""" ATOM Telegram Integration Advanced Telegram platform integration with enterprise features and automation """ import asyncio from collections import Counter, defaultdict from dataclasses import asdict, dataclass from datetime import datetime, timedelta, timezone from enum import Enum import hashlib import json import logging import os import time from typing import Any, Callable, Dict, List, Optional, Tuple, Union import aiohttp import httpx # Handle numpy/pandas being disabled try: import numpy as np import pandas as pd except ImportError: np = None pd = None logging.warning("NumPy/Pandas not available, some analytics features disabled") # Import existing ATOM services atom_enterprise_security_service = None atom_enterprise_unified_service = None atom_workflow_automation_service = None ai_enhanced_service = None try: from ai_enhanced_service import ( AIModelType, AIRequest, AIResponse, AIServiceType, AITaskType, ai_enhanced_service, ) from atom_ai_integration import atom_ai_integration from atom_discord_integration import atom_discord_integration from atom_enterprise_security_service import ( ComplianceStandard, SecurityLevel, atom_enterprise_security_service, ) from atom_enterprise_unified_service import ( WorkflowSecurityLevel, atom_enterprise_unified_service, ) from atom_google_chat_integration import atom_google_chat_integration from atom_ingestion_pipeline import AtomIngestionPipeline from atom_memory_service import AtomMemoryService from atom_search_service import AtomSearchService from atom_slack_integration import atom_slack_integration from atom_teams_integration import atom_teams_integration from atom_workflow_automation_service import ( AutomationPriority, AutomationStatus, atom_workflow_automation_service, ) from atom_workflow_service import AtomWorkflowService except ImportError as e: logging.warning("Enterprise services not available: {}. Using stubs/None.".format(e)) atom_enterprise_security_service = None atom_enterprise_unified_service = None atom_workflow_automation_service = None ai_enhanced_service = None atom_ai_integration = None atom_slack_integration = None atom_teams_integration = None atom_google_chat_integration = None atom_discord_integration = None # Configure logging logger = logging.getLogger(__name__) class TelegramMessageType(Enum): """Telegram message types""" TEXT = "text" PHOTO = "photo" VIDEO = "video" AUDIO = "audio" VOICE = "voice" DOCUMENT = "document" STICKER = "sticker" ANIMATION = "animation" VIDEO_NOTE = "video_note" CONTACT = "contact" LOCATION = "location" POLL = "poll" VENUE = "venue" WEBPAGE_PREVIEW = "webpage_preview" class TelegramChatType(Enum): """Telegram chat types""" PRIVATE = "private" GROUP = "group" SUPERGROUP = "supergroup" CHANNEL = "channel" class TelegramCommandType(Enum): """Telegram command types""" START = "start" HELP = "help" STATUS = "status" SEARCH = "search" WORKFLOW = "workflow" AUTOMATE = "automate" SECURITY = "security" COMPLIANCE = "compliance" ANALYTICS = "analytics" MONITOR = "monitor" REPORT = "report" ADMIN = "admin" @dataclass class TelegramUser: """Telegram user data model""" user_id: int username: Optional[str] first_name: Optional[str] last_name: Optional[str] language_code: Optional[str] is_bot: bool is_premium: bool is_active: bool permissions: List[str] security_level: str created_at: datetime last_active: datetime metadata: Dict[str, Any] @dataclass class TelegramChat: """Telegram chat data model""" chat_id: int chat_type: TelegramChatType title: Optional[str] username: Optional[str] first_name: Optional[str] last_name: Optional[str] description: Optional[str] permissions: Dict[str, Any] security_level: str is_active: bool member_count: int created_at: datetime last_message: datetime metadata: Dict[str, Any] @dataclass class TelegramMessage: """Telegram message data model""" message_id: int chat_id: int user_id: int message_type: TelegramMessageType content: str media_path: Optional[str] reply_to_message_id: Optional[int] forward_from: Optional[int] forward_from_chat: Optional[int] edit_date: Optional[datetime] timestamp: datetime views: int reactions: List[Dict[str, Any]] security_flags: Dict[str, Any] metadata: Dict[str, Any] class AtomTelegramIntegration: """Advanced Telegram integration with enterprise features""" def __init__(self, config: Dict[str, Any]): self.config = config self.db = config.get('database') self.cache = config.get('cache') # Telegram configuration self.telegram_config = { 'bot_token': config.get('bot_token') or os.getenv('TELEGRAM_BOT_TOKEN'), 'bot_username': config.get('bot_username') or os.getenv('TELEGRAM_BOT_USERNAME'), 'webhook_url': config.get('webhook_url') or os.getenv('TELEGRAM_WEBHOOK_URL'), 'admin_user_ids': config.get('admin_user_ids', []), 'allowed_chat_types': config.get('allowed_chat_types', ['private', 'group', 'supergroup', 'channel']), 'max_message_length': config.get('max_message_length', 4096), 'enable_enterprise_features': config.get('enable_enterprise_features', True), 'security_level': config.get('security_level', 'standard'), 'compliance_standards': config.get('compliance_standards', ['SOC2', 'ISO27001']) } # Integration state self.is_initialized = False self.active_chats: Dict[int, TelegramChat] = {} self.active_users: Dict[int, TelegramUser] = {} self.message_history: Dict[int, List[TelegramMessage]] = {} self.command_handlers: Dict[str, Callable] = {} self.message_handlers: List[Callable] = [] # Callback query handlers registry self.callback_handlers = { "action_": self._handle_action_callback, "search_": self._handle_search_callback, "workflow_": self._handle_workflow_callback, "settings_": self._handle_settings_callback, } # Enterprise integration self.enterprise_security = config.get('security_service') or atom_enterprise_security_service self.enterprise_automation = config.get('automation_service') or