update

Backend/alembic/env.py

@@ -8,8 +8,8 @@ from pathlib import Path
 from dotenv import load_dotenv
 load_dotenv()
 sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
-from src.config.database import Base
-from src.config.settings import settings
+from src.shared.config.database import Base
+from src.shared.config.settings import settings
 from src.models import *
 config = context.config
 if config.config_file_name is not None:

Backend/run.py

@@ -1,6 +1,6 @@
 import uvicorn
-from src.config.settings import settings
-from src.config.logging_config import setup_logging, get_logger
+from src.shared.config.settings import settings
+from src.shared.config.logging_config import setup_logging, get_logger
 setup_logging()
 logger = get_logger(__name__)
 if __name__ == '__main__':

Backend/run_tests.sh

@@ -1,16 +0,0 @@
-#!/bin/bash
-
-# Script to run integration tests for the Hotel Booking API
-
-echo "Running integration tests for Hotel Booking API..."
-echo "=================================================="
-
-# Change to Backend directory
-cd "$(dirname "$0")"
-
-# Run pytest with integration marker
-pytest src/tests/ -v -m integration --tb=short
-
-# Exit with pytest's exit code
-exit $?
-

Backend/seeds_data/add_accountant_role.py

@@ -11,7 +11,7 @@ from pathlib import Path
 backend_dir = Path(__file__).parent
 sys.path.insert(0, str(backend_dir))
 
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.role import Role
 
 def add_accountant_role():

Backend/seeds_data/fix_blog_dates.py

@@ -6,7 +6,7 @@ from pathlib import Path
 sys.path.insert(0, str(Path(__file__).parent.parent))
 
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.blog import BlogPost
 from datetime import datetime, timedelta
 

Backend/seeds_data/seed_about_page.py

@@ -8,7 +8,7 @@ import json
 sys.path.insert(0, str(Path(__file__).parent))
 
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.page_content import PageContent, PageType
 from datetime import datetime
 

Backend/seeds_data/seed_banners_company.py

@@ -3,7 +3,7 @@ import os
 from datetime import datetime, timedelta
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src'))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.banner import Banner
 from src.models.system_settings import SystemSettings
 from src.models.user import User

Backend/seeds_data/seed_blog_posts.py

@@ -7,7 +7,7 @@ import os
 from pathlib import Path
 sys.path.insert(0, str(Path(__file__).parent.parent))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.blog import BlogPost
 from src.models.user import User
 from src.models.role import Role

Backend/seeds_data/seed_homepage_footer.py

@@ -3,7 +3,7 @@ import os
 import json
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src'))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.page_content import PageContent, PageType
 
 def seed_homepage_content(db: Session):

Backend/seeds_data/seed_initial_data.py

@@ -3,7 +3,7 @@ import os
 from pathlib import Path
 sys.path.insert(0, str(Path(__file__).parent))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.role import Role
 from src.models.room_type import RoomType
 from src.models.user import User

Backend/seeds_data/seed_loyalty_rewards.py

@@ -3,7 +3,7 @@ import os
 from pathlib import Path
 sys.path.insert(0, str(Path(__file__).parent.parent))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.loyalty_reward import LoyaltyReward, RewardType
 from src.models.loyalty_tier import LoyaltyTier, TierLevel
 from datetime import datetime, timedelta

Backend/seeds_data/seed_luxury_content.py

@@ -3,7 +3,7 @@ import os
 import json
 sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src'))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal, engine
+from src.shared.config.database import SessionLocal, engine
 from src.models.page_content import PageContent
 from src.models.user import User
 

Backend/seeds_data/seed_policy_pages.py

@@ -8,7 +8,7 @@ import json
 sys.path.insert(0, str(Path(__file__).parent))
 
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.page_content import PageContent, PageType
 from datetime import datetime
 

Backend/seeds_data/seed_rooms.py

@@ -3,7 +3,7 @@ import os
 from pathlib import Path
 sys.path.insert(0, str(Path(__file__).parent))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal, engine
+from src.shared.config.database import SessionLocal, engine
 from src.models.room import Room, RoomStatus
 from src.models.room_type import RoomType
 from datetime import datetime

Backend/seeds_data/seed_users.py

@@ -3,7 +3,7 @@ import os
 from pathlib import Path
 sys.path.insert(0, str(Path(__file__).parent))
 from sqlalchemy.orm import Session
-from src.config.database import SessionLocal
+from src.shared.config.database import SessionLocal
 from src.models.role import Role
 from src.models.user import User
 import bcrypt

Backend/src/ai/models/ai_conversation.py

@@ -0,0 +1,138 @@
+"""
+AI Conversation History and Learning Models
+Stores conversation history and learned patterns for self-training
+"""
+
+from sqlalchemy import Column, Integer, String, Text, ForeignKey, DateTime, Boolean, Numeric, JSON, Index
+from sqlalchemy.orm import relationship
+from datetime import datetime
+from ...shared.config.database import Base
+
+
+class AIConversation(Base):
+    """Stores AI assistant conversation history"""
+    __tablename__ = 'ai_conversations'
+    
+    id = Column(Integer, primary_key=True, index=True, autoincrement=True)
+    user_id = Column(Integer, ForeignKey('users.id'), nullable=False, index=True)
+    session_id = Column(String(100), nullable=True, index=True)  # For grouping related conversations
+    user_query = Column(Text, nullable=False)
+    ai_response = Column(Text, nullable=False)
+    intent = Column(String(100), nullable=True, index=True)
+    context_used = Column(JSON, nullable=True)  # Store context data used
+    user_role = Column(String(50), nullable=True, index=True)
+    response_time_ms = Column(Integer, nullable=True)  # Response time in milliseconds
+    is_helpful = Column(Boolean, nullable=True)  # User feedback on helpfulness
+    created_at = Column(DateTime, default=datetime.utcnow, nullable=False, index=True)
+    
+    # Relationships
+    user = relationship('User', foreign_keys=[user_id])
+    feedbacks = relationship('AIConversationFeedback', back_populates='conversation', cascade='all, delete-orphan')
+    learned_patterns = relationship('AILearnedPattern', back_populates='source_conversation')
+    
+    __table_args__ = (
+        Index('idx_ai_conv_user_date', 'user_id', 'created_at'),
+        Index('idx_ai_conv_intent', 'intent'),
+        Index('idx_ai_conv_session', 'session_id'),
+    )
+
+
+class AIConversationFeedback(Base):
+    """User feedback on AI responses for learning"""
+    __tablename__ = 'ai_conversation_feedbacks'
+    
+    id = Column(Integer, primary_key=True, index=True, autoincrement=True)
+    conversation_id = Column(Integer, ForeignKey('ai_conversations.id'), nullable=False, index=True)
+    user_id = Column(Integer, ForeignKey('users.id'), nullable=False)
+    rating = Column(Integer, nullable=True)  # 1-5 rating
+    is_helpful = Column(Boolean, nullable=True)
+    is_correct = Column(Boolean, nullable=True)
+    feedback_text = Column(Text, nullable=True)  # User's text feedback
+    correction = Column(Text, nullable=True)  # If user provides corrected answer
+    created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
+    
+    # Relationships
+    conversation = relationship('AIConversation', back_populates='feedbacks')
+    user = relationship('User', foreign_keys=[user_id])
+
+
+class AILearnedPattern(Base):
+    """Learned patterns from conversations for pattern matching"""
+    __tablename__ = 'ai_learned_patterns'
+    
+    id = Column(Integer, primary_key=True, index=True, autoincrement=True)
+    pattern_keywords = Column(Text, nullable=False)  # Keywords extracted from query
+    query_pattern = Column(Text, nullable=False)  # Pattern template
+    intent = Column(String(100), nullable=False, index=True)
+    response_template = Column(Text, nullable=True)  # Response template
+    context_keys = Column(JSON, nullable=True)  # Which context keys to use
+    confidence_score = Column(Numeric(5, 2), nullable=False, default=0.0)  # Confidence 0-100
+    usage_count = Column(Integer, nullable=False, default=0)  # How many times used
+    success_count = Column(Integer, nullable=False, default=0)  # How many successful matches
+    source_conversation_id = Column(Integer, ForeignKey('ai_conversations.id'), nullable=True)
+    user_role = Column(String(50), nullable=True, index=True)  # Role-specific patterns
+    is_active = Column(Boolean, nullable=False, default=True)
+    created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
+    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow, nullable=False)
+    last_used_at = Column(DateTime, nullable=True)
+    
+    # Relationships
+    source_conversation = relationship('AIConversation', back_populates='learned_patterns')
+    
+    __table_args__ = (
+        Index('idx_ai_pattern_intent_role', 'intent', 'user_role'),
+        Index('idx_ai_pattern_active', 'is_active', 'confidence_score'),
+    )
+
+
+class AIKnowledgeEntry(Base):
+    """Dynamic knowledge base entries learned from interactions"""
+    __tablename__ = 'ai_knowledge_entries'
+    
+    id = Column(Integer, primary_key=True, index=True, autoincrement=True)
+    topic = Column(String(200), nullable=False, index=True)
+    question = Column(Text, nullable=False)  # Common question format
+    answer = Column(Text, nullable=False)  # Best answer
+    keywords = Column(JSON, nullable=True)  # Keywords for matching
+    related_intent = Column(String(100), nullable=True, index=True)
+    source = Column(String(100), nullable=True)  # 'user_feedback', 'admin_added', 'learned'
+    confidence = Column(Numeric(5, 2), nullable=False, default=50.0)  # 0-100
+    usage_count = Column(Integer, nullable=False, default=0)
+    success_count = Column(Integer, nullable=False, default=0)
+    user_role = Column(String(50), nullable=True, index=True)  # Role-specific knowledge
+    is_verified = Column(Boolean, nullable=False, default=False)  # Verified by admin
+    created_by_user_id = Column(Integer, ForeignKey('users.id'), nullable=True)
+    created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
+    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow, nullable=False)
+    last_used_at = Column(DateTime, nullable=True)
+    
+    # Relationships
+    created_by = relationship('User', foreign_keys=[created_by_user_id])
+    
+    __table_args__ = (
+        Index('idx_ai_knowledge_topic_role', 'topic', 'user_role'),
+        Index('idx_ai_knowledge_active', 'is_verified', 'confidence'),
+    )
+
+
+class AITrainingMetrics(Base):
+    """Metrics for tracking AI training and improvement"""
+    __tablename__ = 'ai_training_metrics'
+    
+    id = Column(Integer, primary_key=True, index=True, autoincrement=True)
+    metric_date = Column(DateTime, nullable=False, index=True)  # Date of metrics
+    total_conversations = Column(Integer, nullable=False, default=0)
+    total_patterns_learned = Column(Integer, nullable=False, default=0)
+    total_knowledge_entries = Column(Integer, nullable=False, default=0)
+    average_response_time_ms = Column(Integer, nullable=True)
+    average_rating = Column(Numeric(3, 2), nullable=True)  # Average user rating
+    helpful_rate = Column(Numeric(5, 2), nullable=True)  # Percentage of helpful responses
+    correct_rate = Column(Numeric(5, 2), nullable=True)  # Percentage of correct responses
+    pattern_match_success_rate = Column(Numeric(5, 2), nullable=True)
+    knowledge_usage_rate = Column(Numeric(5, 2), nullable=True)
+    created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
+    
+    __table_args__ = (
+        Index('idx_ai_metrics_date', 'metric_date'),
+    )
+

Backend/src/ai/models/chat.py

@@ -2,7 +2,7 @@ from sqlalchemy import Column, Integer, String, Text, ForeignKey, DateTime, Enum
 from sqlalchemy.orm import relationship
 from datetime import datetime
 import enum
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class ChatStatus(str, enum.Enum):
     pending = 'pending'

Backend/src/ai/routes/ai_assistant_routes.py

@@ -0,0 +1,295 @@
+"""
+AI Assistant API Routes
+"""
+
+from fastapi import APIRouter, Depends, HTTPException, status
+from sqlalchemy.orm import Session
+from typing import Optional
+from pydantic import BaseModel
+
+from ...shared.config.database import get_db
+from ...security.middleware.auth import get_current_user
+from ...auth.models.user import User
+from ...auth.models.role import Role
+from ..services.ai_chat_service import AIChatService
+from ..services.ai_assistant_service import AIAssistantService
+from ..services.ai_learning_service import AILearningService
+from ..services.ai_training_scheduler import get_training_scheduler
+from ...shared.config.logging_config import get_logger
+
+logger = get_logger(__name__)
+
+router = APIRouter(prefix="/ai-assistant", tags=["AI Assistant"])
+
+
+class ChatMessageRequest(BaseModel):
+    message: str
+    context: Optional[dict] = None
+
+
+class ChatMessageResponse(BaseModel):
+    response: str
+    intent: str
+    data_used: dict
+    timestamp: str
+
+
+@router.post("/chat")
+async def chat_with_ai(
+    request: ChatMessageRequest,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """
+    Chat with AI assistant
+    Accessible to all authenticated users (admin, staff, accountant, customer)
+    Responses are filtered based on user role
+    """
+    try:
+        # Load user role
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role:
+            raise HTTPException(
+                status_code=status.HTTP_403_FORBIDDEN,
+                detail="User role not found"
+            )
+        
+        # Initialize AI chat service with current user for role-based responses
+        ai_service = AIChatService(db, current_user)
+        
+        # Generate response with role awareness
+        result = ai_service.generate_response(
+            user_query=request.message,
+            context=request.context
+        )
+        
+        return {
+            "status": "success",
+            "data": {
+                "response": result["response"],
+                "intent": result.get("intent", "unknown"),
+                "data_used": result.get("data_used", {}),
+                "timestamp": result.get("timestamp", ""),
+                "user_role": user_role.name
+            }
+        }
+    
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error in AI chat: {str(e)}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail=f"Error processing AI request: {str(e)}"
+        )
+
+
+@router.get("/status")
+async def get_ai_status(
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """
+    Get comprehensive system status for AI assistant
+    Status is filtered based on user role
+    """
+    try:
+        # Load user role
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role:
+            raise HTTPException(
+                status_code=status.HTTP_403_FORBIDDEN,
+                detail="User role not found"
+            )
+        
+        # Initialize AI assistant with current user for role-based context
+        ai_assistant = AIAssistantService(db, current_user)
+        context = ai_assistant.generate_context_for_ai()
+        
+        return {
+            "status": "success",
+            "data": context
+        }
+    
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting AI status: {str(e)}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail=str(e)
+        )
+
+
+@router.get("/rooms/occupied")
+async def get_occupied_rooms(
+    room_number: Optional[str] = None,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """Get list of occupied rooms - Admin and Staff only"""
+    try:
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role or user_role.name not in ['staff', 'admin']:
+            raise HTTPException(status_code=403, detail="Only staff and admin can access this information")
+        
+        ai_assistant = AIAssistantService(db, current_user)
+        rooms = ai_assistant.search_occupied_rooms(room_number)
+        
+        return {"status": "success", "data": {"rooms": rooms}}
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting occupied rooms: {str(e)}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.get("/rooms/problems")
+async def get_room_problems(
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """Get rooms with problems - Admin and Staff only"""
+    try:
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role or user_role.name not in ['staff', 'admin']:
+            raise HTTPException(status_code=403, detail="Only staff and admin can access this information")
+        
+        ai_assistant = AIAssistantService(db, current_user)
+        problems = ai_assistant.get_room_problems()
+        
+        return {"status": "success", "data": {"problems": problems}}
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting room problems: {str(e)}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.get("/chats/unanswered")
+async def get_unanswered_chats(
+    hours: int = 24,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """Get unanswered chat messages - Admin and Staff only"""
+    try:
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role or user_role.name not in ['staff', 'admin']:
+            raise HTTPException(status_code=403, detail="Only staff and admin can access this information")
+        
+        ai_assistant = AIAssistantService(db, current_user)
+        chats = ai_assistant.get_unanswered_chats(hours)
+        
+        return {"status": "success", "data": {"chats": chats}}
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting unanswered chats: {str(e)}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/training/trigger")
+async def trigger_manual_training(
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """Manually trigger AI training - Admin only"""
+    try:
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role or user_role.name != 'admin':
+            raise HTTPException(status_code=403, detail="Only admin can trigger manual training")
+        
+        learning_service = AILearningService(db)
+        result = learning_service.auto_train_from_all_conversations()
+        
+        return {
+            "status": "success",
+            "message": "Training completed",
+            "data": result
+        }
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error triggering training: {str(e)}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/training/analyze")
+async def trigger_manual_analysis(
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """Manually trigger AI analysis and improvement - Admin only"""
+    try:
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role or user_role.name != 'admin':
+            raise HTTPException(status_code=403, detail="Only admin can trigger manual analysis")
+        
+        learning_service = AILearningService(db)
+        result = learning_service.auto_analyze_and_improve()
+        
+        return {
+            "status": "success",
+            "message": "Analysis completed",
+            "data": result
+        }
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error triggering analysis: {str(e)}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.get("/training/status")
+async def get_training_status(
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db)
+):
+    """Get AI training status and metrics - Admin only"""
+    try:
+        user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        if not user_role or user_role.name != 'admin':
+            raise HTTPException(status_code=403, detail="Only admin can view training status")
+        
+        from ..models.ai_conversation import AIConversation, AILearnedPattern, AIKnowledgeEntry, AITrainingMetrics
+        from sqlalchemy import func
+        from datetime import datetime, timedelta
+        
+        # Get statistics
+        total_conversations = db.query(AIConversation).count()
+        total_patterns = db.query(AILearnedPattern).filter(AILearnedPattern.is_active == True).count()
+        total_knowledge = db.query(AIKnowledgeEntry).count()
+        
+        # Get recent metrics
+        recent_metrics = db.query(AITrainingMetrics).order_by(
+            AITrainingMetrics.metric_date.desc()
+        ).limit(1).first()
+        
+        # Get scheduler status
+        scheduler = get_training_scheduler()
+        
+        return {
+            "status": "success",
+            "data": {
+                "scheduler_running": scheduler.running,
+                "last_training": scheduler.last_training_time.isoformat() if scheduler.last_training_time else None,
+                "last_analysis": scheduler.last_analysis_time.isoformat() if scheduler.last_analysis_time else None,
+                "statistics": {
+                    "total_conversations": total_conversations,
+                    "total_patterns": total_patterns,
+                    "total_knowledge_entries": total_knowledge,
+                },
+                "recent_metrics": {
+                    "average_rating": float(recent_metrics.average_rating) if recent_metrics and recent_metrics.average_rating else None,
+                    "helpful_rate": float(recent_metrics.helpful_rate) if recent_metrics and recent_metrics.helpful_rate else None,
+                    "average_response_time_ms": recent_metrics.average_response_time_ms if recent_metrics else None,
+                } if recent_metrics else None
+            }
+        }
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting training status: {str(e)}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+

