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AI platform insights monitoring and website analysis monitoring services added

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This commit is contained in:
ajaysi
2025-11-11 15:57:45 +05:30
parent d99c7c83a7
commit 7191c7e7f0
81 changed files with 10860 additions and 1567 deletions
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211
backend/api/research_config.py
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@@ -4,12 +4,12 @@ Provides provider availability and persona-aware defaults for research.
"""
from fastapi import APIRouter, Depends, HTTPException, Query
from typing import Dict, Any, Optional
from typing import Dict, Any, Optional, List
from loguru import logger
from pydantic import BaseModel
from middleware.auth_middleware import get_current_user
from services.user_api_key_context import get_exa_key, get_gemini_key
from services.user_api_key_context import get_exa_key, get_gemini_key, get_tavily_key
from services.onboarding.database_service import OnboardingDatabaseService
from services.onboarding.progress_service import get_onboarding_progress_service
from services.database import get_db
@@ -26,8 +26,10 @@ class ProviderAvailability(BaseModel):
"""Provider availability status."""
google_available: bool
exa_available: bool
tavily_available: bool
gemini_key_status: str # 'configured' | 'missing'
exa_key_status: str # 'configured' | 'missing'
tavily_key_status: str # 'configured' | 'missing'
class PersonaDefaults(BaseModel):
@@ -47,6 +49,17 @@ class ResearchConfigResponse(BaseModel):
persona_scheduled: bool = False
class CompetitorAnalysisResponse(BaseModel):
"""Response model for competitor analysis data."""
success: bool
competitors: Optional[List[Dict[str, Any]]] = None
social_media_accounts: Optional[Dict[str, str]] = None
social_media_citations: Optional[List[Dict[str, Any]]] = None
research_summary: Optional[Dict[str, Any]] = None
analysis_timestamp: Optional[str] = None
error: Optional[str] = None
@router.get("/provider-availability", response_model=ProviderAvailability)
async def get_provider_availability(
current_user: Dict = Depends(get_current_user)
@@ -57,6 +70,7 @@ async def get_provider_availability(
Returns:
- google_available: True if Gemini key is configured
- exa_available: True if Exa key is configured
- tavily_available: True if Tavily key is configured
- Key status for each provider
"""
try:
@@ -65,15 +79,19 @@ async def get_provider_availability(
# Check API key availability
gemini_key = get_gemini_key(user_id)
exa_key = get_exa_key(user_id)
tavily_key = get_tavily_key(user_id)
google_available = bool(gemini_key and gemini_key.strip())
exa_available = bool(exa_key and exa_key.strip())
tavily_available = bool(tavily_key and tavily_key.strip())
return ProviderAvailability(
google_available=google_available,
exa_available=exa_available,
tavily_available=tavily_available,
gemini_key_status='configured' if google_available else 'missing',
exa_key_status='configured' if exa_available else 'missing'
exa_key_status='configured' if exa_available else 'missing',
tavily_key_status='configured' if tavily_available else 'missing'
)
except Exception as e:
logger.error(f"[ResearchConfig] Error checking provider availability for user {user_id if 'user_id' in locals() else 'unknown'}: {e}", exc_info=True)
@@ -211,15 +229,19 @@ async def get_research_config(
logger.debug(f"[ResearchConfig] Getting provider availability for user {user_id}")
gemini_key = get_gemini_key(user_id)
exa_key = get_exa_key(user_id)
tavily_key = get_tavily_key(user_id)
google_available = bool(gemini_key and gemini_key.strip())
exa_available = bool(exa_key and exa_key.strip())
tavily_available = bool(tavily_key and tavily_key.strip())
provider_availability = ProviderAvailability(
google_available=google_available,
exa_available=exa_available,
tavily_available=tavily_available,
gemini_key_status='configured' if google_available else 'missing',
exa_key_status='configured' if exa_available else 'missing'
exa_key_status='configured' if exa_available else 'missing',
tavily_key_status='configured' if tavily_available else 'missing'
)
# Get persona defaults
@@ -355,11 +377,190 @@ async def get_research_config(
import traceback
logger.error(f"[ResearchConfig] Full traceback:\n{traceback.format_exc()}")
raise HTTPException(
status_code=500,
status_code=500,
detail=f"Failed to get research config: {str(e)}"
)
@router.get("/competitor-analysis", response_model=CompetitorAnalysisResponse)
async def get_competitor_analysis(
current_user: Dict = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Get competitor analysis data from onboarding for the current user.
Returns competitor data including competitors list, social media accounts,
social media citations, and research summary that was collected during onboarding step 3.
