database.py

# =========================================================
# ULTRA ADVANCED HYBRID NLP TO SQL ENGINE
# PROFESSIONAL MULTI-FILTER ENGINE
# MISTRAL / SQLCODER READY
# =========================================================

import re
import traceback
import os

from huggingface_hub import InferenceClient
from dotenv import load_dotenv
from sqlalchemy import create_engine, text

# =========================================================
# ENVIRONMENT SETUP
# =========================================================

load_dotenv()

HF_TOKEN = os.getenv("HF_TOKEN")
DATABASE_URL = os.getenv("DATABASE_URL")

# Initialize Mistral client
client = None
try:
    if HF_TOKEN:
        client = InferenceClient(
            model="mistralai/Mistral-7B-Instruct-v0.2",
            token=HF_TOKEN
        )
        print("✅ Mistral client initialized")
    else:
        print("⚠️ HF_TOKEN not set - LLM features disabled")
except Exception as e:
    print(f"⚠️ Mistral client error: {e}")
    client = None

# Initialize database engine
engine = None
try:
    if DATABASE_URL:
        engine = create_engine(DATABASE_URL)
        print("✅ Database connection initialized")
    else:
        print("⚠️ DATABASE_URL not set - Database features disabled")
except Exception as e:
    print(f"⚠️ Database connection warning: {e}")
    engine = None

# =========================================================
# CONFIG
# =========================================================

USE_LLM = True

# =========================================================
# DATABASE KNOWLEDGE
# =========================================================

SCHEMA = {
    "table": "vehicle_logs",
    "columns": [
        "timestamp",
        "plate",
        "state",
        "vehicle_type",
        "vehicle_conf",
        "camera_id",
        "location",
        "date",
        "hour",
        "day"
    ]
}

VALID_STATES = {
    "tn": "TN",
    "tamil nadu": "TN",

    "ka": "KA",
    "karnataka": "KA",

    "kl": "KL",
    "kerala": "KL",

    "ap": "AP",
    "andhra": "AP",

    "ts": "TS",
    "telangana": "TS",

    "mh": "MH",
    "maharashtra": "MH",

    "dl": "DL",
    "delhi": "DL",

    "gj": "GJ",
    "gujarat": "GJ",

    "rj": "RJ",
    "rajasthan": "RJ",

    "up": "UP",
    "uttar pradesh": "UP",

    "wb": "WB",
    "west bengal": "WB",

    "hr": "HR",
    "haryana": "HR",

    "pb": "PB",
    "punjab": "PB"
}

KNOWN_LOCATIONS = [
    "adyar",
    "guindy",
    "velachery",
    "besantnagar",
    "besant nagar",
    "thiruvanmiyur",
    "tnagar",
    "t nagar",
    "mylapore",
    "annanagar",
    "anna nagar",
    "koyambedu",
    "nungambakkam",
    "kotturpuram"
]

VEHICLE_TYPES = [
    "suv",
    "bus",
    "truck",
    "bike",
    "auto",
    "taxi",
    "car",
    "jeep",
    "sedan"
]

# =========================================================
# SQL CLEANER
# =========================================================

def clean_sql(sql):

    sql = sql.replace("```sql", "")
    sql = sql.replace("```", "")
    sql = sql.strip()

    if not sql.endswith(";"):
        sql += ";"

    return sql


# =========================================================
# SQL VALIDATOR
# =========================================================

def validate_sql(sql):

    blocked = [
        "DROP",
        "DELETE",
        "UPDATE",
        "INSERT",
        "ALTER",
        "CREATE",
        "TRUNCATE",
        "JOIN",
        "UNION"
    ]

    upper = sql.upper()

    for word in blocked:

        if word in upper:
            return False

    if not upper.startswith("SELECT"):
        return False

    if "VEHICLE_LOGS" not in upper:
        return False

    return True


# =========================================================
# PRODUCTION-GRADE HYBRID NLP ENGINE
# Advanced multi-filter, date-range, time-range support
# =========================================================

class FilterExtractor:
    """
    Production-grade filter extraction engine for complex real-world queries.
    Handles multi-filter extraction, date ranges, time ranges, and advanced aggregations.
    """
    