atom_workflow_automation_service self.ai_service = config.get('ai_service') or ai_enhanced_service # LanceDB handler for semantic search self.lancedb_handler = None try: from core.lancedb_handler import LanceDBHandler self.lancedb_handler = LanceDBHandler() logger.info("LanceDB handler initialized for Telegram integration") except ImportError as e: logger.warning(f"LanceDB not available for inline search: {e}") # Analytics and monitoring self.analytics_metrics = { 'total_messages': 0, 'total_chats': 0, 'total_users': 0, 'commands_executed': 0, 'automations_triggered': 0, 'security_incidents': 0, 'compliance_checks': 0, 'ai_requests': 0, 'message_types': defaultdict(int), 'chat_types': defaultdict(int), 'active_chats': 0, 'active_users': 0 } # Security and compliance self.security_policies = {} self.compliance_rules = {} self.automation_triggers = {} self.message_filters = [] # Performance metrics self.performance_metrics = { 'message_processing_time': 0.0, 'command_response_time': 0.0, 'ai_processing_time': 0.0, 'security_check_time': 0.0, 'compliance_check_time': 0.0, 'automation_execution_time': 0.0, 'webhook_response_time': 0.0 } logger.info("Telegram Integration initialized") async def initialize(self) -> bool: """Initialize Telegram integration""" try: if not self.telegram_config['bot_token']: logger.error("Telegram bot token not provided") return False # Setup enterprise features if self.telegram_config['enable_enterprise_features']: await self._setup_enterprise_features() # Setup security and compliance await self._setup_security_and_compliance() # Setup automation await self._setup_automation() # Load existing data await self._load_existing_data() # Start bot (mock implementation) await self._start_bot() self.is_initialized = True logger.info("Telegram Integration initialized successfully") return True except Exception as e: logger.error(f"Error initializing Telegram integration: {e}") return False async def get_intelligent_workspaces(self, user_id: int) -> List[Dict[str, Any]]: """Get intelligent workspaces for user""" try: workspaces = [] for chat_id, chat in self.active_chats.items(): # Check if user has access to chat if chat.is_active: workspace = { 'id': chat.chat_id, 'name': chat.title or f"Chat {chat.chat_id}", 'type': chat.chat_type.value, 'member_count': chat.member_count, 'description': chat.description, 'last_activity': chat.last_message.isoformat(), 'security_level': chat.security_level, 'permissions': chat.permissions, 'platform': 'telegram' } workspaces.append(workspace) # Sort by last activity workspaces.sort(key=lambda x: x['last_activity'], reverse=True) return workspaces except Exception as e: logger.error(f"Error getting intelligent workspaces: {e}") return [] async def get_intelligent_channels(self, workspace_id: int, user_id: int) -> List[Dict[str, Any]]: """Get intelligent channels for workspace""" try: channels = [] chat = self.active_chats.get(workspace_id) if chat: # For Telegram, workspace is the chat itself channel = { 'id': chat.chat_id, 'name': chat.title or f"Chat {chat.chat_id}", 'type': chat.chat_type.value, 'member_count': chat.member_count, 'description': chat.description, 'security_level': chat.security_level, 'permissions': chat.permissions, 'is_active': chat.is_active, 'last_activity': chat.last_message.isoformat(), 'platform': 'telegram' } channels.append(channel) return channels except Exception as e: logger.error(f"Error getting intelligent channels: {e}") return [] async def send_intelligent_message(self, channel_id: int, message: str, metadata: Dict[str, Any] = None) -> Dict[str, Any]: """Send intelligent message""" try: # Mock implementation - would use actual Telegram API result = { 'success': True, 'channel_id': channel_id, 'message': message, 'timestamp': datetime.utcnow().isoformat(), 'platform': 'telegram', 'metadata': metadata or {} } # Log message if self.telegram_config['enable_enterprise_features']: await self._log_message_event('message_sent', channel_id, result) return result except Exception as e: logger.error(f"Error sending intelligent message: {e}") return { 'success': False, 'error': str(e), 'platform': 'telegram' } async def perform_intelligent_search(self, query: str, user_id: int, workspace_id: int = None) -> List[Dict[str, Any]]: """Perform intelligent search""" try: search_results = [] # Search in message history for chat_id, messages in self.message_history.items(): if workspace_id and chat_id != workspace_id: continue for message in messages: if query.lower() in message.content.lower(): result = { 'id': message.message_id, 'type': 'telegram_message', 'title': f"Message {message.message_id}", 'snippet': message.content[:100] + "..." if len(message.content) > 100 else message.content, 'content': message.content, 'channel_id': message.chat_id, 'user_id': message.user_id, 'timestamp': message.timestamp.isoformat(), 'message_type': message.message_type.value, 'platform': 'telegram', 'relevance_score': self._calculate_relevance_score(query, message.content) } search_results.append(result) # Sort by relevance score search_results.sort(key=lambda x: x['relevance_score'], reverse=True) # AI-enhanced search if self.ai_service: ai_results = await self._perform_ai_search(query, workspace_id) search_results.extend(ai_results) return search_results[:20] # Return top 20 results except Exception as e: logger.error(f"Error performing intelligent search: {e}") return [] async def get_user_conversation_history(self, user_id: int, channel_id: int, limit: int = 50) -> List[Dict[str, Any]]: """Get user conversation history""" try: conversation_history = [] messages = self.message_history.get(channel_id, []) # Filter by user and limit user_messages = [m for m in messages if m.user_id == user_id][-limit:] for message in user_messages: history_item = { 'id': message.message_id, 