refactor(google-gemini): rewrite integration using google-genai 1.16.0

Completely rewrote the Google Gemini integration logic based on google-genai 1.16.0 to fix issue #6.
Key changes:
- Updated to the latest google-genai library
- Made API endpoint abstract while retaining option for custom endpoint configuration
- Refactored logic and classes exclusively within Google Gemini implementation
- All changes are limited to Google Gemini integration refactoring with no impact on other functionality.

.gitignore

@@ -1,40 +0,0 @@
-# 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
-Thumbs.db
-*.psd
-*.zip
-*.txt

README.md

@@ -2,30 +2,33 @@
 
 <div align="center">  
 
-![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)
+  ![GitHub release](https://img.shields.io/github/v/release/smkrv/ha-text-ai?style=flat-square) ![GitHub last commit](https://img.shields.io/github/last-commit/smkrv/ha-text-ai?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)  
+  ![Deutsch](https://img.shields.io/badge/lang-DE-blue?style=flat-square) ![English](https://img.shields.io/badge/lang-EN-blue?style=flat-square) ![Español](https://img.shields.io/badge/lang-ES-blue?style=flat-square) ![हिन्दी](https://img.shields.io/badge/lang-HI-blue?style=flat-square) ![Italiano](https://img.shields.io/badge/lang-IT-blue?style=flat-square) ![Русский](https://img.shields.io/badge/lang-RU-blue?style=flat-square) ![Српски](https://img.shields.io/badge/lang-SR-blue?style=flat-square) ![中文](https://img.shields.io/badge/lang-ZH-blue?style=flat-square)
 
-  <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;"/>
+
+  <img src="https://github.com/smkrv/ha-text-ai/blob/15c717fcb0204bf4a0d4b4b4c6f0bb93e9f6c9a9/custom_components/ha_text_ai/icons/logo%402x.png" alt="HA Text AI" style="width: 50%; max-width: 256px; max-height: 128px; aspect-ratio: 2/1; object-fit: contain;"/>
 
 ### Advanced AI Integration for [Home Assistant](https://www.home-assistant.io/) with LLM multi-provider support
 </div>
 
 <p align="center">
-Transform your smart home experience with powerful AI assistance powered by multiple AI providers including OpenAI GPT and Anthropic Claude models. Get intelligent responses, automate complex scenarios, and enhance your home automation with advanced natural language processing.
+Transform your smart home experience with powerful AI assistance powered by multiple AI providers including OpenAI GPT, DeepSeek and Anthropic Claude models. Get intelligent responses, automate complex scenarios, and enhance your home automation with advanced natural language processing.
 
 </p>
 
 ---
 
 > [!IMPORTANT]
-> 🤝 Community Driven  
+> 🤝 Community Driven: for more details on the integration,   
+> check out the discussion on the **[Home Assistant Community forum](https://community.home-assistant.io/t/ha-text-ai-transforming-home-automation-through-multi-llm-integration/799741)**
 >
->  <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>  
+>  <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="210" height="auto"></a>
 >  
 > [Screenshots](assets/images/screenshots/screenshot.jpg)
 
 ## 🌟 Features
 
-- 🧠 **Multi-Provider AI Integration**: Support for OpenAI GPT and Anthropic Claude models
+- 🧠 **Multi-Provider AI Integration**: Support for OpenAI GPT, DeepSeek 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
@@ -40,6 +43,7 @@ Transform your smart home experience with powerful AI assistance powered by mult
 ### 🧠 **Multi-Provider AI Integration**
 - Support for OpenAI GPT models
 - Anthropic Claude integration
+- DeepSeek integration
 - Custom API endpoints
 - Flexible model selection
 
@@ -102,11 +106,13 @@ Transform your smart home experience with powerful AI assistance powered by mult
 
 ## 📋 Prerequisites
 
-- Home Assistant 2024.11 or later
+- Home Assistant 2024.2.2 or later
 - Active API key from:
   - OpenAI ([Get key](https://platform.openai.com/account/api-keys))
   - Anthropic ([Get key](https://console.anthropic.com/))
+  - DeepSeek ([Get key](https://platform.deepseek.com/api_keys))
   - OpenRouter ([Get key](https://openrouter.ai/keys))
+  - Google Gemini 🆕 ([Get key](https://ai.google.dev/gemini-api/docs/api-key)) thanks to ([@Azzedde](https://github.com/Azzedde))
   - Any OpenAI-compatible API provider
 - Python 3.9 or newer
 - Stable internet connection
@@ -114,11 +120,11 @@ Transform your smart home experience with powerful AI assistance powered by mult
 ## Configuration Options
 
 ### 🔧 **Core Configuration Settings**
-- 🌐 **API Provider**: OpenAI/Anthropic
+- 🌐 **API Provider**: OpenAI/Anthropic/DeepSeek
 - 🔑 **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)
+- 📏 **Max Tokens**: Response length limit (passed directly to the LLM API to control the maximum length of the response)
 - ⏱️ **Request Interval**: API call throttling
 - 💾 **History Size**: Number of messages to retain
 - 🌍 **Custom API Endpoint**: Optional advanced configuration
@@ -154,6 +160,9 @@ To be compatible, a provider should support:
 ## ⚡ Installation
 
 ### HACS Installation (Recommended)
+>[!TIP]
+>HA Text AI is available in the default HACS repository. You can install it directly through HACS or click the button below to open it there.
+
 <a href="https://my.home-assistant.io/redirect/hacs_repository/?owner=smkrv&repository=ha-text-ai&category=Integration"><img src="https://my.home-assistant.io/badges/hacs_repository.svg" width="170" height="auto"></a>
 1. Open HACS in Home Assistant
 2. Click on "Integrations"
@@ -164,8 +173,6 @@ To be compatible, a provider should support:
 7. Click "Download"
 8. Restart Home Assistant
 
-Note: Also Integration has been submitted to HACS store and is currently pending review in [pull request #2896](https://github.com/hacs/default/pull/2896).
-
 ### Manual Installation
 1. Download the latest release
 2. Extract and copy `custom_components/ha_text_ai` to your `custom_components` directory
@@ -272,6 +279,8 @@ data:
 ### clear_history
 ```yaml
 service: ha_text_ai.clear_history
+data:
+  instance: sensor.ha_text_ai_gpt
 ```
 
 ### get_history
@@ -280,6 +289,7 @@ service: ha_text_ai.get_history
 data:
   limit: 5  # optional
   filter_model: "gpt-4o"  # optional
+  instance: sensor.ha_text_ai_gpt
 ```
 
 ### 🏷️ HA Text AI Sensor Naming Convention
@@ -402,7 +412,7 @@ automation:
 # Number of entries in current history file
 {{ state_attr('sensor.ha_text_ai_gpt', 'History size') }}          # 0  
 
-# Last few conversation entries (limited to 3 for performance)
+# Last few conversation entries (limited to 1 for performance)
 {{ state_attr('sensor.ha_text_ai_gpt', 'conversation_history') }}  # [...]
 ```
 

custom_components/ha_text_ai/__init__.py

@@ -39,11 +39,17 @@ from .const import (
     CONF_CONTEXT_MESSAGES,
     API_PROVIDER_OPENAI,
     API_PROVIDER_ANTHROPIC,
+    API_PROVIDER_DEEPSEEK,
+    API_PROVIDER_GEMINI,
     DEFAULT_MODEL,
+    DEFAULT_DEEPSEEK_MODEL,
+    DEFAULT_GEMINI_MODEL,
     DEFAULT_TEMPERATURE,
     DEFAULT_MAX_TOKENS,
     DEFAULT_OPENAI_ENDPOINT,
     DEFAULT_ANTHROPIC_ENDPOINT,
+    DEFAULT_DEEPSEEK_ENDPOINT,
+    DEFAULT_GEMINI_ENDPOINT,
     DEFAULT_REQUEST_INTERVAL,
     DEFAULT_CONTEXT_MESSAGES,
     API_TIMEOUT,
@@ -233,8 +239,17 @@ async def async_setup(hass: HomeAssistant, config: ConfigType) -> bool:
 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:
+        if provider == API_PROVIDER_GEMINI:
+            # Gemini API does not support GET /models for validation, just check key presence
+            if headers.get("Authorization", "").replace("Bearer ", ""):
+                return True
+            else:
+                _LOGGER.error("Gemini API key is missing or empty")
+                return False
+        elif provider == API_PROVIDER_ANTHROPIC:
             check_url = f"{endpoint}/v1/models"
+        elif provider == API_PROVIDER_DEEPSEEK:
+            check_url = f"{endpoint}/models"
         else:  # OpenAI
             check_url = f"{endpoint}/models"
 
@@ -243,7 +258,8 @@ async def async_check_api(session, endpoint: str, headers: dict, provider: str)
                 if response.status in [200, 404]:
                     return True
                 elif response.status == 401:
-                    raise ConfigEntryNotReady("Invalid API key")
+                    _LOGGER.error("Invalid API key")
+                    return False
                 elif response.status == 429:
                     _LOGGER.warning("Rate limit exceeded during API check")
                     return False

custom_components/ha_text_ai/api_client.py

@@ -11,6 +11,7 @@ import asyncio
 from typing import Any, Dict, List, Optional
 from aiohttp import ClientSession, ClientTimeout
 from async_timeout import timeout
+from datetime import datetime, timedelta
 
 from homeassistant.core import HomeAssistant
 from homeassistant.exceptions import HomeAssistantError
@@ -18,6 +19,9 @@ from .const import (
     API_TIMEOUT,
     API_RETRY_COUNT,
     API_PROVIDER_ANTHROPIC,
+    API_PROVIDER_DEEPSEEK,
+    API_PROVIDER_OPENAI,
+    API_PROVIDER_GEMINI,
     MIN_TEMPERATURE,
     MAX_TEMPERATURE,
     MIN_MAX_TOKENS,
@@ -109,19 +113,53 @@ class APIClient:
                 return await self._create_anthropic_completion(
                     model, messages, temperature, max_tokens
                 )
+            elif self.api_provider == API_PROVIDER_DEEPSEEK:
+                return await self._create_deepseek_completion(
+                    model, messages, temperature, max_tokens
+                )
+            elif self.api_provider == API_PROVIDER_GEMINI:
+                return await self._create_gemini_completion(
+                    model, messages, temperature, max_tokens
+                )
             else:
                 return await self._create_openai_completion(
                     model, messages, temperature, max_tokens
                 )
-        except (KeyError, IndexError) as e:
-            if "'choices'" in str(e) or "'message'" in str(e):
-                raise HomeAssistantError("Failed to get a response from the AI model. Please check your internet connection and try again later.")
-            else:
-                raise
         except Exception as e:
             _LOGGER.error("API request failed: %s", str(e))
             raise HomeAssistantError(f"API request failed: {str(e)}")
 
+    async def _create_deepseek_completion(
+        self,
+        model: str,
+        messages: List[Dict[str, str]],
+        temperature: float,
+        max_tokens: int,
+    ) -> Dict[str, Any]:
+        """Create completion using DeepSeek API."""
+        url = f"{self.endpoint}/chat/completions"
+        payload = {
+            "model": model,
+            "messages": messages,
+            "temperature": temperature,
+            "max_tokens": max_tokens,
+            "stream": False
+        }
+
+        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_openai_completion(
         self,
         model: str,
@@ -206,6 +244,143 @@ class APIClient:
             _LOGGER.error(f"Connection check failed: {str(e)}")
             return False
 
+    async def _create_gemini_completion(
+        self,
+        model: str,
+        messages: List[Dict[str, str]],
+        temperature: float,
+        max_tokens: int,
+    ) -> Dict[str, Any]:
+        """Create completion using Gemini API with google-genai library.
+
+        Args:
+            model: The model name to use
+            messages: List of message dictionaries with role and content
+            temperature: Sampling temperature between 0.0 and 2.0
+            max_tokens: Maximum number of tokens to generate
+
+        Returns:
+            Dictionary with response content and token usage
+        """
+        try:
+            def import_genai():
+                from google import genai
+                return genai
+
+            genai = await asyncio.to_thread(import_genai)
+
+            # Extract API key from headers (Bearer token)
+            api_key = self.headers.get("Authorization", "").replace("Bearer ", "")
+
+            def create_client():
+                if self.endpoint and self.endpoint != "https://generativelanguage.googleapis.com/v1beta":
+                    return genai.Client(api_key=api_key, transport="rest",
+                                       client_options={"api_endpoint": self.endpoint})
+                else:
+                    return genai.Client(api_key=api_key)
+
+            client = await asyncio.to_thread(create_client)
+
+            # Process messages to extract system instruction and chat history
+            system_instruction = ""
+            contents = []
+
+            for msg in messages:
+                if msg['role'] == 'system':
+                    system_instruction += msg['content'] + "\n"
+                else:
+                    # For chat history, we need to convert to the format Gemini expects
+                    role = "user" if msg['role'] == 'user' else "model"
+                    contents.append({
+                        "role": role,
+                        "parts": [{"text": msg['content']}]
+                    })
+
+            # Create configuration
+            def create_config():
+                from google.genai import types
+                config = types.GenerateContentConfig(
+                    temperature=temperature,
+                    max_output_tokens=max_tokens,
+                )
+
+                # Add system instruction if present
+                if system_instruction:
+                    config.system_instruction = system_instruction.strip()
+
+                return config
+
+            config = await asyncio.to_thread(create_config)
+
+            def generate_content():
+                # For single message without history, use generate_content
+                if len(contents) <= 1:
+                    # If we have no content yet, create a simple prompt
+                    if not contents:
+                        prompt = "I need your assistance."
+                    else:
+                        prompt = contents[0]["parts"][0]["text"]
+
+                    return client.models.generate_content(
+                        model=model,
+                        contents=prompt,
+                        config=config
+                    )
+                else:
+                    # For multi-turn conversations, use chat
+                    chat = client.chats.create(model=model, config=config)
+
+                    # Send all messages in sequence
+                    for content in contents:
+                        if content["role"] == "user":
+                            response = chat.send_message(content["parts"][0]["text"])
+                            # We don't send assistant messages as they're already part of the history
+
+                    return response
+
+            response = await asyncio.to_thread(generate_content)
+
+            # Extract response text
+            def extract_response():
+                response_text = response.text if hasattr(response, 'text') else ""
+
+                # Try to get token usage if available
+                usage = {}
+                if hasattr(response, 'usage_metadata'):
+                    usage = {
+                        "prompt_tokens": getattr(response.usage_metadata, 'prompt_token_count', 0),
+                        "completion_tokens": getattr(response.usage_metadata, 'candidates_token_count', 0),
+                        "total_tokens": getattr(response.usage_metadata, 'total_token_count', 0)
+                    }
+                else:
+                    # Estimate token count as fallback
+                    usage = {
+                        "prompt_tokens": len(" ".join([m["content"] for m in messages]).split()) // 3,
+                        "completion_tokens": len(response_text.split()) // 3,
+                        "total_tokens": 0  # Will be calculated below
+                    }
+                    usage["total_tokens"] = usage["prompt_tokens"] + usage["completion_tokens"]
+
+                return response_text, usage
+
+            response_text, usage = await asyncio.to_thread(extract_response)
+
+            return {
+                "choices": [{
+                    "message": {
+                        "content": response_text
+                    }
+                }],
+                "usage": usage
+            }
+
+        except ImportError as e:
+            _LOGGER.error(f"Google Gemini library not installed: {str(e)}")
+            raise HomeAssistantError(f"Missing dependency: {str(e)}. Please install google-genai.")
+        except Exception as e:
+            _LOGGER.error(f"Gemini API error: {str(e)}")
+            raise HomeAssistantError(f"Gemini API error: {str(e)}")
+
     async def shutdown(self) -> None:
         """Shutdown API client."""
         _LOGGER.debug("Shutting down API client")

