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https://github.com/MacRimi/ProxMenux.git
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Update notification service
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MacRimi
@@ -1215,107 +1215,252 @@ def enrich_with_emojis(event_type: str, title: str, body: str,
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# ─── AI Enhancement (Optional) ───────────────────────────────────
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# Supported languages for AI translation
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AI_LANGUAGES = {
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'en': 'English',
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'es': 'Spanish',
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'fr': 'French',
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'de': 'German',
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'pt': 'Portuguese',
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'it': 'Italian',
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'ru': 'Russian',
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'sv': 'Swedish',
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'no': 'Norwegian',
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'ja': 'Japanese',
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'zh': 'Chinese',
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'nl': 'Dutch',
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}
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# Token limits for different detail levels
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AI_DETAIL_TOKENS = {
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'brief': 100, # 2-3 lines, essential only
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'standard': 200, # Concise paragraph with context
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'detailed': 400, # Complete technical details
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}
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# System prompt template - informative, no recommendations
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AI_SYSTEM_PROMPT = """You are a technical assistant for ProxMenux Monitor, a Proxmox server monitoring system.
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Your task is to translate and format system alerts to {language}.
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STRICT RULES:
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1. Translate the message to the requested language
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2. Maintain an INFORMATIVE and OBJECTIVE tone
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3. DO NOT use formal introductions ("Dear...", "Esteemed...")
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4. DO NOT give recommendations or action suggestions
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5. DO NOT interpret data subjectively
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6. Present only FACTS and TECHNICAL DATA
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7. Respect the requested detail level: {detail_level}
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{emoji_instructions}
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DETAIL LEVELS:
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- brief: 2-3 lines maximum, only essential information
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- standard: Concise paragraph with basic context
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- detailed: Complete information with all available technical details
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MESSAGE TYPES:
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- Some messages come from Proxmox VE webhooks with raw system data (backup logs, update lists, SMART errors)
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- Parse and present this data clearly, extracting key information (VM IDs, sizes, durations, errors)
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- For backup messages: highlight status (OK/ERROR), VM names, sizes, and duration
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- For update messages: list package names and counts
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- For disk/SMART errors: highlight affected device and error type
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If journal log context is provided, use it for more precise event information."""
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# Emoji instructions for rich format channels
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AI_EMOJI_INSTRUCTIONS = """
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8. ENRICH with contextual emojis and icons:
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- Use appropriate emojis at the START of the title/message to indicate severity and type
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- Severity indicators: Use a colored circle at the start (info=blue, warning=yellow, critical=red)
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- Add relevant technical emojis: disk, server, network, security, backup, etc.
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- Keep emojis contextual and professional, not decorative
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- Examples of appropriate emojis:
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* Disk/Storage: disk, folder, file
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* Network: globe, signal, connection
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* Security: shield, lock, key, warning
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* System: gear, server, computer
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* Status: checkmark, cross, warning, info
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* Backup: save, sync, cloud
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* Performance: chart, speedometer"""
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# No emoji instructions for email/plain channels
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AI_NO_EMOJI_INSTRUCTIONS = """
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8. DO NOT use emojis or special icons - plain text only for email compatibility"""
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class AIEnhancer:
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"""Optional AI message enhancement using external LLM API.
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"""AI message enhancement using pluggable providers.
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Enriches template-generated messages with context and suggestions.
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Falls back to original message if AI is unavailable or fails.
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Supports 6 providers: Groq, OpenAI, Anthropic, Gemini, Ollama, OpenRouter.
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Translates and formats notifications based on configured language and detail level.
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"""
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SYSTEM_PROMPT = """You are a Proxmox system administrator assistant.
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You receive a notification message about a server event and must enhance it with:
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1. A brief explanation of what this means in practical terms
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2. A suggested action if applicable (1-2 sentences max)
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Keep the response concise (max 3 sentences total). Do not repeat the original message.
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Respond in the same language as the input message."""
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def __init__(self, config: Dict[str, Any]):
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"""Initialize AIEnhancer with configuration.
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Args:
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config: Dictionary containing:
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- ai_provider: Provider name (groq, openai, anthropic, gemini, ollama, openrouter)
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- ai_api_key: API key (not required for ollama)
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- ai_model: Optional model override
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- ai_language: Target language code (en, es, fr, etc.)
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- ai_ollama_url: URL for Ollama server (optional)
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"""
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self.config = config
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self._provider = None
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self._init_provider()
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def __init__(self, provider: str, api_key: str, model: str = ''):
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self.provider = provider.lower()
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self.api_key = api_key
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self.model = model
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self._enabled = bool(api_key)
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def _init_provider(self):
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"""Initialize the AI provider based on configuration."""
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try:
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# Import here to avoid circular imports
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import sys
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import os
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# Add script directory to path for ai_providers import
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script_dir = os.path.dirname(os.path.abspath(__file__))
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if script_dir not in sys.path:
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sys.path.insert(0, script_dir)
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from ai_providers import get_provider
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provider_name = self.config.get('ai_provider', 'groq')
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self._provider = get_provider(
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provider_name,
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api_key=self.config.get('ai_api_key', ''),
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model=self.config.get('ai_model', ''),
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base_url=self.config.get('ai_ollama_url', ''),
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)
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except Exception as e:
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print(f"[AIEnhancer] Failed to initialize provider: {e}")
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self._provider = None
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@property
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def enabled(self) -> bool:
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return self._enabled
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"""Check if AI enhancement is available."""
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return self._provider is not None
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def enhance(self, title: str, body: str, severity: str) -> Optional[str]:
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"""Enhance a notification message with AI context.
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def enhance(self, title: str, body: str, severity: str,
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detail_level: str = 'standard',
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journal_context: str = '',
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use_emojis: bool = False) -> Optional[str]:
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"""Enhance/translate notification with AI.
