🚀 Unified Restaurant Search - One Endpoint for Everything!

The ultimate restaurant search endpoint that handles natural language queries, structured filters, and everything in between.

🎯 How it works:

• Natural Language: Just type what you want like “italian restaurants” or “best pizza near me”
• Structured Filters: Use specific parameters for precise control
• Smart Parsing: Automatically understands your intent and applies the best strategy
• Proper Sorting: Results are intelligently ranked by relevance, rating, and distance

🔍 Natural Language Examples:

• ?q=italian restaurants → Finds Italian restaurants
• ?q=best pizza near me → Finds top-rated pizza places nearby
• ?q=romantic dinner spots → Finds romantic restaurants
• ?q=cheap sushi with delivery → Finds affordable sushi with delivery

📍 Location Parameters:

• lat/lng: Your coordinates (decimal degrees)
• radius: Search radius in meters (default: 5000, max: 50000)

🍽️ Preference Parameters:

• cuisines: italian,chinese,mexican,indian,thai,french,american
• priceLevel: 1=$ (budget), 2=$$ (moderate), 3=$$$ (expensive), 4=$$$$ (luxury)
• features: wifi,parking,delivery,takeout,reservations,outdoor,halal,vegan
• tags: romantic,family-friendly,business,casual,fine-dining,popular

🎭 Context Parameters:

• breakfast: Morning dining (6-11 AM optimized)
• lunch: Midday meals (11 AM-3 PM optimized)
• dinner: Evening dining (5-10 PM optimized)
• late_night: Late hours (10 PM+ optimized)
• date_night: Romantic atmosphere, upscale
• family: Kid-friendly, spacious, parking
• business: Quiet, wifi, professional atmosphere

🧮 Advanced Features:

• useBayesian=true: Enable probabilistic modeling for better accuracy
• userId: Enable personalized recommendations (header: x-user-id)

⚡ Performance:

• < 50ms: Hot cache hits
• < 150ms: Cold cache with database query
• < 500ms: Complex multi-strategy analysis
• Redis caching: 5-30 minute TTL based on data type

🎯 Smart Strategy Selection:

• Natural language queries → NLP parsing + content-based
• Location + preferences → Hybrid approach
• Location only → Location-popular
• User ID + preferences → Collaborative filtering
• Context only → Context-aware
• Default → Popular restaurants

📊 Response Format:

• restaurants: Array of restaurants with proper sorting
• strategy: Which strategy was used
• executionTime: Response time in milliseconds
• fromCache: Whether result came from cache
• totalResults: Total number of matching restaurants
• query: Parsed query information (for natural language queries)