'content': message.content, 'message_type': message.message_type.value, 'timestamp': message.timestamp.isoformat(), 'channel_id': message.chat_id, 'platform': 'telegram', 'metadata': message.metadata } conversation_history.append(history_item) return conversation_history except Exception as e: logger.error(f"Error getting user conversation history: {e}") return [] async def get_service_status(self) -> Dict[str, Any]: """Get Telegram service status""" try: return { 'platform': 'telegram', 'status': 'active' if self.is_initialized else 'inactive', 'bot_username': self.telegram_config['bot_username'], 'webhook_url': self.telegram_config['webhook_url'], 'enterprise_features': self.telegram_config['enable_enterprise_features'], 'security_level': self.telegram_config['security_level'], 'compliance_standards': self.telegram_config['compliance_standards'], 'total_messages': self.analytics_metrics['total_messages'], 'total_chats': self.analytics_metrics['total_chats'], 'total_users': self.analytics_metrics['total_users'], 'commands_executed': self.analytics_metrics['commands_executed'], 'automations_triggered': self.analytics_metrics['automations_triggered'], 'security_incidents': self.analytics_metrics['security_incidents'], 'compliance_checks': self.analytics_metrics['compliance_checks'], 'ai_requests': self.analytics_metrics['ai_requests'], 'active_chats': self.analytics_metrics['active_chats'], 'active_users': self.analytics_metrics['active_users'], 'performance_metrics': self.performance_metrics, 'uptime': time.time() - (self._start_time if hasattr(self, '_start_time') else time.time()) } except Exception as e: logger.error(f"Error getting service status: {e}") return {'error': str(e), 'platform': 'telegram'} # Private helper methods async def _setup_enterprise_features(self): """Setup enterprise features""" try: if not self.enterprise_security or not self.enterprise_automation: logger.warning("Enterprise services not available") return # Setup security policies await self._setup_security_policies() # Setup compliance rules await self._setup_compliance_rules() # Setup automation triggers await self._setup_automation_triggers() logger.info("Enterprise features setup complete") except Exception as e: logger.error(f"Error setting up enterprise features: {e}") async def _setup_security_policies(self): """Setup security policies""" try: self.security_policies = { 'message_content_filter': { 'enabled': True, 'blocked_patterns': ['spam', 'malware', 'suspicious'], 'action': 'block' }, 'user_access_control': { 'enabled': True, 'allowed_domains': [], 'blocked_users': [], 'action': 'restrict' }, 'chat_security': { 'enabled': True, 'require_admin_approval': False, 'encryption_required': False, 'action': 'monitor' } } logger.info("Security policies setup complete") except Exception as e: logger.error(f"Error setting up security policies: {e}") async def _setup_compliance_rules(self): """Setup compliance rules""" try: self.compliance_rules = { 'message_retention': { 'enabled': True, 'retention_period': 365, 'auto_delete': False }, 'content_moderation': { 'enabled': True, 'profanity_filter': True, 'hate_speech_filter': True, 'action': 'flag' }, 'audit_logging': { 'enabled': True, 'log_all_messages': True, 'log_user_actions': True, 'action': 'log' } } logger.info("Compliance rules setup complete") except Exception as e: logger.error(f"Error setting up compliance rules: {e}") async def _setup_automation_triggers(self): """Setup automation triggers""" try: self.automation_triggers = { 'message_received': { 'enabled': True, 'conditions': ['chat_type', 'user_role', 'message_content'], 'actions': ['send_notification', 'execute_workflow', 'ai_analysis'] }, 'user_joined': { 'enabled': True, 'conditions': ['user_verification', 'chat_permissions'], 'actions': ['welcome_message', 'role_assignment', 'compliance_check'] }, 'command_executed': { 'enabled': True, 'conditions': ['command_type', 'user_permissions'], 'actions': ['process_command', 'security_check', 'logging'] } } logger.info("Automation triggers setup complete") except Exception as e: logger.error(f"Error setting up automation triggers: {e}") async def _setup_automation(self): """Setup automation""" try: if not self.enterprise_automation: logger.warning("Automation service not available") return # Create Telegram-specific automation telegram_automation_data = { 'name': 'Telegram Integration Automation', 'description': 'Automation for Telegram integration events', 'automation_type': 'integration', 'priority': 'medium', 'conditions': [ { 'type': 'event_triggered', 'platform': 'telegram', 'events': ['message_received', 'user_joined', 'command_executed'] } ], 'actions': [ { 'type': 'notification', 'config': { 'channels': ['platform_admin'], 'message': 'Telegram integration event occurred', 'urgency': 'low' } } ], 'schedule': None, 'timeout': 300, 'retry_policy': { 'max_retries': 2, 'backoff': 'exponential' }, 'notification_rules': [ { 'condition': 'on_error', 'channels': ['platform_admin'], 'urgency': 'medium' } ], 'metadata': { 'platform': 'telegram', 'integration_version': '1.0.0' } } result = await self.enterprise_automation.create_integration_automation('telegram', telegram_automation_data) if result.get('ok'): logger.info("Telegram automation created successfully") else: logger.error(f"Failed to create Telegram automation: {result.get('error')}") except Exception as e: logger.error(f"Error setting up automation: {e}") async def _setup_security_and_compliance(self): """Setup security and compliance monitoring""" try: # Setup monitoring for security events if self.telegram_config['enable_enterprise_features']: # Security monitoring await self._setup_security_monitoring() # Compliance monitoring await self._setup_compliance_monitoring() logger.info("Security and compliance setup complete") except Exception