"""
user_id = None
try:
user_id = str(current_user.get('id'))
print(f"\n[COMPETITOR_ANALYSIS] ===== START: Getting competitor analysis for user_id={user_id} =====")
print(f"[COMPETITOR_ANALYSIS] Current user dict keys: {list(current_user.keys())}")
logger.info(f"[ResearchConfig] Getting competitor analysis for user {user_id}")
if not db:
print(f"[COMPETITOR_ANALYSIS] ❌ ERROR: Database session is None for user {user_id}")
logger.error(f"[ResearchConfig] Database session is None for user {user_id}")
raise HTTPException(status_code=500, detail="Database session not available")
db_service = OnboardingDatabaseService(db=db)
# Get onboarding session - using same pattern as onboarding completion check
print(f"[COMPETITOR_ANALYSIS] Looking up onboarding session for user_id={user_id} (Clerk ID)")
session = db_service.get_session_by_user(user_id, db)
if not session:
print(f"[COMPETITOR_ANALYSIS] ❌ WARNING: No onboarding session found for user_id={user_id}")
logger.warning(f"[ResearchConfig] No onboarding session found for user {user_id}")
return CompetitorAnalysisResponse(
success=False,
error="No onboarding session found. Please complete onboarding first."
)
print(f"[COMPETITOR_ANALYSIS] ✅ Found onboarding session: id={session.id}, user_id={session.user_id}, current_step={session.current_step}")
# Check if step 3 is completed - same pattern as elsewhere (check current_step >= 3 or research_preferences exists)
research_preferences = db_service.get_research_preferences(user_id, db)
print(f"[COMPETITOR_ANALYSIS] Step check: current_step={session.current_step}, research_preferences exists={research_preferences is not None}")
if not research_preferences and session.current_step < 3:
print(f"[COMPETITOR_ANALYSIS] ❌ Step 3 not completed for user_id={user_id} (current_step={session.current_step})")
logger.info(f"[ResearchConfig] Step 3 not completed for user {user_id} (current_step={session.current_step})")
return CompetitorAnalysisResponse(
success=False,
error="Onboarding step 3 (Competitor Analysis) is not completed. Please complete onboarding step 3 first."
)
print(f"[COMPETITOR_ANALYSIS] ✅ Step 3 is completed (current_step={session.current_step} or research_preferences exists)")
# Try Method 1: Get competitor data from CompetitorAnalysis table using OnboardingDatabaseService
# This follows the same pattern as get_website_analysis()
print(f"[COMPETITOR_ANALYSIS] 🔍 Method 1: Querying CompetitorAnalysis table using OnboardingDatabaseService...")
try:
competitors = db_service.get_competitor_analysis(user_id, db)
if competitors:
print(f"[COMPETITOR_ANALYSIS] ✅ Found {len(competitors)} competitor records from CompetitorAnalysis table")
logger.info(f"[ResearchConfig] Found {len(competitors)} competitors from CompetitorAnalysis table for user {user_id}")
# Map competitor fields to match frontend expectations
mapped_competitors = []
for comp in competitors:
mapped_comp = {
**comp, # Keep all original fields
"name": comp.get("title") or comp.get("name") or comp.get("domain", ""),
"description": comp.get("summary") or comp.get("description", ""),
"similarity_score": comp.get("relevance_score") or comp.get("similarity_score", 0.5)
}
mapped_competitors.append(mapped_comp)
print(f"[COMPETITOR_ANALYSIS] ✅ SUCCESS: Returning {len(mapped_competitors)} competitors for user_id={user_id}")
return CompetitorAnalysisResponse(
success=True,
competitors=mapped_competitors,
social_media_accounts={},
social_media_citations=[],
research_summary={
"total_competitors": len(mapped_competitors),
"market_insights": f"Found {len(mapped_competitors)} competitors analyzed during onboarding"
},
analysis_timestamp=None
)
else:
print(f"[COMPETITOR_ANALYSIS] ⚠️ No competitor records found in CompetitorAnalysis table for user_id={user_id}")
except Exception as e:
print(f"[COMPETITOR_ANALYSIS] ❌ EXCEPTION in Method 1: {e}")
import traceback
print(f"[COMPETITOR_ANALYSIS] Traceback:\n{traceback.format_exc()}")
logger.warning(f"[ResearchConfig] Could not retrieve competitor data from CompetitorAnalysis table: {e}", exc_info=True)
# Try Method 2: Get data from Step3ResearchService (which accesses step_data)
# This is where step3_research_service._store_research_data() saves the data
print(f"[COMPETITOR_ANALYSIS] 🔄 Method 2: Trying Step3ResearchService.get_research_data()...")
