bump to version 2.0.8

- Improve JSON history file processing
- Add memory and disk space validation
- Enhance parallel request handling
- Refine token counting heuristics

README.md

@@ -4,7 +4,7 @@
 
 ![GitHub release](https://img.shields.io/github/release/smkrv/ha-text-ai.svg?style=flat-square) ![GitHub last commit](https://img.shields.io/github/last-commit/smkrv/ha-text-ai.svg?style=flat-square) [![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg?style=flat-square)](https://creativecommons.org/licenses/by-nc-sa/4.0/) [![hacs_badge](https://img.shields.io/badge/HACS-Custom-41BDF5.svg?style=flat-square)](https://github.com/hacs/integration) ![/README.md](https://img.shields.io/badge/language-English-green?style=flat-square) ![/README_RU.md](https://img.shields.io/badge/language-Russian-green?style=flat-square) ![](https://img.shields.io/badge/language-Deutch-green?style=flat-square)
 
-  <img src="https://github.com/smkrv/ha-text-ai/blob/524849f6a945ec62c2cf6a6b7ecd9a28b37bf0fa/misc/icons/logo.jpg" alt="HA Text AI" height="160"/>
+  <img src="https://github.com/smkrv/ha-text-ai/blob/2aaf3405759eb2d97624834594e24ace896131df/assets/images/icons/logo.png" alt="HA Text AI" style="width: 80%; max-width: 640px; max-height: 150px; aspect-ratio: 2/1; object-fit: contain;"/>
 
 ### Advanced AI Integration for [Home Assistant](https://www.home-assistant.io/) with LLM multi-provider support
 </div>
@@ -17,63 +17,88 @@ Transform your smart home experience with powerful AI assistance powered by mult
 ---
 
 > [!IMPORTANT]
-> 🚧 BETA 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>  
 >  
-> [Screenshots](misc/screenshots/screenshot.jpg)
+> [Screenshots](assets/images/screenshots/screenshot.jpg)
 
 ## 🌟 Features
 
-- 🧠 **Multi-Provider AI Integration**:
-  - Support for OpenAI GPT models
-  - Anthropic Claude integration
-  - Custom API endpoints
-  - Flexible model selection
+- 🧠 **Multi-Provider AI Integration**: Support for OpenAI GPT and Anthropic Claude models
+- 💬 **Advanced Language Processing**: Context-aware, multi-turn conversations
+- 📝 **Enhanced Memory Management**: Secure file-based history storage
+- ⚡ **Performance Optimization**: Efficient token usage and smart rate limiting
+- 🎯 **Advanced Customization**: Per-request model and parameter selection
+- 🔒 **Enhanced Security**: Secure API key management and usage monitoring
+- 🎨 **Improved User Experience**: Intuitive configuration and rich interfaces
+- 🔄 **Automation Integration**: Event-driven responses and template compatibility 
 
-- 💬 **Advanced Language Processing**:
-  - Context-aware responses
-  - Multi-turn conversations
-  - Custom system instructions
-  - Natural conversation flow
+<details>
+<summary>📦 Detailed Feature Breakdown</summary>
 
-- 📝 **Enhanced Memory Management**:
-  - File-based conversation history storage
-  - Automatic history rotation
-  - Configurable history size limits
-  - Secure storage in Home Assistant
+### 🧠 **Multi-Provider AI Integration**
+- Support for OpenAI GPT models
+- Anthropic Claude integration
+- Custom API endpoints
+- Flexible model selection
 
-- ⚡ **Performance Optimization**:
-  - Efficient token usage
-  - Smart rate limiting
-  - Response caching
-  - Request interval control
+### 💬 **Advanced Language Processing**
+- Context-aware responses
+- Multi-turn conversations
+- Custom system instructions
+- Natural conversation flow
 