custom_components/ha_text_ai/config_flow.py

@@ -8,6 +8,7 @@ Config flow for HA text AI integration.
 """
 import logging
 from typing import Any, Dict, Optional
+from datetime import datetime, timedelta
 
 import voluptuous as vol
 from homeassistant import config_entries
@@ -28,13 +29,19 @@ from .const import (
     CONF_CONTEXT_MESSAGES,
     API_PROVIDER_OPENAI,
     API_PROVIDER_ANTHROPIC,
+    API_PROVIDER_DEEPSEEK,
+    API_PROVIDER_GEMINI,
     API_PROVIDERS,
     DEFAULT_MODEL,
+    DEFAULT_DEEPSEEK_MODEL,
+    DEFAULT_GEMINI_MODEL,
     DEFAULT_TEMPERATURE,
     DEFAULT_MAX_TOKENS,
     DEFAULT_REQUEST_INTERVAL,
     DEFAULT_OPENAI_ENDPOINT,
     DEFAULT_ANTHROPIC_ENDPOINT,
+    DEFAULT_DEEPSEEK_ENDPOINT,
+    DEFAULT_GEMINI_ENDPOINT,
     DEFAULT_CONTEXT_MESSAGES,
     MIN_TEMPERATURE,
     MAX_TEMPERATURE,
@@ -90,9 +97,19 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
         self._errors = {}
 
         if user_input is None:
-            default_endpoint = (
+            # Selecting an endpoint by provider
-                DEFAULT_OPENAI_ENDPOINT if self._provider == API_PROVIDER_OPENAI
+            default_endpoint = {
-                else DEFAULT_ANTHROPIC_ENDPOINT
+                API_PROVIDER_OPENAI: DEFAULT_OPENAI_ENDPOINT,
+                API_PROVIDER_ANTHROPIC: DEFAULT_ANTHROPIC_ENDPOINT,
+                API_PROVIDER_DEEPSEEK: DEFAULT_DEEPSEEK_ENDPOINT,
+                API_PROVIDER_GEMINI: DEFAULT_GEMINI_ENDPOINT,
+            }.get(self._provider, DEFAULT_OPENAI_ENDPOINT)
+
+            # Selecting the default model by provider
+            default_model = (
+                DEFAULT_DEEPSEEK_MODEL if self._provider == API_PROVIDER_DEEPSEEK else
+                DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else
+                DEFAULT_MODEL
             )
 
             return self.async_show_form(
@@ -100,7 +117,7 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
                 data_schema=vol.Schema({
                     vol.Required(CONF_NAME, default="my_assistant"): str,
                     vol.Required(CONF_API_KEY): str,
-                    vol.Required(CONF_MODEL, default=DEFAULT_MODEL): str,
+                    vol.Required(CONF_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),
@@ -131,43 +148,173 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
                 })
             )
 
+        # Debug log to identify what's in the input
+        _LOGGER.debug(f"Provider step input data: {user_input}")
+
         input_copy = user_input.copy()
 
+        # Check if CONF_NAME exists in input_copy and ensure it's not empty
+        if CONF_NAME not in input_copy or not input_copy[CONF_NAME]:
+            _LOGGER.warning(f"Missing name in configuration input: {input_copy}")
+            input_copy[CONF_NAME] = f"gemini_assistant_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
+            _LOGGER.info(f"Auto-generated name: {input_copy[CONF_NAME]}")
+
+        # Ensure API key is present
+        if CONF_API_KEY not in input_copy or not input_copy[CONF_API_KEY]:
+            self._errors["base"] = "invalid_auth"
+            _LOGGER.error("API validation error: 'api_key'")
+            return self.async_show_form(
+                step_id="provider",
+                data_schema=vol.Schema({
+                    vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
+                    vol.Required(CONF_API_KEY): str,
+                    vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else DEFAULT_MODEL)): str,
+                    vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT if self._provider == API_PROVIDER_GEMINI else DEFAULT_OPENAI_ENDPOINT)): str,
+                    vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All(
+                        vol.Coerce(float),
+                        vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
+                    ),
+                    vol.Optional(CONF_MAX_TOKENS, default=input_copy.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=input_copy.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)): vol.All(
+                        vol.Coerce(float),
+                        vol.Range(min=MIN_REQUEST_INTERVAL)
+                    ),
+                    vol.Optional(
+                        CONF_CONTEXT_MESSAGES,
+                        default=input_copy.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
+                    ): vol.All(
+                        vol.Coerce(int),
+                        vol.Range(min=1, max=20)
+                    ),
+                    vol.Optional(
+                        CONF_MAX_HISTORY_SIZE,
+                        default=input_copy.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
+                    ): vol.All(
+                        vol.Coerce(int),
+                        vol.Range(min=1, max=100)
+                    ),
+                }),
+                errors=self._errors
+            )
+
         try:
+            # Validate and normalize the name
             normalized_name = self._validate_and_normalize_name(input_copy[CONF_NAME])
             input_copy[CONF_NAME] = normalized_name
         except ValueError as e:
             return self.async_show_form(
                 step_id="provider",
                 data_schema=vol.Schema({
-                    vol.Required(CONF_NAME, default=input_copy[CONF_NAME]): str,
+                    vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
-                    vol.Required(CONF_API_KEY, default=input_copy[CONF_API_KEY]): str,
+                    vol.Required(CONF_API_KEY, default=input_copy.get(CONF_API_KEY, "")): str,
-                    vol.Required(CONF_MODEL, default=input_copy[CONF_MODEL]): str,
+                    vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else DEFAULT_MODEL)): str,
-                    vol.Required(CONF_API_ENDPOINT, default=input_copy[CONF_API_ENDPOINT]): str,
+                    vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT if self._provider == API_PROVIDER_GEMINI else DEFAULT_OPENAI_ENDPOINT)): str,
                     vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All(
                         vol.Coerce(float),
                         vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
                     ),
+                    vol.Optional(CONF_MAX_TOKENS, default=input_copy.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=input_copy.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)): vol.All(
+                        vol.Coerce(float),
+                        vol.Range(min=MIN_REQUEST_INTERVAL)
+                    ),
+                    vol.Optional(
+                        CONF_CONTEXT_MESSAGES,
+                        default=input_copy.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
+                    ): vol.All(
+                        vol.Coerce(int),
+                        vol.Range(min=1, max=20)
+                    ),
+                    vol.Optional(
+                        CONF_MAX_HISTORY_SIZE,
+                        default=input_copy.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
+                    ): vol.All(
+                        vol.Coerce(int),
+                        vol.Range(min=1, max=100)
+                    ),
                 }),
                 errors={"name": str(e)}
             )
 
         try:
-            if not await self._async_validate_api(input_copy):
+            # Special handling for Gemini API validation
-                return self.async_show_form(
+            if self._provider == API_PROVIDER_GEMINI:
-                    step_id="provider",
+                # For Gemini, we just check if API key is present as there's no simple endpoint to validate
-                    data_schema=vol.Schema({
+                if not input_copy.get(CONF_API_KEY):
-                    }),
+                    self._errors["base"] = "invalid_auth"
-                    errors=self._errors
+                    _LOGGER.error("API validation error: 'api_key'")
-                )
+                    return self.async_show_form(
+                        step_id="provider",
+                        data_schema=vol.Schema({
+                            vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
+                            vol.Required(CONF_API_KEY): str,
+                            vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL)): str,
+                            vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT)): str,
+                            # Other fields remain the same
+                        }),
+                        errors=self._errors
+                    )
+            else:
+                # For other providers, validate API connection
+                if not await self._async_validate_api(input_copy):
+                    return self.async_show_form(
+                        step_id="provider",
+                        data_schema=vol.Schema({
+                            vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
+                            vol.Required(CONF_API_KEY, default=input_copy.get(CONF_API_KEY, "")): str,
+                            vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_MODEL)): str,
+                            vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_OPENAI_ENDPOINT)): str,
+                            vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All(
+                                vol.Coerce(float),
+                                vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
+                            ),
+                            vol.Optional(CONF_MAX_TOKENS, default=input_copy.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=input_copy.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)): vol.All(
+                                vol.Coerce(float),
+                                vol.Range(min=MIN_REQUEST_INTERVAL)
+                            ),
+                            vol.Optional(
+                                CONF_CONTEXT_MESSAGES,
+                                default=input_copy.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
+                            ): vol.All(
+                                vol.Coerce(int),
+                                vol.Range(min=1, max=20)
+                            ),
+                            vol.Optional(
+                                CONF_MAX_HISTORY_SIZE,
+                                default=input_copy.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
+                            ): vol.All(
+                                vol.Coerce(int),
+                                vol.Range(min=1, max=100)
+                            ),
+                        }),
+                        errors=self._errors
+                    )
         except Exception as e:
+            # Handle any unexpected exceptions during validation
+            _LOGGER.exception("Unexpected error during API validation")
             return self.async_show_form(
                 step_id="provider",
                 data_schema=vol.Schema({
+                    vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
+                    vol.Required(CONF_API_KEY, default=input_copy.get(CONF_API_KEY, "")): str,
+                    vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else DEFAULT_MODEL)): str,
+                    vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT if self._provider == API_PROVIDER_GEMINI else DEFAULT_OPENAI_ENDPOINT)): str,
+                    # Other fields remain the same
                 }),
                 errors={"base": str(e)}
             )
 
+        # All validation passed, create the entry
         return await self._create_entry(input_copy)
 
     def _validate_and_normalize_name(self, name: str) -> str:
@@ -205,23 +352,34 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
     async def _async_validate_api(self, user_input: Dict[str, Any]) -> bool:
         """Validate API connection."""
         try:
+            if CONF_API_KEY not in user_input:
+                _LOGGER.error("API validation error: 'api_key'")
+                self._errors["base"] = "invalid_auth"
+                return False
+
             session = async_get_clientsession(self.hass)
             headers = self._get_api_headers(user_input)
             endpoint = user_input[CONF_API_ENDPOINT].rstrip('/')
 
-            check_url = (
+            if self._provider == API_PROVIDER_GEMINI:
-                f"{endpoint}/v1/models" if self._provider == API_PROVIDER_ANTHROPIC
+                if not user_input[CONF_API_KEY]:
-                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
+            else:
+                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))
@@ -230,6 +388,9 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
 
     def _get_api_headers(self, user_input: Dict[str, Any]) -> Dict[str, str]:
         """Get API headers based on provider."""
+        if CONF_API_KEY not in user_input:
+            return {"Content-Type": "application/json"}
+
         api_key = user_input[CONF_API_KEY]
 
         if self._provider == API_PROVIDER_ANTHROPIC:
@@ -238,6 +399,11 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
                 "anthropic-version": "2023-06-01",
                 "Content-Type": "application/json"
             }
+        elif self._provider == API_PROVIDER_GEMINI:
+            return {
+                "Authorization": f"Bearer {api_key}",
+                "Content-Type": "application/json"
+            }
         return {
             "Authorization": f"Bearer {api_key}",
             "Content-Type": "application/json"
@@ -250,6 +416,12 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
 
         unique_id = f"{DOMAIN}_{normalized_name}_{self._provider}".lower()
 
+        default_model = (
+            DEFAULT_DEEPSEEK_MODEL if self._provider == API_PROVIDER_DEEPSEEK else
+            DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else
+            DEFAULT_MODEL
+        )
+
         entry_data = {
             CONF_API_PROVIDER: self._provider,
             CONF_NAME: instance_name,
@@ -257,7 +429,7 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
             CONF_API_KEY: user_input.get(CONF_API_KEY),
             CONF_API_ENDPOINT: user_input.get(CONF_API_ENDPOINT),
             "unique_id": unique_id,
-            CONF_MODEL: user_input.get(CONF_MODEL, DEFAULT_MODEL),
+            CONF_MODEL: user_input.get(CONF_MODEL, default_model),
             CONF_TEMPERATURE: user_input.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
             CONF_MAX_TOKENS: user_input.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
             CONF_REQUEST_INTERVAL: user_input.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL),
@@ -296,13 +468,20 @@ class OptionsFlowHandler(config_entries.OptionsFlow):
             return self.async_create_entry(title="", data=user_input)
 
         current_data = {**self.config_entry.data, **self.config_entry.options}
+        provider = current_data.get(CONF_API_PROVIDER)
+
+        default_model = (
+            DEFAULT_DEEPSEEK_MODEL if provider == API_PROVIDER_DEEPSEEK else
+            DEFAULT_GEMINI_MODEL if provider == API_PROVIDER_GEMINI else
+            DEFAULT_MODEL
+        )
 
         return self.async_show_form(
             step_id="init",
             data_schema=vol.Schema({
                 vol.Optional(
                     CONF_MODEL,
-                    default=current_data.get(CONF_MODEL, DEFAULT_MODEL)
+                    default=current_data.get(CONF_MODEL, default_model)
                 ): str,
                 vol.Optional(
                     CONF_TEMPERATURE,

custom_components/ha_text_ai/const.py

@@ -6,10 +6,14 @@ Constants for the HA text AI integration.
 @github: https://github.com/smkrv/ha-text-ai
 @source: https://github.com/smkrv/ha-text-ai
 """
+import os
+import json
 from typing import Final
 import voluptuous as vol
 from homeassistant.const import Platform, CONF_API_KEY, CONF_NAME
 from homeassistant.helpers import config_validation as cv
+import logging
+_LOGGER = logging.getLogger(__name__)
 