try:
from api.onboarding_utils.step3_research_service import Step3ResearchService
# Step3ResearchService.get_research_data() expects session_id (integer), but we have user_id (string)
# The service uses session.id internally, so we need to pass the session.id
step3_service = Step3ResearchService()
research_data_result = await step3_service.get_research_data(str(session.id))
print(f"[COMPETITOR_ANALYSIS] Step3ResearchService.get_research_data() result: success={research_data_result.get('success')}")
if research_data_result.get('success'):
# Handle both 'research_data' and 'step3_research_data' keys
research_data = research_data_result.get('step3_research_data') or research_data_result.get('research_data', {})
print(f"[COMPETITOR_ANALYSIS] Research data keys: {list(research_data.keys()) if isinstance(research_data, dict) else 'Not a dict'}")
if isinstance(research_data, dict) and research_data.get('competitors'):
competitors_list = research_data.get('competitors', [])
print(f"[COMPETITOR_ANALYSIS] ✅ Found {len(competitors_list)} competitors in step_data via Step3ResearchService")
if competitors_list:
analysis_metadata = research_data.get('analysis_metadata', {})
social_media_data = analysis_metadata.get('social_media_data', {})
# Map competitor fields to match frontend expectations
mapped_competitors = []
for comp in competitors_list:
mapped_comp = {
**comp, # Keep all original fields
"name": comp.get("title") or comp.get("name") or comp.get("domain", ""),
"description": comp.get("summary") or comp.get("description", ""),
"similarity_score": comp.get("relevance_score") or comp.get("similarity_score", 0.5)
}
mapped_competitors.append(mapped_comp)
print(f"[COMPETITOR_ANALYSIS] ✅ SUCCESS: Returning {len(mapped_competitors)} competitors from step_data for user_id={user_id}")
logger.info(f"[ResearchConfig] Found {len(mapped_competitors)} competitors from step_data via Step3ResearchService for user {user_id}")
return CompetitorAnalysisResponse(
success=True,
competitors=mapped_competitors,
social_media_accounts=social_media_data.get('social_media_accounts', {}),
social_media_citations=social_media_data.get('citations', []),
research_summary=research_data.get('research_summary'),
analysis_timestamp=research_data.get('completed_at')
)
else:
print(f"[COMPETITOR_ANALYSIS] ⚠️ Step3ResearchService returned competitors list but it's empty")
else:
print(f"[COMPETITOR_ANALYSIS] ⚠️ Step3ResearchService returned success=True but no competitors in data")
else:
error_msg = research_data_result.get('error', 'Unknown error')
print(f"[COMPETITOR_ANALYSIS] ⚠️ Step3ResearchService returned success=False, error: {error_msg}")
except Exception as e:
print(f"[COMPETITOR_ANALYSIS] ❌ EXCEPTION in Method 2: {e}")
import traceback
print(f"[COMPETITOR_ANALYSIS] Traceback:\n{traceback.format_exc()}")
logger.warning(f"[ResearchConfig] Could not retrieve competitor data from Step3ResearchService: {e}", exc_info=True)
# Fallback: Return empty response with helpful message
print(f"[COMPETITOR_ANALYSIS] ❌ FALLBACK: No competitor analysis data found for user_id={user_id}")
print(f"[COMPETITOR_ANALYSIS] Step 3 is completed (current_step={session.current_step}) but no data found in either source")
logger.info(f"[ResearchConfig] No competitor analysis data found for user {user_id} (step 3 completed but no data found)")
return CompetitorAnalysisResponse(
success=False,
error="Competitor analysis data was not found in the database. Please re-run competitor discovery in Step 3 of onboarding to generate and save competitor data."
)
except HTTPException:
print(f"[COMPETITOR_ANALYSIS] ❌ HTTPException raised (will be re-raised)")
raise
except Exception as e:
print(f"[COMPETITOR_ANALYSIS] ❌ CRITICAL ERROR: {e}")
import traceback
print(f"[COMPETITOR_ANALYSIS] Traceback:\n{traceback.format_exc()}")
logger.error(f"[ResearchConfig] Error getting competitor analysis for user {user_id if user_id else 'unknown'}: {e}", exc_info=True)
raise HTTPException(
status_code=500,
detail=f"Failed to get competitor analysis: {str(e)}"
)
finally:
print(f"[COMPETITOR_ANALYSIS] ===== END: Getting competitor analysis for user_id={user_id} =====\n")
# Helper functions from RESEARCH_AI_HYPERPERSONALIZATION.md
def _get_domain_suggestions(industry: str) -> list[str]: