client.create(
+                model=kwargs["model"],
+                messages=kwargs["messages"],
+                temperature=kwargs["temperature"],
+                max_tokens=kwargs["max_tokens"],
+            )

-            await self.client.close()
-            self._is_ready = False
+            return {
+                "content": response["choices"][0]["message"]["content"],
+                "tokens": {
+                    "prompt": response["usage"]["prompt_tokens"],
+                    "completion": response["usage"]["completion_tokens"],
+                    "total": response["usage"]["total_tokens"]
+                }
+            }
+        except Exception as e:
+            _LOGGER.error(f"Error in OpenAI API call: {str(e)}")
+            raise

-        except Exception as err:
-            _LOGGER.error("Error during shutdown: %s", err)
+    def _update_metrics(self, latency: float, response: dict) -> None:
+        """Update performance metrics."""
+        metrics = self._performance_metrics
+        tokens = response.get("tokens", {})

-    @property
-    def is_ready(self) -> bool:
-        """Return if coordinator is ready."""
-        return self._is_ready
+        metrics["total_tokens"] += tokens.get("total", 0)
+        metrics["prompt_tokens"] += tokens.get("prompt", 0)
+        metrics["completion_tokens"] += tokens.get("completion", 0)
+        metrics["successful_requests"] += 1

-    @property
-    def error_count(self) -> int:
-        """Return current error count."""
-        return self._error_count
+        metrics["average_latency"] = (
+            (metrics["average_latency"] * (metrics["successful_requests"] - 1) + latency)
+            / metrics["successful_requests"]
+        )
+        metrics["max_latency"] = max(metrics["max_latency"], latency)
+        metrics["min_latency"] = min(metrics["min_latency"], latency)

-    def reset_error_count(self) -> None:
-        """Reset error counter."""
-        self._error_count = 0
+    def _update_history(self, question: str, response: dict) -> None:
+        """Update conversation history."""
+        self._conversation_history.append({
+            "timestamp": dt_util.utcnow().isoformat(),
+            "question": question,
+            "response": response["content"]
+        })
+
+        while len(self._conversation_history) > self.max_history_size:
+            self._conversation_history.pop(0)
+
+    def _handle_error(self, error: Exception) -> None:
+        """Handle error and update metrics."""
+        self._performance_metrics["total_errors"] += 1
+        self._performance_metrics["failed_requests"] += 1
+
+        self.last_response = {
+            "timestamp": dt_util.utcnow().isoformat(),
+            "question": "",
+            "response": "",
+            "model": self.model,
+            "instance": self.instance_name,
+            "error": str(error)
+        }
+
+    async def async_clear_history(self) -> None:
+        """Clear conversation history."""
+        self._conversation_history = []
+        await self.async_update_ha_state()
+
+    async def async_get_history(self) -> List[Dict[str, str]]:
+        """Get conversation history."""
+        return self._conversation_history
+
+    async def async_set_system_prompt(self, prompt: str) -> None:
+        """Set system prompt."""
+        self._system_prompt = prompt
+        await self.async_update_ha_state()
@@ -1,14 +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/wiki",
+  "documentation": "https://github.com/smkrv/ha-text-ai",
+  "integration_type": "service",
  "iot_class": "cloud_polling",
  "issue_tracker": "https://github.com/smkrv/ha-text-ai/issues",
-  "requirements": ["openai>=1.0.0"],
+  "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",
+    "certifi>=2024.2.2"
+  ],
+  "single_config_entry": false,
  "ssdp": [],
-  "version": "1.0.8",
+  "usb": [],
+  "version": "2.0.0-alpha",
  "zeroconf": []
 }
@@ -1,45 +1,65 @@
-"""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,
-    ENTITY_ICON,
-    ENTITY_ICON_ERROR,
-    ENTITY_ICON_PROCESSING,
+    ATTR_IS_PROCESSING,
+    ATTR_IS_RATE_LIMITED,
+    ATTR_IS_MAINTENANCE,
+    ATTR_API_VERSION,
+    ATTR_ENDPOINT_STATUS,
+    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,
 )
+
 from .coordinator import HATextAICoordinator

 _LOGGER = logging.getLogger(__name__)
@@ -49,16 +69,19 @@ async def async_setup_entry(
    entry: ConfigEntry,
    async_add_entities: AddEntitiesCallback,
 ) -> None:
-    """Set up the HA text AI sensor."""
