# database.py - Updated for new schema with view option
from supabase import create_client
from typing import Dict, List, Optional
import pandas as pd
from datetime import datetime
from config import SUPABASE_URL, SUPABASE_KEY

# Initialize Supabase client
supabase = create_client(SUPABASE_URL, SUPABASE_KEY)

def ensure_days_past_due_current():
    """
    Update days_past_due to current values.
    Call this at startup or periodically to keep data fresh.
    """
    try:
        # This runs the UPDATE query to refresh days_past_due
        supabase.rpc('refresh_overdue_days', {}).execute()
    except:
        # If the function doesn't exist, we can skip it
        # The data will use whatever days_past_due values are in the table
        pass

def query_database(query: str) -> Dict:
    """Execute AR queries against single ar_data table"""
    try:
        query_lower = query.lower()
        
        # 1. Get all late payment customers
        if "late" in query_lower and "customer" in query_lower:
            result = supabase.table('ar_data')\
                .select('*')\
                .gt('days_past_due', 0)\
                .is_('paid_date', 'null')\
                .execute()
            
            if result.data:
                df = pd.DataFrame(result.data)
                # Group by customer (simple grouping)
                summary = df.groupby(['customer_id', 'company_name', 'customer_email']).agg({
                    'amount': 'sum',
                    'days_past_due': 'max',
                    'invoice_id': 'count'
                }).reset_index()
                
                summary.columns = ['customer_id', 'company_name', 'email', 'total_overdue', 'max_days_overdue', 'invoice_count']
                
                return {
                    "success": True,
                    "data": summary.to_dict('records'),
                    "row_count": len(summary)
                }
        
        # 2. Get invoices overdue by X days
        elif "invoice" in query_lower and "days" in query_lower:
            import re
            days_match = re.search(r'(\d+)\s*days?', query_lower)
            days = int(days_match.group(1)) if days_match else 30
            
            result = supabase.table('ar_data')\
                .select('*')\
                .gt('days_past_due', days)\
                .is_('paid_date', 'null')\
                .order('days_past_due', desc=True)\
                .execute()
            
            return {
                "success": True,
                "data": result.data,
                "row_count": len(result.data) if result.data else 0
            }
        
        # 3. Get VIP customers with unpaid invoices
        elif "vip" in query_lower:
            result = supabase.table('ar_data')\
                .select('*')\
                .eq('vip_flag', True)\
                .is_('paid_date', 'null')\
                .execute()
            
            return {
                "success": True,
                "data": result.data,
                "row_count": len(result.data) if result.data else 0
            }
        
        # 4. Get repeat late payers
        elif "repeat" in query_lower or "12" in query_lower:
            result = supabase.table('ar_data')\
                .select('*')\
                .gt('num_late_12m', 2)\
                .is_('paid_date', 'null')\
                .execute()
            
            return {
                "success": True,
                "data": result.data,
                "row_count": len(result.data) if result.data else 0
            }
        
        # 5. Calculate total outstanding amount
        elif "total" in query_lower and ("outstanding" in query_lower or "money" in query_lower):
            result = supabase.table('ar_data')\
                .select('amount, customer_id')\
                .is_('paid_date', 'null')\
                .execute()
            
            if result.data:
                df = pd.DataFrame(result.data)
                total = df['amount'].sum()
                customer_count = df['customer_id'].nunique()
                
                return {
                    "success": True,
                    "data": [{
                        "total_outstanding": float(total),
                        "invoice_count": len(result.data),
                        "customer_count": customer_count,
                        "average_per_invoice": float(total / len(result.data))
                    }],
                    "row_count": 1
                }
        
        # 6. Get top N customers at risk
        elif "top" in query_lower or "risk" in query_lower or "default" in query_lower:
            import re
            num_match = re.search(r'top\s*(\d+)', query_lower)
            limit = int(num_match.group(1)) if num_match else 5
            
            result = supabase.table('ar_data')\
                .select('*')\
                .is_('paid_date', 'null')\
                .gt('days_past_due', 0)\
                .execute()
            
            if result.data:
                df = pd.DataFrame(result.data)
                
                # Calculate risk score (simplified)
                df['risk_score'] = (
                    df['days_past_due'] * 0.3 + 
                    df['num_late_12m'] * 20 + 
                    df['prior_promises_broken'] * 30 +
                    (df['amount'] / 1000) * 0.1
                )
                
                # Group by customer
                risk_summary = df.groupby(['customer_id', 'company_name', 'country']).agg({
                    'amount': 'sum',
                    'days_past_due': 'max',
                    'risk_score': 'sum',
                    'num_late_12m': 'max'
                }).reset_index()
                