    def __init__(self):
        # ===== VEHICLE TYPE SYNONYMS =====
        self.vehicle_synonyms = {
            # Cars
            "car": "car", "cars": "car", "sedan": "car", "sedans": "car",
            "compact": "car", "compacts": "car", "hatchback": "car",
            # SUVs
            "suv": "suv", "suvs": "suv", "crossover": "suv",
            # Trucks
            "truck": "truck", "trucks": "truck", "lorry": "truck", "lorries": "truck",
            "heavy": "truck", "hgv": "truck",
            # Buses
            "bus": "bus", "buses": "bus", "coach": "bus", "shuttle": "bus",
            # Bikes
            "bike": "bike", "bikes": "bike", "motorcycle": "bike",
            "motorcycles": "bike", "motorbike": "bike", "two-wheeler": "bike",
            # Autos
            "auto": "auto", "autos": "auto", "autorickshaw": "auto",
            "auto-rickshaw": "auto", "tuk-tuk": "auto",
            # Jeeps
            "jeep": "jeep", "jeeps": "jeep", "4x4": "jeep",
            # Taxis
            "taxi": "taxi", "taxis": "taxi", "cab": "taxi", "cabs": "taxi"
        }
        
        # ===== DAY MAPPINGS =====
        self.day_map = {
            "monday": "Monday", "tuesday": "Tuesday", "wednesday": "Wednesday",
            "thursday": "Thursday", "friday": "Friday",
            "saturday": "Saturday", "sunday": "Sunday",
            "weekend": ["Saturday", "Sunday"],
            "weekday": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"]
        }
        
        # ===== LOCATION VARIANTS =====
        self.location_variants = {
            "adyar": ["adyar"],
            "besant nagar": ["besant", "besant nagar", "besantnagar"],
            "t nagar": ["t nagar", "tnagar", "t-nagar"],
            "anna nagar": ["anna", "anna nagar", "annanagar"],
            "velachery": ["velachery"],
            "guindy": ["guindy"],
            "thiruvanmiyur": ["thiruvanmiyur", "mylapore"],
            "mylapore": ["mylapore"],
            "koyambedu": ["koyambedu"],
            "nungambakkam": ["nungambakkam", "nungam"],
            "kotturpuram": ["kotturpuram"]
        }
        
        # ===== STATE MAPPINGS =====
        self.state_map = {
            "tn": "TN", "tamil": "TN", "tamil nadu": "TN",
            "ka": "KA", "karnataka": "KA",
            "kl": "KL", "kerala": "KL",
            "ap": "AP", "andhra": "AP", "andhra pradesh": "AP",
            "ts": "TS", "telangana": "TS",
            "mh": "MH", "maharashtra": "MH",
            "dl": "DL", "delhi": "DL",
            "gj": "GJ", "gujarat": "GJ",
            "rj": "RJ", "rajasthan": "RJ",
            "up": "UP", "uttar pradesh": "UP", "uttar": "UP",
            "wb": "WB", "west bengal": "WB",
            "hr": "HR", "haryana": "HR",
            "pb": "PB", "punjab": "PB"
        }
        
        # ===== TIME PERIOD MAPPINGS =====
        self.time_periods = {
            "morning": (5, 12),      # 5 AM to 12 PM
            "afternoon": (12, 17),   # 12 PM to 5 PM
            "evening": (17, 21),     # 5 PM to 9 PM
            "night": (21, 24),       # 9 PM to 12 AM
            "peak": (8, 10),         # Peak traffic (8-10 AM)
            "rush": (8, 10),         # Rush hour (8-10 AM)
            "midnight": (0, 4)       # Midnight (0-4 AM)
        }

    # ===== EXTRACTION METHODS =====
    
    def extract_plate(self, query):
        """Extract license plate number from query"""
        # Standard Indian plate format: XX00XX0000
        match = re.search(r'\b([A-Z]{2}\d{1,2}[A-Z]{1,3}\d{3,4})\b', query.upper())
        return match.group(1) if match else None
    
    def extract_state(self, query):
        """Extract state code from query"""
        q = query.lower()
        for key, state_code in self.state_map.items():
            # Use word boundaries to avoid partial matches
            if re.search(r'\b' + key + r'\b', q):
                return state_code
        return None
    
    def extract_location(self, query):
        """Extract location with variant matching"""
        q = query.lower()
        # Sort by length (longest first) to match longer variants first
        for canonical, variants in sorted(
            self.location_variants.items(),
            key=lambda x: max(len(v) for v in x[1]),
            reverse=True
        ):
            for variant in variants:
                if variant in q:
                    return canonical
        return None
    
