173 lines
6.1 KiB
Python
173 lines
6.1 KiB
Python
"""
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Research Cache Service
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Provides intelligent caching for Google grounded research results to reduce API costs.
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Only returns cached results for exact keyword matches to ensure accuracy.
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"""
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import hashlib
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import json
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from typing import Dict, Any, Optional, List
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from datetime import datetime, timedelta
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from loguru import logger
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class ResearchCache:
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"""Cache for research results with exact keyword matching."""
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def __init__(self, max_cache_size: int = 100, cache_ttl_hours: int = 24):
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"""
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Initialize the research cache.
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Args:
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max_cache_size: Maximum number of cached entries
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cache_ttl_hours: Time-to-live for cache entries in hours
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"""
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self.cache: Dict[str, Dict[str, Any]] = {}
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self.max_cache_size = max_cache_size
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self.cache_ttl = timedelta(hours=cache_ttl_hours)
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def _generate_cache_key(self, keywords: List[str], industry: str, target_audience: str) -> str:
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"""
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Generate a cache key based on exact keyword match.
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Args:
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keywords: List of research keywords
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industry: Industry context
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target_audience: Target audience context
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Returns:
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MD5 hash of the normalized parameters
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"""
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# Normalize and sort keywords for consistent hashing
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normalized_keywords = sorted([kw.lower().strip() for kw in keywords])
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normalized_industry = industry.lower().strip() if industry else "general"
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normalized_audience = target_audience.lower().strip() if target_audience else "general"
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# Create a consistent string representation
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cache_string = f"{normalized_keywords}|{normalized_industry}|{normalized_audience}"
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# Generate MD5 hash
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return hashlib.md5(cache_string.encode('utf-8')).hexdigest()
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def _is_cache_entry_valid(self, entry: Dict[str, Any]) -> bool:
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"""Check if a cache entry is still valid (not expired)."""
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if 'created_at' not in entry:
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return False
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created_at = datetime.fromisoformat(entry['created_at'])
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return datetime.now() - created_at < self.cache_ttl
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def _cleanup_expired_entries(self):
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"""Remove expired cache entries."""
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expired_keys = []
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for key, entry in self.cache.items():
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if not self._is_cache_entry_valid(entry):
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expired_keys.append(key)
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for key in expired_keys:
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del self.cache[key]
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logger.debug(f"Removed expired cache entry: {key}")
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def _evict_oldest_entries(self, num_to_evict: int):
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"""Evict the oldest cache entries when cache is full."""
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# Sort by creation time and remove oldest entries
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sorted_entries = sorted(
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self.cache.items(),
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key=lambda x: x[1].get('created_at', ''),
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reverse=False
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)
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for i in range(min(num_to_evict, len(sorted_entries))):
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key = sorted_entries[i][0]
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del self.cache[key]
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logger.debug(f"Evicted oldest cache entry: {key}")
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def get_cached_result(self, keywords: List[str], industry: str, target_audience: str) -> Optional[Dict[str, Any]]:
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"""
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Get cached research result for exact keyword match.
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Args:
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keywords: List of research keywords
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industry: Industry context
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target_audience: Target audience context
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Returns:
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Cached research result if found and valid, None otherwise
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"""
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cache_key = self._generate_cache_key(keywords, industry, target_audience)
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if cache_key not in self.cache:
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logger.debug(f"Cache miss for keywords: {keywords}")
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return None
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entry = self.cache[cache_key]
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# Check if entry is still valid
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if not self._is_cache_entry_valid(entry):
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del self.cache[cache_key]
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logger.debug(f"Cache entry expired for keywords: {keywords}")
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return None
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logger.info(f"Cache hit for keywords: {keywords} (saved API call)")
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return entry.get('result')
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def cache_result(self, keywords: List[str], industry: str, target_audience: str, result: Dict[str, Any]):
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"""
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Cache a research result.
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Args:
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keywords: List of research keywords
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industry: Industry context
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target_audience: Target audience context
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result: Research result to cache
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"""
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cache_key = self._generate_cache_key(keywords, industry, target_audience)
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# Cleanup expired entries first
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self._cleanup_expired_entries()
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# Check if cache is full and evict if necessary
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if len(self.cache) >= self.max_cache_size:
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num_to_evict = len(self.cache) - self.max_cache_size + 1
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self._evict_oldest_entries(num_to_evict)
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# Store the result
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self.cache[cache_key] = {
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'result': result,
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'created_at': datetime.now().isoformat(),
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'keywords': keywords,
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'industry': industry,
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'target_audience': target_audience
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}
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logger.info(f"Cached research result for keywords: {keywords}")
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def get_cache_stats(self) -> Dict[str, Any]:
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"""Get cache statistics."""
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self._cleanup_expired_entries()
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return {
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'total_entries': len(self.cache),
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'max_size': self.max_cache_size,
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'ttl_hours': self.cache_ttl.total_seconds() / 3600,
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'entries': [
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{
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'keywords': entry['keywords'],
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'industry': entry['industry'],
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'target_audience': entry['target_audience'],
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'created_at': entry['created_at']
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}
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for entry in self.cache.values()
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]
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}
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def clear_cache(self):
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"""Clear all cached entries."""
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self.cache.clear()
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logger.info("Research cache cleared")
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# Global cache instance
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research_cache = ResearchCache()
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