AI platform insights monitoring and website analysis monitoring services added
This commit is contained in:
ajaysi
@@ -150,8 +150,94 @@ class ResearchService:
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raw_result = None
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else:
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raise
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elif config.provider == ResearchProvider.TAVILY:
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# Tavily research workflow
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from .tavily_provider import TavilyResearchProvider
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from services.database import get_db
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from services.subscription import PricingService
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import os
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import time
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if config.provider != ResearchProvider.EXA:
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# Pre-flight validation (similar to Exa)
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db_val = next(get_db())
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try:
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pricing_service = PricingService(db_val)
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# Check Tavily usage limits
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limits = pricing_service.get_user_limits(user_id)
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tavily_limit = limits.get('limits', {}).get('tavily_calls', 0) if limits else 0
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# Get current usage
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from models.subscription_models import UsageSummary
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from datetime import datetime
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current_period = pricing_service.get_current_billing_period(user_id) or datetime.now().strftime("%Y-%m")
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usage = db_val.query(UsageSummary).filter(
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UsageSummary.user_id == user_id,
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UsageSummary.billing_period == current_period
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).first()
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current_calls = getattr(usage, 'tavily_calls', 0) or 0 if usage else 0
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if tavily_limit > 0 and current_calls >= tavily_limit:
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raise HTTPException(
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status_code=429,
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detail={
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'error': 'Tavily API call limit exceeded',
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'message': f'You have reached your Tavily API call limit ({tavily_limit} calls). Please upgrade your plan or wait for the next billing period.',
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'provider': 'tavily',
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'usage_info': {
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'current': current_calls,
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'limit': tavily_limit
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}
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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.warning(f"Error checking Tavily limits: {e}")
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finally:
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db_val.close()
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# Execute Tavily search
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api_start_time = time.time()
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try:
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tavily_provider = TavilyResearchProvider()
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raw_result = await tavily_provider.search(
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research_prompt, topic, industry, target_audience, config, user_id
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)
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api_duration_ms = (time.time() - api_start_time) * 1000
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# Track usage
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cost = raw_result.get('cost', {}).get('total', 0.001) if isinstance(raw_result.get('cost'), dict) else 0.001
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search_depth = config.tavily_search_depth or "basic"
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tavily_provider.track_tavily_usage(user_id, cost, search_depth)
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# Log API call performance
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blog_writer_logger.log_api_call(
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"tavily_search",
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"search",
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api_duration_ms,
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token_usage={},
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content_length=len(raw_result.get('content', ''))
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)
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# Extract content for downstream analysis
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content = raw_result.get('content', '')
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sources = raw_result.get('sources', [])
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search_widget = "" # Tavily doesn't provide search widgets
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search_queries = raw_result.get('search_queries', [])
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grounding_metadata = None # Tavily doesn't provide grounding metadata
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except RuntimeError as e:
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if "TAVILY_API_KEY not configured" in str(e):
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logger.warning("Tavily not configured, falling back to Google")
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config.provider = ResearchProvider.GOOGLE
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# Continue to Google flow below
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raw_result = None
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else:
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raise
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if config.provider not in [ResearchProvider.EXA, ResearchProvider.TAVILY]:
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# Google research (existing flow) or fallback from Exa
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from .google_provider import GoogleResearchProvider
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import time
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@@ -412,8 +498,94 @@ class ResearchService:
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# Continue to Google flow below
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else:
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raise
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elif config.provider == ResearchProvider.TAVILY:
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# Tavily research workflow
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from .tavily_provider import TavilyResearchProvider
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from services.database import get_db
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from services.subscription import PricingService
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import os
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if config.provider != ResearchProvider.EXA:
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await task_manager.update_progress(task_id, "🌐 Connecting to Tavily AI search...")
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# Pre-flight validation
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db_val = next(get_db())
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try:
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pricing_service = PricingService(db_val)
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# Check Tavily usage limits
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limits = pricing_service.get_user_limits(user_id)
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tavily_limit = limits.get('limits', {}).get('tavily_calls', 0) if limits else 0
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# Get current usage
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from models.subscription_models import UsageSummary
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from datetime import datetime
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current_period = pricing_service.get_current_billing_period(user_id) or datetime.now().strftime("%Y-%m")
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usage = db_val.query(UsageSummary).filter(
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UsageSummary.user_id == user_id,
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UsageSummary.billing_period == current_period
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).first()
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current_calls = getattr(usage, 'tavily_calls', 0) or 0 if usage else 0
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if tavily_limit > 0 and current_calls >= tavily_limit:
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await task_manager.update_progress(task_id, f"❌ Tavily API call limit exceeded ({current_calls}/{tavily_limit})")
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raise HTTPException(
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status_code=429,
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detail={
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'error': 'Tavily API call limit exceeded',
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'message': f'You have reached your Tavily API call limit ({tavily_limit} calls). Please upgrade your plan or wait for the next billing period.',
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'provider': 'tavily',
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'usage_info': {
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'current': current_calls,
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'limit': tavily_limit
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}
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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.warning(f"Error checking Tavily limits: {e}")
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finally:
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db_val.close()
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# Execute Tavily search
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await task_manager.update_progress(task_id, "🤖 Executing Tavily AI search...")
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try:
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tavily_provider = TavilyResearchProvider()
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raw_result = await tavily_provider.search(
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research_prompt, topic, industry, target_audience, config, user_id
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)
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# Track usage
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cost = raw_result.get('cost', {}).get('total', 0.001) if isinstance(raw_result.get('cost'), dict) else 0.001
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search_depth = config.tavily_search_depth or "basic"
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tavily_provider.track_tavily_usage(user_id, cost, search_depth)
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# Extract content for downstream analysis
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if raw_result is None:
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logger.error("raw_result is None after Tavily search")
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raise ValueError("Tavily research result is None - search operation failed unexpectedly")
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if not isinstance(raw_result, dict):
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logger.warning(f"raw_result is not a dict (type: {type(raw_result)}), using defaults")
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raw_result = {}
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content = raw_result.get('content', '')
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sources = raw_result.get('sources', []) or []
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search_widget = "" # Tavily doesn't provide search widgets
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search_queries = raw_result.get('search_queries', []) or []
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grounding_metadata = None # Tavily doesn't provide grounding metadata
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except RuntimeError as e:
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if "TAVILY_API_KEY not configured" in str(e):
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logger.warning("Tavily not configured, falling back to Google")
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await task_manager.update_progress(task_id, "⚠️ Tavily not configured, falling back to Google Search")
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config.provider = ResearchProvider.GOOGLE
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# Continue to Google flow below
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else:
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raise
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if config.provider not in [ResearchProvider.EXA, ResearchProvider.TAVILY]:
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# Google research (existing flow)
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from .google_provider import GoogleResearchProvider
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