    def extract_vehicle_type(self, query):
        """Extract vehicle type with synonym resolution"""
        q = query.lower()
        # Sort by length (longest first) to match longer synonyms first
        for synonym in sorted(self.vehicle_synonyms.keys(), key=len, reverse=True):
            if re.search(r'\b' + synonym + r'\b', q):
                return self.vehicle_synonyms[synonym]
        return None
    
    def extract_date_range(self, query):
        """Extract date range (from X to Y, between X and Y)"""
        # Pattern: "from DD-MM-YYYY to DD-MM-YYYY" or "between DD-MM-YYYY and DD-MM-YYYY"
        patterns = [
            r'from\s+(\d{1,2})[-/](\d{1,2})[-/](\d{4})\s+to\s+(\d{1,2})[-/](\d{1,2})[-/](\d{4})',
            r'between\s+(\d{1,2})[-/](\d{1,2})[-/](\d{4})\s+and\s+(\d{1,2})[-/](\d{1,2})[-/](\d{4})',
            r'from\s+(\d{4}-\d{2}-\d{2})\s+to\s+(\d{4}-\d{2}-\d{2})',
            r'between\s+(\d{4}-\d{2}-\d{2})\s+and\s+(\d{4}-\d{2}-\d{2})'
        ]
        
        for pattern in patterns:
            match = re.search(pattern, query, re.IGNORECASE)
            if match:
                groups = match.groups()
                if len(groups) == 6:  # DD-MM-YYYY format
                    start = f"{groups[2]}-{groups[1].zfill(2)}-{groups[0].zfill(2)}"
                    end = f"{groups[5]}-{groups[4].zfill(2)}-{groups[3].zfill(2)}"
                    return {"start": start, "end": end}
                elif len(groups) == 2:  # YYYY-MM-DD format
                    return {"start": groups[0], "end": groups[1]}
        
        return None
    
    def extract_date(self, query):
        """Extract single date and normalize format"""
        # YYYY-MM-DD format
        match = re.search(r'\d{4}-\d{2}-\d{2}', query)
        if match:
            return match.group(0)
        
        # DD-MM-YYYY or DD/MM/YYYY format
        match = re.search(r'(\d{1,2})[-/](\d{1,2})[-/](\d{4})', query)
        if match:
            day, month, year = match.groups()
            return f"{year}-{month.zfill(2)}-{day.zfill(2)}"
        
        return None
    
    def extract_time_range(self, query):
        """Extract time range (after X, before X, between X and Y)"""
        q = query.lower()
        
        # Check for time period keywords first (morning, afternoon, evening, night)
        for period, (start_hour, end_hour) in self.time_periods.items():
            if period in q:
                return {"start": start_hour, "end": end_hour}
        
        # Pattern: "after HH:MM" or "after HH AM/PM"
        after_match = re.search(r'after\s+(\d{1,2}):?(\d{0,2})\s*(am|pm)?', q)
        if after_match:
            hour = int(after_match.group(1))
            period = after_match.group(3)
            if period and period == "pm" and hour != 12:
                hour += 12
            elif period and period == "am" and hour == 12:
                hour = 0
            return {"start": hour, "end": 23}
        
        # Pattern: "before HH:MM" or "before HH AM/PM"
        before_match = re.search(r'before\s+(\d{1,2}):?(\d{0,2})\s*(am|pm)?', q)
        if before_match:
            hour = int(before_match.group(1))
            period = before_match.group(3)
            if period and period == "pm" and hour != 12:
                hour += 12
            elif period and period == "am" and hour == 12:
                hour = 0
            return {"start": 0, "end": hour}
        