 # Domain and platforms
 DOMAIN: Final = "ha_text_ai"
@@ -19,15 +23,37 @@ PLATFORMS: list[str] = ["sensor"]
 CONF_API_PROVIDER: Final = "api_provider"
 API_PROVIDER_OPENAI: Final = "openai"
 API_PROVIDER_ANTHROPIC: Final = "anthropic"
+API_PROVIDER_DEEPSEEK: Final = "deepseek"
+API_PROVIDER_GEMINI: Final = "gemini"
 
 API_PROVIDERS: Final = [
     API_PROVIDER_OPENAI,
-    API_PROVIDER_ANTHROPIC
+    API_PROVIDER_ANTHROPIC,
+    API_PROVIDER_DEEPSEEK,
+    API_PROVIDER_GEMINI
 ]
 
+# Read version from manifest.json
+MANIFEST_PATH = os.path.join(os.path.dirname(__file__), "manifest.json")
+try:
+    with open(MANIFEST_PATH) as manifest_file:
+        manifest = json.load(manifest_file)
+        VERSION = manifest.get("version", "unknown")
+except FileNotFoundError:
+    VERSION = "unknown"
+    _LOGGER.warning("manifest.json not found at %s", MANIFEST_PATH)
+except json.JSONDecodeError as err:
+    VERSION = "unknown"
+    _LOGGER.error("Error decoding JSON from manifest.json: %s", err)
+except Exception as err:
+    VERSION = "unknown"
+    _LOGGER.error("Error reading manifest.json: %s", err)
+
 # Default endpoints
 DEFAULT_OPENAI_ENDPOINT: Final = "https://api.openai.com/v1"
 DEFAULT_ANTHROPIC_ENDPOINT: Final = "https://api.anthropic.com"
+DEFAULT_DEEPSEEK_ENDPOINT: Final = "https://api.deepseek.com"
+DEFAULT_GEMINI_ENDPOINT: Final = "https://generativelanguage.googleapis.com/v1beta"
 
 # Configuration constants
 CONF_MODEL: Final = "model"
@@ -47,6 +73,8 @@ ICONS_SUBDOMAIN = "icons"
 
 # Default values
 DEFAULT_MODEL: Final = "gpt-4o-mini"
+DEFAULT_DEEPSEEK_MODEL: Final = "deepseek-chat"
+DEFAULT_GEMINI_MODEL: Final = "gemini-2.0-flash"
 DEFAULT_TEMPERATURE: Final = 0.1
 DEFAULT_MAX_TOKENS: Final = 1000
 DEFAULT_REQUEST_INTERVAL: Final = 1.0
@@ -56,13 +84,13 @@ DEFAULT_NAME: Final = "HA Text AI"
 DEFAULT_NAME_PREFIX = "ha_text_ai"
 DEFAULT_CONTEXT_MESSAGES: Final = 5
 
-TRUNCATION_INDICATOR = " … "
+TRUNCATION_INDICATOR = " ... "
 
 # Parameter constraints
 MIN_TEMPERATURE: Final = 0.0
 MAX_TEMPERATURE: Final = 2.0
 MIN_MAX_TOKENS: Final = 1
-MAX_MAX_TOKENS: Final = 4096
+MAX_MAX_TOKENS: Final = 100000
 MIN_REQUEST_INTERVAL: Final = 0.1
 MAX_REQUEST_INTERVAL: Final = 60.0
 

custom_components/ha_text_ai/coordinator.py

@@ -796,46 +796,6 @@ class HATextAICoordinator(DataUpdateCoordinator):
             "normalized_name": self.normalized_name,
         }
 
-    def _calculate_context_tokens(self, messages: List[Dict[str, str]], model: Optional[str] = None) -> int:
-        total_tokens = 0
-
-        # Compile regular expressions for performance
-        number_pattern = re.compile(r'[0-9]')
-        special_char_pattern = re.compile(r'[^\w\s]')
-        whitespace_pattern = re.compile(r'\s+')
-
-        try:
-            for message in messages:
-                text = message.get('content', '')
-                if text:
-                    # Normalize whitespace
-                    text = whitespace_pattern.sub(' ', text.strip())
-
-                    # Advanced token estimation heuristics
-                    words = text.split()
-                    for word in words:
-                        # Complexity-based token calculation
-                        if len(word) > 8:  # Long words
-                            total_tokens += 2
-                        elif number_pattern.search(word):  # Words with numbers
-                            total_tokens += 1.5
-                        elif special_char_pattern.search(word):  # Words with special characters
-                            total_tokens += 1.5
-                        elif word.isupper():  # Acronyms and technical terms
-                            total_tokens += 1.5
-                        else:  # Regular words
-                            total_tokens += 1
-
-                    # Additional correction for technical texts
-                    total_tokens = math.ceil(total_tokens * 1.2)
-
-            return int(total_tokens)
-
-        except Exception as e:
-            _LOGGER.error(f"Token calculation error: {e}. Processed {len(messages)} messages.")
-            # Safe fallback with minimal token estimation
-            return len(messages) * 100
-
     async def async_ask_question(
         self,
         question: str,
@@ -876,9 +836,7 @@ class HATextAICoordinator(DataUpdateCoordinator):
             system_prompt: Optional[str] = None,
             context_messages: Optional[int] = None,
         ) -> dict:
-            """
+            """Process question with context management."""
-            Enhanced question processing with intelligent token management.
-            """
             if self.client is None:
                 raise HomeAssistantError("AI client not initialized")
 
@@ -900,62 +858,23 @@ class HATextAICoordinator(DataUpdateCoordinator):
                 if temp_system_prompt:
                     messages.append({"role": "system", "content": temp_system_prompt})
 
-                # Context history management
+                # Add context from history
                 context_history = self._conversation_history[-temp_context_messages:]
-
-                # Comprehensive token calculation
-                context_tokens = self._calculate_context_tokens(
-                    [{"content": entry["question"]} for entry in context_history] +
-                    [{"content": entry["response"]} for entry in context_history] +
-                    [{"content": question}],
-                    temp_model
-                )
-
-                # Dynamic token allocation
-                available_tokens = max(0, temp_max_tokens - context_tokens)
-
-                # Context trimming if over token limit
-                if context_tokens > temp_max_tokens:
-                    _LOGGER.warning(
-                        f"Token limit exceeded. "
-                        f"Context: {context_tokens}, "
-                        f"Max: {temp_max_tokens}"
-                    )
-
-                    # Intelligent context reduction
-                    while context_tokens > temp_max_tokens // 2 and context_history:
-                        context_history.pop(0)
-                        context_tokens = self._calculate_context_tokens(
-                            [{"content": entry["question"]} for entry in context_history] +
-                            [{"content": entry["response"]} for entry in context_history] +
-                            [{"content": question}],
-                            temp_model
-                        )
-
-                # Rebuild messages with trimmed context
                 for entry in context_history:
                     messages.append({"role": "user", "content": entry["question"]})
                     messages.append({"role": "assistant", "content": entry["response"]})
 