+    """Set up the HA Text AI sensor."""
    coordinator = hass.data[DOMAIN][entry.entry_id]
-    async_add_entities([HATextAISensor(coordinator, entry)], True)
+    instance_name = coordinator.instance_name
+
+    _LOGGER.debug(f"Setting up sensor with instance: {instance_name}")
+
+    sensor = HATextAISensor(coordinator, entry)
+    async_add_entities([sensor], True)

 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,
@@ -67,115 +90,205 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
    ) -> None:
        """Initialize the sensor."""
        super().__init__(coordinator)
+
        self._config_entry = config_entry
+        self._instance_name = coordinator.instance_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_{slugify(self._instance_name)}"
        self._attr_unique_id = f"{config_entry.entry_id}"
-        self._attr_name = "Last Response"
-        self._attr_suggested_display_precision = 0
+
+        self.entity_description = SensorEntityDescription(
+            key=f"ha_text_ai_{self._instance_name}",
+            entity_registry_enabled_default=True,
+        )
+
+        self._current_state = STATE_INITIALIZING
        self._error_count = 0
        self._last_error = None
-        self._state = STATE_INITIALIZING
+        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_time:
-            return None
+        self._attr_device_info = DeviceInfo(
+            identifiers={(DOMAIN, self._attr_unique_id)},
+            name=self._attr_name,  # Используем имя сенсора
+            manufacturer="Community",
+            model=f"{model} ({api_provider} provider)",
+            sw_version="1.0.0",
+        )

-        try:
-            if isinstance(self.coordinator.last_update_success_time, datetime):
-                return dt_util.as_local(self.coordinator.last_update_success_time)
-            return self.coordinator.last_update_success_time
-        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,
-        }
-
-        if not self.coordinator.data:
-            return attributes
-
-        try:
-            history = list(self.coordinator.data.items())
-            if history:
-                last_question, last_data = history[-1]
-
-                # Handle different response formats
-                if isinstance(last_data, dict):
-                    last_response = last_data.get("response", "")
-                    last_updated = last_data.get("timestamp", self.coordinator.last_update_success_time)
-                    response_time = last_data.get("response_time")
-                else:
-                    last_response = str(last_data)
-                    last_updated = self.coordinator.last_update_success_time
-                    response_time = None
-
-                # Convert timestamp to local time if needed
-                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),
-                })
-
-                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,
+                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:
-                self._state = STATE_READY
+            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
+
+            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._state = STATE_DISCONNECTED
+                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()
@@ -3,59 +3,56 @@ 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.
  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.
+      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: box
+
    model:
      name: Model
-      description: >-
-        Select an AI model to use (optional, overrides default setting).
-        Different models have different capabilities and token limits.
-        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:
-          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"
-          mode: dropdown
+      selector:  
+        text:
+          multiline: false

    temperature:
      name: Temperature
-      description: >-
-        Controls response creativity (0-2):
-        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:
@@ -64,17 +61,10 @@ ask_question:
          max: 2.0
          step: 0.1
          mode: slider
-          unit_of_measurement: ""

    max_tokens:
      name: Max Tokens
-      description: >-
-        Maximum length of the response. Higher values allow longer responses but use more API tokens.
-        Recommended ranges:
-        - Short responses (256-512): Quick answers, status updates
-        - Medium responses (512-1024): Detailed explanations, instructions
-        - Long responses (1024-4096): Complex analysis, multiple examples
-        Note: Actual response length may be shorter based on content.
+      description: Maximum length of the response (1-4096 tokens)
      required: false
      default: 1000
      selector:
@@ -83,72 +73,3 @@ ask_question:
          max: 4096
          step: 1
          mode: box
-
-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 will be preserved.
-  fields: {}
-
-get_history:
-  name: Get History
-  description: >-
-    Retrieve recent conversation history, including questions, responses, and timestamps.
-    Results are ordered from newest to oldest and include metadata like model used and response times.
-  fields:
-    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
-      required: false
-      default: 10
-      selector:
-        number:
-          min: 1
-          max: 100
-          step: 1
-          mode: box
-
-    filter_model:
-      name: Filter by Model
-      description: >-
-        Only return conversations using a specific AI model.
-        Leave empty to show all models.
-      required: false
-      selector:
-        select:
-          options:
-            - label: "All Models"
-              value: ""
-            - label: "GPT-3.5 Turbo"
-              value: "gpt-3.5-turbo"
-            - label: "GPT-4"
-              value: "gpt-4"
-          mode: dropdown
-
-set_system_prompt:
-  fields:  
-    prompt:
-      name: System Prompt
-      description: >-
-        Instructions that define how the AI should behave and respond.