Backend/src/ai/services/ai_assistant_service.py

@@ -0,0 +1,434 @@
+"""
+Enterprise AI Assistant Service
+Monitors rooms, bookings, invoices, payments, and chat messages
+Provides intelligent responses to queries about hotel operations
+"""
+
+from typing import Dict, List, Optional, Any
+from datetime import datetime, timedelta
+from sqlalchemy.orm import Session, joinedload
+from sqlalchemy import and_, or_, func
+import json
+import logging
+
+from ...rooms.models.room import Room, RoomStatus
+from ...bookings.models.booking import Booking, BookingStatus
+from ...payments.models.invoice import Invoice
+from ...payments.models.payment import Payment, PaymentStatus
+from ..models.chat import Chat, ChatMessage, ChatStatus
+from ...auth.models.user import User
+from ...shared.config.logging_config import get_logger
+from .ai_knowledge_base import AIKnowledgeBase
+from .ai_role_access_service import AIRoleAccessService
+
+logger = get_logger(__name__)
+
+
+class AIAssistantService:
+    """Enterprise AI Assistant for Hotel Management"""
+    
+    def __init__(self, db: Session, current_user: Optional[User] = None):
+        self.db = db
+        self.current_user = current_user
+        self.role_access_service = AIRoleAccessService(db, current_user) if current_user else None
+    
+    def get_room_status_summary(self) -> Dict[str, Any]:
+        """Get comprehensive room status summary"""
+        try:
+            total_rooms = self.db.query(Room).count()
+            available_rooms = self.db.query(Room).filter(Room.status == RoomStatus.available).count()
+            occupied_rooms = self.db.query(Room).filter(Room.status == RoomStatus.occupied).count()
+            maintenance_rooms = self.db.query(Room).filter(Room.status == RoomStatus.maintenance).count()
+            cleaning_rooms = self.db.query(Room).filter(Room.status == RoomStatus.cleaning).count()
+            
+            # Get rooms with bookings today
+            today = datetime.utcnow().date()
+            rooms_with_bookings = self.db.query(Booking).filter(
+                and_(
+                    Booking.status != BookingStatus.cancelled,
+                    Booking.check_in_date <= today,
+                    Booking.check_out_date > today
+                )
+            ).count()
+            
+            return {
+                "total_rooms": total_rooms,
+                "available": available_rooms,
+                "occupied": occupied_rooms,
+                "maintenance": maintenance_rooms,
+                "cleaning": cleaning_rooms,
+                "rooms_with_active_bookings": rooms_with_bookings,
+                "occupancy_rate": round((occupied_rooms / total_rooms * 100) if total_rooms > 0 else 0, 2)
+            }
+        except Exception as e:
+            logger.error(f"Error getting room status: {str(e)}", exc_info=True)
+            return {}
+    
+    def get_booking_summary(self, days: int = 7) -> Dict[str, Any]:
+        """Get booking summary for specified days"""
+        try:
+            today = datetime.utcnow().date()
+            end_date = today + timedelta(days=days)
+            
+            # Upcoming check-ins
+            upcoming_checkins = self.db.query(Booking).filter(
+                and_(
+                    Booking.status == BookingStatus.confirmed,
+                    Booking.check_in_date >= today,
+                    Booking.check_in_date <= end_date
+                )
+            ).count()
+            
+            # Upcoming check-outs
+            upcoming_checkouts = self.db.query(Booking).filter(
+                and_(
+                    Booking.status == BookingStatus.confirmed,
+                    Booking.check_out_date >= today,
+                    Booking.check_out_date <= end_date
+                )
+            ).count()
+            
+            # Active bookings
+            active_bookings = self.db.query(Booking).filter(
+                and_(
+                    Booking.status == BookingStatus.confirmed,
+                    Booking.check_in_date <= today,
+                    Booking.check_out_date > today
+                )
+            ).count()
+            
+            # Pending bookings
+            pending_bookings = self.db.query(Booking).filter(
+                Booking.status == BookingStatus.pending
+            ).count()
+            
+            return {
+                "upcoming_checkins": upcoming_checkins,
+                "upcoming_checkouts": upcoming_checkouts,
+                "active_bookings": active_bookings,
+                "pending_bookings": pending_bookings,
+                "period_days": days
+            }
+        except Exception as e:
+            logger.error(f"Error getting booking summary: {str(e)}", exc_info=True)
+            return {}
+    
+    def get_payment_summary(self, days: int = 30) -> Dict[str, Any]:
+        """Get payment summary"""
+        try:
+            today = datetime.utcnow().date()
+            start_date = today - timedelta(days=days)
+            
+            # Total payments in period
+            total_payments = self.db.query(func.sum(Payment.amount)).filter(
+                and_(
+                    Payment.payment_status == PaymentStatus.completed,
+                    func.date(Payment.payment_date) >= start_date,
+                    func.date(Payment.payment_date) <= today
+                )
+            ).scalar() or 0
+            
+            # Pending payments
+            pending_payments = self.db.query(func.sum(Payment.amount)).filter(
+                Payment.payment_status == PaymentStatus.pending
+            ).scalar() or 0
+            
+            # Payment count
+            completed_count = self.db.query(Payment).filter(
+                and_(
+                    Payment.payment_status == PaymentStatus.completed,
+                    func.date(Payment.payment_date) >= start_date
+                )
+            ).count()
+            
+            return {
+                "total_revenue": float(total_payments),
+                "pending_amount": float(pending_payments),
+                "completed_payments": completed_count,
+                "period_days": days
+            }
+        except Exception as e:
+            logger.error(f"Error getting payment summary: {str(e)}", exc_info=True)
+            return {}
+    
+    def get_invoice_summary(self) -> Dict[str, Any]:
+        """Get invoice summary"""
+        try:
+            total_invoices = self.db.query(Invoice).count()
+            
+            # Group by status
+            status_counts = {}
+            invoices = self.db.query(Invoice).all()
+            for invoice in invoices:
+                status = invoice.status if hasattr(invoice, 'status') else 'unknown'
+                status_counts[status] = status_counts.get(status, 0) + 1
+            
+            # Overdue invoices
+            today = datetime.utcnow().date()
+            overdue_count = self.db.query(Invoice).filter(
+                and_(
+                    Invoice.due_date < today,
+                    Invoice.status != 'paid'
+                )
+            ).count() if hasattr(Invoice, 'due_date') else 0
+            
+            return {
+                "total_invoices": total_invoices,
+                "status_breakdown": status_counts,
+                "overdue_invoices": overdue_count
+            }
+        except Exception as e:
+            logger.error(f"Error getting invoice summary: {str(e)}", exc_info=True)
+            return {}
+    
+    def get_unanswered_chats(self, hours: int = 24) -> List[Dict[str, Any]]:
+        """Get unanswered chat messages from after working hours"""
+        try:
+            cutoff_time = datetime.utcnow() - timedelta(hours=hours)
+            
+            # Get open chats with unread messages
+            chats = self.db.query(Chat).filter(
+                and_(
+                    Chat.status == ChatStatus.open,
+                    Chat.updated_at >= cutoff_time
+                )
+            ).all()
+            
+            unanswered = []
+            for chat in chats:
+                # Get last message
+                last_message = self.db.query(ChatMessage).filter(
+                    ChatMessage.chat_id == chat.id
+                ).order_by(ChatMessage.created_at.desc()).first()
+                
+                if last_message and last_message.sender_type == 'visitor' and not last_message.is_read:
+                    unanswered.append({
+                        "chat_id": chat.id,
+                        "visitor_name": chat.visitor_name,
+                        "visitor_email": chat.visitor_email,
+                        "last_message": last_message.message[:100],
+                        "last_message_time": last_message.created_at.isoformat(),
+                        "waiting_hours": (datetime.utcnow() - last_message.created_at).total_seconds() / 3600
+                    })
+            
+            return unanswered
+        except Exception as e:
+            logger.error(f"Error getting unanswered chats: {str(e)}", exc_info=True)
+            return []
+    
+    def search_occupied_rooms(self, room_number: Optional[str] = None) -> List[Dict[str, Any]]:
+        """Search for occupied rooms"""
+        try:
+            today = datetime.utcnow().date()
+            
+            # Get rooms with active bookings
+            query = self.db.query(Room).options(
+                joinedload(Room.room_type)
+            ).join(Booking).filter(
+                and_(
+                    Room.status == RoomStatus.occupied,
+                    Booking.status == BookingStatus.confirmed,
+                    Booking.check_in_date <= today,
+                    Booking.check_out_date > today
+                )
+            )
+            
+            if room_number:
+                query = query.filter(Room.room_number.ilike(f"%{room_number}%"))
+            
+            rooms = query.all()
+            
+            result = []
+            for room in rooms:
+                # Get the active booking for this room
+                booking = self.db.query(Booking).options(
+                    joinedload(Booking.user)
+                ).filter(
+                    and_(
+                        Booking.room_id == room.id,
+                        Booking.status == BookingStatus.confirmed,
+                        Booking.check_in_date <= today,
+                        Booking.check_out_date > today
+                    )
+                ).first()
+                
+                result.append({
+                    "room_number": room.room_number,
+                    "room_type": room.room_type.name if room.room_type else "Unknown",
+                    "floor": room.floor,
+                    "booking_id": booking.id if booking else None,
+                    "guest_name": booking.user.full_name if booking and booking.user else "Unknown",
+                    "check_in": booking.check_in_date.isoformat() if booking else None,
+                    "check_out": booking.check_out_date.isoformat() if booking else None
+                })
+            
+            return result
+        except Exception as e:
+            logger.error(f"Error searching occupied rooms: {str(e)}", exc_info=True)
+            return []
+    
+    def get_room_problems(self) -> List[Dict[str, Any]]:
+        """Get rooms with problems (maintenance, issues)"""
+        try:
+            # Rooms in maintenance
+            maintenance_rooms = self.db.query(Room).filter(
+                Room.status == RoomStatus.maintenance
+            ).all()
+            
+            problems = []
+            for room in maintenance_rooms:
+                problems.append({
+                    "room_number": room.room_number,
+                    "issue_type": "maintenance",
+                    "status": room.status.value,
+                    "description": f"Room {room.room_number} is under maintenance"
+                })
+            
+            # Check for maintenance records
+            try:
+                from ...rooms.models.room_maintenance import RoomMaintenance, MaintenanceStatus
+                active_maintenance = self.db.query(RoomMaintenance).filter(
+                    MaintenanceStatus.in_progress == MaintenanceStatus.in_progress
+                ).all()
+                
+                for maint in active_maintenance:
+                    room = self.db.query(Room).filter(Room.id == maint.room_id).first()
+                    if room:
+                        problems.append({
+                            "room_number": room.room_number,
+                            "issue_type": "maintenance",
+                            "status": maint.status.value if hasattr(maint.status, 'value') else str(maint.status),
+                            "description": maint.description or f"Maintenance issue in room {room.room_number}",
+                            "scheduled_start": maint.scheduled_start.isoformat() if maint.scheduled_start else None
+                        })
+            except ImportError:
+                pass  # Maintenance model might not exist
+            
+            return problems
+        except Exception as e:
+            logger.error(f"Error getting room problems: {str(e)}", exc_info=True)
+            return []
+    
+    def get_booking_by_number(self, booking_number: str) -> Optional[Dict[str, Any]]:
+        """Get booking details by booking number"""
+        try:
+            booking = self.db.query(Booking).filter(
+                Booking.booking_number == booking_number
+            ).first()
+            
+            if not booking:
+                return None
+            
+            return {
+                "booking_number": booking.booking_number,
+                "status": booking.status.value if hasattr(booking.status, 'value') else str(booking.status),
+                "guest_name": booking.user.full_name if booking.user else "Unknown",
+                "room_number": booking.room.room_number if booking.room else "Unknown",
+                "check_in": booking.check_in_date.isoformat(),
+                "check_out": booking.check_out_date.isoformat(),
+                "total_price": float(booking.total_price) if booking.total_price else 0,
+                "payment_status": self._get_booking_payment_status(booking.id)
+            }
+        except Exception as e:
+            logger.error(f"Error getting booking: {str(e)}", exc_info=True)
+            return None
+    
+    def get_invoice_by_number(self, invoice_number: str) -> Optional[Dict[str, Any]]:
+        """Get invoice details by invoice number"""
+        try:
+            invoice = self.db.query(Invoice).filter(
+                Invoice.invoice_number == invoice_number
+            ).first()
+            
+            if not invoice:
+                return None
+            
+            return {
+                "invoice_number": invoice.invoice_number,
+                "status": invoice.status if hasattr(invoice, 'status') else "unknown",
+                "amount": float(invoice.total_amount) if hasattr(invoice, 'total_amount') else 0,
+                "due_date": invoice.due_date.isoformat() if hasattr(invoice, 'due_date') and invoice.due_date else None,
+                "booking_number": invoice.booking.booking_number if invoice.booking else None,
+                "created_at": invoice.created_at.isoformat() if hasattr(invoice, 'created_at') else None
+            }
+        except Exception as e:
+            logger.error(f"Error getting invoice: {str(e)}", exc_info=True)
+            return None
+    
+    def _get_booking_payment_status(self, booking_id: int) -> str:
+        """Get payment status for a booking"""
+        try:
+            payments = self.db.query(Payment).filter(
+                Payment.booking_id == booking_id
+            ).all()
+            
+            if not payments:
+                return "unpaid"
+            
+            completed = [p for p in payments if p.payment_status == PaymentStatus.completed]
+            if completed:
+                total_paid = sum(float(p.amount) for p in completed)
+                booking = self.db.query(Booking).filter(Booking.id == booking_id).first()
+                if booking and booking.total_price:
+                    if total_paid >= float(booking.total_price):
+                        return "paid"
+                    else:
+                        return "partially_paid"
+            
+            return "pending"
+        except Exception as e:
+            logger.error(f"Error getting payment status: {str(e)}", exc_info=True)
+            return "unknown"
+    
+    def generate_context_for_ai(self) -> Dict[str, Any]:
+        """Generate comprehensive context for AI assistant with role-based filtering"""
+        context = {
+            "timestamp": datetime.utcnow().isoformat(),
+        }
+        
+        # Use role-based access service if user is provided
+        if self.role_access_service:
+            role_name = self.role_access_service.role_name
+            context["user_role"] = role_name
+            context["role_capabilities"] = AIKnowledgeBase.get_role_info(role_name)
+            
+            # Get role-appropriate data
+            context["room_status"] = self.role_access_service.get_room_status_summary()
+            
+            # Get user-specific bookings
+            context["user_bookings"] = self.role_access_service.get_user_bookings(limit=5)
+            
+            # Financial data only for authorized roles
+            if self.role_access_service.can_access_feature("payment_summary"):
+                payment_summary = self.role_access_service.get_payment_summary()
+                if payment_summary:
+                    context["payment_summary"] = payment_summary
+                
+                invoice_summary = self.role_access_service.get_invoice_summary()
+                if invoice_summary:
+                    context["invoice_summary"] = invoice_summary
+            
+            # Operational data for staff and admin
+            if role_name in ["admin", "staff"]:
+                context["booking_summary"] = self.get_booking_summary()
+                context["unanswered_chats"] = self.get_unanswered_chats()
+                context["room_problems"] = self.get_room_problems()
+            
+            # Add knowledge base information
+            context["application_knowledge"] = {
+                "features": list(AIKnowledgeBase.FEATURES.keys()),
+                "role_info": AIKnowledgeBase.get_role_info(role_name)
+            }
+        else:
+            # Default context without user (shouldn't happen in production)
+            context.update({
+                "room_status": self.get_room_status_summary(),
+                "booking_summary": self.get_booking_summary(),
+                "payment_summary": self.get_payment_summary(),
+                "invoice_summary": self.get_invoice_summary(),
+                "unanswered_chats": self.get_unanswered_chats(),
+                "room_problems": self.get_room_problems(),
+            })
+        
+        return context
+