as e: logger.error(f"Error setting up security and compliance: {e}") async def _setup_security_monitoring(self): """Setup security monitoring""" try: # Define security monitoring rules self.security_monitoring = { 'message_anomaly_detection': { 'enabled': True, 'threshold': 0.8, 'action': 'alert' }, 'user_behavior_analysis': { 'enabled': True, 'baseline_period': 30, 'action': 'monitor' }, 'chat_security_monitoring': { 'enabled': True, 'security_score_threshold': 0.7, 'action': 'flag' } } logger.info("Security monitoring setup complete") except Exception as e: logger.error(f"Error setting up security monitoring: {e}") async def _setup_compliance_monitoring(self): """Setup compliance monitoring""" try: # Define compliance monitoring rules self.compliance_monitoring = { 'message_compliance_checking': { 'enabled': True, 'check_frequency': 'real_time', 'action': 'flag' }, 'user_activity_auditing': { 'enabled': True, 'audit_retention': 365, 'action': 'log' }, 'data_retention_management': { 'enabled': True, 'retention_policy': 'standard', 'action': 'manage' } } logger.info("Compliance monitoring setup complete") except Exception as e: logger.error(f"Error setting up compliance monitoring: {e}") async def _load_existing_data(self): """Load existing data""" try: # Mock implementation - would load from database logger.info("Existing data loaded") except Exception as e: logger.error(f"Error loading existing data: {e}") async def _start_bot(self): """Start Telegram bot""" try: # Mock implementation - would start actual Telegram bot self._start_time = time.time() logger.info("Telegram bot started") except Exception as e: logger.error(f"Error starting bot: {e}") def _calculate_relevance_score(self, query: str, content: str) -> float: """Calculate relevance score for search""" try: # Simple relevance scoring query_words = query.lower().split() content_words = content.lower().split() matches = 0 for word in query_words: if word in content_words: matches += 1 return matches / len(query_words) if query_words else 0.0 except Exception as e: logger.error(f"Error calculating relevance score: {e}") return 0.0 async def _perform_ai_search(self, query: str, workspace_id: int = None) -> List[Dict[str, Any]]: """Perform AI-enhanced search""" try: if not self.ai_service: return [] # Create AI request ai_request = AIRequest( request_id=f"telegram_search_{int(time.time())}", task_type=AITaskType.SEARCH_QUERY, model_type=AIModelType.GPT_4, service_type=AIServiceType.OPENAI, input_data={ 'query': query, 'context': 'telegram_search', 'workspace_id': workspace_id, 'message_history': [asdict(m) for chat_messages in self.message_history.values() for m in chat_messages] }, context={ 'platform': 'telegram', 'workspace_id': workspace_id }, platform='telegram' ) # Process AI request ai_response = await self.ai_service.process_ai_request(ai_request) if ai_response.ok and ai_response.output_data: return ai_response.output_data.get('results', []) return [] except Exception as e: logger.error(f"Error performing AI search: {e}") return [] async def _log_message_event(self, event_type: str, channel_id: int, data: Dict[str, Any]): """Log message event""" try: if self.enterprise_security: await self.enterprise_security.audit_event({ 'event_type': event_type, 'user_id': data.get('user_id'), 'resource': 'telegram_message', 'action': event_type, 'result': 'success', 'ip_address': 'telegram', 'user_agent': 'telegram_bot', 'metadata': { 'channel_id': channel_id, 'platform': 'telegram', 'data': data } }) except Exception as e: logger.error(f"Error logging message event: {e}") async def close(self): """Close Telegram integration""" try: # Mock implementation - would stop actual Telegram bot logger.info("Telegram Integration closed") except Exception as e: logger.error(f"Error closing Telegram integration: {e}") # ======================================================================== # Interactive Keyboard Methods # ======================================================================== async def send_message_with_keyboard( self, chat_id: int, text: str, keyboard: List[List[Dict[str, Any]]], parse_mode: Optional[str] = None, disable_web_page_preview: Optional[bool] = None, disable_notification: Optional[bool] = None, reply_to_message_id: Optional[int] = None, ) -> Dict[str, Any]: """ Send a message with interactive inline keyboard. Args: chat_id: Telegram chat ID text: Message text keyboard: List of rows of buttons parse_mode: "Markdown" or "HTML" disable_web_page_preview: Disable link previews disable_notification: Send silently reply_to_message_id: Reply to specific message Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} # Build API URL url = f"https://api.telegram.org/bot{bot_token}/sendMessage" # Build keyboard (inline keyboard) reply_markup = { "inline_keyboard": keyboard } # Build request payload payload = { "chat_id": chat_id, "text": text, "reply_markup": reply_markup, } # Optional parameters if parse_mode: payload["parse_mode"] = parse_mode if disable_web_page_preview is not None: payload["disable_web_page_preview"] = disable_web_page_preview if disable_notification is not None: payload["disable_notification"] = disable_notification if reply_to_message_id: payload["reply_to_message_id"] = reply_to_message_id # Send request import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Sent keyboard message to chat {chat_id}") return { "success": True, "message_id": data.get("result", {}).get("message_id"), "chat_id": chat_id, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to send keyboard message: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error sending keyboard message: {e}") return {"success": False, "error": str(e)} async def edit_message_keyboard( self, chat_id: int, message_id: int, keyboard: List[List[Dict[str, Any]]], ) -> Dict[str, Any]: """ Edit keyboard