        # Pattern: "between HH AM/PM and HH AM/PM"
        between_match = re.search(
            r'between\s+(\d{1,2}):?(\d{0,2})\s*(am|pm)\s+and\s+(\d{1,2}):?(\d{0,2})\s*(am|pm)',
            q
        )
        if between_match:
            hour1 = int(between_match.group(1))
            period1 = between_match.group(3)
            if period1 == "pm" and hour1 != 12:
                hour1 += 12
            elif period1 == "am" and hour1 == 12:
                hour1 = 0
            
            hour2 = int(between_match.group(4))
            period2 = between_match.group(6)
            if period2 == "pm" and hour2 != 12:
                hour2 += 12
            elif period2 == "am" and hour2 == 12:
                hour2 = 0
            
            return {"start": min(hour1, hour2), "end": max(hour1, hour2)}
        
        return None
    
    def extract_hour(self, query):
        """Extract single hour"""
        # Don't match if this is part of a time range
        if any(k in query.lower() for k in ["between", "from", "to", "after", "before"]):
            return None
        
        match = re.search(r'(\d{1,2}):?(\d{0,2})\s*(am|pm)?', query.lower())
        if match:
            hour = int(match.group(1))
            period = match.group(3)
            if period == "pm" and hour != 12:
                hour += 12
            elif period == "am" and hour == 12:
                hour = 0
            return hour if 0 <= hour < 24 else None
        
        return None
    
    def extract_day(self, query):
        """Extract day of week"""
        q = query.lower()
        for day_key, day_values in self.day_map.items():
            if day_key in q:
                return day_values
        return None
    
    def extract_confidence(self, query):
        """Extract confidence threshold"""
        match = re.search(r'(\d+(?:\.\d+)?)\s*(?:confidence|conf|accuracy)?', query.lower())
        if match:
            conf = float(match.group(1))
            # Normalize to 0-1 if given as percentage
            if conf > 1:
                conf = conf / 100
            return conf if 0 <= conf <= 1 else None
        return None
    
    def extract_filters(self, query):
        """Extract ALL filters simultaneously from query"""
        return {
            "plate": self.extract_plate(query),
            "state": self.extract_state(query),
            "location": self.extract_location(query),
            "vehicle_type": self.extract_vehicle_type(query),
            "date": self.extract_date(query),
            "date_range": self.extract_date_range(query),
            "day": self.extract_day(query),
            "hour": self.extract_hour(query),
            "time_range": self.extract_time_range(query),
            "confidence": self.extract_confidence(query)
        }
    
    def detect_intents(self, query):
        """Detect advanced query intents"""
        q = query.lower()
        return {
            "tracking": any(k in q for k in ["track", "history", "movement", "travel", "route", "where", "location"]),
            "count": any(k in q for k in ["count", "how many", "total", "number of"]),
            "analytics": any(k in q for k in ["analytics", "analysis", "statistics", "distribution"]),
            "top": any(k in q for k in ["top", "most", "leading"]),
            "latest": any(k in q for k in ["latest", "recent", "last", "new"]),
            "hourly": any(k in q for k in ["hourly", "by hour", "per hour"]),
            "daily": any(k in q for k in ["daily", "by day", "per day"]),
            "location_based": any(k in q for k in ["by location", "density", "traffic"]),
            "suspicious": any(k in q for k in ["suspicious", "repeated", "multiple", "across"]),
            "aggregation": any(k in q for k in ["group", "aggregate", "sum", "average"])
        }
    
    def build_sql(self, filters, intents):
        """
        Build production-grade SQL from filters and intents.
        Handles complex aggregations, date ranges, time ranges, and conditions.
        """
        
        # =========================================================
        # ANALYTICS QUERIES (priority over other queries)
        # =========================================================
        
        if intents["top"] or (intents["analytics"] and "top" in " ".join([k for k in intents.keys() if intents[k]])):
            return clean_sql("""
            SELECT plate, state, COUNT(*) as detections
            FROM vehicle_logs
            GROUP BY plate, state
            ORDER BY detections DESC
            LIMIT 20;
            """)
        
        if intents["hourly"] and intents["analytics"]:
            return clean_sql("""
            SELECT hour, COUNT(*) as traffic
            FROM vehicle_logs
            GROUP BY hour
            ORDER BY hour;
            """)
        
        if intents["location_based"] and intents["analytics"]:
            return clean_sql("""
            SELECT location, COUNT(*) as count
            FROM vehicle_logs
            WHERE location IS NOT NULL
            GROUP BY location
            ORDER BY count DESC
            LIMIT 20;
            """)
        
        if intents["suspicious"]:
            return clean_sql("""
            SELECT plate, state, COUNT(*) as detections,
                   COUNT(DISTINCT location) as locations,
                   COUNT(DISTINCT date) as days
            FROM vehicle_logs
            GROUP BY plate, state
            HAVING COUNT(*) > 5
            ORDER BY detections DESC
            LIMIT 20;
            """)
        
