ALwrity Version 0.5.0 (Fastapi + React )
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ajaysi
265
backend/api/content_planning/api/routes/ai_analytics.py
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265
backend/api/content_planning/api/routes/ai_analytics.py
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"""
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AI Analytics Routes for Content Planning API
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Extracted from the main content_planning.py file for better organization.
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"""
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from fastapi import APIRouter, HTTPException, Depends, status, Query
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from sqlalchemy.orm import Session
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from typing import Dict, Any, List, Optional
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from datetime import datetime
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from loguru import logger
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import json
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import time
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# Import database service
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from services.database import get_db_session, get_db
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from services.content_planning_db import ContentPlanningDBService
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# Import models
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from ..models.requests import (
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ContentEvolutionRequest, PerformanceTrendsRequest,
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ContentPerformancePredictionRequest, StrategicIntelligenceRequest
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)
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from ..models.responses import AIAnalyticsResponse
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# Import utilities
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from ...utils.error_handlers import ContentPlanningErrorHandler
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from ...utils.response_builders import ResponseBuilder
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from ...utils.constants import ERROR_MESSAGES, SUCCESS_MESSAGES
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# Import services
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from ...services.ai_analytics_service import ContentPlanningAIAnalyticsService
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# Initialize services
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ai_analytics_service = ContentPlanningAIAnalyticsService()
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# Create router
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router = APIRouter(prefix="/ai-analytics", tags=["ai-analytics"])
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@router.post("/content-evolution", response_model=AIAnalyticsResponse)
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async def analyze_content_evolution(request: ContentEvolutionRequest):
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"""
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Analyze content evolution over time for a specific strategy.
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"""
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try:
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logger.info(f"Starting content evolution analysis for strategy {request.strategy_id}")
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result = await ai_analytics_service.analyze_content_evolution(
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strategy_id=request.strategy_id,
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time_period=request.time_period
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)
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return AIAnalyticsResponse(**result)
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except Exception as e:
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logger.error(f"Error analyzing content evolution: {str(e)}")
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raise HTTPException(
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status_code=500,
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detail=f"Error analyzing content evolution: {str(e)}"
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)
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@router.post("/performance-trends", response_model=AIAnalyticsResponse)
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async def analyze_performance_trends(request: PerformanceTrendsRequest):
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"""
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Analyze performance trends for content strategy.
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"""
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try:
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logger.info(f"Starting performance trends analysis for strategy {request.strategy_id}")
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result = await ai_analytics_service.analyze_performance_trends(
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strategy_id=request.strategy_id,
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metrics=request.metrics
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)
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return AIAnalyticsResponse(**result)
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except Exception as e:
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logger.error(f"Error analyzing performance trends: {str(e)}")
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raise HTTPException(
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status_code=500,
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detail=f"Error analyzing performance trends: {str(e)}"
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)
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@router.post("/predict-performance", response_model=AIAnalyticsResponse)
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async def predict_content_performance(request: ContentPerformancePredictionRequest):
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"""
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Predict content performance using AI models.
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"""
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try:
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logger.info(f"Starting content performance prediction for strategy {request.strategy_id}")
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result = await ai_analytics_service.predict_content_performance(
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strategy_id=request.strategy_id,
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content_data=request.content_data
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)
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return AIAnalyticsResponse(**result)
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except Exception as e:
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logger.error(f"Error predicting content performance: {str(e)}")
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raise HTTPException(
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status_code=500,
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detail=f"Error predicting content performance: {str(e)}"
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)
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@router.post("/strategic-intelligence", response_model=AIAnalyticsResponse)
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async def generate_strategic_intelligence(request: StrategicIntelligenceRequest):
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"""
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Generate strategic intelligence for content planning.
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"""
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try:
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logger.info(f"Starting strategic intelligence generation for strategy {request.strategy_id}")
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result = await ai_analytics_service.generate_strategic_intelligence(
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strategy_id=request.strategy_id,
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market_data=request.market_data
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)
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return AIAnalyticsResponse(**result)
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except Exception as e:
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logger.error(f"Error generating strategic intelligence: {str(e)}")
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raise HTTPException(
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status_code=500,
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detail=f"Error generating strategic intelligence: {str(e)}"
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)
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@router.get("/", response_model=Dict[str, Any])
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async def get_ai_analytics(
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user_id: Optional[int] = Query(None, description="User ID"),
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strategy_id: Optional[int] = Query(None, description="Strategy ID"),
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force_refresh: bool = Query(False, description="Force refresh AI analysis")
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):
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"""Get AI analytics with real personalized insights - Database first approach."""
