Update notification service

AppImage/scripts/ai_providers/__init__.py

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+"""AI Providers for ProxMenux notification enhancement.
+
+This module provides a pluggable architecture for different AI providers
+to enhance and translate notification messages.
+
+Supported providers:
+- Groq: Fast inference, generous free tier (30 req/min)
+- OpenAI: Industry standard, widely used
+- Anthropic: Excellent for text generation, Claude Haiku is fast and affordable
+- Gemini: Google's model, free tier available, good quality/price ratio
+- Ollama: 100% local execution, no costs, complete privacy
+- OpenRouter: Aggregator with access to 100+ models using a single API key
+"""
+from .base import AIProvider, AIProviderError
+from .groq_provider import GroqProvider
+from .openai_provider import OpenAIProvider
+from .anthropic_provider import AnthropicProvider
+from .gemini_provider import GeminiProvider
+from .ollama_provider import OllamaProvider
+from .openrouter_provider import OpenRouterProvider
+
+PROVIDERS = {
+    'groq': GroqProvider,
+    'openai': OpenAIProvider,
+    'anthropic': AnthropicProvider,
+    'gemini': GeminiProvider,
+    'ollama': OllamaProvider,
+    'openrouter': OpenRouterProvider,
+}
+
+# Provider metadata for UI display
+PROVIDER_INFO = {
+    'groq': {
+        'name': 'Groq',
+        'default_model': 'llama-3.3-70b-versatile',
+        'description': 'Fast inference, generous free tier (30 req/min). Ideal to get started.',
+        'requires_api_key': True,
+    },
+    'openai': {
+        'name': 'OpenAI',
+        'default_model': 'gpt-4o-mini',
+        'description': 'Industry standard. Very accurate and widely used.',
+        'requires_api_key': True,
+    },
+    'anthropic': {
+        'name': 'Anthropic (Claude)',
+        'default_model': 'claude-3-haiku-20240307',
+        'description': 'Excellent for writing and translation. Fast and affordable.',
+        'requires_api_key': True,
+    },
+    'gemini': {
+        'name': 'Google Gemini',
+        'default_model': 'gemini-1.5-flash',
+        'description': 'Free tier available, very good quality/price ratio.',
+        'requires_api_key': True,
+    },
+    'ollama': {
+        'name': 'Ollama (Local)',
+        'default_model': 'llama3.2',
+        'description': '100% local execution. No costs, complete privacy, no internet required.',
+        'requires_api_key': False,
+    },
+    'openrouter': {
+        'name': 'OpenRouter',
+        'default_model': 'meta-llama/llama-3.3-70b-instruct',
+        'description': 'Aggregator with access to 100+ models using a single API key. Maximum flexibility.',
+        'requires_api_key': True,
+    },
+}
+
+
+def get_provider(name: str, **kwargs) -> AIProvider:
+    """Factory function to get provider instance.
+    
+    Args:
+        name: Provider name (groq, openai, anthropic, gemini, ollama, openrouter)
+        **kwargs: Provider-specific arguments (api_key, model, base_url)
+        
+    Returns:
+        AIProvider instance
+        
+    Raises:
+        AIProviderError: If provider name is unknown
+    """
+    if name not in PROVIDERS:
+        raise AIProviderError(f"Unknown provider: {name}. Available: {list(PROVIDERS.keys())}")
+    return PROVIDERS[name](**kwargs)
+
+
+def get_provider_info(name: str = None) -> dict:
+    """Get provider metadata for UI display.
+    
+    Args:
+        name: Optional provider name. If None, returns all providers info.
+        
+    Returns:
+        Provider info dict or dict of all providers
+    """
+    if name:
+        return PROVIDER_INFO.get(name, {})
+    return PROVIDER_INFO
+
+
+__all__ = [
+    'AIProvider', 
+    'AIProviderError', 
+    'PROVIDERS', 
+    'PROVIDER_INFO',
+    'get_provider',
+    'get_provider_info',
+]

AppImage/scripts/ai_providers/anthropic_provider.py

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+"""Anthropic (Claude) provider implementation.
+
+Anthropic's Claude models are excellent for text generation and translation.
+Claude Haiku is particularly fast and affordable for notification enhancement.
+"""
+from typing import Optional
+from .base import AIProvider, AIProviderError
+
+
+class AnthropicProvider(AIProvider):
+    """Anthropic provider using their Messages API."""
+    
+    NAME = "anthropic"
+    DEFAULT_MODEL = "claude-3-haiku-20240307"
+    REQUIRES_API_KEY = True
+    API_URL = "https://api.anthropic.com/v1/messages"
+    API_VERSION = "2023-06-01"
+    
+    def generate(self, system_prompt: str, user_message: str,
+                 max_tokens: int = 200) -> Optional[str]:
+        """Generate a response using Anthropic's API.
+        
+        Note: Anthropic uses a different API format than OpenAI.
+        The system prompt goes in a separate field, not in messages.
+        
+        Args:
+            system_prompt: System instructions
+            user_message: User message to process
+            max_tokens: Maximum response length
+            
+        Returns:
+            Generated text or None if failed
+            
+        Raises:
+            AIProviderError: If API key is missing or request fails
+        """
+        if not self.api_key:
+            raise AIProviderError("API key required for Anthropic")
+        
+        # Anthropic uses a different format - system is a top-level field
+        payload = {
+            'model': self.model,
+            'system': system_prompt,
+            'messages': [
+                {'role': 'user', 'content': user_message},
+            ],
+            'max_tokens': max_tokens,
+        }
+        
+        headers = {
+            'Content-Type': 'application/json',
+            'x-api-key': self.api_key,
+            'anthropic-version': self.API_VERSION,
+        }
+        
+        result = self._make_request(self.API_URL, payload, headers)
+        
+        try:
+            # Anthropic returns content as array of content blocks
+            content = result['content']
+            if isinstance(content, list) and len(content) > 0:
+                return content[0].get('text', '').strip()
+            return str(content).strip()
+        except (KeyError, IndexError) as e:
+            raise AIProviderError(f"Unexpected response format: {e}")

AppImage/scripts/ai_providers/base.py

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+"""Base class for AI providers."""
+from abc import ABC, abstractmethod
+from typing import Optional, Dict, Any
+
+
+class AIProviderError(Exception):
+    """Exception for AI provider errors."""
+    pass
+
+
+class AIProvider(ABC):
+    """Abstract base class for AI providers.
+    
+    All provider implementations must inherit from this class and implement
+    the generate() method.
+    """
+    
+    # Provider metadata (override in subclasses)
+    NAME = "base"
+    DEFAULT_MODEL = ""
+    REQUIRES_API_KEY = True
+    
+    def __init__(self, api_key: str = "", model: str = "", base_url: str = ""):
+        """Initialize the AI provider.
+        
+        Args:
+            api_key: API key for authentication (not required for local providers)
+            model: Model name to use (defaults to DEFAULT_MODEL if empty)
+            base_url: Base URL for API calls (used by Ollama and custom endpoints)
+        """
+        self.api_key = api_key
+        self.model = model or self.DEFAULT_MODEL
+        self.base_url = base_url
+    
+    @abstractmethod
+    def generate(self, system_prompt: str, user_message: str, 
+                 max_tokens: int = 200) -> Optional[str]:
+        """Generate a response from the AI model.
+        
+        Args:
+            system_prompt: System instructions for the model
+            user_message: User message/query to process
+            max_tokens: Maximum tokens in the response
+            
+        Returns:
+            Generated text or None if failed
+            
+        Raises:
+            AIProviderError: If there's an error communicating with the provider
+        """
+        pass
+    
+    def test_connection(self) -> Dict[str, Any]:
+        """Test the connection to the AI provider.
+        
+        Sends a simple test message to verify the provider is accessible
+        and the API key is valid.
+        
+        Returns:
+            Dictionary with:
+                - success: bool indicating if connection succeeded
+                - message: Human-readable status message
+                - model: Model name being used
+        """
+        try:
+            response = self.generate(
+                system_prompt="You are a test assistant. Respond with exactly: CONNECTION_OK",
+                user_message="Test connection",
+                max_tokens=20
+            )
+            if response:
+                # Check if response contains our expected text
+                if "CONNECTION_OK" in response.upper() or "CONNECTION" in response.upper():
+                    return {
+                        'success': True,
+                        'message': 'Connection successful',
+                        'model': self.model
+                    }
+                # Even if different response, connection worked
+                return {
+                    'success': True,
+                    'message': f'Connected (response received)',
+                    'model': self.model
+                }
+            return {
+                'success': False,
+                'message': 'No response received from provider',
+                'model': self.model
+            }
+        except AIProviderError as e:
+            return {
+                'success': False,
+                'message': str(e),
+                'model': self.model
+            }
+        except Exception as e:
+            return {
+                'success': False,
+                'message': f'Unexpected error: {str(e)}',
+                'model': self.model
+            }
+    
+    def _make_request(self, url: str, payload: dict, headers: dict, 
+                      timeout: int = 15) -> dict:
+        """Make HTTP request to AI provider API.
+        
+        Args:
+            url: API endpoint URL
+            payload: JSON payload to send
+            headers: HTTP headers
+            timeout: Request timeout in seconds
+            
+        Returns:
+            Parsed JSON response
+            
+        Raises:
+            AIProviderError: If request fails
+        """
+        import json
+        import urllib.request
+        import urllib.error
+        
+        data = json.dumps(payload).encode('utf-8')
+        req = urllib.request.Request(url, data=data, headers=headers, method='POST')
+        
+        try:
+            with urllib.request.urlopen(req, timeout=timeout) as resp:
+                return json.loads(resp.read().decode('utf-8'))
+        except urllib.error.HTTPError as e:
+            error_body = ""
+            try:
+                error_body = e.read().decode('utf-8')
+            except Exception:
+                pass
+            raise AIProviderError(f"HTTP {e.code}: {error_body or e.reason}")
+        except urllib.error.URLError as e:
+            raise AIProviderError(f"Connection error: {e.reason}")
+        except json.JSONDecodeError as e:
+            raise AIProviderError(f"Invalid JSON response: {e}")
+        except Exception as e:
+            raise AIProviderError(f"Request failed: {str(e)}")

AppImage/scripts/ai_providers/gemini_provider.py

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+"""Google Gemini provider implementation.
+
+Google's Gemini models offer a free tier and excellent quality/price ratio.
+Gemini 1.5 Flash is particularly fast and cost-effective.
+"""
+from typing import Optional
+from .base import AIProvider, AIProviderError
+
+
+class GeminiProvider(AIProvider):
+    """Google Gemini provider using the Generative Language API."""
+    
+    NAME = "gemini"
+    DEFAULT_MODEL = "gemini-1.5-flash"
+    REQUIRES_API_KEY = True
+    API_BASE = "https://generativelanguage.googleapis.com/v1beta/models"
+    
+    def generate(self, system_prompt: str, user_message: str,
+                 max_tokens: int = 200) -> Optional[str]:
+        """Generate a response using Google's Gemini API.
+        
+        Note: Gemini uses a different API format. System instructions
+        go in a separate systemInstruction field.
+        
+        Args:
+            system_prompt: System instructions
+            user_message: User message to process
+            max_tokens: Maximum response length
+            
+        Returns:
+            Generated text or None if failed
+            
+        Raises:
+            AIProviderError: If API key is missing or request fails
+        """
+        if not self.api_key:
+            raise AIProviderError("API key required for Gemini")
+        
+        url = f"{self.API_BASE}/{self.model}:generateContent?key={self.api_key}"
+        
+        # Gemini uses a specific format with contents array
+        payload = {
+            'systemInstruction': {
+                'parts': [{'text': system_prompt}]
+            },
+            'contents': [
+                {
+                    'role': 'user',
+                    'parts': [{'text': user_message}]
+                }
+            ],
+            'generationConfig': {
+                'maxOutputTokens': max_tokens,
+                'temperature': 0.3,
+            }
+        }
+        
+        headers = {
+            'Content-Type': 'application/json',
+        }
+        
+        result = self._make_request(url, payload, headers)
+        
+        try:
+            # Gemini returns candidates array with content parts
+            candidates = result.get('candidates', [])
+            if candidates:
+                content = candidates[0].get('content', {})
+                parts = content.get('parts', [])
+                if parts:
+                    return parts[0].get('text', '').strip()
+            raise AIProviderError("No content in response")
+        except (KeyError, IndexError) as e:
+            raise AIProviderError(f"Unexpected response format: {e}")