Backend/src/ai/services/ai_chat_service.py

@@ -0,0 +1,975 @@
+"""
+AI Chat Service - Handles AI-powered chat responses
+Integrates with OpenAI, Anthropic, or other LLM providers
+"""
+
+from typing import Dict, List, Optional, Any
+from datetime import datetime
+import json
+import logging
+import os
+
+from ..services.ai_assistant_service import AIAssistantService
+from ..services.ai_knowledge_base import AIKnowledgeBase
+from ..services.ai_role_access_service import AIRoleAccessService
+from ..services.ai_learning_service import AILearningService
+from ...auth.models.user import User
+from ..models.ai_conversation import AILearnedPattern
+from ...shared.config.logging_config import get_logger
+
+logger = get_logger(__name__)
+
+
+class AIChatService:
+    """AI Chat Service for generating intelligent responses"""
+    
+    def __init__(self, db_session, current_user: Optional[User] = None):
+        self.db = db_session
+        self.current_user = current_user
+        self.ai_assistant = AIAssistantService(db_session, current_user)
+        self.knowledge_base = AIKnowledgeBase()
+        self.role_access_service = AIRoleAccessService(db_session, current_user) if current_user else None
+        self.learning_service = AILearningService(db_session)
+        # Configure AI provider (OpenAI, Anthropic, etc.)
+        self.provider = os.getenv("AI_PROVIDER", "openai")
+        self.api_key = os.getenv("AI_API_KEY", "")
+        self.model = os.getenv("AI_MODEL", "gpt-4")
+    
+    def generate_response(self, user_query: str, context: Optional[Dict] = None, session_id: Optional[str] = None) -> Dict[str, Any]:
+        """
+        Generate AI response based on user query with self-learning
+        """
+        start_time = datetime.utcnow()
+        
+        try:
+            # Check learned patterns first
+            role_name = self.role_access_service.role_name if self.role_access_service else None
+            learned_pattern = self.learning_service.get_learned_pattern(user_query, role_name)
+            knowledge_entry = self.learning_service.get_knowledge_entry(user_query, role_name)
+            
+            # Check for similar past queries
+            similar_queries = self.learning_service.find_similar_queries(user_query, limit=3)
+            
+            # Get current system context
+            system_context = self.ai_assistant.generate_context_for_ai()
+            
+            # Merge with provided context
+            if context:
+                system_context.update(context)
+            
+            # Add learned knowledge to context
+            if learned_pattern:
+                system_context["learned_pattern"] = {
+                    "pattern": learned_pattern.query_pattern,
+                    "intent": learned_pattern.intent,
+                    "confidence": float(learned_pattern.confidence_score)
+                }
+            
+            if knowledge_entry:
+                system_context["knowledge_entry"] = knowledge_entry
+            
+            if similar_queries:
+                system_context["similar_past_queries"] = similar_queries
+            
+            # Analyze query intent (or use learned intent)
+            intent = learned_pattern.intent if learned_pattern else self._analyze_intent(user_query)
+            
+            # Get relevant data based on intent
+            relevant_data = self._get_relevant_data(intent, user_query)
+            
+            # Status-related intents should always use rule-based formatted responses
+            # These provide consistent, well-formatted output with emojis and structure
+            status_intents = [
+                "general_status", "room_status", "room_occupied", "room_available", 
+                "room_problems", "booking_status", "payment_status", "invoice_status",
+                "chat_status", "app_info"
+            ]
+            
+            response = None
+            
+            # For status queries, prioritize rule-based formatted responses
+            if intent in status_intents:
+                # Always use rule-based response for status queries to ensure proper formatting
+                if self.api_key and self.provider == "openai":
+                    # Even with LLM, prefer rule-based for status to maintain format consistency
+                    response = self._generate_rule_based_response(intent, user_query, relevant_data)
+                else:
+                    response = self._generate_rule_based_response(intent, user_query, relevant_data)
+                logger.info(f"Using rule-based formatted response for status intent: {intent}")
+            else:
+                # For non-status queries, use learned patterns/knowledge if available
+                if learned_pattern and learned_pattern.confidence_score >= 70.0 and learned_pattern.response_template:
+                    # Try to use learned pattern response
+                    try:
+                        response = self._apply_learned_pattern(learned_pattern, relevant_data, user_query)
+                        if response:
+                            logger.info(f"Using learned pattern {learned_pattern.id} for query")
+                    except Exception as e:
+                        logger.warning(f"Failed to apply learned pattern: {str(e)}")
+                
+                # Use knowledge entry if available
+                if not response and knowledge_entry and knowledge_entry.get("confidence", 0) >= 70.0:
+                    response = knowledge_entry.get("answer")
+                    logger.info(f"Using knowledge entry for query")
+                
+                # Generate response using LLM or rule-based system if no learned response
+                if not response:
+                    if self.api_key and self.provider == "openai":
+                        response = self._generate_llm_response(user_query, system_context, relevant_data)
+                    else:
+                        # Fallback to rule-based responses
+                        response = self._generate_rule_based_response(intent, user_query, relevant_data)
+            
+            # Calculate response time
+            response_time = int((datetime.utcnow() - start_time).total_seconds() * 1000)
+            
+            # Save conversation for learning (async, don't block response)
+            if self.current_user:
+                try:
+                    self.learning_service.save_conversation(
+                        user_id=self.current_user.id,
+                        user_query=user_query,
+                        ai_response=response,
+                        intent=intent,
+                        context_used=relevant_data,
+                        user_role=role_name,
+                        session_id=session_id,
+                        response_time_ms=response_time
+                    )
+                except Exception as e:
+                    logger.warning(f"Failed to save conversation for learning: {str(e)}")
+            
+            return {
+                "response": response,
+                "intent": intent,
+                "data_used": relevant_data,
+                "timestamp": datetime.utcnow().isoformat(),
+                "used_learned_pattern": learned_pattern.id if learned_pattern else None,
+                "used_knowledge_entry": knowledge_entry.get("topic") if knowledge_entry else None
+            }
+        except Exception as e:
+            logger.error(f"Error generating AI response: {str(e)}", exc_info=True)
+            return {
+                "response": "I apologize, but I'm having trouble processing your request right now. Please try again later.",
+                "error": str(e)
+            }
+    
+    def _analyze_intent(self, query: str) -> str:
+        """Analyze user query intent with comprehensive pattern matching"""
+        query_lower = query.lower()
+        
+        # Room-related queries - expanded patterns
+        room_keywords = ['room', 'rooms', 'occupied', 'available', 'free', 'vacant', 'vacancy', 
+                        'occupancy', 'suite', 'suites', 'accommodation']
+        if any(word in query_lower for word in room_keywords):
+            if any(word in query_lower for word in ['occupied', 'booked', 'taken', 'in use', 'guest']):
+                return "room_occupied"
+            elif any(word in query_lower for word in ['available', 'free', 'vacant', 'empty', 'ready']):
+                return "room_available"
+            elif any(word in query_lower for word in ['problem', 'issue', 'maintenance', 'broken', 'repair', 'fix']):
+                return "room_problems"
+            elif any(word in query_lower for word in ['how many', 'total', 'count', 'number of', 'how much', 'quantity']):
+                return "room_status"
+            elif any(word in query_lower for word in ['status', 'state', 'condition', 'overview']):
+                return "room_status"
+            return "room_status"
+        
+        # Booking-related queries - expanded patterns
+        booking_keywords = ['booking', 'bookings', 'reservation', 'reservations', 'check-in', 'check-out', 
+                           'checkin', 'checkout', 'arrival', 'departure', 'guest', 'guests']
+        if any(word in query_lower for word in booking_keywords):
+            if any(word in query_lower for word in ['number', 'id', 'code', 'reference']):
+                return "booking_by_number"
+            elif any(word in query_lower for word in ['upcoming', 'coming', 'next', 'future', 'scheduled']):
+                return "booking_status"
+            elif any(word in query_lower for word in ['active', 'current', 'today', 'now']):
+                return "booking_status"
+            return "booking_status"
+        
+        # Invoice-related queries - expanded patterns
+        invoice_keywords = ['invoice', 'invoices', 'bill', 'bills', 'receipt', 'receipts', 'statement', 'statements']
+        if any(word in query_lower for word in invoice_keywords):
+            if any(word in query_lower for word in ['number', 'id', 'code', 'reference']):
+                return "invoice_by_number"
+            elif any(word in query_lower for word in ['overdue', 'unpaid', 'pending', 'due']):
+                return "invoice_status"
+            return "invoice_status"
+        
+        # Payment-related queries - expanded patterns
+        payment_keywords = ['payment', 'payments', 'paid', 'unpaid', 'revenue', 'money', 'income', 
+                           'earnings', 'sales', 'financial', 'cash', 'transaction', 'transactions']
+        if any(word in query_lower for word in payment_keywords):
+            if any(word in query_lower for word in ['all', 'list', 'show all', 'every', 'entire']):
+                return "all_payments"
+            return "payment_status"
+        
+        # Chat-related queries - expanded patterns
+        chat_keywords = ['chat', 'chats', 'message', 'messages', 'unanswered', 'customer', 'customers', 
+                        'inquiry', 'inquiries', 'support', 'help', 'contact']
+        if any(word in query_lower for word in chat_keywords):
+            return "chat_status"
+        
+        # App/Platform information queries - for admin only
+        app_keywords = ['app', 'application', 'platform', 'system', 'software', 'what is this', 
+                       'about the app', 'about the platform', 'about the system', 'features',
+                       'capabilities', 'what can', 'how does the app', 'tell me about the app',
+                       'what does this app do', 'app features', 'system features', 'platform features',
+                       'what features', 'list features', 'show features', 'tell me about features',
+                       'what modules', 'what models', 'system overview', 'platform overview']
+        if any(word in query_lower for word in app_keywords):
+            return "app_info"
+        
+        # General status queries - expanded patterns
+        status_keywords = ['status', 'summary', 'overview', 'dashboard', 'report', 'reports', 
+                          'statistics', 'stats', 'info', 'information', 'details', 'what', 'show me', 'tell me']
+        if any(word in query_lower for word in status_keywords):
+            return "general_status"
+        
+        # Questions about "how many", "what", "show", "tell" - default to general status
+        question_words = ['how many', 'how much', 'what', 'show', 'tell', 'give me', 'list', 'display']
+        if any(word in query_lower for word in question_words):
+            return "general_status"
+        
+        return "general_query"
+    
+    def _get_relevant_data(self, intent: str, query: str) -> Dict[str, Any]:
+        """Get relevant data based on intent with role-based filtering"""
+        data = {}
+        role_name = self.role_access_service.role_name if self.role_access_service else "customer"
+        
+        try:
+            if intent == "room_occupied":
+                # Only staff/admin can see occupied room details
+                if role_name in ["admin", "staff"]:
+                    room_number = self._extract_room_number(query)
+                    data["occupied_rooms"] = self.ai_assistant.search_occupied_rooms(room_number)
+                data["room_summary"] = self.ai_assistant.get_room_status_summary()
+            
+            elif intent == "room_available":
+                data["room_summary"] = self.ai_assistant.get_room_status_summary()
+            
+            elif intent == "room_status":
+                data["room_summary"] = self.ai_assistant.get_room_status_summary()
+            
+            elif intent == "room_problems":
+                # Only staff/admin can see room problems
+                if role_name in ["admin", "staff"]:
+                    data["problems"] = self.ai_assistant.get_room_problems()
+            
+            elif intent == "booking_by_number":
+                booking_number = self._extract_booking_number(query)
+                if booking_number:
+                    booking_data = self.ai_assistant.get_booking_by_number(booking_number)
+                    if booking_data:
+                        # Filter based on role
+                        if role_name == "customer":
+                            # Customers can only see their own bookings
+                            user_bookings = self.role_access_service.get_user_bookings(limit=100)
+                            if any(b.get("booking_number") == booking_number for b in user_bookings):
+                                data["booking"] = booking_data
+                        else:
+                            data["booking"] = booking_data
+            
+            elif intent == "booking_status":
+                if role_name in ["admin", "staff"]:
+                    data["booking_summary"] = self.ai_assistant.get_booking_summary()
+                elif role_name == "customer":
+                    # Customers see their own bookings
+                    data["user_bookings"] = self.role_access_service.get_user_bookings(limit=10)
+            
+            elif intent == "invoice_by_number":
+                invoice_number = self._extract_invoice_number(query)
+                if invoice_number:
+                    invoice_data = self.ai_assistant.get_invoice_by_number(invoice_number)
+                    if invoice_data:
+                        # Filter based on role
+                        if role_name == "customer":
+                            user_invoices = self.role_access_service.get_user_invoices(limit=100)
+                            if any(i.get("invoice_number") == invoice_number for i in user_invoices):
+                                data["invoice"] = invoice_data
+                        else:
+                            data["invoice"] = invoice_data
+            
+            elif intent == "invoice_status":
+                if role_name in ["admin", "accountant", "staff"]:
+                    invoice_summary = self.role_access_service.get_invoice_summary()
+                    if invoice_summary:
+                        data["invoice_summary"] = invoice_summary
+                elif role_name == "customer":
+                    # Customers see their own invoices
+                    data["user_invoices"] = self.role_access_service.get_user_invoices(limit=10)
+            
+            elif intent == "all_payments":
+                # Get all payments for admin/accountant
+                if role_name in ["admin", "accountant"]:
+                    data["all_payments"] = self.role_access_service.get_all_payments()
+                elif role_name == "staff":
+                    data["all_payments"] = self.role_access_service.get_user_payments(limit=50)
+                elif role_name == "customer":
+                    data["all_payments"] = self.role_access_service.get_user_payments(limit=None)
+            
+            elif intent == "payment_status":
+                if role_name in ["admin", "accountant", "staff"]:
+                    payment_summary = self.role_access_service.get_payment_summary()
+                    if payment_summary:
+                        data["payment_summary"] = payment_summary
+                elif role_name == "customer":
+                    # Customers see their own payments
+                    data["user_payments"] = self.role_access_service.get_user_payments(limit=10)
+            
+            elif intent == "chat_status":
+                # Only staff/admin can see unanswered chats
+                if role_name in ["admin", "staff"]:
+                    data["unanswered_chats"] = self.ai_assistant.get_unanswered_chats()
+            
+            elif intent == "general_status":
+                data["room_summary"] = self.ai_assistant.get_room_status_summary()
+                
+                if role_name in ["admin", "staff"]:
+                    data["booking_summary"] = self.ai_assistant.get_booking_summary()
+                    data["unanswered_chats"] = self.ai_assistant.get_unanswered_chats()
+                    data["room_problems"] = self.ai_assistant.get_room_problems()
+                elif role_name == "customer":
+                    data["user_bookings"] = self.role_access_service.get_user_bookings(limit=5)
+                    data["user_invoices"] = self.role_access_service.get_user_invoices(limit=5)
+                    data["user_payments"] = self.role_access_service.get_user_payments(limit=5)
+                
+                # Financial summaries only for authorized roles
+                if role_name in ["admin", "accountant", "staff"]:
+                    payment_summary = self.role_access_service.get_payment_summary()
+                    if payment_summary:
+                        data["payment_summary"] = payment_summary
+                    
+                    invoice_summary = self.role_access_service.get_invoice_summary()
+                    if invoice_summary:
+                        data["invoice_summary"] = invoice_summary
+            
+            elif intent == "app_info":
+                # App information - only for admin
+                if role_name == "admin":
+                    # Get comprehensive application knowledge
+                    app_knowledge = self.knowledge_base.get_application_knowledge()
+                    data["app_knowledge"] = app_knowledge
+                else:
+                    # Non-admin users get limited information
+                    data["app_knowledge"] = {
+                        "overview": self.knowledge_base.APPLICATION_OVERVIEW,
+                        "role_info": self.knowledge_base.get_role_info(role_name)
+                    }
+            
+            elif intent == "general_query":
+                # For general queries, get role-appropriate data
+                data["room_summary"] = self.ai_assistant.get_room_status_summary()
+                
+                if role_name in ["admin", "staff"]:
+                    data["booking_summary"] = self.ai_assistant.get_booking_summary()
+                elif role_name == "customer":
+                    data["user_bookings"] = self.role_access_service.get_user_bookings(limit=5)
+                
+                if role_name in ["admin", "accountant"]:
+                    payment_summary = self.role_access_service.get_payment_summary()
+                    if payment_summary:
+                        data["payment_summary"] = payment_summary
+                    
+                    invoice_summary = self.role_access_service.get_invoice_summary()
+                    if invoice_summary:
+                        data["invoice_summary"] = invoice_summary
+        
+        except Exception as e:
+            logger.error(f"Error getting relevant data: {str(e)}", exc_info=True)
+        
+        return data
+    
+    def _extract_room_number(self, query: str) -> Optional[str]:
+        """Extract room number from query"""
+        import re
+        # Look for patterns like "room 101", "room101", "#101"
+        patterns = [
+            r'room\s*#?\s*(\d+)',
+            r'#\s*(\d+)',
+            r'room\s+(\d{3,4})',
+        ]
+        for pattern in patterns:
+            match = re.search(pattern, query, re.IGNORECASE)
+            if match:
+                return match.group(1)
+        return None
+    
+    def _extract_booking_number(self, query: str) -> Optional[str]:
+        """Extract booking number from query"""
+        import re
+        # Look for booking number patterns
+        patterns = [
+            r'booking\s*#?\s*([A-Z0-9-]+)',
+            r'BK[A-Z0-9-]+',
+        ]
+        for pattern in patterns:
+            match = re.search(pattern, query, re.IGNORECASE)
+            if match:
+                return match.group(1) if match.groups() else match.group(0)
+        return None
+    
+    def _extract_invoice_number(self, query: str) -> Optional[str]:
+        """Extract invoice number from query"""
+        import re
+        patterns = [
+            r'invoice\s*#?\s*([A-Z0-9-]+)',
+            r'INV[A-Z0-9-]+',
+        ]
+        for pattern in patterns:
+            match = re.search(pattern, query, re.IGNORECASE)
+            if match:
+                return match.group(1) if match.groups() else match.group(0)
+        return None
+    
+    def _generate_llm_response(self, query: str, context: Dict, data: Dict) -> str:
+        """Generate response using LLM (OpenAI, Anthropic, etc.)"""
+        try:
+            if self.provider == "openai":
+                import openai
+                openai.api_key = self.api_key
+                
+                # Build system prompt
+                system_prompt = self._build_system_prompt(context, data)
+                
+                # Call OpenAI API
+                response = openai.ChatCompletion.create(
+                    model=self.model,
+                    messages=[
+                        {"role": "system", "content": system_prompt},
+                        {"role": "user", "content": query}
+                    ],
+                    temperature=0.7,
+                    max_tokens=500
+                )
+                
+                return response.choices[0].message.content.strip()
+        
+        except ImportError:
+            logger.warning("OpenAI library not installed, falling back to rule-based responses")
+            return self._generate_rule_based_response(self._analyze_intent(query), query, data)
+        except Exception as e:
+            logger.error(f"Error calling LLM: {str(e)}", exc_info=True)
+            return self._generate_rule_based_response(self._analyze_intent(query), query, data)
+    
+    def _build_system_prompt(self, context: Dict, data: Dict) -> str:
+        """Build enterprise-level system prompt for LLM with role awareness"""
+        role_name = context.get("user_role", "customer")
+        role_info = self.knowledge_base.get_role_info(role_name)
+        
+        prompt = f"""You are an enterprise AI assistant for a comprehensive Hotel Booking and Management System (HBMS).
+You provide intelligent, role-aware assistance based on the user's permissions and access level.
+
+USER ROLE: {role_name.upper()}
+ROLE DESCRIPTION: {role_info.get('description', 'Standard user access')}
+
+YOUR CAPABILITIES:
+"""
+        
+        # Add role-specific capabilities
+        can_access = role_info.get("can_access", [])
+        for capability in can_access[:15]:  # Limit to avoid token overflow
+            prompt += f"- {capability}\n"
+        
+        if role_info.get("cannot_access"):
+            prompt += "\nRESTRICTIONS:\n"
+            for restriction in role_info.get("cannot_access", [])[:5]:
+                prompt += f"- Cannot access: {restriction}\n"
+        
+        prompt += """
+\nSYSTEM FEATURES AVAILABLE:
+- Booking Management (create, view, modify, cancel bookings)
+- Room Management (availability, status, types, amenities)
+- Payment Processing (multiple payment methods, status tracking)
+- Invoice Management (generation, tracking, payment reconciliation)
+- Loyalty Program (points, tiers, rewards, referrals)
+- Service Management (additional hotel services)
+- Guest Management (profiles, preferences, CRM)
+- Chat Support System
+- Check-in/Check-out Operations
+- Maintenance and Housekeeping
+
+IMPORTANT SECURITY RULES:
+1. NEVER provide information about other users' bookings, payments, or personal data unless user is Admin
+2. For customers: Only show information about their own bookings, invoices, and payments
+3. For staff: Provide operational data but not financial summaries
+4. For accountant: Provide financial data but not operational details
+5. For admin: Full access to all information
+        
+Current System Status:
+"""
+        prompt += json.dumps(context, indent=2, default=str)
+        
+        if data:
+            prompt += "\n\nRelevant Data for Current Query:\n"
+            prompt += json.dumps(data, indent=2, default=str)
+        
+        prompt += """
+\nINSTRUCTIONS:
+- Provide clear, concise, and helpful responses
+- Use the data provided to answer questions accurately
+- Respect role-based access restrictions
+- If you don't have specific information or the user doesn't have access, explain clearly
+- Be professional and friendly
+- For customers, always refer to data as "your bookings", "your invoices", etc.