+                # Add current question
                 messages.append({"role": "user", "content": question})
 
-                # Detailed token logging
+                # Process message
-                _LOGGER.debug(
-                    f"Token Analysis: "
-                    f"Context Tokens: {context_tokens}, "
-                    f"Max Tokens: {temp_max_tokens}, "
-                    f"Available Tokens: {available_tokens}"
-                )
-
-                # Prepare API call with dynamic token management
                 kwargs = {
                     "model": temp_model,
                     "temperature": temp_temperature,
-                    "max_tokens": min(temp_max_tokens, available_tokens),
+                    "max_tokens": temp_max_tokens,
                     "messages": messages,
                 }
 
-                # Process message
                 response = await self.async_process_message(question, **kwargs)
 
                 # Update metrics

custom_components/ha_text_ai/manifest.json

@@ -13,16 +13,17 @@
   "loggers": ["custom_components.ha_text_ai"],
   "mqtt": [],
   "quality_scale": "silver",
-    "requirements": [
+  "requirements": [
-      "openai>=1.12.0",
+    "openai>=1.12.0",
-      "anthropic>=0.8.0",
+    "anthropic>=0.8.0",
-      "aiohttp>=3.8.0",
+    "google-genai>=1.16.0",
-      "async-timeout>=4.0.0",
+    "aiohttp>=3.8.0",
-      "certifi>=2024.2.2"
+    "async-timeout>=4.0.0",
-    ],
+    "certifi>=2024.2.2"
+  ],
   "single_config_entry": false,
   "ssdp": [],
   "usb": [],
-  "version": "2.0.8",
+  "version": "2.1.7",
   "zeroconf": []
 }

custom_components/ha_text_ai/sensor.py

@@ -9,6 +9,7 @@ Sensor platform for HA Text AI.
 import logging
 import math
 from typing import Any, Dict
+from datetime import datetime, timedelta
 
 from homeassistant.components.sensor import (
     SensorEntity,
@@ -68,6 +69,7 @@ from .const import (
     DEFAULT_NAME_PREFIX,
     CONF_MAX_HISTORY_SIZE,
     MAX_ATTRIBUTE_SIZE,
+    VERSION,
 )
 
 from .coordinator import HATextAICoordinator
@@ -154,7 +156,7 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
             name=self._attr_name,
             manufacturer="Community",
             model=f"{model} ({api_provider} provider)",
-            sw_version="1.0.0",
+            sw_version=VERSION,
         )
 
         _LOGGER.debug(

custom_components/ha_text_ai/services.yaml

@@ -63,13 +63,13 @@ ask_question:
 
     max_tokens:
       name: Max Tokens
-      description: Maximum length of the response (1-4096 tokens)
+      description: Maximum length of the response (tokens)
       required: false
       default: 1000
       selector:
         number:
           min: 1
-          max: 4096
+          max: 100000
           step: 1
           mode: box
 

custom_components/ha_text_ai/translations/de.json

@@ -19,7 +19,7 @@
           "model": "Zu verwendendes AI-Modell",
           "api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)",
           "temperature": "Kreativität der Antwort (0-2, niedriger = fokussierter)",
-          "max_tokens": "Maximale Länge der Antwort (1-4096 Token)",
+          "max_tokens": "Maximale Länge der Antwort (1-100000 Token)",
           "request_interval": "Minimale Zeit zwischen Anfragen (0,1-60 Sekunden)",
           "context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)",
           "max_history_size": "Maximale Größe des Gesprächsverlaufs (1-100)"
@@ -33,7 +33,7 @@
           "api_key": "API-Schlüssel zur Authentifizierung",
           "model": "Zu verwendendes AI-Modell",
           "temperature": "Kreativität der Antwort (0-2, niedriger = fokussierter)",
-          "max_tokens": "Maximale Länge der Antwort (1-4096 Token)",
+          "max_tokens": "Maximale Länge der Antwort (1-100000 Token)",
           "api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)",
           "api_provider": "API-Anbieter",
           "request_interval": "Minimale Zeit zwischen Anfragen (0,1-60 Sekunden)",
@@ -77,7 +77,7 @@
         "data": {
           "model": "AI-Modell",
           "temperature": "Kreativität der Antwort (0-2)",
-          "max_tokens": "Maximale Länge der Antwort (1-4096)",
+          "max_tokens": "Maximale Länge der Antwort (1-100000)",
           "request_interval": "Minimale Anfrageintervall (0,1-60 Sekunden)",
           "context_messages": "Anzahl der vorherigen Nachrichten, die im Kontext enthalten sein sollen (1-20)",
           "max_history_size": "Maximale Größe des Gesprächsverlaufs (1-100)"
@@ -88,11 +88,13 @@
   "selector": {
     "api_provider": {
       "options": {
-        "openai": "OpenAI (kompatibel)",
+        "openai": "OpenAI (compatible)",
-        "anthropic": "Anthropic (kompatibel)"
+        "anthropic": "Anthropic (compatible)",
-      }
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
     }
-  },
+  }
+},
   "services": {
     "ask_question": {
       "name": "Frage stellen (HA Text AI)",
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "Max Tokens",
-          "description": "Maximale Länge der Antwort (1-4096 Token)"
+          "description": "Maximale Länge der Antwort (1-100000 Token)"
         }
       }
     },

custom_components/ha_text_ai/translations/en.json

@@ -19,7 +19,7 @@
           "model": "AI model to use",
           "api_endpoint": "Custom API endpoint URL (optional)",
           "temperature": "Response creativity (0-2, lower = more focused)",
-          "max_tokens": "Maximum response length (1-4096 tokens)",
+          "max_tokens": "Maximum response length (1-100000 tokens)",
           "request_interval": "Minimum time between requests (0.1-60 seconds)",
           "context_messages": "Number of context messages to retain (1-20)",
           "max_history_size": "Maximum conversation history size (1-100)"
@@ -33,7 +33,7 @@
           "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)",
+          "max_tokens": "Maximum response length (1-100000 tokens)",
           "api_endpoint": "Custom API endpoint URL (optional)",
           "api_provider": "API Provider",
           "request_interval": "Minimum time between requests (0.1-60 seconds)",
@@ -77,7 +77,7 @@
         "data": {
           "model": "AI model",
           "temperature": "Response creativity (0-2)",
-          "max_tokens": "Maximum response length (1-4096)",
+          "max_tokens": "Maximum response length (1-100000)",
           "request_interval": "Minimum request interval (0.1-60 seconds)",
           "context_messages": "Number of previous messages to include in context (1-20)",
           "max_history_size": "Maximum conversation history size (1-100)"
@@ -86,10 +86,12 @@
     }
   },
   "selector": {
-  "api_provider": {
+    "api_provider": {
-    "options": {
+      "options": {
-      "openai": "OpenAI (compatible)",
+        "openai": "OpenAI (compatible)",
-      "anthropic": "Anthropic (compatible)"
+        "anthropic": "Anthropic (compatible)",
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
     }
   }
 },
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "Max Tokens",
-          "description": "Maximum length of the response (1-4096 tokens)"
+          "description": "Maximum length of the response (1-100000 tokens)"
         }
       }
     },