        # =========================================================
        # BUILD WHERE CLAUSE FROM FILTERS
        # =========================================================
        
        where_conditions = []
        
        # Plate filter
        if filters["plate"]:
            where_conditions.append(f"plate = '{filters['plate']}'")
        
        # State filter
        if filters["state"]:
            where_conditions.append(f"state = '{filters['state']}'")
        
        # Location filter
        if filters["location"]:
            where_conditions.append(f"LOWER(location) LIKE '%{filters['location'].lower()}%'")
        
        # Vehicle type filter
        if filters["vehicle_type"]:
            where_conditions.append(f"LOWER(vehicle_type) LIKE '%{filters['vehicle_type'].lower()}%'")
        
        # Date range filter
        if filters["date_range"]:
            start = filters["date_range"]["start"]
            end = filters["date_range"]["end"]
            where_conditions.append(f"date BETWEEN '{start}' AND '{end}'")
        elif filters["date"]:
            where_conditions.append(f"date = '{filters['date']}'")
        
        # Day filter
        if filters["day"]:
            if isinstance(filters["day"], list):
                day_conditions = [f"day = '{d}'" for d in filters["day"]]
                where_conditions.append(f"({' OR '.join(day_conditions)})")
            else:
                where_conditions.append(f"day = '{filters['day']}'")
        
        # Time range filter
        if filters["time_range"]:
            start = filters["time_range"]["start"]
            end = filters["time_range"]["end"]
            if start < end:
                where_conditions.append(f"hour BETWEEN {start} AND {end}")
            else:  # Handles ranges like 9 PM to 4 AM (21 to 4)
                where_conditions.append(f"(hour >= {start} OR hour <= {end})")
        elif filters["hour"] is not None:
            where_conditions.append(f"hour = {filters['hour']}")
        
        # Confidence filter
        if filters["confidence"] is not None:
            where_conditions.append(f"vehicle_conf >= {filters['confidence']}")
        
        # =========================================================
        # GENERATE FINAL SQL
        # =========================================================
        
        where_clause = " AND ".join(where_conditions) if where_conditions else "1=1"
        
        # Count queries
        if intents["count"]:
            if filters["plate"]:
                sql = f"""
                SELECT plate, COUNT(*) as detections
                FROM vehicle_logs
                WHERE {where_clause}
                GROUP BY plate
                ORDER BY detections DESC;
                """
            else:
                sql = f"""
                SELECT COUNT(*) as total
                FROM vehicle_logs
                WHERE {where_clause};
                """
        
        # Tracking queries (show detailed records)
        elif intents["tracking"]:
            sql = f"""
            SELECT timestamp, plate, state, vehicle_type, location, camera_id, date, hour, day
            FROM vehicle_logs
            WHERE {where_clause}
            ORDER BY timestamp DESC
            LIMIT 100;
            """
        
        # Hourly aggregation
        elif intents["hourly"]:
            sql = f"""
            SELECT hour, COUNT(*) as traffic
            FROM vehicle_logs
            WHERE {where_clause}
            GROUP BY hour
            ORDER BY hour;
            """
        
        # Location-based aggregation
        elif intents["location_based"]:
            sql = f"""
            SELECT location, COUNT(*) as count
            FROM vehicle_logs
            WHERE {where_clause} AND location IS NOT NULL
            GROUP BY location
            ORDER BY count DESC;
            """
        
        # Default: return all matching records
        else:
            sql = f"""
            SELECT *
            FROM vehicle_logs
            WHERE {where_clause}
            ORDER BY timestamp DESC
            LIMIT 100;
            """
        
        return clean_sql(sql)


def ask_llm(user_query):
    """
    Production-grade hybrid NLP-to-SQL engine.
    Handles complex real-world queries with multiple filters, date ranges, time ranges, and aggregations.
    