+- For staff/admin, provide comprehensive operational insights
+- For accountants, focus on financial data and reports"""
+        
+        return prompt
+    
+    def _generate_rule_based_response(self, intent: str, query: str, data: Dict) -> str:
+        """Generate rule-based response when LLM is not available - with role awareness"""
+        role_name = self.role_access_service.role_name if self.role_access_service else "customer"
+        is_customer = role_name == "customer"
+        
+        if intent == "room_occupied":
+            if data.get("occupied_rooms"):
+                rooms = data["occupied_rooms"]
+                if len(rooms) == 1:
+                    room = rooms[0]
+                    return f"Room {room['room_number']} is currently occupied by {room['guest_name']}. Check-in: {room['check_in']}, Check-out: {room['check_out']}."
+                else:
+                    return f"There are {len(rooms)} occupied rooms. Here are the details: {', '.join([r['room_number'] for r in rooms[:5]])}"
+            else:
+                summary = data.get("room_summary", {})
+                return f"Currently, {summary.get('occupied', 0)} rooms are occupied out of {summary.get('total_rooms', 0)} total rooms."
+        
+        elif intent == "room_available":
+            summary = data.get("room_summary", {})
+            return f"There are {summary.get('available', 0)} available rooms out of {summary.get('total_rooms', 0)} total rooms. {summary.get('cleaning', 0)} rooms are being cleaned."
+        
+        elif intent == "room_status":
+            summary = data.get("room_summary", {})
+            total = summary.get('total_rooms', 0)
+            available = summary.get('available', 0)
+            occupied = summary.get('occupied', 0)
+            maintenance = summary.get('maintenance', 0)
+            cleaning = summary.get('cleaning', 0)
+            occupancy_rate = summary.get('occupancy_rate', 0)
+            
+            response = f"We have {total} total rooms. "
+            response += f"Currently: {available} available, {occupied} occupied, {cleaning} being cleaned, and {maintenance} under maintenance. "
+            response += f"Occupancy rate: {occupancy_rate}%."
+            return response
+        
+        elif intent == "room_problems":
+            problems = data.get("problems", [])
+            if problems:
+                response = f"⚠️ Room Issues: There are {len(problems)} rooms with problems:\n\n"
+                for i, problem in enumerate(problems[:10], 1):
+                    response += f"{i}. Room {problem['room_number']}\n"
+                    response += f"   Issue: {problem.get('issue_type', 'Unknown')}\n"
+                    if problem.get('description'):
+                        response += f"   Details: {problem['description']}\n"
+                    if problem.get('status'):
+                        response += f"   Status: {problem['status']}\n"
+                    response += "\n"
+                if len(problems) > 10:
+                    response += f"... and {len(problems) - 10} more rooms with issues."
+                return response
+            else:
+                return "✅ No room problems reported at this time. All rooms are in good condition!"
+        
+        elif intent == "booking_by_number":
+            booking = data.get("booking")
+            if booking:
+                response = f"Booking {booking['booking_number']}:\n"
+                response += f"• Status: {booking['status']}\n"
+                response += f"• Guest: {booking['guest_name']}\n"
+                response += f"• Room: {booking['room_number']}\n"
+                response += f"• Check-in: {booking['check_in']}\n"
+                response += f"• Check-out: {booking['check_out']}\n"
+                response += f"• Payment Status: {booking['payment_status']}\n"
+                if booking.get('total_price'):
+                    response += f"• Total Price: ${float(booking['total_price']):,.2f}"
+                return response
+            else:
+                return "I couldn't find that booking. Please check the booking number and try again."
+        
+        elif intent == "booking_status":
+            # Role-aware booking status
+            if is_customer:
+                user_bookings = data.get("user_bookings", [])
+                if user_bookings:
+                    response = f"You have {len(user_bookings)} booking(s):\n\n"
+                    for booking in user_bookings[:5]:
+                        response += f"• {booking.get('booking_number', 'N/A')}: {booking.get('status', 'Unknown')}\n"
+                        response += f"  Check-in: {booking.get('check_in', 'N/A')}, Check-out: {booking.get('check_out', 'N/A')}\n"
+                    if len(user_bookings) > 5:
+                        response += f"\n... and {len(user_bookings) - 5} more bookings."
+                    return response
+                else:
+                    return "You don't have any bookings at this time."
+            else:
+                summary = data.get("booking_summary", {})
+                if summary:
+                    response = "Booking Status Summary:\n"
+                    response += f"• Active Bookings: {summary.get('active_bookings', 0)}\n"
+                    response += f"• Upcoming Check-ins: {summary.get('upcoming_checkins', 0)}\n"
+                    response += f"• Upcoming Check-outs: {summary.get('upcoming_checkouts', 0)}\n"
+                    response += f"• Pending Bookings: {summary.get('pending_bookings', 0)}"
+                    return response
+                return "No booking data available at this time."
+        
+        elif intent == "invoice_by_number":
+            invoice = data.get("invoice")
+            if invoice:
+                response = f"Invoice {invoice['invoice_number']}:\n"
+                response += f"• Status: {invoice['status']}\n"
+                response += f"• Amount: ${invoice['amount']:,.2f}\n"
+                if invoice.get('due_date'):
+                    response += f"• Due Date: {invoice['due_date']}\n"
+                if invoice.get('booking_number'):
+                    response += f"• Booking: {invoice['booking_number']}"
+                return response
+            else:
+                return "I couldn't find that invoice. Please check the invoice number."
+        
+        elif intent == "invoice_status":
+            # Role-aware invoice status
+            if is_customer:
+                user_invoices = data.get("user_invoices", [])
+                if user_invoices:
+                    response = f"You have {len(user_invoices)} invoice(s):\n\n"
+                    for invoice in user_invoices[:5]:
+                        status_emoji = "✅" if invoice.get('status') == 'paid' else "⏳" if invoice.get('status') == 'sent' else "⚠️"
+                        response += f"{status_emoji} Invoice {invoice.get('invoice_number', 'N/A')}: {invoice.get('status', 'Unknown')}\n"
+                        response += f"   Amount: ${invoice.get('total_amount', 0):,.2f}, Due: {invoice.get('due_date', 'N/A')}\n"
+                    if len(user_invoices) > 5:
+                        response += f"\n... and {len(user_invoices) - 5} more invoices."
+                    return response
+                else:
+                    return "You don't have any invoices at this time."
+            else:
+                summary = data.get("invoice_summary", {})
+                if summary:
+                    response = "Invoice Status Summary:\n"
+                    response += f"• Total Invoices: {summary.get('total_invoices', 0)}\n"
+                    response += f"• Overdue Invoices: {summary.get('overdue_invoices', 0)}"
+                    if summary.get('status_breakdown'):
+                        response += f"\n• Status Breakdown: {summary['status_breakdown']}"
+                    return response
+                return "No invoice data available at this time."
+        
+        elif intent == "all_payments":
+            # Display all payments in table format
+            all_payments = data.get("all_payments", [])
+            if all_payments:
+                response = f"📋 ALL PAYMENTS ({len(all_payments)} total):\n\n"
+                response += "┌──────────────┬──────────────────────────────┬──────────────────┬──────────┬──────────────────┬──────────┬────────────┬──────────────┐\n"
+                response += "│ Transaction  │ Booking Number               │ Customer         │ Method   │ Type             │ Status   │ Amount     │ Payment Date │\n"
+                response += "├──────────────┼──────────────────────────────┼──────────────────┼──────────┼──────────────────┼──────────┼────────────┼──────────────┤\n"
+                
+                for payment in all_payments:
+                    trans_id = (payment.get('transaction_id') or f"PAY-{payment.get('id', 'N/A')}")[:12]
+                    booking = (payment.get('booking_number') or 'N/A')[:28]
+                    customer = (payment.get('customer_name') or 'N/A')[:16]
+                    method = str(payment.get('payment_method', 'N/A')).replace('_', ' ').title()[:8]
+                    ptype = payment.get('payment_type_display', payment.get('payment_type', 'N/A'))[:16]
+                    status = str(payment.get('payment_status', 'N/A')).title()
+                    
+                    status_emoji = "✅" if status.lower() == 'completed' else "⏳" if status.lower() == 'pending' else "❌" if status.lower() == 'failed' else "🔄" if status.lower() == 'refunded' else "❓"
+                    status_display = f"{status_emoji} {status}"[:10]
+                    
+                    amount = payment.get('amount', 0)
+                    amount_str = f"{amount:,.2f} €"[:12]
+                    
+                    pdate = payment.get('payment_date', None)
+                    if pdate and pdate != 'Invalid Date':
+                        try:
+                            from datetime import datetime
+                            if isinstance(pdate, str):
+                                if 'T' in pdate:
+                                    dt = datetime.fromisoformat(pdate.replace('Z', '+00:00'))
+                                    pdate = dt.strftime('%Y-%m-%d')
+                                else:
+                                    pdate = pdate[:10]
+                            else:
+                                pdate = pdate.strftime('%Y-%m-%d') if hasattr(pdate, 'strftime') else str(pdate)[:10]
+                        except Exception:
+                            pdate = "Invalid Date"
+                    else:
+                        pdate = "Invalid Date"
+                    
+                    response += f"│ {trans_id:<12} │ {booking:<28} │ {customer:<16} │ {method:<8} │ {ptype:<16} │ {status_display:<10} │ {amount_str:<12} │ {pdate:<14} │\n"
+                
+                response += "└──────────────┴──────────────────────────────┴──────────────────┴──────────┴──────────────────┴──────────┴────────────┴──────────────┘\n"
+                
+                # Add summary statistics
+                completed = sum(1 for p in all_payments if p.get('payment_status', '').lower() == 'completed')
+                pending = sum(1 for p in all_payments if p.get('payment_status', '').lower() == 'pending')
+                failed = sum(1 for p in all_payments if p.get('payment_status', '').lower() == 'failed')
+                refunded = sum(1 for p in all_payments if p.get('payment_status', '').lower() == 'refunded')
+                total_amount = sum(float(p.get('amount', 0)) for p in all_payments)
+                completed_amount = sum(float(p.get('amount', 0)) for p in all_payments if p.get('payment_status', '').lower() == 'completed')
+                pending_amount = sum(float(p.get('amount', 0)) for p in all_payments if p.get('payment_status', '').lower() == 'pending')
+                
+                response += f"\n📊 Summary:\n"
+                response += f"• Total Payments: {len(all_payments)}\n"
+                response += f"• ✅ Completed: {completed} ({completed_amount:,.2f} €)\n"
+                response += f"• ⏳ Pending: {pending} ({pending_amount:,.2f} €)\n"
+                response += f"• ❌ Failed: {failed}\n"
+                if refunded > 0:
+                    response += f"• 🔄 Refunded: {refunded}\n"
+                response += f"• Total Amount: {total_amount:,.2f} €"
+                
+                return response
+            else:
+                return "No payments found."
+        
+        elif intent == "payment_status":
+            # Role-aware payment status
+            if is_customer:
+                user_payments = data.get("user_payments", [])
+                if user_payments:
+                    response = f"Your recent payments ({len(user_payments)} total):\n\n"
+                    for payment in user_payments[:5]:
+                        status_emoji = "✅" if payment.get('payment_status') == 'completed' else "⏳" if payment.get('payment_status') == 'pending' else "❌"
+                        response += f"{status_emoji} ${payment.get('amount', 0):,.2f} - {payment.get('payment_method', 'N/A')}\n"
+                        response += f"   Status: {payment.get('payment_status', 'Unknown')}, Date: {payment.get('payment_date', 'N/A')}\n"
+                    if len(user_payments) > 5:
+                        response += f"\n... and {len(user_payments) - 5} more payments."
+                    return response
+                else:
+                    return "You don't have any payment records at this time."
+            else:
+                summary = data.get("payment_summary", {})
+                if summary:
+                    response = "Payment Status Summary:\n"
+                    response += f"• Total Revenue (last 30 days): ${summary.get('total_revenue', 0):,.2f}\n"
+                    response += f"• Pending Payments: ${summary.get('pending_amount', 0):,.2f}\n"
+                    response += f"• Completed Payments: {summary.get('completed_payments', 0)}"
+                    return response
+                return "No payment data available at this time."
+        
+        elif intent == "chat_status":
+            chats = data.get("unanswered_chats", [])
+            if chats:
+                response = f"Chat Status: There are {len(chats)} unanswered chat messages.\n\n"
+                response += "Oldest waiting messages:\n"
+                for i, chat in enumerate(chats[:3], 1):
+                    response += f"{i}. {chat['visitor_name']} - Waiting {chat['waiting_hours']:.1f} hours\n"
+                    response += f"   Last message: {chat['last_message'][:50]}...\n"
+                return response
+            else:
+                return "All chat messages have been answered. Great job! ✅"
+        
+        elif intent == "general_status":
+            # Comprehensive status overview - always show all sections for consistency
+            room_summary = data.get("room_summary", {})
+            booking_summary = data.get("booking_summary", {})
+            payment_summary = data.get("payment_summary", {})
+            invoice_summary = data.get("invoice_summary", {})
+            unanswered_chats = data.get("unanswered_chats", [])
+            problems = data.get("room_problems", [])
+            
+            response = "📊 Hotel Status Overview:\n\n"
+            
+            # Rooms - always show
+            response += "🏨 ROOMS:\n"
+            occupancy_rate = room_summary.get('occupancy_rate', 0)
+            # Format occupancy rate to show one decimal place
+            if isinstance(occupancy_rate, (int, float)):
+                occupancy_rate = f"{occupancy_rate:.1f}"
+            response += f"• Total: {room_summary.get('total_rooms', 0)}\n"
+            response += f"• Available: {room_summary.get('available', 0)}\n"
+            response += f"• Occupied: {room_summary.get('occupied', 0)}\n"
+            response += f"• Cleaning: {room_summary.get('cleaning', 0)}\n"
+            response += f"• Maintenance: {room_summary.get('maintenance', 0)}\n"
+            response += f"• Occupancy Rate: {occupancy_rate}%\n\n"
+            
+            # Bookings - always show
+            response += "📅 BOOKINGS:\n"
+            response += f"• Active: {booking_summary.get('active_bookings', 0)}\n"
+            response += f"• Upcoming Check-ins: {booking_summary.get('upcoming_checkins', 0)}\n"
+            response += f"• Upcoming Check-outs: {booking_summary.get('upcoming_checkouts', 0)}\n"
+            response += f"• Pending: {booking_summary.get('pending_bookings', 0)}\n\n"
+            
+            # Payments - always show
+            response += "💰 PAYMENTS:\n"
+            total_revenue = payment_summary.get('total_revenue', 0) or 0
+            pending_amount = payment_summary.get('pending_amount', 0) or 0
+            response += f"• Revenue (30 days): ${total_revenue:,.2f}\n"
+            response += f"• Pending: ${pending_amount:,.2f}\n"
+            response += f"• Completed: {payment_summary.get('completed_payments', 0)}\n\n"
+            
+            # Invoices - always show
+            response += "🧾 INVOICES:\n"
+            response += f"• Total: {invoice_summary.get('total_invoices', 0)}\n"
+            response += f"• Overdue: {invoice_summary.get('overdue_invoices', 0)}\n\n"
+            
+            # Chats - always show
+            response += "💬 CHATS:\n"
+            response += f"• Unanswered: {len(unanswered_chats)}\n\n"
+            
+            # Problems - show if any, otherwise skip
+            if problems:
+                response += "⚠️ ISSUES:\n"
+                response += f"• Rooms with problems: {len(problems)}\n"
+                for problem in problems[:3]:
+                    response += f"  - Room {problem['room_number']}: {problem.get('description', 'Issue reported')}\n"
+            
+            return response
+        
+        elif intent == "app_info":
+            # Comprehensive application information - formatted for admin
+            app_knowledge = data.get("app_knowledge", {})
+            role_name = self.role_access_service.role_name if self.role_access_service else "customer"
+            
+            if role_name != "admin":
+                response = "📱 Application Overview:\n\n"
+                response += app_knowledge.get("overview", "This is a Hotel Booking and Management System.")
+                response += "\n\n"
+                role_info = app_knowledge.get("role_info", {})
+                if role_info:
+                    response += f"Your Role: {role_name.upper()}\n"
+                    response += f"Description: {role_info.get('description', 'Standard user access')}\n"
+                return response
+            
+            # Admin gets full comprehensive information
+            response = "📱 Hotel Booking & Management System (HBMS) - Complete Overview\n\n"
+            response += "=" * 60 + "\n\n"
+            
+            # Overview
+            response += "📋 SYSTEM OVERVIEW:\n"
+            response += app_knowledge.get("overview", "") + "\n\n"
+            
+            # Core Features
+            features = app_knowledge.get("features", {})
+            if features:
+                response += "🔧 CORE FEATURES & MODULES:\n\n"
+                feature_count = 0
+                for feature_name, feature_info in features.items():
+                    feature_count += 1
+                    feature_title = feature_name.replace("_", " ").title()
+                    response += f"{feature_count}. {feature_title}\n"
+                    response += f"   {feature_info.get('description', 'N/A')}\n"
+                    
+                    if feature_info.get('models'):
+                        models = feature_info.get('models', [])
+                        if models:
+                            response += f"   Models: {', '.join(models[:5])}"
+                            if len(models) > 5:
+                                response += f" (+{len(models) - 5} more)"
+                            response += "\n"
+                    
+                    if feature_info.get('statuses'):
+                        statuses = feature_info.get('statuses', [])
+                        response += f"   Statuses: {', '.join(statuses)}\n"
+                    
+                    response += "\n"
+            
+            # User Roles
+            role_capabilities = app_knowledge.get("role_capabilities", {})
+            if role_capabilities:
+                response += "👥 USER ROLES & PERMISSIONS:\n\n"
+                for role_name_key, role_info in role_capabilities.items():
+                    response += f"• {role_name_key.upper()}\n"
+                    response += f"  {role_info.get('description', '')}\n"
+                    
+                    can_access = role_info.get('can_access', [])
+                    if can_access:
+                        response += f"  Can Access: {len(can_access)} features\n"
+                        # Show first 5 capabilities
+                        for cap in can_access[:5]:
+                            response += f"    - {cap}\n"
+                        if len(can_access) > 5:
+                            response += f"    ... and {len(can_access) - 5} more\n"
+                    
+                    cannot_access = role_info.get('cannot_access', [])
+                    if cannot_access:
+                        response += f"  Restrictions: {len(cannot_access)} items\n"
+                    
+                    response += "\n"
+            
+            # Technology Stack
+            response += "💻 TECHNOLOGY STACK:\n\n"
+            response += "• Backend: FastAPI (Python)\n"
+            response += "• Frontend: React/TypeScript\n"
+            response += "• Database: SQLAlchemy ORM\n"
+            response += "• AI: Self-learning assistant with pattern recognition\n"
+            response += "• Authentication: JWT with MFA support\n"
+            response += "• Security: Role-based access control, audit logging\n\n"
+            
+            # Key Capabilities
+            response += "✨ KEY CAPABILITIES:\n\n"
+            response += "• Complete booking lifecycle management\n"
+            response += "• Multi-role access control (Admin, Staff, Accountant, Customer)\n"
+            response += "• Payment processing with multiple methods\n"
+            response += "• Invoice generation and tracking\n"
+            response += "• Loyalty program with points and rewards\n"
+            response += "• Real-time chat support system\n"
+            response += "• Room maintenance and housekeeping management\n"
+            response += "• Guest profile and CRM features\n"
+            response += "• Analytics and reporting\n"
+            response += "• Content management (blog, pages, banners)\n"
+            response += "• Email campaigns and marketing automation\n"
+            response += "• Group booking management\n"
+            response += "• Dynamic pricing and rate plans\n"
+            response += "• Package deals (room + services)\n"
+            response += "• Review and rating system\n"
+            response += "• Audit logging and security compliance\n\n"
+            
+            # Common Queries
+            common_queries = app_knowledge.get("common_queries", {})
+            if common_queries:
+                response += "💬 COMMON QUERY CATEGORIES:\n\n"
+                for category, queries in common_queries.items():
+                    response += f"• {category.title()}: {', '.join(queries[:3])}"
+                    if len(queries) > 3:
+                        response += f" (+{len(queries) - 3} more)"
+                    response += "\n"
+                response += "\n"
+            
+            response += "=" * 60 + "\n"
+            response += "\n💡 TIP: Ask me about any specific feature, model, or capability for detailed information!"
+            
+            return response
+        
+        elif intent == "general_query":
+            # Try to provide helpful response based on available data
+            room_summary = data.get("room_summary", {})
+            booking_summary = data.get("booking_summary", {})
+            payment_summary = data.get("payment_summary", {})
+            
+            response = "I can help you with information about:\n\n"
+            response += "🏨 Rooms - availability, occupancy, status, problems\n"
+            response += "📅 Bookings - active, upcoming, pending reservations\n"
+            response += "💰 Payments - revenue, pending payments, transactions\n"
+            response += "🧾 Invoices - status, overdue invoices\n"
+            response += "💬 Chats - unanswered customer messages\n\n"
+            
+            if room_summary:
+                response += f"Quick Stats: {room_summary.get('total_rooms', 0)} total rooms, "
+                response += f"{room_summary.get('occupied', 0)} occupied, "
+                response += f"{room_summary.get('available', 0)} available.\n\n"
+            
+            response += "Try asking:\n"
+            response += "• 'How many rooms do we have?'\n"
+            response += "• 'Show me occupied rooms'\n"
+            response += "• 'What's our revenue?'\n"
+            response += "• 'Are there any unanswered chats?'"
+            
+            return response
+        
+        else:
+            return "I can help you with questions about rooms, bookings, invoices, payments, and chat messages. What would you like to know?"
+    
+    def _apply_learned_pattern(self, pattern: AILearnedPattern, data: Dict, query: str) -> Optional[str]:
+        """Apply learned pattern to generate response"""
+        try:
+            response_template = pattern.response_template or ""
+            
+            # Replace placeholders with actual data
+            if "{data}" in response_template and data:
+                # Inject relevant data into response
+                data_str = json.dumps(data, indent=2, default=str)[:500]
+                response = response_template.replace("{data}", data_str)
+            else:
+                response = response_template
+            
+            return response[:2000]  # Limit response length
+        except Exception as e:
+            logger.error(f"Error applying learned pattern: {str(e)}", exc_info=True)
+            return None
+