-        Be specific about the desired expertise, tone, and format of responses.
-        Maximum length: 1000 characters.
-      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
-          type: text
@@ -0,0 +1,261 @@
+{
+    "config": {
+        "step": {
+            "provider": {
+                "title": "KI-Anbieter auswählen",
+                "description": "Wählen Sie den KI-Dienst-Anbieter für diese Instanz",
+                "data": {
+                    "api_provider": "API-Anbieter",
+                    "context_messages": "Anzahl der zu speichernden Kontextnachrichten (1-20)"
+                }
+            },
+            "user": {
+                "title": "HA Text AI Instanz konfigurieren",
+                "description": "Richten Sie eine neue KI-Assistenten-Instanz mit Ihrem ausgewählten Anbieter ein",
+                "data": {
+                    "name": "Instanzname (z.B. 'GPT Assistent', 'Claude Helfer')",
+                    "api_key": "API-Schlüssel für Authentifizierung",
+                    "model": "Zu verwendendes KI-Modell",
+                    "temperature": "Antwort-Kreativität (0-2, niedriger = fokussierter)",
+                    "max_tokens": "Maximale Antwortlänge (1-4096 Token)",
+                    "api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)",
+                    "request_interval": "Minimale Zeit zwischen Anfragen (0,1-60 Sekunden)",
+                    "context_messages": "Anzahl der zu speichernden Kontextnachrichten (1-20)"
+                }
+            }
+        },
+        "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 - bitte überprüfen Sie Ihre Anmeldedaten",
+            "cannot_connect": "Verbindung zum API-Dienst fehlgeschlagen",
+            "invalid_model": "Ausgewähltes Modell ist nicht verfügbar",
+            "rate_limit": "Anfragelimit überschritten",
+            "context_length": "Kontextlänge überschritten",
+            "rate_limit_exceeded": "API-Anfragelimit überschritten",
+            "maintenance": "Dienst ist in Wartung",
+            "invalid_response": "Ungültige API-Antwort erhalten",
+            "api_error": "API-Dienst-Fehler aufgetreten",
+            "timeout": "Anfrage-Zeitüberschreitung",
+            "invalid_instance": "Ungültige Instanz angegeben",
+            "unknown": "Unerwarteter Fehler aufgetreten"
+        }
+    },
+    "options": {
+        "step": {
+            "init": {
+                "title": "Instanzeinstellungen aktualisieren",
+                "description": "Einstellungen für diese KI-Assistenten-Instanz ändern",
+                "data": {
+                    "model": "KI-Modell",
+                    "temperature": "Antwort-Kreativität (0-2)",
+                    "max_tokens": "Maximale Antwortlänge (1-4096)",
+                    "request_interval": "Minimales Anfragen-Intervall (0,1-60 Sekunden)",
+                    "context_messages": "Anzahl der vorherigen Nachrichten, die in den Kontext einbezogen werden sollen (1-20)"
+
+                }
+            }
+        }
+    },
+    "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 in der Gesprächshistorie 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 Eingabeaufforderung für den KI-Assistenten"
+                },
+                "context_messages": {
+                    "name": "Kontextnachrichten",
+                    "description": "Anzahl der vorherigen Nachrichten, die in den Kontext einbezogen werden sollen (1-20)"
+                },
+                "system_prompt": {
+                    "name": "Systemaufforderung",
+                    "description": "Optionale Systemaufforderung zur Kontexteinstellung für diese spezifische Frage"
+                },
+                "model": {
+                    "name": "Modell",
+                    "description": "Wählen Sie das zu verwendende KI-Modell (optional, überschreibt Standardeinstellung)"
+                },
+                "temperature": {
+                    "name": "Temperatur",
+                    "description": "Steuert die Antwort-Kreativität (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 Gesprächsverlauf löschen",
+            "fields": {
+                "instance": {
+                    "name": "Instanz",
+                    "description": "Name der HA Text AI Instanz, für die der Verlauf gelöscht werden soll"
+                }
+            }
+        },
+        "get_history": {
+            "name": "Verlauf abrufen",
+            "description": "Gesprächsverlauf mit optionaler Filterung und Sortierung abrufen",
+            "fields": {
+                "instance": {
+                    "name": "Instanz",
