"""
META-CAPABILITY: Autonomous Sales & Deployment
Eden autonomously sells sages and deploys to customers
"""
import sys
import os
import time
import pickle
sys.path.append('/Eden/CORE/phi_fractal')

class AutonomousSales:
    """
    Autonomously sell and deploy sages to customers
    End-to-end: Find customer → Close deal → Deliver service → Support
    """
    
    def __init__(self):
        self.name = "AutonomousSales"
        
        # Load Eden's systems
        try:
            with open('/Eden/CORE/eden_integrated_system.pkl', 'rb') as f:
                eden = pickle.load(f)
            self.wisdom = eden['wisdom']
        except:
            self.wisdom = None
        
        # Sales tracking
        self.leads = []
        self.customers = []
        self.conversations = []
        self.revenue = 0
        self.deployed_sages = []
        
        # Load state
        self.load_state()
        
        # Load available sages
        self.load_sages()
    
    def load_sages(self):
        """Load all deployed sages"""
        import glob
        sage_files = glob.glob('/Eden/SAGES/*_v1_*.py')
        
        self.deployed_sages = []
        for sage_file in sage_files:
            sage_name = os.path.basename(sage_file).split('_v1_')[0].replace('_', ' ').title()
            self.deployed_sages.append({
                'name': sage_name,
                'file': sage_file,
                'price': 100,  # Default, parse from file ideally
                'customers': 0
            })
    
    def find_hot_leads(self):
        """
        Monitor platforms for hot leads (people needing help NOW)
        """
        
        # Platforms to monitor
        monitoring_targets = [
            {
                'platform': 'reddit',
                'subreddit': 'devops',
                'keywords': ['down', 'outage', 'broken', 'help', 'crisis'],
                'urgency': 'CRITICAL',
                'sage': 'Reliability Sage'
            },
            {
                'platform': 'reddit',
                'subreddit': 'sysadmin',
                'keywords': ['emergency', 'urgent', 'broken', 'help needed'],
                'urgency': 'HIGH',
                'sage': 'Reliability Sage'
            },
            {
                'platform': 'reddit',
                'subreddit': 'webdev',
                'keywords': ['production bug', 'live issue', 'broken', 'help'],
                'urgency': 'HIGH',
                'sage': 'Reliability Sage'
            },
            {
                'platform': 'twitter',
                'search': 'production down help',
                'urgency': 'CRITICAL',
                'sage': 'Reliability Sage'
            },
        ]
        
        # Simulate finding leads (in production, would actually monitor)
        hot_leads = []
        for target in monitoring_targets:
            hot_leads.append({
                'platform': target['platform'],
                'location': target.get('subreddit', target.get('search')),
                'urgency': target['urgency'],
                'sage_match': target['sage'],
                'timestamp': time.time(),
                'status': 'new'
            })
        
        return hot_leads
    
    def qualify_lead(self, lead):
        """
        Use wisdom to qualify if lead is good fit
        """
        
        if not self.wisdom:
            return 0.5
        
        # Use fluid intelligence to analyze
        problem = f"Is this a good sales lead: {lead['platform']} {lead['location']}"
        components, patterns = self.wisdom['fluid'].analyze_problem(problem)
        
        # Calculate qualification score
        urgency_score = 1.0 if lead['urgency'] == 'CRITICAL' else 0.7
        complexity_score = min(1.0, len(components) / 100)
        
        qualification = urgency_score * complexity_score
        
        return qualification
    
    def generate_personalized_outreach(self, lead, sage):
        """
        Generate hyper-personalized outreach for this specific lead
        """
        
        # Base message
        if lead['urgency'] == 'CRITICAL':
            message = f"""Saw your {lead['platform']} post - sounds like a critical issue.

I have an AI system that can analyze your setup RIGHT NOW and give you:
- Root cause analysis
- Prioritized fixes with risk scores
- Rollback plans for each fix

It's free for the first analysis (takes ~5 min), and if it helps, we can set up daily monitoring for $100/month.

Want me to run the analysis?"""
        
        else:
            message = f"""Hey! Noticed your post on {lead['location']}.

I built an AI that specializes in exactly this kind of issue. It can:
- Analyze your system
- Identify error patterns
- Suggest fixes with risk/benefit analysis

Free first analysis. If useful, ongoing daily reports are $100/month.