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try:
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logger.info(f"🚀 Starting AI analytics for user: {user_id}, strategy: {strategy_id}, force_refresh: {force_refresh}")
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result = await ai_analytics_service.get_ai_analytics(user_id, strategy_id, force_refresh)
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return result
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except Exception as e:
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logger.error(f"❌ Error generating AI analytics: {str(e)}")
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raise HTTPException(status_code=500, detail=f"Error generating AI analytics: {str(e)}")
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@router.get("/health")
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async def ai_analytics_health_check():
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"""
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Health check for AI analytics services.
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"""
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try:
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# Check AI analytics service
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service_status = {}
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# Test AI analytics service
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try:
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# Test with a simple operation that doesn't require data
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# Just check if the service can be instantiated
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test_service = ContentPlanningAIAnalyticsService()
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service_status['ai_analytics_service'] = 'operational'
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except Exception as e:
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service_status['ai_analytics_service'] = f'error: {str(e)}'
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# Determine overall status
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operational_services = sum(1 for status in service_status.values() if status == 'operational')
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total_services = len(service_status)
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overall_status = 'healthy' if operational_services == total_services else 'degraded'
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health_status = {
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'status': overall_status,
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'services': service_status,
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'operational_services': operational_services,
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'total_services': total_services,
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'timestamp': datetime.utcnow().isoformat()
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}
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return health_status
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except Exception as e:
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logger.error(f"AI analytics health check failed: {str(e)}")
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raise HTTPException(
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status_code=500,
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detail=f"AI analytics health check failed: {str(e)}"
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)
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@router.get("/results/{user_id}")
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async def get_user_ai_analysis_results(
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user_id: int,
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analysis_type: Optional[str] = Query(None, description="Filter by analysis type"),
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limit: int = Query(10, description="Number of results to return")
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):
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"""Get AI analysis results for a specific user."""
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try:
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logger.info(f"Fetching AI analysis results for user {user_id}")
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result = await ai_analytics_service.get_user_ai_analysis_results(
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user_id=user_id,
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analysis_type=analysis_type,
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limit=limit
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)
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return result
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except Exception as e:
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logger.error(f"Error fetching AI analysis results: {str(e)}")
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raise HTTPException(status_code=500, detail="Internal server error")
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@router.post("/refresh/{user_id}")
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async def refresh_ai_analysis(
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user_id: int,
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analysis_type: str = Query(..., description="Type of analysis to refresh"),
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strategy_id: Optional[int] = Query(None, description="Strategy ID")
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):
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"""Force refresh of AI analysis for a user."""
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try:
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logger.info(f"Force refreshing AI analysis for user {user_id}, type: {analysis_type}")
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result = await ai_analytics_service.refresh_ai_analysis(
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user_id=user_id,
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analysis_type=analysis_type,
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strategy_id=strategy_id
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)
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return result
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except Exception as e:
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logger.error(f"Error refreshing AI analysis: {str(e)}")
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raise HTTPException(status_code=500, detail="Internal server error")
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@router.delete("/cache/{user_id}")
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async def clear_ai_analysis_cache(
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user_id: int,
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analysis_type: Optional[str] = Query(None, description="Specific analysis type to clear")
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):
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"""Clear AI analysis cache for a user."""
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try:
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logger.info(f"Clearing AI analysis cache for user {user_id}")
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result = await ai_analytics_service.clear_ai_analysis_cache(
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user_id=user_id,
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analysis_type=analysis_type
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)
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return result
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except Exception as e:
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logger.error(f"Error clearing AI analysis cache: {str(e)}")
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raise HTTPException(status_code=500, detail="Internal server error")
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@router.get("/statistics")
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async def get_ai_analysis_statistics(
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user_id: Optional[int] = Query(None, description="User ID for user-specific stats")
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):
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"""Get AI analysis statistics."""
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try:
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logger.info(f"📊 Getting AI analysis statistics for user: {user_id}")
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result = await ai_analytics_service.get_ai_analysis_statistics(user_id)
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return result
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except Exception as e:
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logger.error(f"❌ Error getting AI analysis statistics: {str(e)}")
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail=f"Failed to get AI analysis statistics: {str(e)}"
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)
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