+                    "description": "Name der HA Text AI Instanz, aus der der Verlauf abgerufen werden soll"
+                },
+                "limit": {
+                    "name": "Limit",
+                    "description": "Anzahl der zurückzugebenden Gespräche (1-100)"
+                },
+                "filter_model": {
+                    "name": "Modell filtern",
+                    "description": "Gespräche nach bestimmtem KI-Modell filtern"
+                },
+                "start_date": {
+                    "name": "Startdatum",
+                    "description": "Gespräche ab diesem Datum/Zeitpunkt filtern"
+                },
+                "include_metadata": {
+                    "name": "Metadaten einbeziehen",
+                    "description": "Zusätzliche Informationen wie verwendete Token, Antwortzeit usw. einbeziehen"
+                },
+                "sort_order": {
+                    "name": "Sortierreihenfolge",
+                    "description": "Sortierreihenfolge der Ergebnisse (neueste oder älteste zuerst)"
+                }
+            }
+        },
+        "set_system_prompt": {
+            "name": "Systemaufforderung festlegen",
+            "description": "Standardmäßige Systemverhaltensinstruktionen für alle zukünftigen Gespräche festlegen",
+            "fields": {
+                "instance": {
+                    "name": "Instanz",
+                    "description": "Name der HA Text AI Instanz, für die die Systemaufforderung festgelegt werden soll"
+                },
+                "prompt": {
+                    "name": "Systemaufforderung",
+                    "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": "Anfragelimit",
+                    "maintenance": "Wartung",
+                    "initializing": "Initialisierung",
+                    "retrying": "Wiederholung",
+                    "queued": "In 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": "Systemaufforderung"
+                    },
+                    "response_time": {
+                        "name": "Letzte Antwortzeit"
+                    },
+                    "total_responses": {
+                        "name": "Gesamte Antworten"
+                    },
+                    "error_count": {
+                        "name": "Fehleranzahl"
+                    },
+                    "last_error": {
+                        "name": "Letzter Fehler"
+                    },
+                    "api_status": {
+                        "name": "API-Status"
+                    },
+                    "tokens_used": {
+                        "name": "Insgesamt verwendete Token"
+                    },
+                    "average_response_time": {
+                        "name": "Durchschnittliche Antwortzeit"
+                    },
+                    "last_request_time": {
+                        "name": "Letzte Anforderungszeit"
+                    },
+                    "is_processing": {
+                        "name": "Verarbeitungsstatus"
+                    },
+                    "is_rate_limited": {
+                        "name": "Status Anfragelimit"
+                    },
+                    "is_maintenance": {
+                        "name": "Wartungsstatus"
+                    },
+                    "api_version": {
+                        "name": "API-Version"
+                    },
+                    "endpoint_status": {
+                        "name": "Endpunktstatus"
+                    },
+                    "performance_metrics": {
+                        "name": "Leistungsmetriken"
+                    },
+                    "history_size": {
+                        "name": "Verlaufsgröße"
+                    },
+                    "uptime": {
+                        "name": "Betriebszeit"
+                    },
+                    "total_tokens": {
+                        "name": "Gesamte Token"
+                    },
+                    "prompt_tokens": {
+                        "name": "Prompt-Token"
+                    },
+                    "completion_tokens": {
+                        "name": "Abschluss-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"
+                    }
+                }
+            }
+        }
+    }
+}
@@ -1,54 +1,260 @@
 {
    "config": {
        "step": {
-            "user": {
-                "title": "Set up HA Text AI",
-                "description": "Configure your OpenAI integration",
+            "provider": {
+                "title": "Select AI Provider",
+                "description": "Choose which AI service provider to use for this instance",