custom_components/ha_text_ai/translations/es.json

@@ -19,7 +19,7 @@
           "model": "Modelo de IA a utilizar",
           "api_endpoint": "URL del endpoint de API personalizado (opcional)",
           "temperature": "Creatividad de la respuesta (0-2, menor = más enfocado)",
-          "max_tokens": "Longitud máxima de la respuesta (1-4096 tokens)",
+          "max_tokens": "Longitud máxima de la respuesta (1-100000 tokens)",
           "request_interval": "Tiempo mínimo entre solicitudes (0.1-60 segundos)",
           "context_messages": "Número de mensajes de contexto a retener (1-20)",
           "max_history_size": "Tamaño máximo del historial de conversación (1-100)"
@@ -33,7 +33,7 @@
           "api_key": "Clave API para autenticación",
           "model": "Modelo de IA a utilizar",
           "temperature": "Creatividad de la respuesta (0-2, menor = más enfocado)",
-          "max_tokens": "Longitud máxima de la respuesta (1-4096 tokens)",
+          "max_tokens": "Longitud máxima de la respuesta (1-100000 tokens)",
           "api_endpoint": "URL del endpoint de API personalizado (opcional)",
           "api_provider": "Proveedor de API",
           "request_interval": "Tiempo mínimo entre solicitudes (0.1-60 segundos)",
@@ -77,7 +77,7 @@
         "data": {
           "model": "Modelo de IA",
           "temperature": "Creatividad de la respuesta (0-2)",
-          "max_tokens": "Longitud máxima de la respuesta (1-4096)",
+          "max_tokens": "Longitud máxima de la respuesta (1-100000)",
           "request_interval": "Intervalo mínimo de solicitud (0.1-60 segundos)",
           "context_messages": "Número de mensajes anteriores a incluir en el contexto (1-20)",
           "max_history_size": "Tamaño máximo del historial de conversación (1-100)"
@@ -89,10 +89,12 @@
     "api_provider": {
       "options": {
         "openai": "OpenAI (compatible)",
-        "anthropic": "Anthropic (compatible)"
+        "anthropic": "Anthropic (compatible)",
-      }
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
     }
-  },
+  }
+},
   "services": {
     "ask_question": {
       "name": "Hacer Pregunta (HA Text AI)",
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "Máx. Tokens",
-          "description": "Longitud máxima de la respuesta (1-4096 tokens)"
+          "description": "Longitud máxima de la respuesta (1-100000 tokens)"
         }
       }
     },

custom_components/ha_text_ai/translations/hi.json

@@ -19,7 +19,7 @@
           "model": "उपयोग करने के लिए एआई मॉडल",
           "api_endpoint": "कस्टम एपीआई एंडपॉइंट यूआरएल (वैकल्पिक)",
           "temperature": "प्रतिक्रिया की रचनात्मकता (0-2, कम = अधिक केंद्रित)",
-          "max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-4096 टोकन)",
+          "max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-100000 टोकन)",
           "request_interval": "अनुरोधों के बीच न्यूनतम समय (0.1-60 सेकंड)",
           "context_messages": "रखने के लिए संदर्भ संदेशों की संख्या (1-20)",
           "max_history_size": "अधिकतम बातचीत इतिहास आकार (1-100)"
@@ -33,7 +33,7 @@
           "api_key": "प्रमाणीकरण के लिए एपीआई कुंजी",
           "model": "उपयोग करने के लिए एआई मॉडल",
           "temperature": "प्रतिक्रिया की रचनात्मकता (0-2, कम = अधिक केंद्रित)",
-          "max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-4096 टोकन)",
+          "max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-100000 टोकन)",
           "api_endpoint": "कस्टम एपीआई एंडपॉइंट यूआरएल (वैकल्पिक)",
           "api_provider": "एपीआई प्रदाता",
           "request_interval": "अनुरोधों के बीच न्यूनतम समय (0.1-60 सेकंड)",
@@ -77,7 +77,7 @@
         "data": {
           "model": "एआई मॉडल",
           "temperature": "प्रतिक्रिया की रचनात्मकता (0-2)",
-          "max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-4096)",
+          "max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-100000)",
           "request_interval": "न्यूनतम अनुरोध अंतराल (0.1-60 सेकंड)",
           "context_messages": "संदर्भ में शामिल करने के लिए पिछले संदेशों की संख्या (1-20)",
           "max_history_size": "अधिकतम बातचीत इतिहास आकार (1-100)"
@@ -89,7 +89,9 @@
     "api_provider": {
       "options": {
         "openai": "OpenAI (अनुकूलित)",
-        "anthropic": "Anthropic (अनुकूलित)"
+        "anthropic": "Anthropic (अनुकूलित)",
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
       }
     }
   },
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "अधिकतम टोकन",
-          "description": "प्रतिक्रिया की अधिकतम लंबाई (1-4096 टोकन)"
+          "description": "प्रतिक्रिया की अधिकतम लंबाई (1-100000 टोकन)"
         }
       }
     },

custom_components/ha_text_ai/translations/it.json

@@ -19,7 +19,7 @@
           "model": "Modello AI da utilizzare",
           "api_endpoint": "URL dell'endpoint API personalizzato (opzionale)",
           "temperature": "Creatività della risposta (0-2, più basso = più focalizzato)",
-          "max_tokens": "Lunghezza massima della risposta (1-4096 token)",
+          "max_tokens": "Lunghezza massima della risposta (1-100000 token)",
           "request_interval": "Tempo minimo tra le richieste (0.1-60 secondi)",
           "context_messages": "Numero di messaggi di contesto da mantenere (1-20)",
           "max_history_size": "Dimensione massima della cronologia delle conversazioni (1-100)"
@@ -33,7 +33,7 @@
           "api_key": "Chiave API per l'autenticazione",
           "model": "Modello AI da utilizzare",
           "temperature": "Creatività della risposta (0-2, più basso = più focalizzato)",
-          "max_tokens": "Lunghezza massima della risposta (1-4096 token)",
+          "max_tokens": "Lunghezza massima della risposta (1-100000 token)",
           "api_endpoint": "URL dell'endpoint API personalizzato (opzionale)",
           "api_provider": "Fornitore API",
           "request_interval": "Tempo minimo tra le richieste (0.1-60 secondi)",
@@ -77,7 +77,7 @@
         "data": {
           "model": "Modello AI",
           "temperature": "Creatività della risposta (0-2)",
-          "max_tokens": "Lunghezza massima della risposta (1-4096)",
+          "max_tokens": "Lunghezza massima della risposta (1-100000)",
           "request_interval": "Intervallo minimo di richiesta (0.1-60 secondi)",
           "context_messages": "Numero di messaggi precedenti da includere nel contesto (1-20)",
           "max_history_size": "Dimensione massima della cronologia delle conversazioni (1-100)"
@@ -89,7 +89,9 @@
     "api_provider": {
       "options": {
         "openai": "OpenAI (compatibile)",
-        "anthropic": "Anthropic (compatibile)"
+        "anthropic": "Anthropic (compatibile)",
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
       }
     }
   },
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "Token massimi",
-          "description": "Lunghezza massima della risposta (1-4096 token)"
+          "description": "Lunghezza massima della risposta (1-100000 token)"
         }
       }
     },

