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