AppImage/scripts/ai_providers/groq_provider.py

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+"""Groq AI provider implementation.
+
+Groq provides fast inference with a generous free tier (30 requests/minute).
+Uses the OpenAI-compatible API format.
+"""
+from typing import Optional
+from .base import AIProvider, AIProviderError
+
+
+class GroqProvider(AIProvider):
+    """Groq AI provider using their OpenAI-compatible API."""
+    
+    NAME = "groq"
+    DEFAULT_MODEL = "llama-3.3-70b-versatile"
+    REQUIRES_API_KEY = True
+    API_URL = "https://api.groq.com/openai/v1/chat/completions"
+    
+    def generate(self, system_prompt: str, user_message: str,
+                 max_tokens: int = 200) -> Optional[str]:
+        """Generate a response using Groq's API.
+        
+        Args:
+            system_prompt: System instructions
+            user_message: User message to process
+            max_tokens: Maximum response length
+            
+        Returns:
+            Generated text or None if failed
+            
+        Raises:
+            AIProviderError: If API key is missing or request fails
+        """
+        if not self.api_key:
+            raise AIProviderError("API key required for Groq")
+        
+        payload = {
+            'model': self.model,
+            'messages': [
+                {'role': 'system', 'content': system_prompt},
+                {'role': 'user', 'content': user_message},
+            ],
+            'max_tokens': max_tokens,
+            'temperature': 0.3,
+        }
+        
+        headers = {
+            'Content-Type': 'application/json',
+            'Authorization': f'Bearer {self.api_key}',
+        }
+        
+        result = self._make_request(self.API_URL, payload, headers)
+        
+        try:
+            return result['choices'][0]['message']['content'].strip()
+        except (KeyError, IndexError) as e:
+            raise AIProviderError(f"Unexpected response format: {e}")

AppImage/scripts/ai_providers/ollama_provider.py

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+"""Ollama provider implementation.
+
+Ollama enables 100% local AI execution with no costs and complete privacy.
+No internet connection required - perfect for sensitive enterprise environments.
+"""
+from typing import Optional
+from .base import AIProvider, AIProviderError
+
+
+class OllamaProvider(AIProvider):
+    """Ollama provider for local AI execution."""
+    
+    NAME = "ollama"
+    DEFAULT_MODEL = "llama3.2"
+    REQUIRES_API_KEY = False
+    DEFAULT_URL = "http://localhost:11434"
+    
+    def __init__(self, api_key: str = "", model: str = "", base_url: str = ""):
+        """Initialize Ollama provider.
+        
+        Args:
+            api_key: Not used for Ollama (local execution)
+            model: Model name (default: llama3.2)
+            base_url: Ollama server URL (default: http://localhost:11434)
+        """
+        super().__init__(api_key, model, base_url)
+        # Use default URL if not provided
+        if not self.base_url:
+            self.base_url = self.DEFAULT_URL
+    
+    def generate(self, system_prompt: str, user_message: str,
+                 max_tokens: int = 200) -> Optional[str]:
+        """Generate a response using local Ollama server.
+        
+        Args:
+            system_prompt: System instructions
+            user_message: User message to process
+            max_tokens: Maximum response length (maps to num_predict)
+            
+        Returns:
+            Generated text or None if failed
+            
+        Raises:
+            AIProviderError: If Ollama server is unreachable
+        """
+        url = f"{self.base_url.rstrip('/')}/api/chat"
+        
+        payload = {
+            'model': self.model,
+            'messages': [
+                {'role': 'system', 'content': system_prompt},
+                {'role': 'user', 'content': user_message},
+            ],
+            'stream': False,
+            'options': {
+                'num_predict': max_tokens,
+                'temperature': 0.3,
+            }
+        }
+        
+        headers = {
+            'Content-Type': 'application/json',
+        }
+        
+        try:
+            result = self._make_request(url, payload, headers, timeout=30)
+        except AIProviderError as e:
+            if "Connection" in str(e) or "refused" in str(e).lower():
+                raise AIProviderError(
+                    f"Cannot connect to Ollama at {self.base_url}. "
+                    "Make sure Ollama is running (ollama serve)"
+                )
+            raise
+        
+        try:
+            message = result.get('message', {})
+            return message.get('content', '').strip()
+        except (KeyError, AttributeError) as e:
+            raise AIProviderError(f"Unexpected response format: {e}")
+    
+    def test_connection(self):
+        """Test connection to Ollama server.
+        
+        Also checks if the specified model is available.
+        """
+        import json
+        import urllib.request
+        import urllib.error
+        
+        # First check if server is running
+        try:
+            url = f"{self.base_url.rstrip('/')}/api/tags"
+            req = urllib.request.Request(url, method='GET')
+            with urllib.request.urlopen(req, timeout=5) as resp:
+                data = json.loads(resp.read().decode('utf-8'))
+                models = [m.get('name', '').split(':')[0] for m in data.get('models', [])]
+                
+                if self.model not in models and f"{self.model}:latest" not in [m.get('name', '') for m in data.get('models', [])]:
+                    return {
+                        'success': False,
+                        'message': f"Model '{self.model}' not found. Available: {', '.join(models[:5])}...",
+                        'model': self.model
+                    }
+        except urllib.error.URLError:
+            return {
+                'success': False,
+                'message': f"Cannot connect to Ollama at {self.base_url}. Make sure Ollama is running.",
+                'model': self.model
+            }
+        except Exception as e:
+            return {
+                'success': False,
+                'message': f"Error checking Ollama: {str(e)}",
+                'model': self.model
+            }
+        
+        # If server is up and model exists, do the actual test
+        return super().test_connection()