-- 🎯 **Advanced Customization**:
-  - Per-request model selection
-  - Adjustable parameters
-  - Custom system prompts
-  - Temperature control
+### 📝 **Enhanced Memory Management**
+- File-based conversation history storage
+- Automatic history rotation
+- Configurable history size limits
+- Secure storage in Home Assistant
 
-- 🔒 **Enhanced Security**:
-  - Secure API key storage
-  - Rate limiting protection
-  - Error handling
-  - Usage monitoring
+### ⚡ **Performance Optimization**
+- Efficient token usage
+- Smart rate limiting
+- Response caching
+- Request interval control
 
-- 🎨 **Improved User Experience**:
-  - Intuitive configuration UI
-  - Detailed sensor attributes
-  - Rich service interface
-  - Model selection UI
+### 🎯 **Advanced Customization**
+- Per-request model selection
+- Adjustable parameters
+- Custom system prompts
+- Temperature control
 
-- 🔄 **Automation Integration**:
-  - Event-driven responses
-  - Conditional logic support
-  - Template compatibility
-  - Model-specific automation
+### 🔒 **Enhanced Security**
+- Secure API key storage
+- Rate limiting protection
+- Error handling
+- Usage monitoring
+
+### 🎨 **Improved User Experience**
+- Intuitive configuration UI
+- Detailed sensor attributes
+- Rich service interface
+- Model selection UI
+
+### 🔄 **Automation Integration**
+- Event-driven responses
+- Conditional logic support
+- Template compatibility
+- Model-specific automation
+
+</details>
+
+#### 🌐 Translations
+
+| Code | Language | Status |
+|------|----------|--------|
+| 🇩🇪 de | Deutsch | Full |
+| 🇬🇧 en | English | Primary |
+| 🇪🇸 es | Español | Full |
+| 🇮🇳 hi | हिन्दी | Full |
+| 🇮🇹 it | Italiano | Full |
+| 🇷🇺 ru | Русский | Full |
+| 🇷🇸 sr | Српски | Full |
+| 🇨🇳 zh | 中文 | Full |
 
 ## 📋 Prerequisites
 
@@ -82,41 +107,50 @@ Transform your smart home experience with powerful AI assistance powered by mult
   - OpenAI ([Get key](https://platform.openai.com/account/api-keys))
   - Anthropic ([Get key](https://console.anthropic.com/))
   - OpenRouter ([Get key](https://openrouter.ai/keys))
+  - Any OpenAI-compatible API provider
 - 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)
+## Configuration Options
 
-#### ⓘ 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  
+### 🔧 **Core Configuration Settings**
+- 🌐 **API Provider**: OpenAI/Anthropic
+- 🔑 **API Key**: Provider-specific authentication
+- 🤖 **Model Selection**: Flexible, provider-specific models
+- 🌡️ **Temperature**: Creativity control (0.0-2.0)
+- 📏 **Max Tokens**: Response length limit (token usage is estimated using a heuristic method based on word count and specific word characteristics, which may differ from actual token usage)
+- ⏱️ **Request Interval**: API call throttling
+- 💾 **History Size**: Number of messages to retain
+- 🌍 **Custom API Endpoint**: Optional advanced configuration
 
-#### Additional Notes  
-- Not all providers guarantee full compatibility  
-- Performance may vary between providers  
-- Check individual provider's documentation  
+<details>
+<summary>🌐 Potentially Compatible Providers</summary>
+
+#### Flexible Provider Ecosystem
+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
+
+#### 🚨 Compatibility 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  
+#### 🔍 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
 
+</details>
+
 ## ⚡ Installation
 
 ### HACS Installation (Recommended)
@@ -144,7 +178,8 @@ To be compatible, a provider should support:
 3. Search for "HA Text AI"
 4. Follow the configuration steps
 
-### Via YAML
+<details>
+<summary>📦 Via YAML (Advanced)</summary>
 
 ### Platform Configuration (Global Settings)
 
@@ -202,6 +237,8 @@ sensor:
 | `temperature` | Float | ❌ | Platform setting | Override global temperature |
 | `max_tokens` | Integer | ❌ | Platform setting | Override global max tokens |
 
