Recovered state: integrated TrendSurferAgent, restored frontend/backend files, and cleaned up recovery scripts
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ajaysi
@@ -11,7 +11,8 @@ from sqlalchemy.orm import Session
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# Import database services
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from services.content_planning_db import ContentPlanningDBService
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from services.ai_analysis_db_service import AIAnalysisDBService
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from services.onboarding.data_service import OnboardingDataService
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from services.database import SessionLocal, get_session_for_user
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from api.content_planning.services.content_strategy.onboarding import OnboardingDataIntegrationService
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# Import migrated content gap analysis services
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from services.content_gap_analyzer.content_gap_analyzer import ContentGapAnalyzer
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@@ -30,7 +31,7 @@ class GapAnalysisService:
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def __init__(self):
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self.ai_analysis_db_service = AIAnalysisDBService()
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self.onboarding_service = OnboardingDataService()
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self.onboarding_integration_service = OnboardingDataIntegrationService()
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# Initialize migrated services
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self.content_gap_analyzer = ContentGapAnalyzer()
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@@ -57,13 +58,13 @@ class GapAnalysisService:
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logger.error(f"Error creating content gap analysis: {str(e)}")
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raise ContentPlanningErrorHandler.handle_general_error(e, "create_gap_analysis")
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async def get_gap_analyses(self, user_id: Optional[int] = None, strategy_id: Optional[int] = None, force_refresh: bool = False) -> Dict[str, Any]:
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async def get_gap_analyses(self, user_id: Optional[Any] = None, strategy_id: Optional[int] = None, force_refresh: bool = False) -> Dict[str, Any]:
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"""Get content gap analysis with real AI insights - Database first approach."""
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try:
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logger.info(f"🚀 Starting content gap analysis for user: {user_id}, strategy: {strategy_id}, force_refresh: {force_refresh}")
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# Use user_id or default to 1
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current_user_id = user_id or 1
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current_user_id = user_id or "1"
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# Skip database check if force_refresh is True
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if not force_refresh:
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@@ -93,13 +94,17 @@ class GapAnalysisService:
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# No recent analysis found or force refresh requested, run new AI analysis
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logger.info(f"🔄 Running new gap analysis for user {current_user_id} (force_refresh: {force_refresh})")
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# Get personalized inputs from onboarding data
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personalized_inputs = self.onboarding_service.get_personalized_ai_inputs(current_user_id)
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# Get personalized inputs from onboarding data (SSOT)
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db = get_session_for_user(str(current_user_id))
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try:
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personalized_inputs = await self.onboarding_integration_service.process_onboarding_data(str(current_user_id), db)
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finally:
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db.close()
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logger.info(f"📊 Using personalized inputs: {len(personalized_inputs)} data points")
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# Generate real AI-powered gap analysis
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gap_analysis = await self.ai_engine_service.generate_content_recommendations(personalized_inputs)
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gap_analysis = await self.ai_engine_service.generate_content_recommendations(personalized_inputs, user_id=str(current_user_id))
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logger.info(f"✅ AI gap analysis completed: {len(gap_analysis)} recommendations")
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@@ -148,67 +153,34 @@ class GapAnalysisService:
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logger.error(f"Error getting content gap analysis: {str(e)}")
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raise ContentPlanningErrorHandler.handle_general_error(e, "get_gap_analysis_by_id")
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async def analyze_content_gaps(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
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async def analyze_content_gaps(self, request_data: Dict[str, Any], user_id: str) -> Dict[str, Any]:
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"""Analyze content gaps between your website and competitors."""
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try:
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logger.info(f"Starting content gap analysis for: {request_data.get('website_url', 'Unknown')}")
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# Use migrated services for actual analysis
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analysis_results = {}
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# 1. Website Analysis
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logger.info("Performing website analysis...")
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website_analysis = await self.website_analyzer.analyze_website_content(request_data.get('website_url'))
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analysis_results['website_analysis'] = website_analysis
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# 2. Competitor Analysis
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logger.info("Performing competitor analysis...")
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competitor_analysis = await self.competitor_analyzer.analyze_competitors(request_data.get('competitor_urls', []))
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analysis_results['competitor_analysis'] = competitor_analysis
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# 3. Keyword Research
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logger.info("Performing keyword research...")
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keyword_analysis = await self.keyword_researcher.research_keywords(
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industry=request_data.get('industry'),
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target_keywords=request_data.get('target_keywords')
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)
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analysis_results['keyword_analysis'] = keyword_analysis
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# 4. Content Gap Analysis
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logger.info("Performing content gap analysis...")
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gap_analysis = await self.content_gap_analyzer.identify_content_gaps(
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website_url=request_data.get('website_url'),
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# Use ContentGapAnalyzer for comprehensive analysis
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results = await self.content_gap_analyzer.analyze_comprehensive_gap(
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target_url=request_data.get('website_url'),
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competitor_urls=request_data.get('competitor_urls', []),
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keyword_data=keyword_analysis
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target_keywords=request_data.get('target_keywords', []),
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user_id=user_id,
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industry=request_data.get('industry', 'general')
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)
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analysis_results['gap_analysis'] = gap_analysis
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# 5. AI-Powered Recommendations
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logger.info("Generating AI recommendations...")
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recommendations = await self.ai_engine_service.generate_recommendations(
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website_analysis=website_analysis,
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competitor_analysis=competitor_analysis,
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gap_analysis=gap_analysis,
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keyword_analysis=keyword_analysis
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)
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analysis_results['recommendations'] = recommendations
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if 'error' in results:
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raise Exception(results['error'])
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# 6. Strategic Opportunities
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logger.info("Identifying strategic opportunities...")
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opportunities = await self.ai_engine_service.identify_strategic_opportunities(
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gap_analysis=gap_analysis,
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competitor_analysis=competitor_analysis,
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keyword_analysis=keyword_analysis
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)
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analysis_results['opportunities'] = opportunities
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# Prepare response
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# Map results to ContentGapAnalysisFullResponse structure
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# ContentGapAnalyzer returns a rich structure, we map it to the response model
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response_data = {
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'website_analysis': analysis_results['website_analysis'],
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'competitor_analysis': analysis_results['competitor_analysis'],
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'gap_analysis': analysis_results['gap_analysis'],
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'recommendations': analysis_results['recommendations'],
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'opportunities': analysis_results['opportunities'],
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'website_analysis': {
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'serp_analysis': results.get('serp_analysis', {}),
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'keyword_expansion': results.get('keyword_expansion', {})
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},
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'competitor_analysis': results.get('competitor_content', {}),
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'gap_analysis': results.get('gap_analysis', {}),
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'recommendations': results.get('recommendations', []),
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'opportunities': results.get('ai_insights', {}).get('strategic_insights', []),
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'created_at': datetime.utcnow()
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}
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