AppImage/scripts/ai_providers/openai_provider.py

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+"""OpenAI provider implementation.
+
+OpenAI is the industry standard for AI APIs. gpt-4o-mini provides
+excellent quality at a reasonable price point.
+"""
+from typing import Optional
+from .base import AIProvider, AIProviderError
+
+
+class OpenAIProvider(AIProvider):
+    """OpenAI provider using their Chat Completions API."""
+    
+    NAME = "openai"
+    DEFAULT_MODEL = "gpt-4o-mini"
+    REQUIRES_API_KEY = True
+    API_URL = "https://api.openai.com/v1/chat/completions"
+    
+    def generate(self, system_prompt: str, user_message: str,
+                 max_tokens: int = 200) -> Optional[str]:
+        """Generate a response using OpenAI's API.
+        
+        Args:
+            system_prompt: System instructions
+            user_message: User message to process
+            max_tokens: Maximum response length
+            
+        Returns:
+            Generated text or None if failed
+            
+        Raises:
+            AIProviderError: If API key is missing or request fails
+        """
+        if not self.api_key:
+            raise AIProviderError("API key required for OpenAI")
+        
+        payload = {
+            'model': self.model,
+            'messages': [
+                {'role': 'system', 'content': system_prompt},
+                {'role': 'user', 'content': user_message},
+            ],
+            'max_tokens': max_tokens,
+            'temperature': 0.3,
+        }
+        
+        headers = {
+            'Content-Type': 'application/json',
+            'Authorization': f'Bearer {self.api_key}',
+        }
+        
+        result = self._make_request(self.API_URL, payload, headers)
+        
+        try:
+            return result['choices'][0]['message']['content'].strip()
+        except (KeyError, IndexError) as e:
+            raise AIProviderError(f"Unexpected response format: {e}")

AppImage/scripts/ai_providers/openrouter_provider.py

@@ -0,0 +1,62 @@
+"""OpenRouter provider implementation.
+
+OpenRouter is an aggregator that provides access to 100+ AI models
+using a single API key. Maximum flexibility for choosing models.
+Uses OpenAI-compatible API format.
+"""
+from typing import Optional
+from .base import AIProvider, AIProviderError
+
+
+class OpenRouterProvider(AIProvider):
+    """OpenRouter provider for multi-model access."""
+    
+    NAME = "openrouter"
+    DEFAULT_MODEL = "meta-llama/llama-3.3-70b-instruct"
+    REQUIRES_API_KEY = True
+    API_URL = "https://openrouter.ai/api/v1/chat/completions"
+    
+    def generate(self, system_prompt: str, user_message: str,
+                 max_tokens: int = 200) -> Optional[str]:
+        """Generate a response using OpenRouter's API.
+        
+        OpenRouter uses OpenAI-compatible format with additional
+        headers for app identification.
+        
+        Args:
+            system_prompt: System instructions
+            user_message: User message to process
+            max_tokens: Maximum response length
+            
+        Returns:
+            Generated text or None if failed
+            
+        Raises:
+            AIProviderError: If API key is missing or request fails
+        """
+        if not self.api_key:
+            raise AIProviderError("API key required for OpenRouter")
+        
+        payload = {
+            'model': self.model,
+            'messages': [
+                {'role': 'system', 'content': system_prompt},
+                {'role': 'user', 'content': user_message},
+            ],
+            'max_tokens': max_tokens,
+            'temperature': 0.3,
+        }
+        
+        headers = {
+            'Content-Type': 'application/json',
+            'Authorization': f'Bearer {self.api_key}',
+            'HTTP-Referer': 'https://github.com/MacRimi/ProxMenux',
+            'X-Title': 'ProxMenux Monitor',
+        }
+        
+        result = self._make_request(self.API_URL, payload, headers)
+        
+        try:
+            return result['choices'][0]['message']['content'].strip()
+        except (KeyError, IndexError) as e:
+            raise AIProviderError(f"Unexpected response format: {e}")