of an existing message. Args: chat_id: Telegram chat ID message_id: Message to edit keyboard: New keyboard layout Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/editMessageReplyMarkup" reply_markup = { "inline_keyboard": keyboard } payload = { "chat_id": chat_id, "message_id": message_id, "reply_markup": reply_markup, } import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Edited keyboard for message {message_id} in chat {chat_id}") return { "success": True, "message_id": message_id, "chat_id": chat_id, } else: error_msg = data.get("description", "Unknown error") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error editing message keyboard: {e}") return {"success": False, "error": str(e)} async def answer_callback_query( self, callback_query_id: str, text: Optional[str] = None, show_alert: Optional[bool] = False, url: Optional[str] = None, cache_time: Optional[int] = None, ) -> Dict[str, Any]: """ Answer a callback query from an inline keyboard button. Args: callback_query_id: Callback query ID from update text: Notification text (max 200 chars) show_alert: Show as alert instead of notification url: URL to open cache_time: Cache button response (seconds) Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/answerCallbackQuery" payload = { "callback_query_id": callback_query_id, } if text: payload["text"] = text if show_alert: payload["show_alert"] = show_alert if url: payload["url"] = url if cache_time is not None: payload["cache_time"] = cache_time import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Answered callback query {callback_query_id}") return { "success": True, "callback_query_id": callback_query_id, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to answer callback query: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error answering callback query: {e}") return {"success": False, "error": str(e)} async def handle_callback_query(self, callback_query: Dict[str, Any]) -> None: """ Handle a callback query from button press. Routes callback to appropriate handler based on callback_data. """ try: callback_id = callback_query.get("id") data = callback_query.get("data", "") message = callback_query.get("message", {}) from_user = callback_query.get("from", {}) logger.info(f"Received callback query {callback_id} with data: {data}") # Send immediate answer to show processing await self.answer_callback_query( callback_query_id=callback_id, text="Processing...", cache_time=0, # Don't cache while processing ) # Route to appropriate handler based on data if data: for prefix, handler in self.callback_handlers.items(): if data.startswith(prefix): await handler(callback_id, data, user_id) return # No matching handler found logger.warning(f"No handler found for callback data: {data}") await self.answer_callback_query( callback_query_id=callback_id, text="Unknown action", show_alert=True ) else: logger.warning("Received callback query with no data") await self.answer_callback_query( callback_query_id=callback_id, text="Invalid callback", show_alert=True ) except Exception as e: logger.error(f"Error handling callback query: {e}") async def _handle_action_callback(self, callback_query_id: str, data: str, user_id: int): """ Handle action callbacks (e.g., button presses for actions). Expected format: action__ Example: action_approve_request_123 """ try: # Parse action from data parts = data.split('_') if len(parts) < 2: await self.answer_callback_query( callback_query_id=callback_query_id, text="Invalid action format", show_alert=True ) return action_name = parts[1] params = parts[2:] if len(parts) > 2 else [] logger.info(f"Handling action callback: action={action_name}, params={params}, user={user_id}") # Route to specific action handlers if action_name == "approve_request": await self._handle_approve_request(callback_query_id, params, user_id) elif action_name == "deny_request": await self._handle_deny_request(callback_query_id, params, user_id) elif action_name == "execute_workflow": await self._handle_execute_workflow(callback_query_id, params, user_id) else: await self.answer_callback_query( callback_query_id=callback_query_id, text=f"Unknown action: {action_name}", show_alert=True ) except Exception as e: logger.error(f"Error handling action callback: {e}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Error processing action", show_alert=True ) async def _handle_search_callback(self, callback_query_id: str, data: str, user_id: int): """ Handle search callbacks (e.g., search refinement). Expected format: search__ Example: search_recent_messages """ try: # Parse search type from data parts = data.split('_') if len(parts) < 2: await self.answer_callback_query( callback_query_id=callback_query_id, text="Invalid search format", show_alert=True ) return search_type = parts[1] query = '_'.join(parts[2:]) if len(parts) > 2 else "" logger.info(f"Handling search callback: type={search_type}, query={query}, user={user_id}") # Route to specific search handlers if search_type == "recent_messages": await self._handle_search_recent_messages(callback_query_id, user_id) elif search_type == "communications": await self._handle_search_communications(callback_query_id, query, user_id) elif search_type == "workflows": await self._handle_search_workflows(callback_query_id, query, user_id) else: await self.answer_callback_query( callback_query_id=callback_query_id, text=f"Unknown search type: {search_type}", show_alert=True ) except Exception as e: logger.error(f"Error handling search callback: {e}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Error processing search", show_alert=True ) async def _handle_workflow_callback(self, callback_query_id: str, data: str, user_id: int): """ Handle workflow callbacks (e.g., workflow execution triggers). Expected format: workflow__ Example: workflow_123_start """ try: # Parse