                # Rename for consistency
                risk_summary.rename(columns={'days_past_due': 'max_days_overdue'}, inplace=True)
                
                # Sort by risk score and get top N
                risk_summary = risk_summary.nlargest(limit, 'risk_score')
                
                return {
                    "success": True,
                    "data": risk_summary.to_dict('records'),
                    "row_count": len(risk_summary)
                }
        
        # 7. Get by country
        elif any(country in query_lower for country in ['sweden', 'norway', 'denmark', 'swedish', 'norwegian', 'danish']):
            country_map = {
                'swedish': 'Sweden', 'norwegian': 'Norway', 'danish': 'Denmark',
                'sweden': 'Sweden', 'norway': 'Norway', 'denmark': 'Denmark'
            }
            
            country = None
            for key, value in country_map.items():
                if key in query_lower:
                    country = value
                    break
            
            if country:
                result = supabase.table('ar_data')\
                    .select('*')\
                    .eq('country', country)\
                    .is_('paid_date', 'null')\
                    .execute()
                
                return {
                    "success": True,
                    "data": result.data,
                    "row_count": len(result.data) if result.data else 0
                }
        
        # 8. Get most overdue account(s)
        elif "most" in query_lower and "overdue" in query_lower:
            result = supabase.table('ar_data')\
                .select('*')\
                .gt('days_past_due', 0)\
                .is_('paid_date', 'null')\
                .order('days_past_due', desc=True)\
                .limit(1)\
                .execute()
            
            return {
                "success": True,
                "data": result.data,
                "row_count": len(result.data) if result.data else 0
            }
        
        # Default: Get all overdue invoices
        else:
            result = supabase.table('ar_data')\
                .select('*')\
                .gt('days_past_due', 0)\
                .is_('paid_date', 'null')\
                .order('days_past_due', desc=True)\
                .execute()
            
            return {
                "success": True,
                "data": result.data,
                "row_count": len(result.data) if result.data else 0
            }
            
    except Exception as e:
        return {
            "success": False,
            "error": str(e),
            "data": [],
            "row_count": 0
        }

def get_sample_data() -> tuple:
    """Get sample data for UI preview from single ar_data table."""
    try:
        # Get sample AR data (simplified - no need for separate customer/invoice queries)
        ar_sample = supabase.table('ar_data')\
            .select('customer_id, company_name, country, segment, vip_flag, invoice_id, amount, due_date, days_past_due')\
            .limit(5)\
            .order('days_past_due', desc=True)\
            .execute()
        
        # Split into customer and invoice views for backward compatibility
        if ar_sample.data:
            df = pd.DataFrame(ar_sample.data)
            
            # Customer view (unique customers only)
            df_customers = df[['customer_id', 'company_name', 'country', 'segment', 'vip_flag']].drop_duplicates()
            
            # Invoice view
            df_invoices = df[['invoice_id', 'amount', 'due_date', 'days_past_due', 'company_name']].copy()
            df_invoices.rename(columns={'days_past_due': 'days_overdue'}, inplace=True)
            
            return df_customers, df_invoices
        else:
            return pd.DataFrame(), pd.DataFrame()
            
    except Exception as e:
        print(f"Error getting sample data: {e}")
        return pd.DataFrame(), pd.DataFrame()

def get_full_customers(page: int = 0, page_size: int = 50, search: str = "") -> Dict:
    """Get customer data from ar_data table (unique customers only)."""
    try:
        # Get all customer data, then deduplicate in Python
        query = supabase.table('ar_data').select('customer_id, representative_name, customer_email, company_name, country, segment, vip_flag')
        
        # Add search filter if provided
        if search:
            query = query.or_(f'company_name.ilike.%{search}%,country.ilike.%{search}%,segment.ilike.%{search}%')
        
        result = query.execute()
        
        if result.data:
            # Deduplicate customers using pandas
            df = pd.DataFrame(result.data)
            unique_customers = df.drop_duplicates(subset=['customer_id']).to_dict('records')
            
            # Apply pagination to deduplicated results
            start_idx = page * page_size
            end_idx = start_idx + page_size
            paginated_customers = unique_customers[start_idx:end_idx]
            
            return {
                "success": True,
                "data": paginated_customers,
                "total_count": len(unique_customers),
                "page": page,
                "page_size": page_size,
                "total_pages": (len(unique_customers) + page_size - 1) // page_size
            }
        else:
            return {
                "success": True,
                "data": [],
                "total_count": 0,
                "page": page,
                "page_size": page_size,
                "total_pages": 0
            }
            
    except Exception as e:
        return {"success": False, "error": str(e), "data": []}

def get_full_invoices(page: int = 0, page_size: int = 50, search: str = "") -> Dict:
    """Get invoice data from ar_data table with pagination and search."""
    try:
        # Query ar_data table directly
        query = supabase.table('ar_data').select('*')
        