    Features:
    - Multi-filter extraction (plate, state, location, vehicle type, date, time, confidence)
    - Date range support (from X to Y)
    - Time range support (after X, before X, between X and Y)
    - Time period recognition (morning, afternoon, evening, night, peak hour, rush hour)
    - Advanced intent detection (tracking, count, analytics, top vehicles, suspicious vehicles, etc.)
    - Production SQL generation with proper GROUP BY, HAVING, ORDER BY
    - Timeout protection
    
    Example queries:
    - "show buses in adyar from 10-04-2026 to 18-10-2026"
    - "show TN cars after 8 PM"
    - "show suspicious vehicles detected in more than 5 locations"
    - "show traffic density by location"
    - "show top 10 most detected vehicles"
    - "count bikes between 6 PM and 9 PM"
    """
    
    try:
        # Initialize the advanced filter extractor
        extractor = FilterExtractor()
        
        # Extract ALL filters from the query (simultaneous extraction)
        filters = extractor.extract_filters(user_query)
        
        # Detect query intents
        intents = extractor.detect_intents(user_query)
        
        # Log extracted information for debugging
        print(f"\n📊 QUERY ANALYSIS:")
        print(f"   Extracted Filters:")
        print(f"     - Plate: {filters['plate']}")
        print(f"     - State: {filters['state']}")
        print(f"     - Location: {filters['location']}")
        print(f"     - Vehicle Type: {filters['vehicle_type']}")
        print(f"     - Date: {filters['date']}")
        print(f"     - Date Range: {filters['date_range']}")
        print(f"     - Day: {filters['day']}")
        print(f"     - Hour: {filters['hour']}")
        print(f"     - Time Range: {filters['time_range']}")
        print(f"     - Confidence: {filters['confidence']}")
        print(f"   Detected Intents:")
        intent_list = [k for k, v in intents.items() if v]
        print(f"     - {', '.join(intent_list) if intent_list else 'General query'}")
        
        # Build SQL from filters and intents
        sql = extractor.build_sql(filters, intents)
        
        return sql
        
    except Exception as e:
        print(f"❌ Filter extraction error: {e}")
        traceback.print_exc()
        # Fallback to basic query
        return clean_sql("SELECT * FROM vehicle_logs ORDER BY timestamp DESC LIMIT 10;")



# =========================================================
# QUERY EXECUTION
# =========================================================

def run_query(user_query):
    """Execute NLP-to-SQL query with timeout protection"""

    sql = ""
    try:

        sql = ask_llm(user_query)

        print("\n" + "="*40)
        print("USER QUERY:")
        print(user_query)

        print("\nGENERATED SQL:")
        print(sql)
        print("="*40)

        if engine is None:
            return {
                "query": user_query,
                "error": "❌ Database not configured - DATABASE_URL missing",
                "sql": sql,
                "result": [],
                "count": 0
            }

        try:
            # Execute with timeout protection
            with engine.connect() as conn:
                # Set statement timeout to 30 seconds
                conn.execute(text("SET statement_timeout = 30000"))  # 30 seconds
                
                result = conn.execute(text(sql))

                rows = [
                    dict(r._mapping)
                    for r in result
                ]

            return {
                "query": user_query,
                "sql": sql,
                "count": len(rows),
                "result": rows
            }
            
        except Exception as query_error:
            print(f"❌ Query Execution Error (possible timeout): {query_error}")
            return {
                "query": user_query,
                "error": f"Query timeout or error: {str(query_error)}",
                "sql": sql,
                "result": [],
                "count": 0
            }

    except Exception as e:

        print(f"❌ Run Query Error: {e}")
        traceback.print_exc()

        return {
            "query": user_query,
            "error": str(e),
            "sql": sql if sql else "",
            "result": [],
            "count": 0
        }

# =========================================================
# DATABASE OPERATIONS
# =========================================================

def save_detection(plate, state, vehicle_type, vehicle_conf, date, time):
    """Save a vehicle detection to the database
    
    Note: The table schema uses timestamp, date, hour, day columns.
    The 'time' parameter is extracted to hour for the hour column.
    """
    
    try:
        
        if engine is None:
            print("⚠️ Engine not initialized - save_detection skipped")
            return False
        
        # Extract hour from time string (HH:MM:SS)
        try:
            hour = int(time.split(":")[0]) if time else 0
        except:
            hour = 0
        
        # Extract day of week from date (simplified)
        from datetime import datetime
        try:
            dt = datetime.strptime(date, "%Y-%m-%d")
            day = dt.strftime("%A")
        except:
            day = "Unknown"
        