+</details>
+
 ## 🛠️ Available Services
 
 ### ask_question
@@ -214,12 +251,14 @@ data:
   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
+  instance: sensor.ha_text_ai_gpt
 ```
 
 ### set_system_prompt
 ```yaml
 service: ha_text_ai.set_system_prompt
 data:
+  instance: sensor.ha_text_ai_gpt
   prompt: |
     You are a home automation expert focused on:
     1. Energy efficiency
@@ -258,7 +297,7 @@ 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
+sensor.ha_text_ai_abc      # Custom suffix
 ```
 
 #### Response Retrieval
@@ -275,6 +314,7 @@ automation:
       - service: ha_text_ai.ask_question
         data:
           question: "Home automation advice"
+          instance: sensor.ha_text_ai_gpt
       - service: notify.mobile
         data:
           message: >
@@ -291,6 +331,16 @@ automation:
 
 ### 🔍 HA Text AI Sensor Attributes
 
+- 🤖 **Model and Provider Information**: Tracking current AI model and service provider
+- 🚦 **System Status**: Real-time API and processing readiness
+- 📊 **Performance Metrics**: Request success rates and response times
+- 💬 **Conversation Tracking**: Token usage and interaction history are estimated using a heuristic method based on word count and specific word characteristics, which may differ from actual token usage.
+- 🕒 **Last Interaction Details**: Recent query and response tracking
+- ❤️ **System Health**: Error monitoring and service uptime
+
+<details>
+<summary>📦 Detailed Sensor Attributes</summary>
+
 #### Model and Provider Information
 ```yaml
 # Name of the AI model currently in use (e.g., latest version of GPT)  
@@ -352,7 +402,6 @@ automation:
 
