src/services/smart_context.py

import time
import re
from typing import Dict, Any, List, Optional
from datetime import datetime
from utils.config import config

class SmartContextDetector:
    """Intelligently detects when context is relevant to user queries"""
    
    def __init__(self):
        # Keywords that suggest time/weather relevance
        self.time_indicators = [
            'time', 'date', 'today', 'now', 'current', 'moment', 
            'morning', 'afternoon', 'evening', 'night', 'weekend',
            'what time', 'what day', 'what year', 'what month'
        ]
        
        self.weather_indicators = [
            'weather', 'temperature', 'rain', 'snow', 'sunny', 'cloudy',
            'forecast', 'climate', 'season', 'hot', 'cold', 'warm', 'cool',
            'umbrella', 'jacket', 'outdoor', 'outside'
        ]
        
        self.location_indicators = [
            'in', 'at', 'near', 'around', 'local', 'here', 'there'
        ]
    
    def should_include_time_context(self, user_query: str, 
                                  conversation_history: List[Dict] = None) -> bool:
        """Determine if time context is relevant to the query"""
        query_lower = user_query.lower()
        
        # Direct time references
        if any(indicator in query_lower for indicator in self.time_indicators):
            return True
        
        # Check conversation context for time-related discussions
        if conversation_history:
            recent_messages = conversation_history[-3:]  # Last 3 messages
            context_text = " ".join([msg.get('content', '') for msg in recent_messages]).lower()
            if any(word in context_text for word in self.time_indicators):
                return True
        
        return False
    
    def should_include_weather_context(self, user_query: str,
                                     conversation_history: List[Dict] = None) -> bool:
        """Determine if weather context is relevant to the query"""
        query_lower = user_query.lower()
        
        # Direct weather references
        if any(indicator in query_lower for indicator in self.weather_indicators):
            return True
        
        # Location + activity combinations that often involve weather
        location_mentioned = any(loc.lower() in query_lower for loc in 
                               ['new york', 'london', 'tokyo', 'paris', 'los angeles', 'sydney', 'singapore', 'mumbai'])
        activity_mentioned = any(activity in query_lower for activity in 
                               ['outdoor', 'outside', 'walk', 'run', 'travel', 'trip', 'plans', 'going'])
        
        if location_mentioned and activity_mentioned:
            return True
        
        # Check conversation context
        if conversation_history:
            recent_messages = conversation_history[-3:]
            context_text = " ".join([msg.get('content', '') for msg in recent_messages]).lower()
            if any(word in context_text for word in self.weather_indicators):
                return True
        
        return False
    
    def extract_location_if_relevant(self, user_query: str) -> Optional[str]:
        """Extract location if query suggests location-specific context"""
        # Common locations
        locations = {
            'new york': ['new york', 'ny', 'nyc'],
            'london': ['london', 'uk', 'england'],
            'tokyo': ['tokyo', 'japan', 'jp'],
            'paris': ['paris', 'france', 'fr'],
            'los angeles': ['los angeles', 'la', 'california'],
            'sydney': ['sydney', 'australia', 'au'],
            'singapore': ['singapore', 'sg'],
            'mumbai': ['mumbai', 'india', 'in']
        }
        
        query_lower = user_query.lower()
        for location, aliases in locations.items():
            if any(alias in query_lower for alias in aliases):
                return location
        
        return None
    
    def get_relevant_context(self, user_query: str, 
                           conversation_history: List[Dict] = None) -> Dict[str, Any]:
        """Get only the context that's actually relevant"""
        context = {
            'include_time': self.should_include_time_context(user_query, conversation_history),
            'include_weather': self.should_include_weather_context(user_query, conversation_history),
            'detected_location': self.extract_location_if_relevant(user_query),
            'timestamp': time.time()
        }
        
        # Add actual context data only if needed
        if context['include_time']:
            now = datetime.now()
            context['time_data'] = {
                'current_time': now.strftime("%A, %B %d, %Y at %I:%M %p"),
                'day_of_week': now.strftime("%A"),
                'is_business_hours': 9 <= now.hour <= 17
            }
        
        return context

# Global instance
smart_context = SmartContextDetector()