        # Use timestamp for current time, date for the date field, hour for hourly grouping
        query = f"""
        INSERT INTO vehicle_logs 
        (plate, state, vehicle_type, vehicle_conf, date, hour, day, timestamp, camera_id, location)
        VALUES ('{plate}', '{state}', '{vehicle_type}', {vehicle_conf}, '{date}', {hour}, '{day}', NOW(), 'CAM-01', 'default')
        """
        
        with engine.connect() as conn:
            conn.execute(text(query))
            conn.commit()
            
        print(f"✅ Saved: {plate} from {state} at {time}")
        return True
        
    except Exception as e:
        print(f"❌ Save Error: {e}")
        traceback.print_exc()
        return False


def health_check():
    """Check database health with timeout protection"""
    
    try:
        
        if engine is None:
            return False, "❌ Database not configured"
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 10000"))  # 10 second timeout
            result = conn.execute(text("SELECT COUNT(*) FROM vehicle_logs"))
            count = result.scalar()
            
        return True, f"✅ Database OK - {count} records"
        
    except Exception as e:
        print(f"❌ Health Check Error (timeout?): {e}")
        return False, f"❌ Database Error: {str(e)}"


def get_vehicles_by_state():
    """Get vehicle count by state with timeout protection"""
    
    try:
        
        sql = """
        SELECT state, COUNT(*) as count
        FROM vehicle_logs
        GROUP BY state
        ORDER BY count DESC
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))  # 15 second timeout
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
            
        return rows
        
    except Exception as e:
        print(f"❌ State Query Error (timeout?): {e}")
        return []


def get_hourly_traffic():
    """Get traffic by hour with timeout protection"""
    
    try:
        
        sql = """
        SELECT hour, COUNT(*) as traffic
        FROM vehicle_logs
        GROUP BY hour
        ORDER BY hour
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))  # 15 second timeout
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
            
        return rows
        
    except Exception as e:
        print(f"❌ Hourly Traffic Error (timeout?): {e}")
        return []


def get_top_plates():
    """Get top detected plates with timeout protection"""
    
    try:
        
        sql = """
        SELECT plate, COUNT(*) as detections
        FROM vehicle_logs
        GROUP BY plate
        ORDER BY detections DESC
        LIMIT 20
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))  # 15 second timeout
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
            
        return rows
        
    except Exception as e:
        print(f"❌ Top Plates Error (timeout?): {e}")
        return []


def get_suspicious_vehicles():
    """Get vehicles detected multiple times (potentially suspicious) with timeout protection"""
    
    try:
        
        sql = """
        SELECT plate, state, COUNT(*) as detections, 
               COUNT(DISTINCT location) as locations,
               COUNT(DISTINCT date) as days
        FROM vehicle_logs
        GROUP BY plate, state
        HAVING COUNT(*) > 5
        ORDER BY detections DESC
        LIMIT 20
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))  # 15 second timeout
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
            
        return rows
        
    except Exception as e:
        print(f"❌ Suspicious Vehicles Error (timeout?): {e}")
        return []


# =========================================================
# ADVANCED ANALYTICAL FUNCTIONS
# =========================================================

def get_route_history(plate, limit=50):
    """
    Get route history for a specific vehicle.
    Shows all detections in chronological order with locations.
    """
    try:
        sql = f"""
        SELECT timestamp, plate, state, location, camera_id, date, hour, day
        FROM vehicle_logs
        WHERE plate = '{plate}'
        ORDER BY timestamp DESC
        LIMIT {limit}
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ Route History Error: {e}")
        return []


def get_vehicles_by_location(location):
    """Get all vehicles detected in a specific location"""
    try:
        sql = f"""
        SELECT DISTINCT plate, state, COUNT(*) as detections
        FROM vehicle_logs
        WHERE LOWER(location) LIKE '%{location.lower()}%'
        GROUP BY plate, state
        ORDER BY detections DESC
        LIMIT 50
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ Vehicles by Location Error: {e}")
        return []


def get_multi_location_detections(min_locations=2):
    """Get vehicles detected across multiple locations (suspicious activity indicator)"""
    try:
        sql = f"""
        SELECT plate, state, COUNT(*) as detections,
               COUNT(DISTINCT location) as locations,
               COUNT(DISTINCT date) as days
        FROM vehicle_logs
        GROUP BY plate, state
        HAVING COUNT(DISTINCT location) >= {min_locations}
        ORDER BY locations DESC, detections DESC
        LIMIT 20
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ Multi-Location Detection Error: {e}")
        return []