                "data": {
-                    "api_key": "Your OpenAI API key",
-                    "model": "AI model to use for responses",
-                    "temperature": "Temperature for response generation (0-2)",
-                    "max_tokens": "Maximum tokens in response (1-4096)",
-                    "api_endpoint": "API endpoint URL",
-                    "request_interval": "Minimum time between API requests (seconds)"
+                    "api_provider": "API Provider",
+                    "context_messages": "Number of context messages to retain (1-20)"
+                }
+            },
+            "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)",
+                    "request_interval": "Minimum time between requests (0.1-60 seconds)",
+                    "context_messages": "Number of context messages to retain (1-20)"
                }
            }
+        },
+        "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"
        }
    },
    "options": {
        "step": {
            "init": {
-                "title": "HA Text AI Options",
+                "title": "Update Instance Settings",
+                "description": "Modify settings for this AI assistant instance",
                "data": {
-                    "temperature": "Response temperature (0-2)",
-                    "max_tokens": "Maximum response length",
-                    "request_interval": "Time between requests"
+                    "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)"
                }
            }
        }
    },
    "services": {
        "ask_question": {
-            "name": "Ask Question",
-            "description": "Send a question to the AI model",
-            "fields": {  
+            "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 for the AI"
+                    "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": "Clear conversation 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"
+            "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 system behavior instructions"
+            "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"
+                    }
+                }
+            }
        }
    }
 }
@@ -1,54 +1,260 @@
 {
    "config": {
        "step": {
-            "user": {
-                "title": "Настройка HA Text AI",
-                "description": "Настройка интеграции с OpenAI",
+            "provider": {
+                "title": "Выбор провайдера ИИ",
+                "description": "Выберите сервис ИИ для этого экземпляра",
                "data": {
-                    "api_key": "Ваш ключ API OpenAI",
-                    "model": "Модель ИИ для генерации ответов",
-                    "temperature": "Температура генерации ответов (0-2)",
-                    "max_tokens": "Максимальное количество токенов в ответе (1-4096)",
-                    "api_endpoint": "URL конечной точки API",
-                    "request_interval": "Минимальное время между запросами к API (секунды)"
+                    "api_provider": "Провайдер API",
+                    "context_messages": "Количество сообщений в контексте (1-20)"  
+                }
+            },
+            "user": {
+                "title": "Настройка экземпляра HA Text AI",
+                "description": "Настройте нового помощника ИИ с выбранным провайдером",
+                "data": {
+                    "name": "Название экземпляра (например, 'GPT Помощник', 'Claude Ассистент')",
+                    "api_key": "API-ключ для аутентификации",
+                    "model": "Модель ИИ для использования",
+                    "temperature": "Креативность ответов (0-2, меньше = более сфокусированно)",
+                    "max_tokens": "Максимальная длина ответа (1-4096 токенов)",
+                    "api_endpoint": "Пользовательский URL-адрес API (необязательно)",
+                    "request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
+                    "context_messages": "Количество сохраняемых контекстных сообщений (1-20)"
                }
            }
+        },
+        "error": {
+            "name_exists": "Экземпляр с таким именем уже существует",
+            "invalid_name": "Некорректное имя экземпляра",
+            "invalid_auth": "Ошибка аутентификации - проверьте API-ключ",
+            "invalid_api_key": "Неверный API-ключ - проверьте учетные данные",
+            "cannot_connect": "Не удалось подключиться к сервису API",
+            "invalid_model": "Выбранная модель недоступна",
+            "rate_limit": "Превышен лимит запросов",
+            "context_length": "Превышена длина контекста",
+            "rate_limit_exceeded": "Превышен лимит API",
+            "maintenance": "Сервис на техническом обслуживании",
+            "invalid_response": "Получен некорректный ответ API",
+            "api_error": "Произошла ошибка сервиса API",
+            "timeout": "Время ожидания истекло",
+            "invalid_instance": "Указан неверный экземпляр",
+            "unknown": "Произошла непредвиденная ошибка"
        }
    },
    "options": {
        "step": {
            "init": {
-                "title": "Настройки HA Text AI",
+                "title": "Обновление настроек экземпляра",
+                "description": "Измените настройки для этого помощника ИИ",
                "data": {
-                    "temperature": "Температура ответов (0-2)",
-                    "max_tokens": "Максимальная длина ответа",
-                    "request_interval": "Время между запросами"
+                    "model": "Модель ИИ",
+                    "temperature": "Креативность ответов (0-2)",
+                    "max_tokens": "Максимальная длина ответа (1-4096)",
+                    "request_interval": "Минимальный интервал запросов (0.1-60 секунд)",
+                    "context_messages": "Количество предыдущих сообщений для включения в контекст (1-20)"
                }
            }
        }
    },
    "services": {
        "ask_question": {
-            "name": "Задать вопрос",
-            "description": "Отправить вопрос модели ИИ",
+            "name": "Задать вопрос (HA Text AI)",
+            "description": "Отправьте вопрос модели ИИ и получите подробный ответ. Ответ будет сохранен в истории беседы и может быть извлечен позже.",
            "fields": {
+                "instance": {
+                    "name": "Экземпляр",
+                    "description": "Название экземпляра HA Text AI для использования"
+                },
                "question": {
                    "name": "Вопрос",
-                    "description": "Ваш вопрос для ИИ"
+                    "description": "Ваш вопрос или запрос помощнику ИИ"
+                },
+                "context_messages": {
+                    "name": "Контекстные сообщения",
+                    "description": "Количество предыдущих сообщений для включения в контекст (1-20)"
+                },
+                "system_prompt": {
+                    "name": "Системный промпт",
+                    "description": "Необязательный системный промпт для установки контекста для этого конкретного вопроса"
+                },
+                "model": {
+                    "name": "Модель",
+                    "description": "Выберите модель ИИ (необязательно, переопределяет настройки по умолчанию)"
+                },
+                "temperature": {
+                    "name": "Температура",
+                    "description": "Управляет креативностью ответа (0.0-2.0)"
+                },
+                "max_tokens": {
+                    "name": "Максимальное количество токенов",
+                    "description": "Максимальная длина ответа (1-4096 токенов)"
                }
            }
        },
        "clear_history": {
            "name": "Очистить историю",
-            "description": "Очистить историю разговора"
+            "description": "Удалить все сохраненные вопросы и ответы из истории беседы",
+            "fields": {
+                "instance": {
+                    "name": "Экземпляр",
+                    "description": "Название экземпляра HA Text AI для очистки истории"
+                }
+            }
        },
        "get_history": {
            "name": "Получить историю",
-            "description": "Получить историю разговора"
+            "description": "Получить историю беседы с дополнительной фильтрацией и сортировкой",
+            "fields": {
+                "instance": {
+                    "name": "Экземпляр",
+                    "description": "Название экземпляра HA Text AI для получения истории"
+                },
+                "limit": {
+                    "name": "Лимит",
+                    "description": "Количество возвращаемых бесед (1-100)"
+                },
+                "filter_model": {
+                    "name": "Фильтр модели",
+                    "description": "Фильтрация бесед по конкретной модели ИИ"
+                },
+                "start_date": {
+                    "name": "Начальная дата",
+                    "description": "Фильтрация бесед, начиная с указанной даты/времени"
+                },
+                "include_metadata": {
+                    "name": "Включить метаданные",
+                    "description": "Включить дополнительную информацию, например, использованные токены, время ответа и т.д."