Backend/src/ai/services/ai_knowledge_base.py

@@ -0,0 +1,382 @@
+"""
+Enterprise AI Knowledge Base
+Comprehensive documentation of all application features, models, and capabilities
+"""
+
+from typing import Dict, List, Any
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+class AIKnowledgeBase:
+    """Enterprise Knowledge Base for AI Assistant - Documents entire application"""
+    
+    APPLICATION_OVERVIEW = """
+    This is a comprehensive Hotel Booking and Management System (HBMS) - an enterprise-grade
+    solution for managing hotel operations, reservations, payments, guest services, and business analytics.
+    
+    The system supports multiple user roles: Admin, Staff, Accountant, and Customer, each with
+    different access levels and permissions.
+    """
+    
+    # Core Models and Features
+    FEATURES = {
+        "booking_management": {
+            "description": "Complete booking lifecycle management including creation, confirmation, check-in, check-out, and cancellation",
+            "models": ["Booking", "BookingStatus"],
+            "key_fields": ["booking_number", "user_id", "room_id", "check_in_date", "check_out_date", 
+                          "num_guests", "total_price", "status", "special_requests"],
+            "statuses": ["pending", "confirmed", "checked_in", "checked_out", "cancelled"],
+            "relationships": ["User", "Room", "Payment", "Invoice", "ServiceUsage", "CheckInCheckOut"]
+        },
+        
+        "room_management": {
+            "description": "Room inventory, availability, status tracking, and maintenance",
+            "models": ["Room", "RoomType", "RoomStatus"],
+            "key_fields": ["room_number", "floor", "status", "price", "capacity", "amenities", "room_size", "view"],
+            "statuses": ["available", "occupied", "maintenance", "cleaning"],
+            "relationships": ["RoomType", "Booking", "Review", "RoomMaintenance", "HousekeepingTask"]
+        },
+        
+        "payment_processing": {
+            "description": "Payment handling for bookings with multiple payment methods and status tracking",
+            "models": ["Payment", "PaymentMethod", "PaymentStatus", "PaymentType"],
+            "key_fields": ["amount", "payment_method", "payment_type", "payment_status", "transaction_id", "payment_date"],
+            "payment_methods": ["cash", "credit_card", "debit_card", "bank_transfer", "e_wallet", "stripe", "paypal", "borica"],
+            "statuses": ["pending", "completed", "failed", "refunded"],
+            "payment_types": ["full", "deposit", "remaining"],
+            "relationships": ["Booking"]
+        },
+        
+        "invoice_management": {
+            "description": "Invoice generation, tracking, and payment reconciliation",
+            "models": ["Invoice", "InvoiceItem", "InvoiceStatus"],
+            "key_fields": ["invoice_number", "total_amount", "subtotal", "tax_amount", "discount_amount", 
+                          "balance_due", "status", "due_date", "paid_date"],
+            "statuses": ["draft", "sent", "paid", "overdue", "cancelled"],
+            "relationships": ["Booking", "User", "InvoiceItem"]
+        },
+        
+        "user_management": {
+            "description": "User accounts, roles, authentication, and guest profiles",
+            "models": ["User", "Role", "RefreshToken", "PasswordResetToken"],
+            "key_fields": ["email", "full_name", "phone", "role_id", "is_active", "currency"],
+            "roles": ["admin", "staff", "customer", "accountant"],
+            "guest_fields": ["is_vip", "lifetime_value", "satisfaction_score", "total_visits", "last_visit_date"],
+            "relationships": ["Role", "Booking", "Payment", "Invoice", "Review", "Favorite"]
+        },
+        
+        "loyalty_program": {
+            "description": "Customer loyalty program with tiers, points, rewards, and referrals",
+            "models": ["LoyaltyTier", "UserLoyalty", "LoyaltyPointTransaction", "LoyaltyReward", 
+                      "RewardRedemption", "Referral"],
+            "key_fields": ["tier_level", "points_balance", "lifetime_points", "referral_code"],
+            "relationships": ["User", "Booking"]
+        },
+        
+        "service_management": {
+            "description": "Additional hotel services like spa, restaurant, room service",
+            "models": ["Service", "ServiceUsage", "ServiceBooking", "ServiceBookingItem", "ServicePayment"],
+            "key_fields": ["service_name", "price", "category", "description"],
+            "relationships": ["Booking"]
+        },
+        
+        "promotion_system": {
+            "description": "Discount codes, promotional campaigns, and special offers",
+            "models": ["Promotion"],
+            "key_fields": ["code", "discount_type", "discount_value", "start_date", "end_date", "is_active"],
+            "relationships": ["Booking"]
+        },
+        
+        "reviews_and_ratings": {
+            "description": "Guest reviews and ratings for rooms and services",
+            "models": ["Review"],
+            "key_fields": ["rating", "comment", "is_verified"],
+            "relationships": ["User", "Room"]
+        },
+        
+        "chat_system": {
+            "description": "Real-time chat support between guests and staff",
+            "models": ["Chat", "ChatMessage", "ChatStatus"],
+            "key_fields": ["visitor_name", "visitor_email", "status", "message", "sender_type", "is_read"],
+            "statuses": ["open", "closed"],
+            "relationships": ["User"]
+        },
+        
+        "check_in_check_out": {
+            "description": "Check-in and check-out process management",
+            "models": ["CheckInCheckOut"],
+            "key_fields": ["checked_in_at", "checked_out_at", "checked_in_by", "checked_out_by", "notes"],
+            "relationships": ["Booking", "User"]
+        },
+        
+        "maintenance_tracking": {
+            "description": "Room maintenance scheduling and tracking",
+            "models": ["RoomMaintenance", "RoomInspection"],
+            "key_fields": ["scheduled_start", "scheduled_end", "status", "description", "priority"],
+            "relationships": ["Room"]
+        },
+        
+        "housekeeping": {
+            "description": "Housekeeping task management and scheduling",
+            "models": ["HousekeepingTask"],
+            "key_fields": ["task_type", "status", "scheduled_time", "completed_at"],
+            "relationships": ["Room"]
+        },
+        
+        "guest_management": {
+            "description": "Comprehensive guest profile management and CRM features",
+            "models": ["GuestNote", "GuestPreference", "GuestTag", "GuestSegment", "GuestCommunication"],
+            "key_fields": ["notes", "preferences", "tags", "communication_history"],
+            "relationships": ["User"]
+        },
+        
+        "group_bookings": {
+            "description": "Group booking management for multiple rooms",
+            "models": ["GroupBooking"],
+            "key_fields": ["group_name", "contact_person", "total_rooms", "group_discount"],
+            "relationships": ["Booking"]
+        },
+        
+        "rate_plans": {
+            "description": "Dynamic pricing and rate plan management",
+            "models": ["RatePlan"],
+            "key_fields": ["name", "base_price", "season_multiplier", "valid_from", "valid_to"],
+            "relationships": ["Booking"]
+        },
+        
+        "packages": {
+            "description": "Pre-configured booking packages (room + services)",
+            "models": ["Package"],
+            "key_fields": ["name", "price", "includes", "valid_period"],
+            "relationships": ["RoomType", "Service"]
+        },
+        
+        "blog_and_content": {
+            "description": "Content management for hotel blog and marketing",
+            "models": ["BlogPost", "Banner", "PageContent"],
+            "key_fields": ["title", "content", "is_published", "published_at"],
+            "relationships": []
+        },
+        
+        "analytics_and_reporting": {
+            "description": "Business intelligence, analytics, and financial reporting",
+            "features": ["Revenue reports", "Occupancy analytics", "Guest analytics", "Payment reports", 
+                       "Invoice reports", "Booking trends", "Customer lifetime value"],
+            "models": ["AuditLog"]
+        },
+        
+        "system_settings": {
+            "description": "System-wide configuration and settings",
+            "models": ["SystemSettings"],
+            "key_fields": ["key", "value", "category"],
+            "categories": ["general", "payment", "email", "company_info"]
+        },
+        
+        "security_and_compliance": {
+            "description": "Security, audit logging, and GDPR compliance",
+            "models": ["SecurityEvent", "AuditLog", "GDPRCompliance"],
+            "features": ["Action audit trails", "Security event logging", "GDPR data requests", 
+                        "Cookie consent management"]
+        },
+        
+        "notifications": {
+            "description": "System notifications and alerts",
+            "models": ["Notification"],
+            "key_fields": ["type", "message", "is_read", "priority"],
+            "relationships": ["User"]
+        },
+        
+        "workflows": {
+            "description": "Automated workflow management for business processes",
+            "models": ["Workflow"],
+            "key_fields": ["name", "trigger", "actions", "conditions"],
+            "relationships": []
+        },
+        
+        "email_campaigns": {
+            "description": "Marketing email campaigns and automation",
+            "models": ["EmailCampaign"],
+            "key_fields": ["subject", "content", "recipient_segment", "scheduled_time"],
+            "relationships": ["GuestSegment"]
+        }
+    }
+    
+    ROLE_CAPABILITIES = {
+        "admin": {
+            "description": "Full system access with all administrative privileges",
+            "can_access": [
+                "All bookings (all customers)",
+                "All rooms and room management",
+                "All payments and financial data",
+                "All invoices",
+                "All users and user management",
+                "System settings and configuration",
+                "Analytics and reports",
+                "Audit logs and security events",
+                "Content management (blog, banners, pages)",
+                "Promotion management",
+                "Loyalty program administration",
+                "Service management",
+                "Maintenance and housekeeping",
+                "Check-in/check-out operations",
+                "Chat management",
+                "Email campaigns",
+                "Workflow management",
+                "Group bookings",
+                "Rate plans and packages"
+            ],
+            "cannot_access": [],
+            "restrictions": "None - full access"
+        },
+        
+        "accountant": {
+            "description": "Financial data access for accounting and reporting",
+            "can_access": [
+                "All payments and payment history",
+                "All invoices and invoice management",
+                "Financial reports and analytics",
+                "Revenue summaries",
+                "Payment reconciliation",
+                "Invoice generation and editing",
+                "Booking financial details (for invoicing)",
+                "Customer payment history",
+                "Refund processing",
+                "Financial dashboard statistics"
+            ],
+            "cannot_access": [
+                "User personal information (except payment-related)",
+                "System settings",
+                "Content management",
+                "Room operational details (unless related to billing)",
+                "Security and audit logs (financial audit access only)"
+            ],
+            "restrictions": "Financial and payment data only"
+        },
+        
+        "staff": {
+            "description": "Operational staff with access to daily hotel operations",
+            "can_access": [
+                "All bookings and booking management",
+                "Room status and availability",
+                "Check-in and check-out operations",
+                "Guest information (for operations)",
+                "Room maintenance and housekeeping tasks",
+                "Service bookings and service usage",
+                "Chat system for customer support",
+                "Basic booking reports",
+                "Occupancy status",
+                "Group bookings",
+                "Guest preferences and notes (operational)"
+            ],
+            "cannot_access": [
+                "Financial reports and analytics",
+                "System settings",
+                "User management (except guest profile updates)",
+                "Content management",
+                "Email campaigns",
+                "Workflow management",
+                "Full payment details (can view payment status only)",
+                "Invoice editing (view only)"
+            ],
+            "restrictions": "Operational data only, no financial or system administration"
+        },
+        
+        "customer": {
+            "description": "Hotel guests with access to their own booking and account information",
+            "can_access": [
+                "Own bookings (view, cancel)",
+                "Own booking details",
+                "Own invoices (view only)",
+                "Own payment history",
+                "Own profile information",
+                "Room browsing and availability (public)",
+                "Service browsing",
+                "Booking creation",
+                "Review submission",
+                "Favorite rooms",
+                "Loyalty points and rewards",
+                "Referral code usage",
+                "Chat with support"
+            ],
+            "cannot_access": [
+                "Other customers' bookings or information",
+                "All bookings overview",
+                "Financial reports",
+                "System settings",
+                "Room management",
+                "Staff operations",
+                "Admin features",
+                "Other users' data"
+            ],
+            "restrictions": "Only own data and customer-facing features"
+        }
+    }
+    
+    COMMON_QUERIES = {
+        "booking": [
+            "booking status", "check-in date", "check-out date", "booking number",
+            "cancel booking", "modify booking", "upcoming bookings", "past bookings"
+        ],
+        "room": [
+            "available rooms", "room types", "room amenities", "room prices",
+            "room availability", "occupied rooms", "room status"
+        ],
+        "payment": [
+            "payment status", "payment history", "payment methods", "refund",
+            "outstanding balance", "payment due", "transaction"
+        ],
+        "invoice": [
+            "invoice status", "invoice number", "invoice amount", "due date",
+            "paid invoice", "outstanding invoice", "invoice download"
+        ],
+        "loyalty": [
+            "loyalty points", "loyalty tier", "rewards", "referral code",
+            "points balance", "points history"
+        ],
+        "general": [
+            "hotel information", "contact", "policies", "services", "amenities",
+            "location", "FAQ", "help"
+        ]
+    }
+    
+    @classmethod
+    def get_application_knowledge(cls) -> Dict[str, Any]:
+        """Get comprehensive application knowledge for AI context"""
+        return {
+            "overview": cls.APPLICATION_OVERVIEW,
+            "features": cls.FEATURES,
+            "role_capabilities": cls.ROLE_CAPABILITIES,
+            "common_queries": cls.COMMON_QUERIES
+        }
+    
+    @classmethod
+    def get_role_info(cls, role_name: str) -> Dict[str, Any]:
+        """Get information about a specific role"""
+        return cls.ROLE_CAPABILITIES.get(role_name.lower(), {})
+    
+    @classmethod
+    def get_feature_info(cls, feature_name: str) -> Dict[str, Any]:
+        """Get information about a specific feature"""
+        return cls.FEATURES.get(feature_name.lower(), {})
+    
+    @classmethod
+    def can_role_access_feature(cls, role_name: str, feature: str) -> bool:
+        """Check if a role can access a specific feature"""
+        role_info = cls.ROLE_CAPABILITIES.get(role_name.lower(), {})
+        can_access = role_info.get("can_access", [])
+        
+        # Admin can access everything
+        if role_name.lower() == "admin":
+            return True
+        
+        # Check if feature is in can_access list
+        feature_keywords = feature.lower().split("_")
+        for accessible in can_access:
+            accessible_lower = accessible.lower()
+            if any(keyword in accessible_lower for keyword in feature_keywords):
+                return True
+        
+        return False
+