def get_peak_traffic_hours():
    """Identify peak traffic hours based on detections"""
    try:
        sql = """
        SELECT hour, COUNT(*) as traffic_count,
               ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage
        FROM vehicle_logs
        GROUP BY hour
        ORDER BY traffic_count DESC
        LIMIT 10
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ Peak Traffic Hours Error: {e}")
        return []


def get_vehicle_density_by_location():
    """Get traffic density (vehicle count) by location"""
    try:
        sql = """
        SELECT location, COUNT(*) as vehicle_count,
               COUNT(DISTINCT plate) as unique_vehicles,
               ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage
        FROM vehicle_logs
        WHERE location IS NOT NULL
        GROUP BY location
        ORDER BY vehicle_count DESC
        LIMIT 20
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ Vehicle Density Error: {e}")
        return []


def get_high_confidence_detections(confidence_threshold=0.9):
    """Get detections with high confidence scores"""
    try:
        sql = f"""
        SELECT plate, state, vehicle_type, COUNT(*) as detections,
               ROUND(AVG(vehicle_conf), 3) as avg_confidence
        FROM vehicle_logs
        WHERE vehicle_conf >= {confidence_threshold}
        GROUP BY plate, state, vehicle_type
        ORDER BY avg_confidence DESC, detections DESC
        LIMIT 30
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ High Confidence Detections Error: {e}")
        return []


def get_daily_traffic_summary(date=None):
    """Get traffic summary for a specific date or today"""
    try:
        if date:
            where_clause = f"WHERE date = '{date}'"
        else:
            where_clause = "WHERE date = CURDATE()"
        
        sql = f"""
        SELECT 
            COUNT(*) as total_vehicles,
            COUNT(DISTINCT plate) as unique_vehicles,
            COUNT(DISTINCT location) as locations_covered,
            COUNT(DISTINCT hour) as peak_hours
        FROM vehicle_logs
        {where_clause}
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            row = dict(result.fetchone()._mapping)
        
        return row
    except Exception as e:
        print(f"❌ Daily Summary Error: {e}")
        return {}


def get_state_wise_distribution():
    """Get vehicle distribution across states"""
    try:
        sql = """
        SELECT state, COUNT(*) as detections,
               COUNT(DISTINCT plate) as unique_vehicles,
               ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage
        FROM vehicle_logs
        GROUP BY state
        ORDER BY detections DESC
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ State Distribution Error: {e}")
        return []


def query_by_date_range(start_date, end_date, state=None, location=None):
    """Query vehicles detected within a date range"""
    try:
        where_conditions = [f"date BETWEEN '{start_date}' AND '{end_date}'"]
        
        if state:
            where_conditions.append(f"state = '{state}'")
        if location:
            where_conditions.append(f"LOWER(location) LIKE '%{location.lower()}%'")
        
        where_clause = " AND ".join(where_conditions)
        
        sql = f"""
        SELECT *
        FROM vehicle_logs
        WHERE {where_clause}
        ORDER BY timestamp DESC
        LIMIT 500
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 30000"))  # Longer timeout for large ranges
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ Date Range Query Error: {e}")
        return []


def query_by_time_range(start_hour, end_hour, location=None, vehicle_type=None):
    """Query vehicles detected within a time range (hour of day)"""
    try:
        where_conditions = []
        
        if start_hour < end_hour:
            where_conditions.append(f"hour BETWEEN {start_hour} AND {end_hour}")
        else:  # Handles ranges like 9 PM to 4 AM (21 to 4)
            where_conditions.append(f"(hour >= {start_hour} OR hour <= {end_hour})")
        
        if location:
            where_conditions.append(f"LOWER(location) LIKE '%{location.lower()}%'")
        if vehicle_type:
            where_conditions.append(f"LOWER(vehicle_type) LIKE '%{vehicle_type.lower()}%'")
        
        where_clause = " AND ".join(where_conditions)
        
        sql = f"""
        SELECT *
        FROM vehicle_logs
        WHERE {where_clause}
        ORDER BY timestamp DESC
        LIMIT 200
        """
        
        with engine.connect() as conn:
            conn.execute(text("SET statement_timeout = 15000"))
            result = conn.execute(text(sql))
            rows = [dict(r._mapping) for r in result]
        
        return rows
    except Exception as e:
        print(f"❌ Time Range Query Error: {e}")
        return []