+                },
+                "sort_order": {
+                    "name": "Порядок сортировки",
+                    "description": "Порядок результатов (сначала новые или старые)"
+                }
+            }
        },
        "set_system_prompt": {
            "name": "Установить системный промпт",
-            "description": "Установить инструкции поведения системы"
+            "description": "Установить инструкции по умолчанию для поведения ИИ во всех будущих разговорах",
+            "fields": {
+                "instance": {
+                    "name": "Экземпляр",
+                    "description": "Название экземпляра HA Text AI для установки системного промпта"
+                },
+                "prompt": {
+                    "name": "Системный промпт",
+                    "description": "Инструкции, определяющие, как ИИ должен вести себя 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": "Максимальное количество токенов"
+                    },
+                    "system_prompt": {
+                        "name": "Системный промпт"
+                    },
+                    "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": "Всего использовано токенов"
+                    },
+                    "average_response_time": {
+                        "name": "Среднее время ответа"
+                    },
+                    "last_request_time": {
+                        "name": "Время последнего запроса"
+                    },
+                    "is_processing": {
+                        "name": "Статус обработки"
+                    },
+                    "is_rate_limited": {
+                        "name": "Статус лимита запросов"
+                    },
+                    "is_maintenance": {
+                        "name": "Статус обслуживания"
+                    },
+                    "api_version": {
+                        "name": "Версия API"
+                    },
+                    "endpoint_status": {
+                        "name": "Статус эндпоинта"
+                    },
+                    "performance_metrics": {
+                        "name": "Показатели производительности"
+                    },
+                    "history_size": {
+                        "name": "Размер истории"
+                    },
+                    "uptime": {
+                        "name": "Время работы"
+                    },
+                    "total_tokens": {
+                        "name": "Всего токенов"
+                    },
+                    "prompt_tokens": {
+                        "name": "Токены промпта"
+                    },
+                    "completion_tokens": {
+                        "name": "Токены завершения"
+                    },
+                    "successful_requests": {
+                        "name": "Успешные запросы"
+                    },
+                    "failed_requests": {
+                        "name": "Неудачные запросы"
+                    },
+                    "average_latency": {
+                        "name": "Средняя задержка"
+                    },
+                    "max_latency": {
+                        "name": "Максимальная задержка"
+                    },
+                    "min_latency": {
+                        "name": "Минимальная задержка"
+                    }
+                }
+            }
        }
    }
 }
@@ -1,9 +1,5 @@
 {
  "name": "HA text AI",
  "render_readme": true,
-  "domains": ["sensor"],
-  "homeassistant": "2024.11.0",
-  "icon": "mdi:brain",
-  "version": "1.0.8",
-  "documentation": "https://github.com/smkrv/ha-text-ai"
+  "homeassistant": "2024.11.0"
 }
@@ -1,3 +0,0 @@
-pytest
-pytest-asyncio
-homeassistant
@@ -0,0 +1,25 @@
+```
+ha-text-ai/
+│
+├── custom_components/
+    ├── 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
+```
Author	SHA1	Message	Date
SMKRV	0fdc3c93d3	Release v2.0.0-alpha	2024-11-26 14:02:37 +03:00
SMKRV	d6e76f7805	Validate HACS	2024-11-26 13:16:10 +03:00
SMKRV	b05afe1085	Release v2.0.0-alpha	2024-11-26 02:08:55 +03:00
SMKRV	2a4911f5f8	Release v2.0.0-alpha	2024-11-26 02:04:23 +03:00
SMKRV	208074d845	Release v2.0.0-alpha	2024-11-26 01:20:08 +03:00
SMKRV	616ff2c3fe	💡 Support the Project	2024-11-26 00:14:26 +03:00
SMKRV	987c939956	Support the Project	2024-11-26 00:12:43 +03:00
SMKRV	1615cc744e	Support the Project	2024-11-26 00:12:10 +03:00
SMKRV	2d793a4b25	Support the Project	2024-11-26 00:11:55 +03:00
SMKRV	aeeb4d5504	Support the Project	2024-11-26 00:09:46 +03:00
SMKRV	daec801073	Misc	2024-11-25 23:50:33 +03:00
SMKRV	e4916a7b7c	Misc	2024-11-25 23:49:42 +03:00