 # Last few conversation entries (limited to 3 for performance)
 {{ state_attr('sensor.ha_text_ai_gpt', 'conversation_history') }}  # [...]
-
 ```
 
 #### Last Interaction Details
@@ -381,7 +430,7 @@ automation:
 
 ### History Storage
 Conversation history stored in `.storage/ha_text_ai_history/` directory:
-- Each instance has its own history file
+- Each instance has its own history file (JSON)
 - Files are automatically rotated when size limit is reached
 - Archived history files are timestamped
 - Default maximum file size: 1MB
@@ -391,6 +440,7 @@ Conversation history stored in `.storage/ha_text_ai_history/` directory:
 - Use these attributes for monitoring and automation
 - Some values might be 0 or empty initially
 
+</details>
 
 ## 📘 FAQ
 
@@ -427,7 +477,6 @@ A: Yes, archived history files are stored with timestamps and can be accessed ma
 **Q: How much history is kept?**  
 A: By default, up to 100 conversations are stored, but this can be configured. Files are automatically rotated when they reach 1MB.
 
-
 ## 🤝 Contributing
 
 Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md).
@@ -474,9 +523,11 @@ If you want to say thanks financially, you can send a small token of appreciatio
 
 ---
 
+<div align="center"><img src="https://github.com/smkrv/ha-text-ai/blob/2aaf3405759eb2d97624834594e24ace896131df/assets/images/icons/footer_icon.png" alt="HA Text AI" style="width: 128px; height: auto;"/></div>  
 <div align="center">
 
-Made with ❤️ and Claude 3.5 Sonnet for the Home Assistant Community
+Made with ❤️ for the Home Assistant Community,  
+utilizing Claude 3.5 Sonnet, Gemini Pro 1.5, and Qwen 2.5 Coder 32B Instruct.
 
 [Report Bug](https://github.com/smkrv/ha-text-ai/issues) · [Request Feature](https://github.com/smkrv/ha-text-ai/issues)
 

custom_components/ha_text_ai/__init__.py

@@ -11,8 +11,9 @@ from __future__ import annotations
 import logging
 import os
 import shutil
+import hashlib
 from datetime import datetime, timedelta
-from typing import Any, Dict
+from typing import Any, Dict, TypeVar
 
 import voluptuous as vol
 from async_timeout import timeout
@@ -52,11 +53,13 @@ from .const import (
     SERVICE_SET_SYSTEM_PROMPT,
     DEFAULT_MAX_HISTORY,
     CONF_MAX_HISTORY_SIZE,
+    ICONS_SUBDOMAIN,
 )
 
 _LOGGER = logging.getLogger(__name__)
 
 CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)
+ConfigType = TypeVar("ConfigType", bound=Dict[str, Any])
 
 SERVICE_SCHEMA_ASK_QUESTION = vol.Schema({
     vol.Required("instance"): cv.string,
@@ -90,19 +93,18 @@ def get_coordinator_by_instance(hass: HomeAssistant, instance: str) -> HATextAIC
 
     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, {})
+def get_file_hash(file_path: str) -> str:
+    """Calculate SHA256 hash of file."""
+    sha256_hash = hashlib.sha256()
+    with open(file_path, "rb") as f:
+        for byte_block in iter(lambda: f.read(4096), b""):
+            sha256_hash.update(byte_block)
+    return sha256_hash.hexdigest()
 
-    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_setup(hass: HomeAssistant, config: ConfigType) -> bool:
+    """Set up the Home Assistant Text AI component."""
+    # Initialize domain data storage
+    hass.data.setdefault(DOMAIN, {})
 
     async def async_ask_question(call: ServiceCall) -> None:
         """Handle ask_question service."""
@@ -150,6 +152,7 @@ async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
             _LOGGER.error("Error setting system prompt: %s", str(err))
             raise HomeAssistantError(f"Failed to set system prompt: {str(err)}")
 
+    # Register services
     hass.services.async_register(
         DOMAIN,
         SERVICE_ASK_QUESTION,
@@ -178,6 +181,53 @@ async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
         schema=SERVICE_SCHEMA_SET_SYSTEM_PROMPT
     )
 
+    # Handle icons
+    try:
+        source_icon_path = os.path.join(
+            os.path.dirname(__file__),
+            ICONS_SUBDOMAIN,
+            'icon@2x.png'
+        )
+
+        destination_directory = os.path.join(
+            hass.config.path('www'),
+            DOMAIN,
+            ICONS_SUBDOMAIN
+        )
+
+        destination_icon_path = os.path.join(
+            destination_directory,
+            'icon.png'
+        )
+
+        if not os.path.exists(source_icon_path):