Backend/src/ai/services/ai_learning_service.py

@@ -0,0 +1,818 @@
+"""
+AI Learning Service - Self-learning and pattern recognition system
+Learns from conversations, stores patterns, and improves responses over time
+"""
+
+from typing import Dict, List, Optional, Any, Tuple
+from datetime import datetime, timedelta
+from sqlalchemy.orm import Session
+from sqlalchemy import and_, or_, func, desc
+import json
+import re
+import logging
+from collections import Counter
+
+from ..models.ai_conversation import (
+    AIConversation, AIConversationFeedback, AILearnedPattern,
+    AIKnowledgeEntry, AITrainingMetrics
+)
+from ...shared.config.logging_config import get_logger
+
+logger = get_logger(__name__)
+
+
+class AILearningService:
+    """Service for AI self-learning and pattern recognition"""
+    
+    def __init__(self, db: Session):
+        self.db = db
+    
+    def save_conversation(
+        self,
+        user_id: int,
+        user_query: str,
+        ai_response: str,
+        intent: str,
+        context_used: Optional[Dict] = None,
+        user_role: Optional[str] = None,
+        session_id: Optional[str] = None,
+        response_time_ms: Optional[int] = None
+    ) -> AIConversation:
+        """Save conversation for learning"""
+        try:
+            conversation = AIConversation(
+                user_id=user_id,
+                session_id=session_id,
+                user_query=user_query,
+                ai_response=ai_response,
+                intent=intent,
+                context_used=context_used or {},
+                user_role=user_role,
+                response_time_ms=response_time_ms
+            )
+            self.db.add(conversation)
+            self.db.commit()
+            self.db.refresh(conversation)
+            
+            # Trigger learning process in background
+            self._learn_from_conversation(conversation)
+            
+            return conversation
+        except Exception as e:
+            logger.error(f"Error saving conversation: {str(e)}", exc_info=True)
+            self.db.rollback()
+            raise
+    
+    def save_feedback(
+        self,
+        conversation_id: int,
+        user_id: int,
+        rating: Optional[int] = None,
+        is_helpful: Optional[bool] = None,
+        is_correct: Optional[bool] = None,
+        feedback_text: Optional[str] = None,
+        correction: Optional[str] = None
+    ) -> AIConversationFeedback:
+        """Save user feedback for learning"""
+        try:
+            feedback = AIConversationFeedback(
+                conversation_id=conversation_id,
+                user_id=user_id,
+                rating=rating,
+                is_helpful=is_helpful,
+                is_correct=is_correct,
+                feedback_text=feedback_text,
+                correction=correction
+            )
+            self.db.add(feedback)
+            
+            # Update conversation helpfulness
+            conversation = self.db.query(AIConversation).filter(
+                AIConversation.id == conversation_id
+            ).first()
+            if conversation:
+                conversation.is_helpful = is_helpful
+            
+            self.db.commit()
+            self.db.refresh(feedback)
+            
+            # Trigger learning from feedback
+            if feedback.is_correct == False or correction:
+                self._learn_from_feedback(conversation, feedback)
+            
+            return feedback
+        except Exception as e:
+            logger.error(f"Error saving feedback: {str(e)}", exc_info=True)
+            self.db.rollback()
+            raise
+    
+    def find_similar_queries(self, query: str, intent: Optional[str] = None, limit: int = 5) -> List[Dict[str, Any]]:
+        """Find similar past queries to learn from"""
+        try:
+            # Extract keywords from query
+            keywords = self._extract_keywords(query)
+            
+            # Search for similar queries
+            query_obj = self.db.query(AIConversation).filter(
+                AIConversation.user_query.ilike(f"%{query[:50]}%")
+            )
+            
+            if intent:
+                query_obj = query_obj.filter(AIConversation.intent == intent)
+            
+            similar = query_obj.order_by(desc(AIConversation.created_at)).limit(limit).all()
+            
+            results = []
+            for conv in similar:
+                results.append({
+                    "query": conv.user_query,
+                    "response": conv.ai_response,
+                    "intent": conv.intent,
+                    "is_helpful": conv.is_helpful,
+                    "created_at": conv.created_at.isoformat()
+                })
+            
+            return results
+        except Exception as e:
+            logger.error(f"Error finding similar queries: {str(e)}", exc_info=True)
+            return []
+    
+    def get_learned_pattern(self, query: str, user_role: Optional[str] = None) -> Optional[AILearnedPattern]:
+        """Get learned pattern that matches query"""
+        try:
+            keywords = self._extract_keywords(query)
+            
+            # Search patterns by keywords
+            patterns = self.db.query(AILearnedPattern).filter(
+                and_(
+                    AILearnedPattern.is_active == True,
+                    or_(*[AILearnedPattern.pattern_keywords.contains(kw) for kw in keywords[:5]])
+                )
+            )
+            
+            if user_role:
+                patterns = patterns.filter(
+                    or_(
+                        AILearnedPattern.user_role == user_role,
+                        AILearnedPattern.user_role.is_(None)
+                    )
+                )
+            
+            # Order by confidence and usage
+            patterns = patterns.order_by(
+                desc(AILearnedPattern.confidence_score),
+                desc(AILearnedPattern.usage_count)
+            ).limit(1).all()
+            
+            if patterns:
+                pattern = patterns[0]
+                # Update usage stats
+                pattern.usage_count += 1
+                pattern.last_used_at = datetime.utcnow()
+                self.db.commit()
+                return pattern
+            
+            return None
+        except Exception as e:
+            logger.error(f"Error getting learned pattern: {str(e)}", exc_info=True)
+            return None
+    
+    def get_knowledge_entry(self, query: str, user_role: Optional[str] = None) -> Optional[Dict[str, Any]]:
+        """Get knowledge base entry that matches query"""
+        try:
+            keywords = self._extract_keywords(query)
+            query_lower = query.lower()
+            
+            # Search knowledge entries
+            entries = self.db.query(AIKnowledgeEntry).filter(
+                and_(
+                    or_(
+                        AIKnowledgeEntry.question.ilike(f"%{query[:50]}%"),
+                        *[AIKnowledgeEntry.keywords.contains([kw]) for kw in keywords[:3]]
+                    ),
+                    or_(
+                        AIKnowledgeEntry.is_verified == True,
+                        AIKnowledgeEntry.confidence >= 70.0
+                    )
+                )
+            )
+            
+            if user_role:
+                entries = entries.filter(
+                    or_(
+                        AIKnowledgeEntry.user_role == user_role,
+                        AIKnowledgeEntry.user_role.is_(None)
+                    )
+                )
+            
+            entries = entries.order_by(
+                desc(AIKnowledgeEntry.confidence),
+                desc(AIKnowledgeEntry.success_count)
+            ).limit(1).all()
+            
+            if entries:
+                entry = entries[0]
+                # Update usage stats
+                entry.usage_count += 1
+                entry.last_used_at = datetime.utcnow()
+                self.db.commit()
+                
+                return {
+                    "topic": entry.topic,
+                    "question": entry.question,
+                    "answer": entry.answer,
+                    "confidence": float(entry.confidence)
+                }
+            
+            return None
+        except Exception as e:
+            logger.error(f"Error getting knowledge entry: {str(e)}", exc_info=True)
+            return None
+    
+    def _learn_from_conversation(self, conversation: AIConversation):
+        """Learn patterns from a conversation - automatically learns from all conversations"""
+        try:
+            # Always extract keywords and patterns (learn from all conversations)
+            keywords = self._extract_keywords(conversation.user_query)
+            
+            # Check if similar pattern exists
+            existing_pattern = self.get_learned_pattern(
+                conversation.user_query,
+                conversation.user_role
+            )
+            
+            if existing_pattern:
+                # Update existing pattern confidence
+                existing_pattern.success_count += 1
+                existing_pattern.usage_count += 1
+                
+                # Adjust confidence based on helpfulness
+                if conversation.is_helpful is True:
+                    existing_pattern.confidence_score = min(
+                        100.0,
+                        existing_pattern.confidence_score + 1.0
+                    )
+                elif conversation.is_helpful is False:
+                    existing_pattern.confidence_score = max(
+                        0.0,
+                        existing_pattern.confidence_score - 2.0
+                    )
+                else:
+                    # Neutral - slight increase
+                    existing_pattern.confidence_score = min(
+                        100.0,
+                        existing_pattern.confidence_score + 0.3
+                    )
+                
+                existing_pattern.last_used_at = datetime.utcnow()
+            else:
+                # Create new pattern - learn from all conversations
+                initial_confidence = 60.0 if conversation.is_helpful is True else 50.0
+                if conversation.is_helpful is False:
+                    initial_confidence = 30.0  # Lower confidence for unhelpful patterns
+                
+                pattern = AILearnedPattern(
+                    pattern_keywords=json.dumps(keywords),
+                    query_pattern=conversation.user_query[:200],
+                    intent=conversation.intent or "general_query",
+                    response_template=conversation.ai_response[:500],
+                    context_keys=conversation.context_used,
+                    confidence_score=initial_confidence,
+                    usage_count=1,
+                    success_count=1 if conversation.is_helpful is not False else 0,
+                    source_conversation_id=conversation.id,
+                    user_role=conversation.user_role,
+                    last_used_at=datetime.utcnow()
+                )
+                self.db.add(pattern)
+            
+            # Automatically extract knowledge from every conversation
+            # This enables the AI to build its knowledge base autonomously
+            self._auto_extract_knowledge(conversation)
+            
+            self.db.commit()
+        except Exception as e:
+            logger.error(f"Error learning from conversation: {str(e)}", exc_info=True)
+            self.db.rollback()
+    
+    def _learn_from_feedback(self, conversation: AIConversation, feedback: AIConversationFeedback):
+        """Learn from user feedback and corrections"""
+        try:
+            # If user provided correction, create knowledge entry
+            if feedback.correction:
+                knowledge = AIKnowledgeEntry(
+                    topic=self._extract_topic(conversation.user_query),
+                    question=conversation.user_query,
+                    answer=feedback.correction,
+                    keywords=self._extract_keywords(conversation.user_query),
+                    related_intent=conversation.intent,
+                    source='user_feedback',
+                    confidence=75.0,
+                    user_role=conversation.user_role,
+                    created_by_user_id=feedback.user_id
+                )
+                self.db.add(knowledge)
+            
+            # Update pattern confidence based on feedback
+            patterns = self.db.query(AILearnedPattern).filter(
+                AILearnedPattern.source_conversation_id == conversation.id
+            ).all()
+            
+            for pattern in patterns:
+                if feedback.is_helpful:
+                    pattern.confidence_score = min(100.0, pattern.confidence_score + 2.0)
+                    pattern.success_count += 1
+                elif feedback.is_helpful == False:
+                    pattern.confidence_score = max(0.0, pattern.confidence_score - 5.0)
+                
+                if feedback.is_correct == False:
+                    pattern.is_active = False  # Deactivate incorrect patterns
+            
+            self.db.commit()
+        except Exception as e:
+            logger.error(f"Error learning from feedback: {str(e)}", exc_info=True)
+            self.db.rollback()
+    
+    def _extract_keywords(self, text: str) -> List[str]:
+        """Extract keywords from text"""
+        # Remove common stop words
+        stop_words = {
+            'the', 'a', 'an', 'and', 'or', 'but', 'in', 'on', 'at', 'to', 'for',
+            'of', 'with', 'by', 'from', 'as', 'is', 'are', 'was', 'were', 'be',
+            'been', 'have', 'has', 'had', 'do', 'does', 'did', 'will', 'would',
+            'should', 'could', 'may', 'might', 'can', 'this', 'that', 'these',
+            'those', 'i', 'you', 'he', 'she', 'it', 'we', 'they', 'me', 'him',
+            'her', 'us', 'them', 'my', 'your', 'his', 'her', 'its', 'our', 'their',
+            'what', 'which', 'who', 'whom', 'whose', 'where', 'when', 'why', 'how',
+            'show', 'tell', 'give', 'get', 'find', 'search', 'list', 'all'
+        }
+        
+        # Extract words
+        words = re.findall(r'\b[a-z]+\b', text.lower())
+        keywords = [w for w in words if w not in stop_words and len(w) > 2]
+        
+        # Count frequency and return top keywords
+        word_freq = Counter(keywords)
+        return [word for word, _ in word_freq.most_common(10)]
+    
+    def _extract_topic(self, query: str) -> str:
+        """Extract topic from query"""
+        # Simple topic extraction - can be enhanced
+        keywords = self._extract_keywords(query)
+        if keywords:
+            return keywords[0].title()
+        return "General"
+    
+    def train_from_history(self, days: int = 7) -> Dict[str, Any]:
+        """Train AI from recent conversation history"""
+        try:
+            cutoff_date = datetime.utcnow() - timedelta(days=days)
+            
+            # Get conversations from last N days
+            conversations = self.db.query(AIConversation).filter(
+                AIConversation.created_at >= cutoff_date
+            ).all()
+            
+            trained_patterns = 0
+            trained_knowledge = 0
+            improved_patterns = 0
+            
+            for conv in conversations:
+                # Learn from helpful conversations
+                if conv.is_helpful is True:
+                    self._learn_from_conversation(conv)
+                    trained_patterns += 1
+                
+                # Get feedback for this conversation
+                feedbacks = self.db.query(AIConversationFeedback).filter(
+                    AIConversationFeedback.conversation_id == conv.id
+                ).all()
+                
+                for feedback in feedbacks:
+                    if feedback.correction:
+                        # Create knowledge entry from correction
+                        knowledge = AIKnowledgeEntry(
+                            topic=self._extract_topic(conv.user_query),
+                            question=conv.user_query,
+                            answer=feedback.correction,
+                            keywords=self._extract_keywords(conv.user_query),
+                            related_intent=conv.intent,
+                            source='training',
+                            confidence=80.0,
+                            user_role=conv.user_role
+                        )
+                        self.db.add(knowledge)
+                        trained_knowledge += 1
+            
+            self.db.commit()
+            
+            # Update training metrics
+            self._update_training_metrics()
+            
+            return {
+                "conversations_analyzed": len(conversations),
+                "patterns_trained": trained_patterns,
+                "knowledge_entries_created": trained_knowledge,
+                "improved_patterns": improved_patterns
+            }
+        except Exception as e:
+            logger.error(f"Error in training: {str(e)}", exc_info=True)
+            self.db.rollback()
+            return {"error": str(e)}
+    
+    def _update_training_metrics(self):
+        """Update training metrics"""
+        try:
+            today = datetime.utcnow().date()
+            
+            # Calculate metrics
+            total_conversations = self.db.query(AIConversation).count()
+            total_patterns = self.db.query(AILearnedPattern).filter(
+                AILearnedPattern.is_active == True
+            ).count()
+            total_knowledge = self.db.query(AIKnowledgeEntry).filter(
+                AIKnowledgeEntry.is_verified == True
+            ).count()
+            
+            # Average response time
+            avg_response_time = self.db.query(
+                func.avg(AIConversation.response_time_ms)
+            ).filter(
+                AIConversation.response_time_ms.isnot(None)
+            ).scalar()
+            
+            # Average rating
+            avg_rating = self.db.query(
+                func.avg(AIConversationFeedback.rating)
+            ).filter(
+                AIConversationFeedback.rating.isnot(None)
+            ).scalar()
+            
+            # Helpful rate
+            total_with_feedback = self.db.query(AIConversation).filter(
+                AIConversation.is_helpful.isnot(None)
+            ).count()
+            helpful_count = self.db.query(AIConversation).filter(
+                AIConversation.is_helpful == True
+            ).count()
+            helpful_rate = (helpful_count / total_with_feedback * 100) if total_with_feedback > 0 else None
+            
+            # Create or update metrics
+            metrics = self.db.query(AITrainingMetrics).filter(
+                func.date(AITrainingMetrics.metric_date) == today
+            ).first()
+            
+            if not metrics:
+                metrics = AITrainingMetrics(metric_date=datetime.utcnow())
+                self.db.add(metrics)
+            
+            metrics.total_conversations = total_conversations
+            metrics.total_patterns_learned = total_patterns
+            metrics.total_knowledge_entries = total_knowledge
+            metrics.average_response_time_ms = int(avg_response_time) if avg_response_time else None
+            metrics.average_rating = float(avg_rating) if avg_rating else None
+            metrics.helpful_rate = float(helpful_rate) if helpful_rate else None
+            
+            self.db.commit()
+        except Exception as e:
+            logger.error(f"Error updating training metrics: {str(e)}", exc_info=True)
+            self.db.rollback()
+    
+    def auto_train_from_all_conversations(self) -> Dict[str, Any]:
+        """Automatically train from all conversations - self-learning method"""
+        try:
+            logger.info("Starting automatic self-training from all conversations...")
+            
+            # Get all conversations that haven't been processed for learning
+            # Process conversations from last 30 days by default
+            cutoff_date = datetime.utcnow() - timedelta(days=30)
+            conversations = self.db.query(AIConversation).filter(
+                AIConversation.created_at >= cutoff_date
+            ).order_by(desc(AIConversation.created_at)).all()
+            
+            trained_patterns = 0
+            created_knowledge = 0
+            improved_patterns = 0
+            analyzed_conversations = 0
+            
+            for conv in conversations:
+                analyzed_conversations += 1
+                
+                # Always learn from conversations (even without explicit feedback)
+                # The AI learns from patterns in successful responses
+                if conv.is_helpful is not False:  # Learn from helpful or neutral conversations
+                    # Extract and save knowledge automatically
+                    self._auto_extract_knowledge(conv)
+                    created_knowledge += 1
+                
+                # Learn patterns from all conversations
+                self._learn_from_conversation(conv)
+                trained_patterns += 1
+            
+            # Auto-optimize patterns based on usage and success
+            improved_patterns = self._auto_optimize_patterns()
+            
+            # Auto-merge similar patterns
+            merged = self._auto_merge_similar_patterns()
+            
+            # Update metrics
+            self._update_training_metrics()
+            
+            logger.info(f"Auto-training completed: {analyzed_conversations} conversations analyzed, "
+                       f"{trained_patterns} patterns trained, {created_knowledge} knowledge entries created, "
+                       f"{improved_patterns} patterns improved, {merged} patterns merged")
+            
+            return {
+                "status": "success",
+                "conversations_analyzed": analyzed_conversations,
+                "patterns_trained": trained_patterns,
+                "knowledge_entries_created": created_knowledge,
+                "patterns_improved": improved_patterns,
+                "patterns_merged": merged,
+                "timestamp": datetime.utcnow().isoformat()
+            }
+        except Exception as e:
+            logger.error(f"Error in auto-training: {str(e)}", exc_info=True)
+            self.db.rollback()
+            return {"status": "error", "error": str(e)}
+    
+    def _auto_extract_knowledge(self, conversation: AIConversation):
+        """Automatically extract knowledge from conversations"""
+        try:
+            # Check if similar knowledge already exists
+            keywords = self._extract_keywords(conversation.user_query)
+            existing = self.db.query(AIKnowledgeEntry).filter(
+                and_(
+                    AIKnowledgeEntry.question.ilike(f"%{conversation.user_query[:50]}%"),
+                    or_(
+                        AIKnowledgeEntry.user_role == conversation.user_role,
+                        AIKnowledgeEntry.user_role.is_(None)
+                    )
+                )
+            ).first()
+            
+            if not existing:
+                # Create new knowledge entry (only for helpful or neutral conversations)
+                # Don't learn from explicitly unhelpful responses
+                if conversation.is_helpful is not False:
+                    knowledge = AIKnowledgeEntry(
+                        topic=self._extract_topic(conversation.user_query),
+                        question=conversation.user_query,
+                        answer=conversation.ai_response,
+                        keywords=keywords,
+                        related_intent=conversation.intent,
+                        source='auto_learned',
+                        confidence=60.0 if conversation.is_helpful is True else 50.0,
+                        user_role=conversation.user_role,
+                        is_verified=False  # Auto-learned entries need verification
+                    )
+                    self.db.add(knowledge)
+            else:
+                # Update existing knowledge if this response is better
+                # Increase confidence if response is marked as helpful
+                existing.usage_count += 1
+                if conversation.is_helpful is True:
+                    existing.confidence = min(100.0, existing.confidence + 5.0)
+                    existing.success_count += 1
+                    # Update answer if confidence is high enough
+                    if existing.confidence >= 80.0:
+                        existing.answer = conversation.ai_response
+                        existing.updated_at = datetime.utcnow()
+                elif conversation.is_helpful is False:
+                    existing.confidence = max(20.0, existing.confidence - 3.0)
+                else:
+                    # Neutral - slight increase
+                    existing.confidence = min(100.0, existing.confidence + 1.0)
+                    existing.success_count += 1
+                
+                existing.last_used_at = datetime.utcnow()
+            
+            # Don't commit here - let the caller commit
+        except Exception as e:
+            logger.error(f"Error auto-extracting knowledge: {str(e)}", exc_info=True)
+            # Don't rollback here - let the caller handle it
+    
+    def _auto_optimize_patterns(self) -> int:
+        """Automatically optimize patterns based on performance"""
+        try:
+            improved = 0
+            
+            # Get all active patterns
+            patterns = self.db.query(AILearnedPattern).filter(
+                AILearnedPattern.is_active == True
+            ).all()
+            
+            for pattern in patterns:
+                # Calculate success rate
+                if pattern.usage_count > 0:
+                    success_rate = (pattern.success_count / pattern.usage_count) * 100
+                    
+                    # Adjust confidence based on success rate
+                    if success_rate >= 80:
+                        # High success rate - increase confidence
+                        pattern.confidence_score = min(100.0, pattern.confidence_score + 1.0)
+                        improved += 1
+                    elif success_rate < 50 and pattern.usage_count >= 5:
+                        # Low success rate - decrease confidence or deactivate
+                        pattern.confidence_score = max(0.0, pattern.confidence_score - 2.0)
+                        if pattern.confidence_score < 30:
+                            pattern.is_active = False
+                            logger.info(f"Deactivated low-performing pattern {pattern.id}")
+                        improved += 1
+                    
+                    # Update last used timestamp
+                    pattern.updated_at = datetime.utcnow()
+            
+            self.db.commit()
+            return improved
+        except Exception as e:
+            logger.error(f"Error optimizing patterns: {str(e)}", exc_info=True)
+            self.db.rollback()
+            return 0
+    
+    def _auto_merge_similar_patterns(self) -> int:
+        """Automatically merge similar patterns to reduce redundancy"""
+        try:
+            merged = 0
+            
+            # Get patterns with same intent and role
+            patterns_by_intent = {}
+            all_patterns = self.db.query(AILearnedPattern).filter(
+                AILearnedPattern.is_active == True
+            ).all()
+            
+            for pattern in all_patterns:
+                key = (pattern.intent, pattern.user_role)
+                if key not in patterns_by_intent:
+                    patterns_by_intent[key] = []
+                patterns_by_intent[key].append(pattern)
+            
+            # Merge similar patterns within each intent group
+            for (intent, role), patterns in patterns_by_intent.items():
+                if len(patterns) < 2:
+                    continue
+                
+                # Sort by confidence and usage
+                patterns.sort(key=lambda p: (p.confidence_score, p.usage_count), reverse=True)
+                
+                # Keep the best pattern and merge others into it
+                best_pattern = patterns[0]
+                for pattern in patterns[1:]:
+                    # Check if patterns are similar (same keywords or similar query pattern)
+                    best_keywords = set(json.loads(best_pattern.pattern_keywords) if best_pattern.pattern_keywords else [])
+                    pattern_keywords = set(json.loads(pattern.pattern_keywords) if pattern.pattern_keywords else [])
+                    
+                    # If 70% keywords overlap, merge them
+                    if best_keywords and pattern_keywords:
+                        overlap = len(best_keywords & pattern_keywords) / len(best_keywords | pattern_keywords)
+                        if overlap >= 0.7:
+                            # Merge: combine usage counts and update confidence
+                            best_pattern.usage_count += pattern.usage_count
+                            best_pattern.success_count += pattern.success_count
+                            best_pattern.confidence_score = (
+                                (best_pattern.confidence_score * best_pattern.usage_count + 
+                                 pattern.confidence_score * pattern.usage_count) / 
+                                (best_pattern.usage_count + pattern.usage_count)
+                            )
+                            
+                            # Deactivate the merged pattern
+                            pattern.is_active = False
+                            merged += 1
+                            logger.info(f"Merged pattern {pattern.id} into {best_pattern.id}")
+            
+            self.db.commit()
+            return merged
+        except Exception as e:
+            logger.error(f"Error merging patterns: {str(e)}", exc_info=True)
+            self.db.rollback()
+            return 0
+    
+    def auto_analyze_and_improve(self) -> Dict[str, Any]:
+        """Automatically analyze performance and improve - self-improvement method"""
+        try:
+            logger.info("Starting automatic self-analysis and improvement...")
+            
+            # Analyze conversation quality
+            recent_conversations = self.db.query(AIConversation).filter(
+                AIConversation.created_at >= datetime.utcnow() - timedelta(days=7)
+            ).all()
+            
+            # Find patterns in successful vs unsuccessful conversations
+            successful_queries = []
+            unsuccessful_queries = []
+            
+            for conv in recent_conversations:
+                if conv.is_helpful is True:
+                    successful_queries.append(conv.user_query)
+                elif conv.is_helpful is False:
+                    unsuccessful_queries.append(conv.user_query)
+            
+            # Extract common patterns from successful queries
+            if successful_queries:
+                common_success_keywords = self._find_common_keywords(successful_queries)
+                logger.info(f"Common keywords in successful queries: {common_success_keywords[:10]}")
+            
+            # Identify problematic patterns
+            if unsuccessful_queries:
+                common_failure_keywords = self._find_common_keywords(unsuccessful_queries)
+                logger.info(f"Common keywords in unsuccessful queries: {common_failure_keywords[:10]}")
+            
+            # Improve knowledge entries based on usage
+            improved_knowledge = self._improve_knowledge_entries()
+            
+            # Clean up old inactive patterns
+            cleaned = self._cleanup_old_patterns()
+            
+            # Update metrics
+            self._update_training_metrics()
+            
+            return {
+                "status": "success",
+                "knowledge_entries_improved": improved_knowledge,
+                "old_patterns_cleaned": cleaned,
+                "timestamp": datetime.utcnow().isoformat()
+            }
+        except Exception as e:
+            logger.error(f"Error in auto-analysis: {str(e)}", exc_info=True)
+            return {"status": "error", "error": str(e)}
+    
+    def _find_common_keywords(self, queries: List[str]) -> List[str]:
+        """Find common keywords across multiple queries"""
+        all_keywords = []
+        for query in queries:
+            keywords = self._extract_keywords(query)
+            all_keywords.extend(keywords)
+        
+        # Count frequency
+        keyword_freq = Counter(all_keywords)
+        return [word for word, _ in keyword_freq.most_common(20)]
+    
+    def _improve_knowledge_entries(self) -> int:
+        """Improve knowledge entries based on usage statistics"""
+        try:
+            improved = 0
+            
+            # Get knowledge entries with usage data
+            entries = self.db.query(AIKnowledgeEntry).filter(
+                AIKnowledgeEntry.usage_count > 0
+            ).all()
+            
+            for entry in entries:
+                # Calculate success rate
+                if entry.usage_count > 0:
+                    success_rate = (entry.success_count / entry.usage_count) * 100
+                    
+                    # Auto-verify entries with high success rate
+                    if success_rate >= 85 and entry.usage_count >= 5 and not entry.is_verified:
+                        entry.is_verified = True
+                        entry.confidence = min(100.0, entry.confidence + 10.0)
+                        improved += 1
+                        logger.info(f"Auto-verified knowledge entry {entry.id} (success rate: {success_rate:.1f}%)")
+                    
+                    # Increase confidence for successful entries
+                    elif success_rate >= 70:
+                        entry.confidence = min(100.0, entry.confidence + 2.0)
+                        improved += 1
+                    
+                    # Decrease confidence for unsuccessful entries
+                    elif success_rate < 40 and entry.usage_count >= 3:
+                        entry.confidence = max(20.0, entry.confidence - 5.0)
+                        improved += 1
+            
+            self.db.commit()
+            return improved
+        except Exception as e:
+            logger.error(f"Error improving knowledge entries: {str(e)}", exc_info=True)
+            self.db.rollback()
+            return 0
+    
+    def _cleanup_old_patterns(self) -> int:
+        """Clean up old inactive or low-performing patterns"""
+        try:
+            cutoff_date = datetime.utcnow() - timedelta(days=90)
+            
+            # Find patterns that haven't been used in 90 days and have low confidence
+            old_patterns = self.db.query(AILearnedPattern).filter(
+                and_(
+                    or_(
+                        AILearnedPattern.last_used_at < cutoff_date,
+                        AILearnedPattern.last_used_at.is_(None)
+                    ),
+                    AILearnedPattern.confidence_score < 40.0,
+                    AILearnedPattern.is_active == True
+                )
+            ).all()
+            
+            cleaned = 0
+            for pattern in old_patterns:
+                pattern.is_active = False
+                cleaned += 1
+            
+            self.db.commit()
+            logger.info(f"Cleaned up {cleaned} old inactive patterns")
+            return cleaned
+        except Exception as e:
+            logger.error(f"Error cleaning up patterns: {str(e)}", exc_info=True)
+            self.db.rollback()
+            return 0
+