SMKRV	a08abd76e3	Misc	2024-11-25 23:48:55 +03:00
SMKRV	a2be709608	Misc	2024-11-25 23:48:16 +03:00
SMKRV	69002ef926	Misc	2024-11-25 23:45:28 +03:00
SMKRV	9ade5a7194	misc	2024-11-25 23:43:05 +03:00
SMKRV	9b3f4f605b	Sensor Attributes	2024-11-25 17:59:17 +03:00
SMKRV	b862968d01	Release v2.0.0-alpha	2024-11-25 17:31:42 +03:00
SMKRV	29f3ae5592	Release v2.0.0	2024-11-25 17:10:38 +03:00
SMKRV	107d2a64fc	Release v2.0.0	2024-11-25 17:09:39 +03:00
SMKRV	e24bb884ef	Release v2.0.0	2024-11-25 17:08:23 +03:00
SMKRV	107a2ef962	Release v2.0.0	2024-11-25 17:04:53 +03:00
SMKRV	9d58f2cf1e	Release v2.0.0	2024-11-25 17:04:18 +03:00
SMKRV	29f6860fe1	Release v2.0.0	2024-11-25 17:03:29 +03:00
SMKRV	fa89026e05	Release v2.0.0	2024-11-25 17:00:29 +03:00
SMKRV	9968452c46	Release v2.0.0	2024-11-25 16:57:14 +03:00
SMKRV	9665634013	Release v2.0.0	2024-11-25 16:55:12 +03:00
SMKRV	76d10ba8fb	Release v2.0.0	2024-11-25 16:54:42 +03:00
SMKRV	e9ea10203e	Release v2.0.0	2024-11-25 16:54:07 +03:00
SMKRV	92a4c2da02	Release v2.0.0	2024-11-25 16:53:38 +03:00
SMKRV	b6d8eb98f6	Release v2.0.0	2024-11-25 16:52:20 +03:00
SMKRV	b6b01bccd7	Release v2.0.0	2024-11-25 16:51:42 +03:00
SMKRV	ace2339b4f	Release v2.0.0	2024-11-25 16:46:27 +03:00
SMKRV	166c1f9c9c	Release v2.0.0	2024-11-25 16:45:43 +03:00
SMKRV	e4039a08bc	Release v2.0.0	2024-11-25 16:45:05 +03:00
SMKRV	1da5b5941d	Release v2.0.0	2024-11-25 16:44:14 +03:00
SMKRV	6683f12c80	Release v2.0.0	2024-11-25 16:42:51 +03:00
SMKRV	2277f48e46	Release v2.0.0	2024-11-25 16:40:55 +03:00
SMKRV	d206bde15a	Release v2.0.0	2024-11-25 16:37:57 +03:00
SMKRV	af16d03915	Release v2.0.0	2024-11-25 16:34:36 +03:00
SMKRV	bf26cd3cfb	Release v2.0.0	2024-11-25 16:25:58 +03:00
SMKRV	094062773a	Release v2.0.0	2024-11-25 16:18:54 +03:00
SMKRV	4cd95813bc	Release v2.0.0	2024-11-25 15:51:08 +03:00
SMKRV	c2064f0b64	Release v2.0.0	2024-11-25 15:42:04 +03:00
SMKRV	fafd927610	Release v2.0.0	2024-11-25 14:59:44 +03:00
SMKRV	7f46380054	Release v2.0.0	2024-11-25 02:05:13 +03:00
SMKRV	351a8b18dd	Release v2.0.0	2024-11-25 02:03:29 +03:00
SMKRV	39833b333f	Release v2.0.0	2024-11-25 01:52:37 +03:00
SMKRV	888a41375b	Release v2.0.0	2024-11-25 01:43:06 +03:00
SMKRV	823abb22e4	Release v2.0.0	2024-11-25 01:20:44 +03:00
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SMKRV	326f876410	Handles the VSE GPT API endpoint correctly	2024-11-20 12:23:26 +03:00
SMKRV	58a7ae4229	Resoved blocking SSL verification issue in coordinator.py API endpoint handling in config_flow.py changes Added support for the custom models in const.py Requirements in manifest.json updated	2024-11-20 12:07:30 +03:00
SMKRV	8f796ad9dc	Retry constants	2024-11-20 01:40:29 +03:00
SMKRV	8be860007a	Retry constants MAX_RETRIES: Final = 3 RETRY_DELAY: Final = 1.0	2024-11-20 01:39:19 +03:00
SMKRV	1985e201b4	Updated	2024-11-20 01:29:14 +03:00
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SMKRV	962a089bf4	Stability improvements	2024-11-19 23:38:07 +03:00
SMKRV	4c56565b66	Stability improvements	2024-11-19 23:30:28 +03:00
SMKRV	8432038f09	Stability improvements	2024-11-19 23:21:54 +03:00
SMKRV	929d916d41	Bugfixes	2024-11-19 19:39:05 +03:00
SMKRV	675975d951	Minor changes	2024-11-19 19:31:26 +03:00
SMKRV	524ec87395	Minor changes	2024-11-19 19:30:42 +03:00
SMKRV	94f8193996	last_update_success_time > last_update_success	2024-11-19 19:28:01 +03:00
SMKRV	7c3fcf73c3	Text edits	2024-11-19 19:23:03 +03:00
SMKRV	20bbf89679	Changes	2024-11-19 19:20:52 +03:00
SMKRV	86dca52d07	Small changes	2024-11-19 19:18:16 +03:00
SMKRV	78d1561e74	Markdown	2024-11-19 19:17:04 +03:00
SMKRV	054e4af258	Quick bugfix	2024-11-19 19:15:57 +03:00
SMKRV	dc03faa97e	docs: update HACS installation for custom repository - Change HACS badge from Default to Custom - Add custom repository installation steps - Update installation instructions - Revise documentation format	2024-11-19 19:03:51 +03:00
SMKRV	9a7635c2ae	Release v1.1.0	2024-11-19 18:55:14 +03:00
SMKRV	df3d79c20c	feat: add multi-provider support, config improvements	2024-11-19 18:53:51 +03:00
SMKRV	d6144be7ed	v.1.0.10	2024-11-19 17:49:48 +03:00
SMKRV	9afbb904b3	__init__.py: added: from .coordinator import HATextAICoordinator	2024-11-19 17:48:00 +03:00
SMKRV	93558b2444	Version update	2024-11-19 17:34:27 +03:00
SMKRV	9f93f1ee18	Main changes: Removed the validate_endpoint function Optimized the validate_api_connection function Simplified API connection verification Preserved all error handling and retry logic Improved exception handling The integration should now correctly verify the OpenAI API connection without false endpoint_not_available errors.	2024-11-19 17:33:27 +03:00
SMKRV	30a9b53ba1	Markdown changes	2024-11-19 17:18:23 +03:00
SMKRV	5175970d55	structure.md added	2024-11-19 17:16:30 +03:00