+            _LOGGER.error("Source icon not found: %s", source_icon_path)
+            return True
+
+        def create_directory():
+            os.makedirs(destination_directory, exist_ok=True)
+
+        await hass.async_add_executor_job(create_directory)
+
+        should_copy = True
+
+        if os.path.exists(destination_icon_path):
+            source_hash = await hass.async_add_executor_job(get_file_hash, source_icon_path)
+            dest_hash = await hass.async_add_executor_job(get_file_hash, destination_icon_path)
+            should_copy = source_hash != dest_hash
+
+        if should_copy:
+            def copy_file():
+                shutil.copyfile(source_icon_path, destination_icon_path)
+
+            await hass.async_add_executor_job(copy_file)
+            _LOGGER.debug("Icon updated: %s", destination_icon_path)
+
+    except PermissionError as e:
+        _LOGGER.error("Permission denied when managing icons: %s", str(e))
+    except Exception as e:
+        _LOGGER.error("Failed to manage icons: %s", str(e))
+
     return True
 
 async def async_check_api(session, endpoint: str, headers: dict, provider: str) -> bool:

custom_components/ha_text_ai/const.py

@@ -41,7 +41,9 @@ CONF_IS_ANTHROPIC: Final = "is_anthropic"
 CONF_CONTEXT_MESSAGES: Final = "context_messages"
 
 ABSOLUTE_MAX_HISTORY_SIZE = 500
-MAX_ENTRY_SIZE = 1 * 1024 * 1024
+MAX_ATTRIBUTE_SIZE = 4 * 1024
+MAX_HISTORY_FILE_SIZE = 1 * 1024 * 1024
+ICONS_SUBDOMAIN = "icons"
 
 # Default values
 DEFAULT_MODEL: Final = "gpt-4o-mini"

custom_components/ha_text_ai/manifest.json

@@ -13,16 +13,16 @@
   "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"
-  ],
+    "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": [],
   "usb": [],
-  "version": "2.0.5-beta",
+  "version": "2.0.8",
   "zeroconf": []
 }

custom_components/ha_text_ai/sensor.py

@@ -67,6 +67,7 @@ from .const import (
     ENTITY_ICON_PROCESSING,
     DEFAULT_NAME_PREFIX,
     CONF_MAX_HISTORY_SIZE,
+    MAX_ATTRIBUTE_SIZE,
 )
 
 from .coordinator import HATextAICoordinator
@@ -178,12 +179,29 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
 
     def _sanitize_attributes(self, attributes: Dict[str, Any]) -> Dict[str, Any]:
         """Sanitize all attributes for JSON serialization."""
-        return {
+        sanitized = {
             key: self._sanitize_value(value)
             for key, value in attributes.items()
             if value is not None
         }
 
+        # Log metrics for debugging
+        metrics_keys = [
+            METRIC_TOTAL_TOKENS,
+            METRIC_PROMPT_TOKENS,
+            METRIC_COMPLETION_TOKENS,
+            METRIC_SUCCESSFUL_REQUESTS,
+            METRIC_FAILED_REQUESTS,
+            METRIC_AVERAGE_LATENCY,
+            METRIC_MAX_LATENCY,
+            METRIC_MIN_LATENCY,
+        ]
+
+        metrics_values = {k: sanitized.get(k) for k in metrics_keys if k in sanitized}
+        _LOGGER.debug(f"Metrics for {self.entity_id}: {metrics_values}")
+
+        return sanitized
+
     @property
     def native_value(self) -> StateType:
         """Return the native value of the sensor."""
@@ -212,68 +230,65 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
 
         try:
             data = self.coordinator.data
+            metrics = data.get("metrics", {})
+
+            # Base attributes
             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_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,
+                ATTR_TOTAL_ERRORS: metrics.get("total_errors", 0),
                 "instance_name": self._instance_name,
                 "normalized_name": self._normalized_name,
-                ATTR_SYSTEM_PROMPT: data.get("system_prompt"),
+                ATTR_SYSTEM_PROMPT: (data.get("system_prompt", "")[:MAX_ATTRIBUTE_SIZE]
+                                   if data.get("system_prompt") else None),
                 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_UPTIME: round(data.get("uptime", 0), 2),
                 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")),
+            # History limit
+            conversation_history = data.get("conversation_history", [])
+            if conversation_history:
+                limited_history = []
+                for entry in conversation_history:
+                    limited_entry = {
+                        "timestamp": entry["timestamp"],