        # Add search filter if provided
        if search:
            query = query.or_(f'invoice_id.ilike.%{search}%,company_name.ilike.%{search}%,customer_email.ilike.%{search}%')
        
        # Add pagination
        start_idx = page * page_size
        end_idx = start_idx + page_size - 1
        
        result = query.range(start_idx, end_idx).order('days_past_due', desc=True).execute()
        
        # Get total count from same table
        count_result = supabase.table('ar_data').select('invoice_id', count='exact').execute()
        total_count = count_result.count or 0
        
        return {
            "success": True,
            "data": result.data or [],
            "total_count": total_count,
            "page": page,
            "page_size": page_size,
            "total_pages": (total_count + page_size - 1) // page_size
        }
    except Exception as e:
        return {"success": False, "error": str(e), "data": []}

def get_email_activity(page: int = 0, page_size: int = 50) -> Dict:
    """Get email activity from dedicated mock_emails table with pagination."""
    try:
        # Get data directly from mock_emails table for better performance
        start_idx = page * page_size
        end_idx = start_idx + page_size - 1
        
        result = supabase.table('mock_emails')\
            .select('*')\
            .range(start_idx, end_idx)\
            .order('created_at', desc=True)\
            .execute()
        
        # Get total count
        count_result = supabase.table('mock_emails')\
            .select('id', count='exact')\
            .execute()
        total_count = count_result.count or 0
        
        # Format the data for display
        formatted_data = []
        for record in result.data or []:
            formatted_data.append({
                "timestamp": record.get('created_at', ''),
                "recipient": record.get('recipient', ''),
                "subject": record.get('subject', ''),
                "status": record.get('status', 'UNKNOWN'),
                "invoice_id": record.get('invoice_id', ''),
                "tone": record.get('tone', ''),
                "body": record.get('body', '')
            })
        
        return {
            "success": True,
            "data": formatted_data,
            "total_count": total_count,
            "page": page,
            "page_size": page_size,
            "total_pages": (total_count + page_size - 1) // page_size
        }
    except Exception as e:
        # Fallback to demo_activity_log if mock_emails table fails
        try:
            result = supabase.table('demo_activity_log')\
                .select('*')\
                .eq('action_type', 'mock_email_created')\
                .range(start_idx, end_idx)\
                .order('created_at', desc=True)\
                .execute()
            
            count_result = supabase.table('demo_activity_log')\
                .select('id', count='exact')\
                .eq('action_type', 'mock_email_created')\
                .execute()
            total_count = count_result.count or 0
            
            formatted_data = []
            for record in result.data or []:
                details = record.get('details', {})
                formatted_data.append({
                    "timestamp": details.get('timestamp', record.get('created_at', '')),
                    "recipient": details.get('recipient', ''),
                    "subject": details.get('subject', ''),
                    "status": details.get('status', 'UNKNOWN'),
                    "invoice_id": details.get('invoice_id', ''),
                    "tone": details.get('tone', ''),
                    "body": details.get('body', '')
                })
            
            return {
                "success": True,
                "data": formatted_data,
                "total_count": total_count,
                "page": page,
                "page_size": page_size,
                "total_pages": (total_count + page_size - 1) // page_size
            }
        except:
            return {"success": False, "error": f"Email retrieval failed: {str(e)}", "data": []}

# Removed get_consolidated_ar_data - replaced by get_basic_ar_data using single ar_data table

def get_activity_log(page: int = 0, page_size: int = 50) -> Dict:
    """Get all activity log data with pagination."""
    try:
        start_idx = page * page_size
        end_idx = start_idx + page_size - 1
        
        result = supabase.table('demo_activity_log')\
            .select('*')\
            .range(start_idx, end_idx)\
            .order('created_at', desc=True)\
            .execute()
        
        # Get total count
        count_result = supabase.table('demo_activity_log')\
            .select('id', count='exact')\
            .execute()
        total_count = count_result.count or 0
        
        return {
            "success": True,
            "data": result.data or [],
            "total_count": total_count,
            "page": page,
            "page_size": page_size,
            "total_pages": (total_count + page_size - 1) // page_size
        }
    except Exception as e:
        return {"success": False, "error": str(e), "data": []}

def store_mock_email(email_record: Dict) -> None:
    """Store mock email in dedicated mock_emails table."""
    try:
        supabase.table('mock_emails').insert({
            "recipient": email_record.get("recipient", ""),
            "subject": email_record.get("subject", ""),
            "body": email_record.get("body", ""),
            "status": email_record.get("status", "MOCK - NOT SENT"),
            "tone": email_record.get("tone", "friendly"),
            "invoice_id": email_record.get("invoice_id", ""),
            "customer_id": email_record.get("recipient", "").split('@')[0]  # Extract customer ID from email
        }).execute()
    except Exception as e:
        print(f"Mock email storage error: {e}")

def log_activity(action_type: str, customer_id: str, details: Dict) -> None:
    """Log agent activity for demo purposes."""
    try:
        supabase.table('demo_activity_log').insert({
            "action_type": action_type,
            "customer_id": customer_id,
            "details": details,
            "simulated": True
        }).execute()
    except Exception as e:
        print(f"Activity logging error: {e}")

def get_basic_ar_data(page: int = 0, page_size: int = 50, search: str = "") -> Dict:
    """Get AR data from single ar_data table - ultra-simple approach."""
    try:
        # Query the single ar_data table - no JOINs needed!
        query = supabase.table('ar_data').select('*')
        
        # Simple search across key fields
        if search:
            query = query.or_(f'invoice_id.ilike.%{search}%,company_name.ilike.%{search}%,customer_email.ilike.%{search}%,country.ilike.%{search}%,customer_id.ilike.%{search}%')
        
        # Get data with pagination, ordered by most overdue first
        start_idx = page * page_size
        end_idx = start_idx + page_size - 1
        
        result = query.range(start_idx, end_idx).order('days_past_due', desc=True).execute()
        
        # Simple data formatting - no complex processing needed
        formatted_data = []
        for record in result.data or []:
            formatted_record = {
                'Invoice ID': record.get('invoice_id', ''),
                'Company Name': record.get('company_name', ''),
                'Email': record.get('customer_email', ''),
                'Country': record.get('country', ''),
                'Amount': f"€{record.get('amount', 0):,.2f}",
                'Due Date': record.get('due_date', ''),
                'Days Overdue': record.get('days_past_due', 0),
                'VIP': 'Yes' if record.get('vip_flag', False) else 'No',
                'Status': 'Paid' if record.get('paid_date') else 'Outstanding',
                'Segment': record.get('segment', ''),
                'Rep': record.get('representative_name', '')
            }
            formatted_data.append(formatted_record)
        
        # Get total count from same table
        count_result = supabase.table('ar_data').select('invoice_id', count='exact').execute()
        total_count = count_result.count or 0
        
        return {
            "success": True,
            "data": formatted_data,
            "total_count": total_count,
            "page": page,
            "page_size": page_size,
            "total_pages": (total_count + page_size - 1) // page_size
        }
        
    except Exception as e:
        return {"success": False, "error": str(e), "data": []}

def validate_database_setup() -> Dict:
    """Validate database connection and required objects exist - single table approach."""
    validation_results = {
        "success": True,
        "errors": [],
        "warnings": [],
        "info": []
    }
    
    try:
        # Test basic connection using the main ar_data table
        result = supabase.table('ar_data').select('invoice_id').limit(1).execute()
        validation_results["info"].append(f"✅ Database connection: OK ({len(result.data)} AR records found)")
        
        # Test required tables exist (simplified structure)
        tables_to_check = ['ar_data', 'demo_activity_log', 'mock_emails']
        for table in tables_to_check:
            try:
                result = supabase.table(table).select('*').limit(1).execute()
                validation_results["info"].append(f"✅ Table '{table}': OK")
            except Exception as e:
                validation_results["errors"].append(f"❌ Table '{table}': Missing or inaccessible ({str(e)[:50]})")
                validation_results["success"] = False
        
        # Check if AR data exists
        try:
            ar_result = supabase.table('ar_data').select('invoice_id', count='exact').execute()
            ar_count = ar_result.count or 0
            
            if ar_count == 0:
                validation_results["warnings"].append("⚠️ No AR data found. Run seeds.sql to populate demo data")
            else:
                validation_results["info"].append(f"✅ Data check: {ar_count} AR records in single table")
                
                # Check data distribution
                vip_result = supabase.table('ar_data').select('invoice_id', count='exact').eq('vip_flag', True).execute()
                overdue_result = supabase.table('ar_data').select('invoice_id', count='exact').gt('days_past_due', 0).execute()
                
                vip_count = vip_result.count or 0
                overdue_count = overdue_result.count or 0
                
                validation_results["info"].append(f"✅ Data breakdown: {vip_count} VIP records, {overdue_count} overdue records")
                
        except Exception as e:
            validation_results["warnings"].append(f"⚠️ Could not check AR data counts: {str(e)[:50]}")
    
    except Exception as e:
        validation_results["errors"].append(f"❌ Critical database connection error: {str(e)}")
        validation_results["success"] = False
    
    return validation_results