Backend/src/ai/services/ai_role_access_service.py

@@ -0,0 +1,383 @@
+"""
+Enterprise Role-Based Access Control Service for AI Assistant
+Filters and controls data access based on user roles
+"""
+
+from typing import Dict, List, Optional, Any
+from datetime import datetime, timedelta
+from sqlalchemy.orm import Session, joinedload
+from sqlalchemy import and_, or_, func
+import logging
+
+from ...auth.models.user import User
+from ...auth.models.role import Role
+from ...bookings.models.booking import Booking, BookingStatus
+from ...payments.models.invoice import Invoice
+from ...payments.models.payment import Payment, PaymentStatus
+from ...rooms.models.room import Room, RoomStatus
+from ...shared.config.logging_config import get_logger
+
+logger = get_logger(__name__)
+
+
+class AIRoleAccessService:
+    """Role-based data access control for AI Assistant"""
+    
+    def __init__(self, db: Session, current_user: User):
+        self.db = db
+        self.current_user = current_user
+        
+        # Load user role - try from relationship first, then query
+        self.user_role = None
+        if hasattr(current_user, 'role') and current_user.role:
+            self.user_role = current_user.role
+        
+        if not self.user_role:
+            self.user_role = db.query(Role).filter(Role.id == current_user.role_id).first()
+        
+        if not self.user_role:
+            # Fallback to customer role if not found
+            logger.warning(f"Role not found for user {current_user.id}, defaulting to customer")
+            self.user_role = db.query(Role).filter(Role.name == 'customer').first()
+        
+        self.role_name = self.user_role.name.lower() if self.user_role else "customer"
+    
+    def get_user_bookings(self, limit: int = 10) -> List[Dict[str, Any]]:
+        """Get bookings based on role permissions"""
+        if self.role_name in ["admin", "staff"]:
+            # Admin and staff can see all bookings
+            bookings = self.db.query(Booking).options(
+                joinedload(Booking.user),
+                joinedload(Booking.room).joinedload(Room.room_type)
+            ).order_by(Booking.created_at.desc()).limit(limit).all()
+        elif self.role_name == "accountant":
+            # Accountant can see all bookings (for invoicing purposes)
+            bookings = self.db.query(Booking).options(
+                joinedload(Booking.user),
+                joinedload(Booking.room).joinedload(Room.room_type)
+            ).order_by(Booking.created_at.desc()).limit(limit).all()
+        else:
+            # Customers can only see their own bookings
+            bookings = self.db.query(Booking).options(
+                joinedload(Booking.user),
+                joinedload(Booking.room).joinedload(Room.room_type)
+            ).filter(Booking.user_id == self.current_user.id).order_by(
+                Booking.created_at.desc()
+            ).limit(limit).all()
+        
+        result = []
+        for booking in bookings:
+            booking_dict = {
+                "booking_number": booking.booking_number,
+                "status": booking.status.value if hasattr(booking.status, 'value') else str(booking.status),
+                "check_in": booking.check_in_date.isoformat(),
+                "check_out": booking.check_out_date.isoformat(),
+                "num_guests": booking.num_guests,
+                "total_price": float(booking.total_price) if booking.total_price else 0,
+            }
+            
+            # Add user info based on role
+            if self.role_name in ["admin", "staff", "accountant"]:
+                booking_dict["guest_name"] = booking.user.full_name if booking.user else "Unknown"
+                booking_dict["guest_email"] = booking.user.email if booking.user else None
+            else:
+                booking_dict["guest_name"] = "Your booking"
+            
+            # Add room info
+            if booking.room:
+                booking_dict["room_number"] = booking.room.room_number
+                if booking.room.room_type:
+                    booking_dict["room_type"] = booking.room.room_type.name
+            
+            result.append(booking_dict)
+        
+        return result
+    
+    def get_user_invoices(self, limit: int = 10) -> List[Dict[str, Any]]:
+        """Get invoices based on role permissions"""
+        if self.role_name in ["admin", "accountant"]:
+            # Admin and accountant can see all invoices
+            invoices = self.db.query(Invoice).options(
+                joinedload(Invoice.user),
+                joinedload(Invoice.booking)
+            ).order_by(Invoice.created_at.desc()).limit(limit).all()
+        elif self.role_name == "staff":
+            # Staff can view invoices but not edit
+            invoices = self.db.query(Invoice).options(
+                joinedload(Invoice.user),
+                joinedload(Invoice.booking)
+            ).order_by(Invoice.created_at.desc()).limit(limit).all()
+        else:
+            # Customers can only see their own invoices
+            invoices = self.db.query(Invoice).options(
+                joinedload(Invoice.user),
+                joinedload(Invoice.booking)
+            ).filter(Invoice.user_id == self.current_user.id).order_by(
+                Invoice.created_at.desc()
+            ).limit(limit).all()
+        
+        result = []
+        for invoice in invoices:
+            invoice_dict = {
+                "invoice_number": invoice.invoice_number,
+                "status": invoice.status.value if hasattr(invoice.status, 'value') else str(invoice.status),
+                "total_amount": float(invoice.total_amount) if invoice.total_amount else 0,
+                "balance_due": float(invoice.balance_due) if invoice.balance_due else 0,
+                "due_date": invoice.due_date.isoformat() if invoice.due_date else None,
+                "paid_date": invoice.paid_date.isoformat() if invoice.paid_date else None,
+            }
+            
+            # Add user info based on role
+            if self.role_name in ["admin", "staff", "accountant"]:
+                invoice_dict["customer_name"] = invoice.customer_name if hasattr(invoice, 'customer_name') else (
+                    invoice.user.full_name if invoice.user else "Unknown"
+                )
+                invoice_dict["customer_email"] = invoice.customer_email if hasattr(invoice, 'customer_email') else (
+                    invoice.user.email if invoice.user else None
+                )
+            else:
+                invoice_dict["customer_name"] = "Your invoice"
+            
+            if invoice.booking:
+                invoice_dict["booking_number"] = invoice.booking.booking_number
+            
+            result.append(invoice_dict)
+        
+        return result
+    
+    def get_user_payments(self, limit: Optional[int] = 10) -> List[Dict[str, Any]]:
+        """Get payments based on role permissions"""
+        if self.role_name in ["admin", "accountant"]:
+            # Admin and accountant can see all payments
+            query = self.db.query(Payment).options(
+                joinedload(Payment.booking).joinedload(Booking.user)
+            ).order_by(Payment.created_at.desc())
+            if limit:
+                payments = query.limit(limit).all()
+            else:
+                payments = query.all()
+        elif self.role_name == "staff":
+            # Staff can see payment status but limited details
+            query = self.db.query(Payment).options(
+                joinedload(Payment.booking).joinedload(Booking.user)
+            ).order_by(Payment.created_at.desc())
+            if limit:
+                payments = query.limit(limit).all()
+            else:
+                payments = query.all()
+        else:
+            # Customers can only see their own payments
+            query = self.db.query(Payment).options(
+                joinedload(Payment.booking)
+            ).join(Booking).filter(Booking.user_id == self.current_user.id).order_by(
+                Payment.created_at.desc()
+            )
+            if limit:
+                payments = query.limit(limit).all()
+            else:
+                payments = query.all()
+        
+        result = []
+        for payment in payments:
+            payment_type = payment.payment_type.value if hasattr(payment.payment_type, 'value') else str(payment.payment_type)
+            
+            # Format payment type with deposit percentage if available
+            if payment_type == 'deposit' and payment.deposit_percentage:
+                payment_type_display = f"Deposit ({payment.deposit_percentage}%)"
+            elif payment_type == 'deposit':
+                payment_type_display = "Deposit (20%)"  # Default
+            elif payment_type == 'full':
+                payment_type_display = "Full Payment"
+            elif payment_type == 'remaining':
+                payment_type_display = "Remaining"
+            else:
+                payment_type_display = payment_type
+            
+            payment_dict = {
+                "id": payment.id,
+                "amount": float(payment.amount) if payment.amount else 0,
+                "payment_method": payment.payment_method.value if hasattr(payment.payment_method, 'value') else str(payment.payment_method),
+                "payment_type": payment_type,
+                "payment_type_display": payment_type_display,
+                "payment_status": payment.payment_status.value if hasattr(payment.payment_status, 'value') else str(payment.payment_status),
+                "payment_date": payment.payment_date.isoformat() if payment.payment_date else None,
+                "transaction_id": payment.transaction_id or f"PAY-{payment.id}",
+                "deposit_percentage": payment.deposit_percentage,
+            }
+            
+            if payment.booking:
+                payment_dict["booking_number"] = payment.booking.booking_number
+                
+                # Add user info based on role
+                if self.role_name in ["admin", "staff", "accountant"] and payment.booking.user:
+                    payment_dict["customer_name"] = payment.booking.user.full_name
+                    payment_dict["customer_email"] = payment.booking.user.email
+                else:
+                    payment_dict["customer_name"] = "Your payment"
+            
+            result.append(payment_dict)
+        
+        return result
+    
+    def get_all_payments(self) -> List[Dict[str, Any]]:
+        """Get all payments without limit - for admin and accountant only"""
+        if self.role_name not in ["admin", "accountant"]:
+            return []
+        return self.get_user_payments(limit=None)
+    
+    def get_room_status_summary(self) -> Dict[str, Any]:
+        """Get room status summary based on role permissions"""
+        total_rooms = self.db.query(Room).count()
+        available_rooms = self.db.query(Room).filter(Room.status == RoomStatus.available).count()
+        occupied_rooms = self.db.query(Room).filter(Room.status == RoomStatus.occupied).count()
+        
+        result = {
+            "total_rooms": total_rooms,
+            "available": available_rooms,
+            "occupied": occupied_rooms,
+        }
+        
+        # Additional details for admin/staff
+        if self.role_name in ["admin", "staff"]:
+            maintenance_rooms = self.db.query(Room).filter(Room.status == RoomStatus.maintenance).count()
+            cleaning_rooms = self.db.query(Room).filter(Room.status == RoomStatus.cleaning).count()
+            
+            today = datetime.utcnow().date()
+            rooms_with_bookings = self.db.query(Booking).filter(
+                and_(
+                    Booking.status != BookingStatus.cancelled,
+                    Booking.check_in_date <= today,
+                    Booking.check_out_date > today
+                )
+            ).count()
+            
+            result.update({
+                "maintenance": maintenance_rooms,
+                "cleaning": cleaning_rooms,
+                "rooms_with_active_bookings": rooms_with_bookings,
+                "occupancy_rate": round((occupied_rooms / total_rooms * 100) if total_rooms > 0 else 0, 2)
+            })
+        else:
+            # Customers get simplified room availability info
+            result["occupancy_rate"] = round((occupied_rooms / total_rooms * 100) if total_rooms > 0 else 0, 2)
+        
+        return result
+    
+    def get_payment_summary(self, days: int = 30) -> Optional[Dict[str, Any]]:
+        """Get payment summary - only for admin, accountant, and staff"""
+        if self.role_name not in ["admin", "accountant", "staff"]:
+            return None  # Customers cannot access payment summaries
+        
+        today = datetime.utcnow().date()
+        start_date = today - timedelta(days=days)
+        
+        # Total payments in period
+        total_payments = self.db.query(func.sum(Payment.amount)).filter(
+            and_(
+                Payment.payment_status == PaymentStatus.completed,
+                func.date(Payment.payment_date) >= start_date,
+                func.date(Payment.payment_date) <= today
+            )
+        ).scalar() or 0
+        
+        # Pending payments
+        pending_payments = self.db.query(func.sum(Payment.amount)).filter(
+            Payment.payment_status == PaymentStatus.pending
+        ).scalar() or 0
+        
+        # Payment count
+        completed_count = self.db.query(Payment).filter(
+            and_(
+                Payment.payment_status == PaymentStatus.completed,
+                func.date(Payment.payment_date) >= start_date
+            )
+        ).count()
+        
+        result = {
+            "total_revenue": float(total_payments),
+            "pending_amount": float(pending_payments),
+            "completed_payments": completed_count,
+            "period_days": days
+        }
+        
+        # Additional details for admin and accountant
+        if self.role_name in ["admin", "accountant"]:
+            failed_count = self.db.query(Payment).filter(
+                Payment.payment_status == PaymentStatus.failed
+            ).count()
+            result["failed_payments"] = failed_count
+        
+        return result
+    
+    def get_invoice_summary(self) -> Optional[Dict[str, Any]]:
+        """Get invoice summary - only for admin, accountant, and staff"""
+        if self.role_name not in ["admin", "accountant", "staff"]:
+            return None  # Customers cannot access invoice summaries
+        
+        total_invoices = self.db.query(Invoice).count()
+        
+        # Group by status
+        status_counts = {}
+        invoices = self.db.query(Invoice).all()
+        for invoice in invoices:
+            status = invoice.status.value if hasattr(invoice.status, 'value') else str(invoice.status)
+            status_counts[status] = status_counts.get(status, 0) + 1
+        
+        # Overdue invoices
+        today = datetime.utcnow().date()
+        overdue_count = self.db.query(Invoice).filter(
+            and_(
+                Invoice.due_date < today,
+                Invoice.status != 'paid'
+            )
+        ).count()
+        
+        result = {
+            "total_invoices": total_invoices,
+            "status_breakdown": status_counts,
+            "overdue_invoices": overdue_count
+        }
+        
+        return result
+    
+    def can_access_feature(self, feature: str) -> bool:
+        """Check if current user can access a feature"""
+        if self.role_name == "admin":
+            return True
+        
+        feature_lower = feature.lower()
+        
+        # Define feature access rules
+        if feature_lower in ["payment_summary", "invoice_summary", "financial_reports"]:
+            return self.role_name in ["admin", "accountant", "staff"]
+        
+        if feature_lower in ["all_bookings", "all_users", "system_settings"]:
+            return self.role_name == "admin"
+        
+        if feature_lower in ["operational_reports", "room_management", "maintenance"]:
+            return self.role_name in ["admin", "staff"]
+        
+        # Default: allow if it's user's own data
+        return True
+    
+    def filter_sensitive_data(self, data: Dict[str, Any], data_type: str) -> Dict[str, Any]:
+        """Filter sensitive data based on role"""
+        if self.role_name == "admin":
+            return data  # Admin sees everything
+        
+        filtered = data.copy()
+        
+        # Remove sensitive financial data for staff
+        if self.role_name == "staff" and data_type in ["payment", "invoice"]:
+            if "transaction_id" in filtered:
+                filtered["transaction_id"] = "***" if filtered.get("transaction_id") else None
+            if "payment_method_details" in filtered:
+                del filtered["payment_method_details"]
+        
+        # Remove other users' personal info for non-admin roles
+        if self.role_name != "admin" and data_type in ["booking", "invoice", "payment"]:
+            # Only show own data, not other users' details
+            pass  # This is handled at query level
+        
+        return filtered
+

Backend/src/ai/services/ai_training_scheduler.py

@@ -0,0 +1,171 @@
+"""
+AI Training Scheduler - Automatic background training for AI self-learning
+Runs periodic training tasks to improve AI performance autonomously
+"""
+
+import threading
+import time
+from datetime import datetime, timedelta
+from typing import Optional
+from sqlalchemy.orm import Session
+import logging
+
+from ...shared.config.database import get_db
+from ...shared.config.logging_config import get_logger
+from .ai_learning_service import AILearningService
+
+logger = get_logger(__name__)
+
+
+class AITrainingScheduler:
+    """Background scheduler for automatic AI training"""
+    
+    def __init__(self):
+        self.running = False
+        self.thread: Optional[threading.Thread] = None
+        self.training_interval_hours = 6  # Train every 6 hours
+        self.analysis_interval_hours = 24  # Analyze every 24 hours
+        self.last_training_time: Optional[datetime] = None
+        self.last_analysis_time: Optional[datetime] = None
+    
+    def start(self):
+        """Start the background training scheduler"""
+        if self.running:
+            logger.warning("AI Training Scheduler is already running")
+            return
+        
+        self.running = True
+        self.thread = threading.Thread(target=self._scheduler_loop, daemon=True)
+        self.thread.start()
+        logger.info("AI Training Scheduler started - automatic self-learning enabled")
+    
+    def stop(self):
+        """Stop the background training scheduler"""
+        if not self.running:
+            return
+        
+        self.running = False
+        if self.thread:
+            self.thread.join(timeout=5.0)
+        logger.info("AI Training Scheduler stopped")
+    
+    def _scheduler_loop(self):
+        """Main scheduler loop that runs training tasks periodically"""
+        logger.info("AI Training Scheduler loop started")
+        
+        # Run initial training after 1 minute (to let app fully start)
+        time.sleep(60)
+        
+        while self.running:
+            try:
+                current_time = datetime.utcnow()
+                
+                # Check if it's time for training
+                should_train = False
+                if self.last_training_time is None:
+                    should_train = True
+                else:
+                    time_since_training = current_time - self.last_training_time
+                    if time_since_training >= timedelta(hours=self.training_interval_hours):
+                        should_train = True
+                
+                if should_train:
+                    logger.info("Starting scheduled automatic training...")
+                    self._run_training()
+                    self.last_training_time = current_time
+                
+                # Check if it's time for analysis
+                should_analyze = False
+                if self.last_analysis_time is None:
+                    should_analyze = True
+                else:
+                    time_since_analysis = current_time - self.last_analysis_time
+                    if time_since_analysis >= timedelta(hours=self.analysis_interval_hours):
+                        should_analyze = True
+                
+                if should_analyze:
+                    logger.info("Starting scheduled automatic analysis...")
+                    self._run_analysis()
+                    self.last_analysis_time = current_time
+                
+                # Sleep for 1 hour before checking again
+                time.sleep(3600)
+                
+            except Exception as e:
+                logger.error(f"Error in scheduler loop: {str(e)}", exc_info=True)
+                # Sleep for 10 minutes before retrying on error
+                time.sleep(600)
+    
+    def _run_training(self):
+        """Run automatic training from conversations"""
+        try:
+            # Get database session
+            db_gen = get_db()
+            db = next(db_gen)
+            
+            try:
+                learning_service = AILearningService(db)
+                result = learning_service.auto_train_from_all_conversations()
+                
+                if result.get("status") == "success":
+                    logger.info(
+                        f"Automatic training completed: "
+                        f"{result.get('conversations_analyzed', 0)} conversations analyzed, "
+                        f"{result.get('patterns_trained', 0)} patterns trained, "
+                        f"{result.get('knowledge_entries_created', 0)} knowledge entries created"
+                    )
+                else:
+                    logger.warning(f"Training completed with errors: {result.get('error', 'Unknown error')}")
+            finally:
+                db.close()
+        except Exception as e:
+            logger.error(f"Error running automatic training: {str(e)}", exc_info=True)
+    
+    def _run_analysis(self):
+        """Run automatic analysis and improvement"""
+        try:
+            # Get database session
+            db_gen = get_db()
+            db = next(db_gen)
+            
+            try:
+                learning_service = AILearningService(db)
+                result = learning_service.auto_analyze_and_improve()
+                
+                if result.get("status") == "success":
+                    logger.info(
+                        f"Automatic analysis completed: "
+                        f"{result.get('knowledge_entries_improved', 0)} knowledge entries improved, "
+                        f"{result.get('old_patterns_cleaned', 0)} old patterns cleaned"
+                    )
+                else:
+                    logger.warning(f"Analysis completed with errors: {result.get('error', 'Unknown error')}")
+            finally:
+                db.close()
+        except Exception as e:
+            logger.error(f"Error running automatic analysis: {str(e)}", exc_info=True)
+    
+    def trigger_manual_training(self):
+        """Manually trigger training (for testing or on-demand training)"""
+        logger.info("Manual training triggered")
+        self._run_training()
+        self.last_training_time = datetime.utcnow()
+    
+    def trigger_manual_analysis(self):
+        """Manually trigger analysis (for testing or on-demand analysis)"""
+        logger.info("Manual analysis triggered")
+        self._run_analysis()
+        self.last_analysis_time = datetime.utcnow()
+
+
+# Global scheduler instance
+_global_scheduler: Optional[AITrainingScheduler] = None
+
+
+def get_training_scheduler() -> AITrainingScheduler:
+    """Get or create the global training scheduler instance"""
+    global _global_scheduler
+    if _global_scheduler is None:
+        _global_scheduler = AITrainingScheduler()
+    return _global_scheduler
+

Backend/src/analytics/models/audit_log.py

@@ -1,7 +1,7 @@
 from sqlalchemy import Column, Integer, String, Text, DateTime, ForeignKey, JSON
 from sqlalchemy.orm import relationship
 from datetime import datetime
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class AuditLog(Base):
     __tablename__ = 'audit_logs'

Backend/src/analytics/routes/analytics_routes.py

@@ -1,9 +1,9 @@
 from fastapi import APIRouter, Depends, HTTPException, Query
 from sqlalchemy.orm import Session
 from typing import Optional
-from ..config.database import get_db
-from ..middleware.auth import authorize_roles, get_current_user
-from ..models.user import User
+from ...shared.config.database import get_db
+from ...security.middleware.auth import authorize_roles, get_current_user
+from ...auth.models.user import User
 from ..services.analytics_service import AnalyticsService
 
 router = APIRouter(prefix='/analytics', tags=['analytics'])

Backend/src/analytics/routes/audit_routes.py

@@ -3,9 +3,9 @@ from sqlalchemy.orm import Session
 from sqlalchemy import desc, or_, func
 from typing import Optional
 from datetime import datetime
-from ..config.database import get_db
-from ..middleware.auth import get_current_user, authorize_roles
-from ..models.user import User
+from ...shared.config.database import get_db
+from ...security.middleware.auth import get_current_user, authorize_roles
+from ...auth.models.user import User
 from ..models.audit_log import AuditLog
 router = APIRouter(prefix='/audit-logs', tags=['audit-logs'])
 

Backend/src/analytics/routes/report_routes.py

@@ -3,15 +3,15 @@ from sqlalchemy.orm import Session, load_only, joinedload
 from sqlalchemy import func, and_
 from typing import Optional
 from datetime import datetime, timedelta
-from ..config.database import get_db
-from ..middleware.auth import get_current_user, authorize_roles
-from ..models.user import User
-from ..models.booking import Booking, BookingStatus
-from ..models.payment import Payment, PaymentStatus
-from ..models.room import Room, RoomStatus
-from ..models.service_usage import ServiceUsage
-from ..models.service import Service
-from ..utils.response_helpers import success_response
+from ...shared.config.database import get_db
+from ...security.middleware.auth import get_current_user, authorize_roles
+from ...auth.models.user import User
+from ...bookings.models.booking import Booking, BookingStatus
+from ...payments.models.payment import Payment, PaymentStatus
+from ...rooms.models.room import Room, RoomStatus
+from ...hotel_services.models.service_usage import ServiceUsage
+from ...hotel_services.models.service import Service
+from ...shared.utils.response_helpers import success_response
 router = APIRouter(prefix='/reports', tags=['reports'])
 
 @router.get('')

Backend/src/analytics/services/analytics_service.py

@@ -2,15 +2,15 @@ from sqlalchemy.orm import Session, load_only
 from sqlalchemy import func, and_, or_, case, extract, distinct
 from typing import Optional, Dict, List, Any
 from datetime import datetime, timedelta, date
-from ..models.booking import Booking, BookingStatus
-from ..models.payment import Payment, PaymentStatus, PaymentMethod
-from ..models.room import Room, RoomStatus
-from ..models.room_type import RoomType
-from ..models.user import User
-from ..models.service_usage import ServiceUsage
-from ..models.service import Service
-from ..models.review import Review, ReviewStatus
-from ..models.invoice import Invoice
+from ...bookings.models.booking import Booking, BookingStatus
+from ...payments.models.payment import Payment, PaymentStatus, PaymentMethod
+from ...rooms.models.room import Room, RoomStatus
+from ...rooms.models.room_type import RoomType
+from ...auth.models.user import User
+from ...hotel_services.models.service_usage import ServiceUsage
+from ...hotel_services.models.service import Service
+from ...reviews.models.review import Review, ReviewStatus
+from ...payments.models.invoice import Invoice
 import logging
 
 logger = logging.getLogger(__name__)
@@ -290,7 +290,7 @@ class AnalyticsService:
             start_date = end_date - timedelta(days=30)
         
         # Get staff users
-        from ..models.role import Role
+        from ...auth.models.role import Role
         staff_users = db.query(User).join(Role, User.role_id == Role.id).filter(
             or_(Role.name == 'staff', Role.name == 'admin')
         ).all()

Backend/src/analytics/services/audit_service.py

@@ -2,7 +2,7 @@ from sqlalchemy.orm import Session
 from typing import Optional, Dict, Any
 from datetime import datetime
 from ..models.audit_log import AuditLog
-from ..config.logging_config import get_logger
+from ...shared.config.logging_config import get_logger
 logger = get_logger(__name__)
 
 class AuditService:

Backend/src/auth/models/password_reset_token.py

@@ -1,7 +1,7 @@
 from sqlalchemy import Column, Integer, String, DateTime, Boolean, ForeignKey
 from sqlalchemy.orm import relationship
 from datetime import datetime
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class PasswordResetToken(Base):
     __tablename__ = 'password_reset_tokens'

Backend/src/auth/models/refresh_token.py

@@ -1,7 +1,7 @@
 from sqlalchemy import Column, Integer, String, DateTime, ForeignKey
 from sqlalchemy.orm import relationship
 from datetime import datetime
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class RefreshToken(Base):
     __tablename__ = 'refresh_tokens'

Backend/src/auth/models/role.py

@@ -1,7 +1,7 @@
 from sqlalchemy import Column, Integer, String, DateTime
 from sqlalchemy.orm import relationship
 from datetime import datetime
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class Role(Base):
     __tablename__ = 'roles'

Backend/src/auth/models/user.py

@@ -1,7 +1,7 @@
 from sqlalchemy import Column, Integer, String, Boolean, Text, ForeignKey, DateTime, Numeric
 from sqlalchemy.orm import relationship
 from datetime import datetime
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class User(Base):
     __tablename__ = 'users'

