feat: image generation overhaul (model-aware text, dim clamping, \.30 pricing), event-driven dashboard cache invalidation, SEO insights (AI visibility, GSC, keyword gap), YouTube OAuth/publish, blog writer & content planning improvements, scheduler monitoring updates
This commit is contained in:
ajaysi
@@ -3,7 +3,7 @@
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from fastapi import APIRouter, HTTPException, Depends, status
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from pydantic import BaseModel, Field
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from typing import Dict, Any, List, Optional
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from datetime import datetime
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from datetime import datetime, timedelta
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import json
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import os
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from loguru import logger
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@@ -22,9 +22,18 @@ from api.content_planning.services.content_strategy.onboarding import Onboarding
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from models.onboarding import SEOPageAudit, WebsiteAnalysis, OnboardingSession
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from sqlalchemy.orm.attributes import flag_modified
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from sqlalchemy import desc
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# Phase 2B: Import semantic monitoring
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from services.intelligence.monitoring.semantic_dashboard import RealTimeSemanticMonitor, SemanticHealthMetric
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# GSC services for keyword gap analysis
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from services.gsc_service import GSCService
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from services.gsc_brainstorm_service import GSCBrainstormService
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# Import SIF models for guardian audit
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from models.website_analysis_monitoring_models import SIFIndexingTask, SIFIndexingExecutionLog
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router = APIRouter(prefix="/api/seo-dashboard", tags=["SEO Dashboard"])
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# Initialize the SEO analyzer
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@@ -577,6 +586,172 @@ async def get_sif_indexing_health(current_user: dict = Depends(get_current_user)
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raise HTTPException(status_code=500, detail="Failed to get SIF indexing health")
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async def get_guardian_audit(current_user: dict = Depends(get_current_user)) -> Dict[str, Any]:
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"""
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Get the latest Content Guardian audit report for the current user.
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Returns audit data (quality, brand voice, safety, cannibalization) or a
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null-state response if no audit has been performed yet.
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"""
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try:
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user_id = str(current_user.get("id"))
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db_session = get_session_for_user(user_id)
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if not db_session:
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raise HTTPException(status_code=500, detail="Database connection unavailable")
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try:
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# Find the most recent SIF indexing task for this user
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task = (
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db_session.query(SIFIndexingTask)
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.filter(SIFIndexingTask.user_id == user_id)
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.order_by(desc(SIFIndexingTask.created_at))
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.first()
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)
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if not task:
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return {
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"has_audit": False,
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"status": "not_available",
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"message": "No SIF indexing task found. Onboarding may not be complete.",
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}
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# Get the latest execution log with a guardian report
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log = (
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db_session.query(SIFIndexingExecutionLog)
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.filter(
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SIFIndexingExecutionLog.task_id == task.id,
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SIFIndexingExecutionLog.result_data.isnot(None),
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)
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.order_by(desc(SIFIndexingExecutionLog.execution_date))
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.first()
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)
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if not log or not log.result_data:
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return {
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"has_audit": False,
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"status": "pending",
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"message": "SIF indexing has not completed a run yet.",
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}
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guardian_report = log.result_data.get("guardian_report")
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if not guardian_report:
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return {
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"has_audit": False,
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"status": "no_report",
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"message": "Guardian audit was not performed on the last indexing run.",
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}
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return {
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"has_audit": True,
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"status": "available",
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"audit_timestamp": guardian_report.get("audit_timestamp"),
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"website_url": guardian_report.get("website_url"),
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"total_pages_crawled": guardian_report.get("total_pages_crawled", 0),
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"content_quality": guardian_report.get("content_quality"),
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"brand_voice_consistency": guardian_report.get("brand_voice_consistency"),
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"safety_issues": guardian_report.get("safety_issues"),
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"cannibalization_issues": guardian_report.get("cannibalization_issues"),
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"last_execution_time": log.execution_date.isoformat() if log.execution_date else None,
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}
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finally:
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db_session.close()
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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"Failed to get guardian audit: {e}")
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raise HTTPException(status_code=500, detail="Failed to get guardian audit")
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async def get_keyword_gaps(
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current_user: dict = Depends(get_current_user),
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site_url: Optional[str] = None,
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) -> Dict[str, Any]:
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"""
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Get keyword gap analysis from GSC data.
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Returns keyword gaps, quick wins, content opportunities, and page-level opportunities
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derived from the user's Google Search Console search analytics (last 30 days).
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"""
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try:
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user_id = str(current_user.get("id"))
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gsc_service = GSCService()
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brainstorm_service = GSCBrainstormService(gsc_service)
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# Resolve site URL
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if not site_url:
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sites = gsc_service.get_site_list(user_id)
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if not sites:
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return {
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"error": "No GSC sites found. Connect Google Search Console first.",
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"keyword_gaps": [],
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"quick_wins": [],
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"content_opportunities": [],
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"page_opportunities": [],
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"summary": {},
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}
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site_url = sites[0].get("siteUrl", "")
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# Fetch GSC analytics (last 30 days)
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end_date = datetime.now().strftime("%Y-%m-%d")
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start_date = (datetime.now() - timedelta(days=30)).strftime("%Y-%m-%d")
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analytics = gsc_service.get_search_analytics(
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user_id=user_id,
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site_url=site_url,
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start_date=start_date,
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end_date=end_date,
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)
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if "error" in analytics:
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return {
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"error": analytics.get("error", "Failed to fetch GSC data"),
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"keyword_gaps": [],
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"quick_wins": [],
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"content_opportunities": [],
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"page_opportunities": [],
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"summary": {},
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}
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query_rows = analytics.get("query_data", {}).get("rows", [])
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page_rows = analytics.get("page_data", {}).get("rows", [])
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keywords_data = GSCBrainstormService._parse_query_rows(query_rows)
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pages_data = GSCBrainstormService._parse_page_rows(page_rows)
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if not keywords_data:
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return {
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"error": "No keyword data available for the last 30 days.",
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"keyword_gaps": [],
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"quick_wins": [],
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"content_opportunities": [],
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"page_opportunities": [],
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"summary": {
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"site_url": site_url,
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"date_range": {"start": start_date, "end": end_date},
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"total_keywords_analyzed": 0,
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},
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}
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# Run rule-based analysis WITHOUT topic filter (site-wide)
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content_opportunities = GSCBrainstormService._identify_content_opportunities(keywords_data)
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keyword_gaps = GSCBrainstormService._identify_keyword_gaps(keywords_data)
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quick_wins = GSCBrainstormService._identify_quick_wins(keywords_data)
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page_opportunities = GSCBrainstormService._identify_page_opportunities(pages_data)
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summary = GSCBrainstormService._compute_summary(
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keywords_data, pages_data, site_url, start_date, end_date
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)
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return {
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"keyword_gaps": keyword_gaps,
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"quick_wins": quick_wins,
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"content_opportunities": content_opportunities,
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"page_opportunities": page_opportunities,
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"summary": summary,
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}
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except Exception as e:
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logger.error(f"Failed to get keyword gaps: {e}")
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raise HTTPException(status_code=500, detail=f"Failed to get keyword gaps: {str(e)}")
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async def get_onboarding_task_health(
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current_user: dict = Depends(get_current_user),
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site_url: Optional[str] = None,
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