+                        "question": entry["question"][:MAX_ATTRIBUTE_SIZE],
+                        "response": entry["response"][:MAX_ATTRIBUTE_SIZE]
                     }
-                )
+                    limited_history.append(limited_entry)
+                attributes[ATTR_CONVERSATION_HISTORY] = limited_history
 
-            # Add last response
+            # Metrics
+            if isinstance(metrics, dict):
+                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: round(metrics.get("average_latency", 0), 2),
+                    METRIC_MAX_LATENCY: round(metrics.get("max_latency", 0), 2),
+                    METRIC_MIN_LATENCY: (metrics.get("min_latency")
+                                       if metrics.get("min_latency") != float("inf")
+                                       else None),
+                })
+
+            # Last response handling
             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]
+                attributes.update({
+                    ATTR_RESPONSE: last_response.get("response", "")[:MAX_ATTRIBUTE_SIZE],
+                    ATTR_QUESTION: last_response.get("question", "")[:MAX_ATTRIBUTE_SIZE],
+                    "last_model": last_response.get("model", ""),
+                    "last_timestamp": last_response.get("timestamp", ""),
+                    "last_error": (last_response.get("error", "")[:MAX_ATTRIBUTE_SIZE]
+                                 if last_response.get("error") else None),
+                })
 
             return self._sanitize_attributes(attributes)
 
@@ -299,6 +314,12 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
 
             self._is_processing = data.get("is_processing", False)
 
+            # Update metrics
+            metrics = data.get("metrics", {})
+            if isinstance(metrics, dict):
+                self._metrics.update(metrics)
+                _LOGGER.debug(f"Updated metrics for {self.entity_id}: {self._metrics}")
+
             # Update conversation history and system prompt
             self._conversation_history = data.get("conversation_history", [])
             self._system_prompt = data.get("system_prompt")

custom_components/ha_text_ai/translations/es.json

@@ -95,7 +95,7 @@
   },
   "services": {
     "ask_question": {
-      "name": "Hacer Pregunta (IA de Texto de HA)",
+      "name": "Hacer Pregunta (HA Text AI)",
       "description": "Envía una pregunta al modelo de IA y recibe una respuesta detallada. La respuesta se almacenará en el historial de conversación y se podrá recuperar más tarde.",
       "fields": {
         "instance": {

custom_components/ha_text_ai/translations/hi.json

@@ -95,7 +95,7 @@
   },
   "services": {
     "ask_question": {
-      "name": "प्रश्न पूछें (एचए टेक्स्ट एआई)",
+      "name": "प्रश्न पूछें (HA Text AI)",
       "description": "एआई मॉडल को एक प्रश्न भेजें और विस्तृत प्रतिक्रिया प्राप्त करें। प्रतिक्रिया बातचीत के इतिहास में संग्रहीत की जाएगी और बाद में पुनर्प्राप्त की जा सकती है।",
       "fields": {
         "instance": {

custom_components/ha_text_ai/translations/ru.json

@@ -95,7 +95,7 @@
   },
   "services": {
     "ask_question": {
-      "name": "Задать вопрос (Текстовый ИИ HA)",
+      "name": "Задать вопрос (HA Text AI)",
       "description": "Отправить вопрос модели ИИ и получить подробный ответ. Ответ будет сохранен в истории разговора и может быть получен позже.",
       "fields": {
         "instance": {

custom_components/ha_text_ai/translations/zh.json

@@ -95,7 +95,7 @@
   },
   "services": {
     "ask_question": {
-      "name": "提问（HA文本AI）",
+      "name": "提问 (HA Text AI)",
       "description": "向AI模型发送问题并接收详细响应。响应将存储在对话历史中，可以稍后检索。",
       "fields": {
         "instance": {

structure.md

@@ -1,25 +1,30 @@
 ```
-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
+ha_text_ai/
+├── __init__.py
+├── api_client.py
+├── config_flow.py
+├── const.py
+├── coordinator.py
+├── icons
+│   ├── dark_icon.png
+│   ├── dark_icon@2x.png
+│   ├── dark_logo.png
+│   ├── dark_logo@2x.png
+│   ├── icon.png
+│   ├── icon@2x.png
+│   ├── logo.png
+│   └── logo@2x.png
+├── manifest.json
+├── sensor.py
+├── services.yaml
+└── translations
+    ├── de.json
+    ├── en.json
+    ├── es.json
+    ├── hi.json
+    ├── it.json
+    ├── ru.json
+    ├── sr.json
+    └── zh.json
+
 ```