workflow info from data parts = data.split('_') if len(parts) < 3: await self.answer_callback_query( callback_query_id=callback_query_id, text="Invalid workflow format", show_alert=True ) return workflow_id = parts[1] action = parts[2] logger.info(f"Handling workflow callback: workflow={workflow_id}, action={action}, user={user_id}") # Route to specific workflow actions if action == "start": await self._handle_start_workflow(callback_query_id, workflow_id, user_id) elif action == "stop": await self._handle_stop_workflow(callback_query_id, workflow_id, user_id) elif action == "status": await self._handle_workflow_status(callback_query_id, workflow_id, user_id) else: await self.answer_callback_query( callback_query_id=callback_query_id, text=f"Unknown workflow action: {action}", show_alert=True ) except Exception as e: logger.error(f"Error handling workflow callback: {e}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Error processing workflow", show_alert=True ) async def _handle_settings_callback(self, callback_query_id: str, data: str, user_id: int): """ Handle settings callbacks (e.g., settings changes). Expected format: settings__ Example: settings_notifications_enabled """ try: # Parse setting from data parts = data.split('_') if len(parts) < 3: await self.answer_callback_query( callback_query_id=callback_query_id, text="Invalid settings format", show_alert=True ) return setting_name = parts[1] value = '_'.join(parts[2:]) if len(parts) > 2 else "" logger.info(f"Handling settings callback: setting={setting_name}, value={value}, user={user_id}") # Route to specific setting handlers if setting_name == "notifications": await self._handle_notifications_setting(callback_query_id, value, user_id) elif setting_name == "language": await self._handle_language_setting(callback_query_id, value, user_id) elif setting_name == "theme": await self._handle_theme_setting(callback_query_id, value, user_id) else: await self.answer_callback_query( callback_query_id=callback_query_id, text=f"Unknown setting: {setting_name}", show_alert=True ) except Exception as e: logger.error(f"Error handling settings callback: {e}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Error updating settings", show_alert=True ) # ------------------------------------------------------------------------ # Action sub-handlers # ------------------------------------------------------------------------ async def _handle_approve_request(self, callback_query_id: str, params: List[str], user_id: int): """Handle request approval action""" request_id = params[0] if params else None logger.info(f"Approving request {request_id} by user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Request approved" ) async def _handle_deny_request(self, callback_query_id: str, params: List[str], user_id: int): """Handle request denial action""" request_id = params[0] if params else None logger.info(f"Denying request {request_id} by user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Request denied" ) async def _handle_execute_workflow(self, callback_query_id: str, params: List[str], user_id: int): """Handle workflow execution action""" workflow_id = params[0] if params else None logger.info(f"Executing workflow {workflow_id} by user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Workflow execution started" ) # ------------------------------------------------------------------------ # Search sub-handlers # ------------------------------------------------------------------------ async def _handle_search_recent_messages(self, callback_query_id: str, user_id: int): """Handle recent messages search""" logger.info(f"Searching recent messages for user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Search completed" ) async def _handle_search_communications(self, callback_query_id: str, query: str, user_id: int): """Handle communications search""" logger.info(f"Searching communications for '{query}' by user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Search completed" ) async def _handle_search_workflows(self, callback_query_id: str, query: str, user_id: int): """Handle workflows search""" logger.info(f"Searching workflows for '{query}' by user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Search completed" ) # ------------------------------------------------------------------------ # Workflow sub-handlers # ------------------------------------------------------------------------ async def _handle_start_workflow(self, callback_query_id: str, workflow_id: str, user_id: int): """Handle workflow start action""" logger.info(f"Starting workflow {workflow_id} by user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Workflow started" ) async def _handle_stop_workflow(self, callback_query_id: str, workflow_id: str, user_id: int): """Handle workflow stop action""" logger.info(f"Stopping workflow {workflow_id} by user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Workflow stopped" ) async def _handle_workflow_status(self, callback_query_id: str, workflow_id: str, user_id: int): """Handle workflow status query""" logger.info(f"Getting status of workflow {workflow_id} for user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Status: Running" ) # ------------------------------------------------------------------------ # Settings sub-handlers # ------------------------------------------------------------------------ async def _handle_notifications_setting(self, callback_query_id: str, value: str, user_id: int): """Handle notifications setting""" logger.info(f"Setting notifications to '{value}' for user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Notifications updated" ) async def _handle_language_setting(self, callback_query_id: str, value: str, user_id: int): """Handle language setting""" logger.info(f"Setting language to '{value}' for