Backend/src/auth/routes/auth_routes.py

@@ -5,12 +5,12 @@ from pathlib import Path
 import aiofiles
 import uuid
 import os
-from ..config.database import get_db
+from ...shared.config.database import get_db
 from ..services.auth_service import auth_service
 from ..schemas.auth import RegisterRequest, LoginRequest, RefreshTokenRequest, ForgotPasswordRequest, ResetPasswordRequest, AuthResponse, TokenResponse, MessageResponse, MFAInitResponse, EnableMFARequest, VerifyMFARequest, MFAStatusResponse, UpdateProfileRequest
-from ..middleware.auth import get_current_user
+from ...security.middleware.auth import get_current_user
 from ..models.user import User
-from ..services.audit_service import audit_service
+from ...analytics.services.audit_service import audit_service
 from slowapi import Limiter, _rate_limit_exceeded_handler
 from slowapi.util import get_remote_address
 from slowapi.errors import RateLimitExceeded
@@ -58,7 +58,7 @@ async def register(
     
     try:
         result = await auth_service.register(db=db, name=register_request.name, email=register_request.email, password=register_request.password, phone=register_request.phone)
-        from ..config.settings import settings
+        from ...shared.config.settings import settings
         max_age = 7 * 24 * 60 * 60  # 7 days for registration
         # Use secure cookies in production (HTTPS required)
         # Set access token in httpOnly cookie for security
@@ -144,7 +144,7 @@ async def login(
                     status='success'
                 )
             return {'status': 'success', 'requires_mfa': True, 'user_id': result['user_id']}
-        from ..config.settings import settings
+        from ...shared.config.settings import settings
         max_age = 7 * 24 * 60 * 60 if login_request.rememberMe else 1 * 24 * 60 * 60
         # Use secure cookies in production (HTTPS required)
         # Set access token in httpOnly cookie for security
@@ -215,7 +215,7 @@ async def refresh_token(
         raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail='Refresh token not found')
     try:
         result = await auth_service.refresh_access_token(db, refreshToken)
-        from ..config.settings import settings
+        from ...shared.config.settings import settings
         # Set new access token in httpOnly cookie
         # Use 'lax' in development for cross-origin support, 'strict' in production
         samesite_value = 'strict' if settings.is_production else 'lax'
@@ -250,7 +250,7 @@ async def logout(
         await auth_service.logout(db, refreshToken)
     
     # Delete both access and refresh token cookies
-    from ..config.settings import settings
+    from ...shared.config.settings import settings
     # Use 'lax' in development for cross-origin support, 'strict' in production
     samesite_value = 'strict' if settings.is_production else 'lax'
     response.delete_cookie(key='refreshToken', path='/', secure=settings.is_production, samesite=samesite_value)
@@ -320,7 +320,7 @@ async def reset_password(request: ResetPasswordRequest, db: Session=Depends(get_
             status_code = status.HTTP_404_NOT_FOUND
         raise HTTPException(status_code=status_code, detail=str(e))
 from ..services.mfa_service import mfa_service
-from ..config.settings import settings
+from ...shared.config.settings import settings
 
 @router.get('/mfa/init')
 async def init_mfa(current_user: User=Depends(get_current_user), db: Session=Depends(get_db)):
@@ -380,7 +380,7 @@ async def regenerate_backup_codes(current_user: User=Depends(get_current_user),
 async def upload_avatar(request: Request, image: UploadFile=File(...), current_user: User=Depends(get_current_user), db: Session=Depends(get_db)):
     try:
         # Use comprehensive file validation (magic bytes + size)
-        from ..utils.file_validation import validate_uploaded_image
+        from ...shared.utils.file_validation import validate_uploaded_image
         max_avatar_size = 2 * 1024 * 1024  # 2MB for avatars
         
         # Validate file completely (MIME type, size, magic bytes, integrity)

Backend/src/auth/routes/user_routes.py

@@ -3,14 +3,14 @@ from sqlalchemy.orm import Session
 from sqlalchemy import or_
 from typing import Optional
 import bcrypt
-from ..config.database import get_db
-from ..middleware.auth import get_current_user, authorize_roles
+from ...shared.config.database import get_db
+from ...security.middleware.auth import get_current_user, authorize_roles
 from ..models.user import User
 from ..models.role import Role
-from ..models.booking import Booking, BookingStatus
-from ..utils.role_helpers import can_manage_users
-from ..utils.response_helpers import success_response
-from ..services.audit_service import audit_service
+from ...bookings.models.booking import Booking, BookingStatus
+from ...shared.utils.role_helpers import can_manage_users
+from ...shared.utils.response_helpers import success_response
+from ...analytics.services.audit_service import audit_service
 from ..schemas.user import CreateUserRequest, UpdateUserRequest
 router = APIRouter(prefix='/users', tags=['users'])
 

Backend/src/auth/services/auth_service.py

@@ -11,13 +11,13 @@ from ..models.user import User
 from ..models.refresh_token import RefreshToken
 from ..models.password_reset_token import PasswordResetToken
 from ..models.role import Role
-from ..utils.mailer import send_email
-from ..utils.email_templates import (
+from ...shared.utils.mailer import send_email
+from ...shared.utils.email_templates import (
     welcome_email_template,
     password_reset_email_template,
     password_changed_email_template
 )
-from ..config.settings import settings
+from ...shared.config.settings import settings
 import os
 
 logger = logging.getLogger(__name__)
@@ -116,7 +116,7 @@ class AuthService:
 
     async def register(self, db: Session, name: str, email: str, password: str, phone: Optional[str] = None) -> dict:
         # Validate password strength
-        from ..utils.password_validation import validate_password_strength
+        from ...shared.utils.password_validation import validate_password_strength
         is_valid, errors = validate_password_strength(password)
         if not is_valid:
             error_message = 'Password does not meet requirements: ' + '; '.join(errors)
@@ -361,7 +361,7 @@ class AuthService:
                 raise ValueError("Current password is incorrect")
             
             # Validate new password strength
-            from ..utils.password_validation import validate_password_strength
+            from ...shared.utils.password_validation import validate_password_strength
             is_valid, errors = validate_password_strength(password)
             if not is_valid:
                 error_message = 'New password does not meet requirements: ' + '; '.join(errors)

Backend/src/auth/services/oauth_service.py

@@ -6,9 +6,9 @@ import secrets
 from urllib.parse import urlencode
 import logging
 
-from ..models.security_event import OAuthProvider, OAuthToken
+from ...security.models.security_event import OAuthProvider, OAuthToken
 from ..models.user import User
-from ..config.logging_config import get_logger
+from ...shared.config.logging_config import get_logger
 
 logger = get_logger(__name__)
 

Backend/src/bookings/models/booking.py

@@ -2,7 +2,7 @@ from sqlalchemy import Column, Integer, String, DateTime, Numeric, Boolean, Text
 from sqlalchemy.orm import relationship
 from datetime import datetime
 import enum
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class BookingStatus(str, enum.Enum):
     pending = 'pending'

Backend/src/bookings/models/checkin_checkout.py

@@ -1,7 +1,7 @@
 from sqlalchemy import Column, Integer, DateTime, Numeric, Text, ForeignKey
 from sqlalchemy.orm import relationship
 from datetime import datetime
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class CheckInCheckOut(Base):
     __tablename__ = 'checkin_checkout'

Backend/src/bookings/models/group_booking.py

@@ -2,7 +2,7 @@ from sqlalchemy import Column, Integer, String, DateTime, Numeric, Boolean, Text
 from sqlalchemy.orm import relationship
 from datetime import datetime
 import enum
-from ..config.database import Base
+from ...shared.config.database import Base
 
 class GroupBookingStatus(str, enum.Enum):
     draft = 'draft'

Backend/src/bookings/routes/booking_routes.py

@@ -5,25 +5,25 @@ from typing import Optional
 from datetime import datetime
 import random
 import os
-from ..config.database import get_db
-from ..config.settings import settings
-from ..middleware.auth import get_current_user, authorize_roles
-from ..models.user import User
-from ..models.role import Role
+from ...shared.config.database import get_db
+from ...shared.config.settings import settings
+from ...security.middleware.auth import get_current_user, authorize_roles
+from ...auth.models.user import User
+from ...auth.models.role import Role
 from ..models.booking import Booking, BookingStatus
-from ..models.room import Room, RoomStatus
-from ..models.room_type import RoomType
-from ..models.payment import Payment, PaymentMethod, PaymentType, PaymentStatus
-from ..models.service_usage import ServiceUsage
-from ..models.user_loyalty import UserLoyalty
-from ..models.referral import Referral, ReferralStatus
-from ..services.room_service import normalize_images, get_base_url
+from ...rooms.models.room import Room, RoomStatus
+from ...rooms.models.room_type import RoomType
+from ...payments.models.payment import Payment, PaymentMethod, PaymentType, PaymentStatus
+from ...hotel_services.models.service_usage import ServiceUsage
+from ...loyalty.models.user_loyalty import UserLoyalty
+from ...loyalty.models.referral import Referral, ReferralStatus
+from ...rooms.services.room_service import normalize_images, get_base_url
 from fastapi import Request
-from ..utils.mailer import send_email
-from ..utils.email_templates import booking_confirmation_email_template, booking_status_changed_email_template
-from ..services.loyalty_service import LoyaltyService
-from ..utils.currency_helpers import get_currency_symbol
-from ..utils.response_helpers import success_response
+from ...shared.utils.mailer import send_email
+from ...shared.utils.email_templates import booking_confirmation_email_template, booking_status_changed_email_template
+from ...loyalty.services.loyalty_service import LoyaltyService
+from ...shared.utils.currency_helpers import get_currency_symbol
+from ...shared.utils.response_helpers import success_response
 from ..schemas.booking import CreateBookingRequest, UpdateBookingRequest
 router = APIRouter(prefix='/bookings', tags=['bookings'])
 
@@ -216,7 +216,7 @@ async def create_booking(booking_data: CreateBookingRequest, current_user: User=
             raise HTTPException(status_code=409, detail='Room already booked for the selected dates')
         
         # Check for maintenance blocks
-        from ..models.room_maintenance import RoomMaintenance, MaintenanceStatus
+        from ...rooms.models.room_maintenance import RoomMaintenance, MaintenanceStatus
         maintenance_block = db.query(RoomMaintenance).filter(
             and_(
                 RoomMaintenance.room_id == room_id,
@@ -251,7 +251,7 @@ async def create_booking(booking_data: CreateBookingRequest, current_user: User=
         # Calculate services total if any (using Pydantic model)
         services_total = 0.0
         if services:
-            from ..models.service import Service
+            from ...hotel_services.models.service import Service
             for service_item in services:
                 service_id = service_item.service_id
                 quantity = service_item.quantity
@@ -314,8 +314,8 @@ async def create_booking(booking_data: CreateBookingRequest, current_user: User=
         # Process referral code if provided
         if referral_code:
             try:
-                from ..services.loyalty_service import LoyaltyService
-                from ..models.system_settings import SystemSettings
+                from ...loyalty.services.loyalty_service import LoyaltyService
+                from ...system.models.system_settings import SystemSettings
                 
                 # Check if loyalty program is enabled
                 setting = db.query(SystemSettings).filter(
@@ -338,7 +338,7 @@ async def create_booking(booking_data: CreateBookingRequest, current_user: User=
                 logger.warning(f"Failed to process referral code {referral_code}: {referral_error}")
                 # Don't fail the booking if referral processing fails
         if payment_method in ['stripe', 'paypal']:
-            from ..models.payment import Payment, PaymentMethod, PaymentStatus, PaymentType
+            from ...payments.models.payment import Payment, PaymentMethod, PaymentStatus, PaymentType
             if payment_method == 'stripe':
                 payment_method_enum = PaymentMethod.stripe
             elif payment_method == 'paypal':
@@ -352,14 +352,14 @@ async def create_booking(booking_data: CreateBookingRequest, current_user: User=
             db.flush()
             logger.info(f'Payment created: ID={payment.id}, method={(payment.payment_method.value if hasattr(payment.payment_method, 'value') else payment.payment_method)}')
         if requires_deposit and deposit_amount > 0:
-            from ..models.payment import Payment, PaymentMethod, PaymentStatus, PaymentType
+            from ...payments.models.payment import Payment, PaymentMethod, PaymentStatus, PaymentType
             deposit_payment = Payment(booking_id=booking.id, amount=deposit_amount, payment_method=PaymentMethod.stripe, payment_type=PaymentType.deposit, deposit_percentage=deposit_percentage, payment_status=PaymentStatus.pending, payment_date=None)
             db.add(deposit_payment)
             db.flush()
             logger.info(f'Deposit payment created: ID={deposit_payment.id}, amount={deposit_amount}, percentage={deposit_percentage}%')
         # Add service usages (services already extracted from Pydantic model)
         if services:
-            from ..models.service import Service
+            from ...hotel_services.models.service import Service
             for service_item in services:
                 service_id = service_item.service_id
                 quantity = service_item.quantity
@@ -375,7 +375,7 @@ async def create_booking(booking_data: CreateBookingRequest, current_user: User=
         
         # Send booking confirmation notification
         try:
-            from ..services.notification_service import NotificationService
+            from ...notifications.services.notification_service import NotificationService
             if booking.status == BookingStatus.confirmed:
                 NotificationService.send_booking_confirmation(db, booking)
         except Exception as e:
@@ -384,11 +384,11 @@ async def create_booking(booking_data: CreateBookingRequest, current_user: User=
             logger.warning(f'Failed to send booking confirmation notification: {e}')
         
         try:
-            from ..services.invoice_service import InvoiceService
-            from ..utils.mailer import send_email
+            from ...payments.services.invoice_service import InvoiceService
+            from ...shared.utils.mailer import send_email
             from sqlalchemy.orm import joinedload, selectinload
             booking = db.query(Booking).options(selectinload(Booking.service_usages).selectinload(ServiceUsage.service)).filter(Booking.id == booking.id).first()
-            from ..models.system_settings import SystemSettings
+            from ...system.models.system_settings import SystemSettings
             company_settings = {}
             for key in ['company_name', 'company_address', 'company_phone', 'company_email', 'company_tax_id', 'company_logo_url']:
                 setting = db.query(SystemSettings).filter(SystemSettings.key == key).first()
@@ -503,7 +503,7 @@ async def get_booking_by_id(id: int, request: Request, current_user: User=Depend
         booking = db.query(Booking).options(selectinload(Booking.payments), selectinload(Booking.service_usages).selectinload(ServiceUsage.service), joinedload(Booking.user), joinedload(Booking.room).joinedload(Room.room_type)).filter(Booking.id == id).first()
         if not booking:
             raise HTTPException(status_code=404, detail='Booking not found')
-        from ..utils.role_helpers import is_admin
+        from ...shared.utils.role_helpers import is_admin
         if not is_admin(current_user, db) and booking.user_id != current_user.id:
             raise HTTPException(status_code=403, detail='Forbidden')
         import logging
@@ -612,7 +612,7 @@ async def cancel_booking(id: int, current_user: User=Depends(get_current_user),
             
             if not active_booking:
                 # Check for maintenance
-                from ..models.room_maintenance import RoomMaintenance, MaintenanceStatus
+                from ...rooms.models.room_maintenance import RoomMaintenance, MaintenanceStatus
                 active_maintenance = db.query(RoomMaintenance).filter(
                     and_(
                         RoomMaintenance.room_id == booking.room_id,
@@ -630,7 +630,7 @@ async def cancel_booking(id: int, current_user: User=Depends(get_current_user),
             db.flush()
         db.commit()
         try:
-            from ..models.system_settings import SystemSettings
+            from ...system.models.system_settings import SystemSettings
             client_url_setting = db.query(SystemSettings).filter(SystemSettings.key == 'client_url').first()
             client_url = client_url_setting.value if client_url_setting and client_url_setting.value else settings.CLIENT_URL or os.getenv('CLIENT_URL', 'http://localhost:5173')
             email_html = booking_status_changed_email_template(booking_number=booking.booking_number, guest_name=booking.user.full_name if booking.user else 'Guest', status='cancelled', client_url=client_url)
@@ -673,7 +673,7 @@ async def update_booking(id: int, booking_data: UpdateBookingRequest, current_us
                     # Set room to cleaning when checked out (housekeeping needed)
                     if room:
                         # Check if there's active maintenance
-                        from ..models.room_maintenance import RoomMaintenance, MaintenanceStatus
+                        from ...rooms.models.room_maintenance import RoomMaintenance, MaintenanceStatus
                         active_maintenance = db.query(RoomMaintenance).filter(
                             and_(
                                 RoomMaintenance.room_id == room.id,
@@ -710,7 +710,7 @@ async def update_booking(id: int, booking_data: UpdateBookingRequest, current_us
                         
                         if not active_booking:
                             # Check for maintenance
-                            from ..models.room_maintenance import RoomMaintenance, MaintenanceStatus
+                            from ...rooms.models.room_maintenance import RoomMaintenance, MaintenanceStatus
                             active_maintenance = db.query(RoomMaintenance).filter(
                                 and_(
                                     RoomMaintenance.room_id == room.id,
@@ -753,7 +753,7 @@ async def update_booking(id: int, booking_data: UpdateBookingRequest, current_us
         # Send booking confirmation notification if status changed to confirmed
         if new_status == BookingStatus.confirmed:
             try:
-                from ..services.notification_service import NotificationService
+                from ...notifications.services.notification_service import NotificationService
                 NotificationService.send_booking_confirmation(db, booking)
             except Exception as e:
                 import logging
@@ -778,7 +778,7 @@ async def update_booking(id: int, booking_data: UpdateBookingRequest, current_us
         if status_value and old_status != booking.status:
             if booking.status in [BookingStatus.confirmed, BookingStatus.cancelled]:
                 try:
-                    from ..models.system_settings import SystemSettings
+                    from ...system.models.system_settings import SystemSettings
                     client_url_setting = db.query(SystemSettings).filter(SystemSettings.key == 'client_url').first()
                     client_url = client_url_setting.value if client_url_setting and client_url_setting.value else settings.CLIENT_URL or os.getenv('CLIENT_URL', 'http://localhost:5173')
                     if booking.status == BookingStatus.confirmed:
@@ -797,7 +797,7 @@ async def update_booking(id: int, booking_data: UpdateBookingRequest, current_us
                         if booking.user:
                             try:
                                 # Check if booking already earned points
-                                from ..models.loyalty_point_transaction import LoyaltyPointTransaction, TransactionSource
+                                from ...loyalty.models.loyalty_point_transaction import LoyaltyPointTransaction, TransactionSource
                                 existing_points = db.query(LoyaltyPointTransaction).filter(
                                     LoyaltyPointTransaction.booking_id == booking.id,
                                     LoyaltyPointTransaction.source == TransactionSource.booking
@@ -815,7 +815,7 @@ async def update_booking(id: int, booking_data: UpdateBookingRequest, current_us
                                         user_loyalty = db.query(UserLoyalty).filter(UserLoyalty.user_id == booking.user_id).first()
                                         if user_loyalty and user_loyalty.referral_code:
                                             # Check if there's a referral for this user that hasn't been rewarded yet
-                                            from ..models.referral import Referral
+                                            from ...loyalty.models.referral import Referral
                                             referral = db.query(Referral).filter(
                                                 Referral.referred_user_id == booking.user_id,
                                                 Referral.booking_id == booking.id,
@@ -999,7 +999,7 @@ async def admin_create_booking(booking_data: dict, current_user: User=Depends(au
         services = booking_data.get('services', [])
         services_total = 0.0
         if services:
-            from ..models.service import Service
+            from ...hotel_services.models.service import Service
             for service_item in services:
                 service_id = service_item.get('service_id')
                 quantity = service_item.get('quantity', 1)
@@ -1078,7 +1078,7 @@ async def admin_create_booking(booking_data: dict, current_user: User=Depends(au
         db.flush()
         
         # Create payment records based on payment_status
-        from ..models.payment import Payment, PaymentMethod, PaymentStatus, PaymentType
+        from ...payments.models.payment import Payment, PaymentMethod, PaymentStatus, PaymentType
         from datetime import datetime as dt
         
         # Determine payment method enum
@@ -1179,7 +1179,7 @@ async def admin_create_booking(booking_data: dict, current_user: User=Depends(au
         
         # Add service usages if any
         if services:
-            from ..models.service import Service
+            from ...hotel_services.models.service import Service
             for service_item in services:
                 service_id = service_item.get('service_id')
                 quantity = service_item.get('quantity', 1)

Backend/src/bookings/routes/group_booking_routes.py

@@ -4,18 +4,18 @@ from typing import Optional, List
 from datetime import datetime
 from decimal import Decimal
 
-from ..config.database import get_db
-from ..middleware.auth import get_current_user, authorize_roles
-from ..models.user import User
-from ..models.role import Role
+from ...shared.config.database import get_db
+from ...security.middleware.auth import get_current_user, authorize_roles
+from ...auth.models.user import User
+from ...auth.models.role import Role
 from ..models.group_booking import (
     GroupBooking, GroupBookingMember, GroupRoomBlock, GroupPayment,
     GroupBookingStatus, PaymentOption
 )
-from ..models.room import Room
-from ..models.room_type import RoomType
+from ...rooms.models.room import Room
+from ...rooms.models.room_type import RoomType
 from ..services.group_booking_service import GroupBookingService
-from ..services.room_service import get_base_url
+from ...rooms.services.room_service import get_base_url
 from fastapi import Request
 
 router = APIRouter(prefix='/group-bookings', tags=['group-bookings'])

Backend/src/bookings/services/group_booking_service.py

@@ -9,10 +9,10 @@ from ..models.group_booking import (
     GroupBookingStatus, PaymentOption
 )
 from ..models.booking import Booking, BookingStatus
-from ..models.room import Room, RoomStatus
-from ..models.room_type import RoomType
-from ..models.user import User
-from ..models.payment import Payment, PaymentStatus, PaymentMethod
+from ...rooms.models.room import Room, RoomStatus
+from ...rooms.models.room_type import RoomType
+from ...auth.models.user import User
+from ...payments.models.payment import Payment, PaymentStatus, PaymentMethod
 import logging
 
 logger = logging.getLogger(__name__)