Research component integration, Copilotkit implementation, SEO copilotkit implementation, Wix SEO metadata complete, Wix SEO metadata review
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ajaysi
188
backend/services/blog_writer/research/exa_provider.py
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188
backend/services/blog_writer/research/exa_provider.py
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"""
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Exa Research Provider
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Neural search implementation using Exa API for high-quality, citation-rich research.
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"""
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from exa_py import Exa
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import os
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from loguru import logger
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from models.subscription_models import APIProvider
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from .base_provider import ResearchProvider as BaseProvider
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class ExaResearchProvider(BaseProvider):
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"""Exa neural search provider."""
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def __init__(self):
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self.api_key = os.getenv("EXA_API_KEY")
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if not self.api_key:
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raise RuntimeError("EXA_API_KEY not configured")
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self.exa = Exa(self.api_key)
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logger.info("✅ Exa Research Provider initialized")
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async def search(self, prompt, topic, industry, target_audience, config, user_id):
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"""Execute Exa neural search and return standardized results."""
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# Build Exa query
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query = f"{topic} {industry} {target_audience}"
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# Map source types to Exa categories
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category = self._map_source_type_to_category(config.source_types)
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logger.info(f"[Exa Research] Executing search: {query}")
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# Execute Exa search
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results = self.exa.search_and_contents(
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query,
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type="auto",
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category=category,
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num_results=min(config.max_sources, 25),
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contents={
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'text': {'max_characters': 1000},
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'summary': {'query': f"Key insights about {topic}"},
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'highlights': {
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'num_sentences': 2,
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'highlights_per_url': 3
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}
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}
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)
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# Transform to standardized format
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sources = self._transform_sources(results.results)
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content = self._aggregate_content(results.results)
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search_type = getattr(results, 'resolvedSearchType', 'neural') if hasattr(results, 'resolvedSearchType') else 'neural'
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# Get cost if available
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cost = 0.005 # Default Exa cost for 1-25 results
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if hasattr(results, 'costDollars'):
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if hasattr(results.costDollars, 'total'):
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cost = results.costDollars.total
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logger.info(f"[Exa Research] Search completed: {len(sources)} sources, type: {search_type}")
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return {
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'sources': sources,
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'content': content,
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'search_type': search_type,
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'provider': 'exa',
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'search_queries': [query],
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'cost': {'total': cost}
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}
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def get_provider_enum(self):
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"""Return EXA provider enum for subscription tracking."""
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return APIProvider.EXA
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def estimate_tokens(self) -> int:
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"""Estimate token usage for Exa (not token-based)."""
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return 0 # Exa is per-search, not token-based
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def _map_source_type_to_category(self, source_types):
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"""Map SourceType enum to Exa category parameter."""
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if not source_types:
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return None
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category_map = {
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'research paper': 'research paper',
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'news': 'news',
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'web': 'personal site',
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'industry': 'company',
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'expert': 'linkedin profile'
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}
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for st in source_types:
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if st.value in category_map:
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return category_map[st.value]
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return None
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def _transform_sources(self, results):
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"""Transform Exa results to ResearchSource format."""
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sources = []
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for idx, result in enumerate(results):
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source_type = self._determine_source_type(result.url if hasattr(result, 'url') else '')
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sources.append({
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'title': result.title if hasattr(result, 'title') else '',
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'url': result.url if hasattr(result, 'url') else '',
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'excerpt': self._get_excerpt(result),
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'credibility_score': 0.85, # Exa results are high quality
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'published_at': result.publishedDate if hasattr(result, 'publishedDate') else None,
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'index': idx,
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'source_type': source_type,
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'content': result.text if hasattr(result, 'text') else '',
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'highlights': result.highlights if hasattr(result, 'highlights') else [],
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'summary': result.summary if hasattr(result, 'summary') else ''
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})
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return sources
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def _get_excerpt(self, result):
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"""Extract excerpt from Exa result."""
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if hasattr(result, 'text') and result.text:
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return result.text[:500]
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elif hasattr(result, 'summary') and result.summary:
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return result.summary
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return ''
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def _determine_source_type(self, url):
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"""Determine source type from URL."""
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if not url:
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return 'web'
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url_lower = url.lower()
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if 'arxiv.org' in url_lower or 'research' in url_lower:
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return 'academic'
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elif any(news in url_lower for news in ['cnn.com', 'bbc.com', 'reuters.com', 'theguardian.com']):
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return 'news'
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elif 'linkedin.com' in url_lower:
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return 'expert'
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else:
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return 'web'
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def _aggregate_content(self, results):
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"""Aggregate content from Exa results for LLM analysis."""
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content_parts = []
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for idx, result in enumerate(results):
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if hasattr(result, 'summary') and result.summary:
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content_parts.append(f"Source {idx + 1}: {result.summary}")
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elif hasattr(result, 'text') and result.text:
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content_parts.append(f"Source {idx + 1}: {result.text[:1000]}")
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return "\n\n".join(content_parts)
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def track_exa_usage(self, user_id: str, cost: float):
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"""Track Exa API usage after successful call."""
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from services.database import get_db
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from services.subscription import PricingService
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from sqlalchemy import text
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db = next(get_db())
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try:
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pricing_service = PricingService(db)
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current_period = pricing_service.get_current_billing_period(user_id)
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# Update exa_calls and exa_cost via SQL UPDATE
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update_query = text("""
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UPDATE usage_summaries
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SET exa_calls = COALESCE(exa_calls, 0) + 1,
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exa_cost = COALESCE(exa_cost, 0) + :cost,
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total_calls = total_calls + 1,
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total_cost = total_cost + :cost
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WHERE user_id = :user_id AND billing_period = :period
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""")
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db.execute(update_query, {
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'cost': cost,
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'user_id': user_id,
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'period': current_period
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})
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db.commit()
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logger.info(f"[Exa] Tracked usage: user={user_id}, cost=${cost}")
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except Exception as e:
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logger.error(f"[Exa] Failed to track usage: {e}")
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db.rollback()
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finally:
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db.close()
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