user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Language updated" ) async def _handle_theme_setting(self, callback_query_id: str, value: str, user_id: int): """Handle theme setting""" logger.info(f"Setting theme to '{value}' for user {user_id}") await self.answer_callback_query( callback_query_id=callback_query_id, text="Theme updated" ) # ======================================================================== # Inline Mode Methods # ======================================================================== async def answer_inline_query( self, inline_query_id: str, results: List[Dict[str, Any]], cache_time: Optional[int] = 300, personal: Optional[bool] = None, next_offset: Optional[str] = None, ) -> Dict[str, Any]: """ Answer an inline query. Args: inline_query_id: Inline query ID results: List of result objects cache_time: Cache duration in seconds personal: Cache only for user next_offset: Offset for pagination Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/answerInlineQuery" # Build inline query results inline_results = [] for result in results[:50]: # Limit to 50 results inline_results.append({ "type": "article", "id": result.get("id", str(result.get("result_id"))), "title": result.get("title", ""), "description": result.get("description", ""), "input_message_content": { "message_text": result.get("message", "") }, }) payload = { "inline_query_id": inline_query_id, "results": inline_results, "cache_time": cache_time, "is_personal": personal or False, } if next_offset: payload["next_offset"] = next_offset import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Answered inline query {inline_query_id}") return { "success": True, "inline_query_id": inline_query_id, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to answer inline query: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error answering inline query: {e}") return {"success": False, "error": str(e)} async def handle_inline_query(self, inline_query: Dict[str, Any]) -> None: """ Handle an inline query. Searches for results and responds to the inline query using semantic search. """ try: query_id = inline_query.get("id") query = inline_query.get("query", "") from_user = inline_query.get("from", {}) user_id = from_user.get("id") logger.info(f"Received inline query {query_id} from user {user_id}: {query}") # Perform semantic search results = [] if query and len(query.strip()) >= 2: # Use LanceDB for semantic search if available if self.lancedb_handler: try: # Search in communications table search_results = await self.lancedb_handler.semantic_search( table_name="communications", query_text=query, limit=10 ) # Convert LanceDB results to Telegram inline format for result in search_results: inline_result = self._format_lancedb_result_for_inline(result) if inline_result: results.append(inline_result) logger.info(f"Found {len(results)} semantic search results for query: {query}") except Exception as e: logger.error(f"Error performing semantic search: {e}") # Fall back to simple results results = await self._perform_simple_inline_search(query) else: # Use simple search if LanceDB not available results = await self._perform_simple_inline_search(query) # Answer with results await self.answer_inline_query( inline_query_id=query_id, results=results, cache_time=300, ) except Exception as e: logger.error(f"Error handling inline query: {e}") except Exception as e: logger.error(f"Error handling inline query: {e}") def _format_lancedb_result_for_inline(self, result: Dict[str, Any]) -> Optional[Dict[str, Any]]: """ Format LanceDB search result for Telegram inline query response. Args: result: LanceDB search result Returns: Formatted inline result dict or None if formatting fails """ try: # Extract relevant fields from result comm_id = result.get('id', '') subject = result.get('subject', 'No Subject') body = result.get('body', '') sender = result.get('sender', 'Unknown') platform = result.get('platform', 'unknown') timestamp = result.get('timestamp', '') # Create message text for the inline result message_text = f"*{subject}*\n\n" message_text += f"From: {sender}\n" message_text += f"Platform: {platform}\n\n" # Add truncated body if body: body_preview = body[:200] + "..." if len(body) > 200 else body message_text += f"{body_preview}" # Format as Telegram inline result inline_result = { "type": "article", "id": comm_id or str(hash(subject + body)), "title": subject, "description": f"From {sender} via {platform}", "input_message_content": { "message_text": message_text, "parse_mode": "Markdown" } } return inline_result except Exception as e: logger.error(f"Error formatting LanceDB result: {e}") return None async def _perform_simple_inline_search(self, query: str) -> List[Dict[str, Any]]: """ Perform a simple inline search without LanceDB (fallback). Args: query: Search query string Returns: List of inline results """ try: # Return simple static results as fallback results = [ { "type": "article", "id": "help_1", "title": f"Search: {query}", "description": "Advanced search not available", "input_message_content": { "message_text": f"Semantic search is not configured. Your query: {query}" } } ] logger.debug(f"Performed simple inline search for: {query}") return results except Exception as e: logger.error(f"Error in simple inline search: {e}") return [] # ======================================================================== # Chat Action Methods # ======================================================================== async def send_chat_action( self, chat_id: int, action: str, progress: Optional[int] = None, ) -> Dict[str, Any]: """ Send a chat action indicator. Args: chat_id: Telegram chat ID action: Action type (typing, upload_photo, etc.) progress: Progress percentage (0-100) Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/sendChatAction" payload = { "chat_id": chat_id, "action": action, } if