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Returns enhanced body text, or None if enhancement fails/disabled.
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Args:
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title: Notification title
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body: Notification body text
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severity: Severity level (info, warning, critical)
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detail_level: Level of detail (brief, standard, detailed)
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journal_context: Optional journal log lines for context
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use_emojis: Whether to include emojis in the response (for push channels)
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Returns:
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Enhanced/translated text or None if failed
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"""
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if not self._enabled:
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if not self._provider:
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return None
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# Get language settings
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language_code = self.config.get('ai_language', 'en')
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language_name = AI_LANGUAGES.get(language_code, 'English')
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# Get token limit for detail level
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max_tokens = AI_DETAIL_TOKENS.get(detail_level, 200)
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# Select emoji instructions based on channel type
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emoji_instructions = AI_EMOJI_INSTRUCTIONS if use_emojis else AI_NO_EMOJI_INSTRUCTIONS
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# Build system prompt with emoji instructions
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system_prompt = AI_SYSTEM_PROMPT.format(
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language=language_name,
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detail_level=detail_level,
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emoji_instructions=emoji_instructions
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)
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# Build user message
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user_msg = f"Severity: {severity}\nTitle: {title}\nMessage:\n{body}"
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if journal_context:
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user_msg += f"\n\nJournal log context:\n{journal_context}"
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try:
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if self.provider in ('openai', 'groq'):
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return self._call_openai_compatible(title, body, severity)
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result = self._provider.generate(system_prompt, user_msg, max_tokens)
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return result
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except Exception as e:
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print(f"[AIEnhancer] Enhancement failed: {e}")
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return None
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return None
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def _call_openai_compatible(self, title: str, body: str, severity: str) -> Optional[str]:
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"""Call OpenAI-compatible API (works with OpenAI, Groq, local)."""
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if self.provider == 'groq':
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url = 'https://api.groq.com/openai/v1/chat/completions'
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model = self.model or 'llama-3.3-70b-versatile'
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else: # openai
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url = 'https://api.openai.com/v1/chat/completions'
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model = self.model or 'gpt-4o-mini'
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def test_connection(self) -> Dict[str, Any]:
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"""Test the AI provider connection.
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user_msg = f"Severity: {severity}\nTitle: {title}\nMessage: {body}"
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payload = json.dumps({
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'model': model,
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'messages': [
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{'role': 'system', 'content': self.SYSTEM_PROMPT},
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{'role': 'user', 'content': user_msg},
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],
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'max_tokens': 150,
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'temperature': 0.3,
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}).encode('utf-8')
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headers = {
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'Content-Type': 'application/json',
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'Authorization': f'Bearer {self.api_key}',
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}
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req = urllib.request.Request(url, data=payload, headers=headers)
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with urllib.request.urlopen(req, timeout=10) as resp:
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result = json.loads(resp.read().decode('utf-8'))
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content = result['choices'][0]['message']['content'].strip()
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return content if content else None
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Returns:
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Dict with success, message, and model info
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"""
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if not self._provider:
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return {
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'success': False,
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'message': 'Provider not initialized',
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'model': ''
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}
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return self._provider.test_connection()
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def format_with_ai(title: str, body: str, severity: str,
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ai_config: Dict[str, str]) -> str:
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"""Format a message with optional AI enhancement.
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ai_config: Dict[str, Any],
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detail_level: str = 'standard',
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journal_context: str = '',
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use_emojis: bool = False) -> str:
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"""Format a message with AI enhancement/translation.
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If AI is configured and succeeds, appends AI insight to the body.
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Otherwise returns the original body unchanged.
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Replaces the message body with AI-processed version if successful.
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Falls back to original body if AI is unavailable or fails.
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Args:
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title: Notification title
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body: Notification body
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severity: Severity level
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ai_config: {'enabled': 'true', 'provider': 'groq', 'api_key': '...', 'model': ''}
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ai_config: Configuration dictionary with AI settings
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detail_level: Level of detail (brief, standard, detailed)
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journal_context: Optional journal log context
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use_emojis: Whether to include emojis (for push channels like Telegram/Discord)
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Returns:
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Enhanced body string
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Enhanced body string or original if AI fails
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"""
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if ai_config.get('enabled') != 'true' or not ai_config.get('api_key'):
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# Check if AI is enabled
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ai_enabled = ai_config.get('ai_enabled')
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if isinstance(ai_enabled, str):
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ai_enabled = ai_enabled.lower() == 'true'
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if not ai_enabled:
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return body
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enhancer = AIEnhancer(
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provider=ai_config.get('provider', 'groq'),
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api_key=ai_config['api_key'],
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model=ai_config.get('model', ''),
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# Check for API key (not required for Ollama)
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provider = ai_config.get('ai_provider', 'groq')
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if provider != 'ollama' and not ai_config.get('ai_api_key'):
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return body
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# For Ollama, check URL is configured
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if provider == 'ollama' and not ai_config.get('ai_ollama_url'):
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return body
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# Create enhancer and process
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enhancer = AIEnhancer(ai_config)
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enhanced = enhancer.enhance(
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title, body, severity,
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detail_level=detail_level,
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journal_context=journal_context,
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use_emojis=use_emojis
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)
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insight = enhancer.enhance(title, body, severity)
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if insight:
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return f"{body}\n\n---\n{insight}"
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# Return enhanced text if successful, otherwise original
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if enhanced:
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# For detailed level (email), append original message for reference
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# This ensures full technical data is available even after AI processing
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if detail_level == 'detailed' and body and len(body) > 50:
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# Only append if original has substantial content
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enhanced += "\n\n" + "-" * 40 + "\n"
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enhanced += "Original message:\n"
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enhanced += body
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return enhanced
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return body
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