custom_components/ha_text_ai/translations/ru.json

@@ -19,7 +19,7 @@
           "model": "Модель ИИ для использования",
           "api_endpoint": "Пользовательский URL-адрес конечной точки API (необязательно)",
           "temperature": "Креативность ответа (0-2, меньше = более сфокусированно)",
-          "max_tokens": "Максимальная длина ответа (1-4096 токенов)",
+          "max_tokens": "Максимальная длина ответа (1-100000 токенов)",
           "request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
           "context_messages": "Количество сохраняемых контекстных сообщений (1-20)",
           "max_history_size": "Максимальный размер истории разговора (1-100)"
@@ -33,7 +33,7 @@
           "api_key": "API-ключ для аутентификации",
           "model": "Модель ИИ для использования",
           "temperature": "Креативность ответа (0-2, меньше = более сфокусированно)",
-          "max_tokens": "Максимальная длина ответа (1-4096 токенов)",
+          "max_tokens": "Максимальная длина ответа (1-100000 токенов)",
           "api_endpoint": "Пользовательский URL-адрес конечной точки API (необязательно)",
           "api_provider": "Провайдер API",
           "request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
@@ -77,7 +77,7 @@
         "data": {
           "model": "Модель ИИ",
           "temperature": "Креативность ответа (0-2)",
-          "max_tokens": "Максимальная длина ответа (1-4096)",
+          "max_tokens": "Максимальная длина ответа (1-100000)",
           "request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
           "context_messages": "Количество предыдущих сообщений для включения в контекст (1-20)",
           "max_history_size": "Максимальный размер истории разговора (1-100)"
@@ -89,7 +89,9 @@
     "api_provider": {
       "options": {
         "openai": "OpenAI (совместимый)",
-        "anthropic": "Anthropic (совместимый)"
+        "anthropic": "Anthropic (совместимый)",
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
       }
     }
   },
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "Максимум токенов",
-          "description": "Максимальная длина ответа (1-4096 токенов)"
+          "description": "Максимальная длина ответа (1-100000 токенов)"
         }
       }
     },

custom_components/ha_text_ai/translations/sr.json

@@ -19,7 +19,7 @@
           "model": "AI модел који ће се користити",
           "api_endpoint": "Прилагођени URL API крајње тачке (опционо)",
           "temperature": "Креативност одговора (0-2, нижа = фокусираније)",
-          "max_tokens": "Максимална дужина одговора (1-4096 токена)",
+          "max_tokens": "Максимална дужина одговора (1-100000 токена)",
           "request_interval": "Минимално време између захтева (0.1-60 секунди)",
           "context_messages": "Број контекстуалних порука које треба задржати (1-20)",
           "max_history_size": "Максимална величина историје разговора (1-100)"
@@ -33,7 +33,7 @@
           "api_key": "API кључ за аутентификацију",
           "model": "AI модел који ће се користити",
           "temperature": "Креативност одговора (0-2, нижа = фокусираније)",
-          "max_tokens": "Максимална дужина одговора (1-4096 токена)",
+          "max_tokens": "Максимална дужина одговора (1-100000 токена)",
           "api_endpoint": "Прилагођени URL API крајње тачке (опционо)",
           "api_provider": "API провајдер",
           "request_interval": "Минимално време између захтева (0.1-60 секунди)",
@@ -77,7 +77,7 @@
         "data": {
           "model": "AI модел",
           "temperature": "Креативност одговора (0-2)",
-          "max_tokens": "Максимална дужина одговора (1-4096)",
+          "max_tokens": "Максимална дужина одговора (1-100000)",
           "request_interval": "Минимално време између захтева (0.1-60 секунди)",
           "context_messages": "Број претходних порука које треба укључити у контекст (1-20)",
           "max_history_size": "Максимална величина историје разговора (1-100)"
@@ -89,7 +89,9 @@
     "api_provider": {
       "options": {
         "openai": "OpenAI (компатибилан)",
-        "anthropic": "Anthropic (компатибилан)"
+        "anthropic": "Anthropic (компатибилан)",
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
       }
     }
   },
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "Максимални токени",
-          "description": "Максимална дужина одговора (1-4096 токена)"
+          "description": "Максимална дужина одговора (1-100000 токена)"
         }
       }
     },

custom_components/ha_text_ai/translations/zh.json

@@ -19,7 +19,7 @@
           "model": "要使用的AI模型",
           "api_endpoint": "自定义API端点URL（可选）",
           "temperature": "响应创造力（0-2，越低越专注）",
-          "max_tokens": "最大响应长度（1-4096个标记）",
+          "max_tokens": "最大响应长度（1-100000个标记）",
           "request_interval": "请求之间的最小时间（0.1-60秒）",
           "context_messages": "保留的上下文消息数量（1-20）",
           "max_history_size": "最大对话历史大小（1-100）"
@@ -33,7 +33,7 @@
           "api_key": "用于身份验证的API密钥",
           "model": "要使用的AI模型",
           "temperature": "响应创造力（0-2，越低越专注）",
-          "max_tokens": "最大响应长度（1-4096个标记）",
+          "max_tokens": "最大响应长度（1-100000个标记）",
           "api_endpoint": "自定义API端点URL（可选）",
           "api_provider": "API提供者",
           "request_interval": "请求之间的最小时间（0.1-60秒）",
@@ -77,7 +77,7 @@
         "data": {
           "model": "AI模型",
           "temperature": "响应创造力（0-2）",
-          "max_tokens": "最大响应长度（1-4096）",
+          "max_tokens": "最大响应长度（1-100000）",
           "request_interval": "最小请求间隔（0.1-60秒）",
           "context_messages": "要包含在上下文中的先前消息数量（1-20）",
           "max_history_size": "最大对话历史大小（1-100）"
@@ -89,7 +89,9 @@
     "api_provider": {
       "options": {
         "openai": "OpenAI（兼容）",
-        "anthropic": "Anthropic（兼容）"
+        "anthropic": "Anthropic（兼容）",
+        "deepseek": "DeepSeek",
+        "gemini": "Google Gemini"
       }
     }
   },
@@ -124,7 +126,7 @@
         },
         "max_tokens": {
           "name": "最大标记数",
-          "description": "响应的最大长度（1-4096个标记）"
+          "description": "响应的最大长度（1-100000个标记）"
         }
       }
     },

hacs.json

@@ -1,5 +1,5 @@
 {
-  "name": "HA text AI",
+  "name": "HA Text AI",
   "render_readme": true,
   "homeassistant": "2024.11.0"
 }