progress is not None: payload["progress"] = progress import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Sent chat action '{action}' to chat {chat_id}") return { "success": True, "chat_id": chat_id, "action": action, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to send chat action: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error sending chat action: {e}") return {"success": False, "error": str(e)} # ======================================================================== # Enhanced Message Methods # ======================================================================== async def send_intelligent_message( self, channel_id: int, message: str, metadata: Optional[Dict[str, Any]] = None, parse_mode: Optional[str] = None, disable_web_page_preview: Optional[bool] = None, disable_notification: Optional[bool] = None, reply_to_message_id: Optional[int] = None, ) -> Dict[str, Any]: """ Enhanced send message with support for parse mode and reply. Args: channel_id: Telegram chat ID message: Message text metadata: Optional metadata parse_mode: Markdown or HTML disable_web_page_preview: Disable link previews disable_notification: Send silently reply_to_message_id: Reply to specific message Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/sendMessage" payload = { "chat_id": channel_id, "text": message, } # Optional parameters if parse_mode: payload["parse_mode"] = parse_mode if disable_web_page_preview is not None: payload["disable_web_page_preview"] = disable_web_page_preview if disable_notification is not None: payload["disable_notification"] = disable_notification if reply_to_message_id: payload["reply_to_message_id"] = reply_to_message_id import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Sent intelligent message to channel {channel_id}") return { "success": True, "message_id": data.get("result", {}).get("message_id"), "channel_id": channel_id, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to send message: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error sending intelligent message: {e}") return {"success": False, "error": str(e)} async def send_photo( self, chat_id: int, photo: str, caption: Optional[str] = None, parse_mode: Optional[str] = None, ) -> Dict[str, Any]: """ Send a photo to Telegram chat. Args: chat_id: Telegram chat ID photo: Photo URL or file_id caption: Photo caption parse_mode: Markdown or HTML Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/sendPhoto" payload = { "chat_id": chat_id, "photo": photo, } if caption: payload["caption"] = caption if parse_mode: payload["parse_mode"] = parse_mode import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Sent photo to chat {chat_id}") return { "success": True, "message_id": data.get("result", {}).get("message_id"), "chat_id": chat_id, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to send photo: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error sending photo: {e}") return {"success": False, "error": str(e)} async def send_poll( self, chat_id: int, question: str, options: List[str], is_anonymous: bool = False, allows_multiple_answers: bool = False, explanation: Optional[str] = None, ) -> Dict[str, Any]: """ Send a poll to Telegram chat. Args: chat_id: Telegram chat ID question: Poll question options: List of answer options is_anonymous: Anonymous poll allows_multiple_answers: Allow multiple selections explanation: Additional explanation Returns: Result dict with success status """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/sendPoll" # Build poll options poll_options = [] for option in options: poll_options.append({"text": option}) payload = { "chat_id": chat_id, "question": question, "options": poll_options, "is_anonymous": is_anonymous, "allows_multiple_answers": allows_multiple_answers, } if explanation: payload["explanation"] = explanation import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): logger.info(f"Sent poll to chat {chat_id}") return { "success": True, "message_id": data.get("result", {}).get("message_id"), "poll_id": data.get("result", {}).get("poll_id"), "chat_id": chat_id, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to send poll: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error sending poll: {e}") return {"success": False, "error": str(e)} async def get_chat_info( self, chat_id: int, ) -> Dict[str, Any]: """ Get information about a Telegram chat. Args: chat_id: Telegram chat ID Returns: Chat information dict """ try: bot_token = self.config.get('bot_token') if not bot_token: return {"success": False, "error": "Bot token not configured"} url = f"https://api.telegram.org/bot{bot_token}/getChat" payload = {"chat_id": chat_id} import httpx async with httpx.AsyncClient() as client: response = await client.post(url, json=payload) data = response.json() if data.get("ok"): result = data.get("result", {}) logger.info(f"Retrieved chat info for {chat_id}") return { "success": True, "chat_id": chat_id, "chat_info": result, } else: error_msg = data.get("description", "Unknown error") logger.error(f"Failed to get chat info: {error_msg}") return {"success": False, "error": error_msg} except Exception as e: logger.error(f"Error getting chat info: {e}") return {"success": False, "error": str(e)} # Global Telegram integration instance atom_telegram_integration = AtomTelegramIntegration({ 'bot_token': os.getenv('TELEGRAM_BOT_TOKEN'), 'bot_username': os.getenv('TELEGRAM_BOT_USERNAME'), 'webhook_url': os.getenv('TELEGRAM_WEBHOOK_URL'), 'enable_enterprise_features': True, 'security_level': 'standard', 'compliance_standards': ['SOC2', 'ISO27001'], 'database': None, # Would be actual database connection 'cache': None, # Would be actual cache client 'security_service': atom_enterprise_security_service, 'automation_service': atom_workflow_automation_service, 'ai_service': ai_enhanced_service })