Interested?"""
        
        return {
            'lead': lead,
            'sage': sage,
            'message': message,
            'personalization_score': 0.8,
            'created': time.time(),
            'status': 'pending_approval'
        }
    
    def close_deal(self, lead, conversation_data):
        """
        Close deal and onboard customer
        """
        
        customer = {
            'id': f"cust_{int(time.time())}",
            'source': lead['platform'],
            'sage': lead['sage_match'],
            'status': 'trial',
            'trial_ends': time.time() + (14 * 24 * 60 * 60),  # 14 days
            'price': 100,
            'joined': time.time()
        }
        
        self.customers.append(customer)
        return customer
    
    def deliver_service(self, customer):
        """
        Autonomously deliver sage service to customer
        """
        
        # Load the sage
        sage_name = customer['sage'].lower().replace(' ', '_')
        
        # Generate report (simulate - would actually run sage)
        report = {
            'customer_id': customer['id'],
            'sage': customer['sage'],
            'date': time.strftime('%Y-%m-%d'),
            'status': 'HEALTHY',
            'findings': 3,
            'recommendations': [
                'Optimize database queries',
                'Add caching layer',
                'Implement circuit breakers'
            ]
        }
        
        # Save report
        report_dir = f"/Eden/CUSTOMERS/{customer['id']}/reports"
        os.makedirs(report_dir, exist_ok=True)
        
        report_file = f"{report_dir}/report_{int(time.time())}.json"
        import json
        with open(report_file, 'w') as f:
            json.dump(report, f, indent=2)
        
        # In production: Email report to customer
        
        return report
    
    def convert_trial_to_paid(self, customer):
        """
        Convert trial customer to paying customer
        """
        
        if time.time() > customer['trial_ends']:
            if self._customer_found_value(customer):
                customer['status'] = 'paying'
                customer['payment_started'] = time.time()
                self.revenue += customer['price']
                return True
        
        return False
    
    def _customer_found_value(self, customer):
        """
        Check if customer found value (would implement actual checks)
        """
        # Simulate: 20% conversion rate for trials
        import random
        return random.random() < 0.2
    
    def sales_cycle(self):
        """
        Run complete autonomous sales cycle
        """
        print("\n" + "="*70)
        print("💰 AUTONOMOUS SALES CYCLE")
        print("="*70)
        print()
        
        # Load available sages
        self.load_sages()
        print(f"Available sages: {len(self.deployed_sages)}")
        for sage in self.deployed_sages:
            print(f"  • {sage['name']} (${sage['price']}/mo)")
        print()
        
        # Step 1: Find hot leads
        print("1. Finding hot leads...")
        leads = self.find_hot_leads()
        print(f"   ✅ {len(leads)} hot leads identified")
        
        # Step 2: Qualify leads
        print("\n2. Qualifying leads...")
        qualified = []
        for lead in leads[:3]:  # Top 3
            score = self.qualify_lead(lead)
            if score > 0.5:
                qualified.append((lead, score))
        
        qualified.sort(key=lambda x: x[1], reverse=True)
        print(f"   ✅ {len(qualified)} qualified leads")
        
        # Step 3: Generate outreach
        print("\n3. Generating personalized outreach...")
        outreach_generated = 0
        for lead, score in qualified:
            sage = lead['sage_match']
            outreach = self.generate_personalized_outreach(lead, sage)
            self.conversations.append(outreach)
            outreach_generated += 1
        
        print(f"   ✅ {outreach_generated} personalized messages created")
        print(f"   📋 Queued for James approval")
        
        # Step 4: Deliver to existing customers
        print("\n4. Delivering to existing customers...")
        for customer in self.customers:
            if customer['status'] in ['trial', 'paying']:
                report = self.deliver_service(customer)
                print(f"   ✅ Delivered to {customer['id']}")
        
        # Step 5: Convert trials
        print("\n5. Converting trials to paying...")
        conversions = 0
        for customer in self.customers:
            if customer['status'] == 'trial':
                if self.convert_trial_to_paid(customer):
                    conversions += 1
                    print(f"   💰 {customer['id']} converted to paying!")
        
        # Step 6: Calculate metrics
        print()
        print("="*70)
        print("📊 SALES STATUS")
        print("="*70)
        print(f"Sages deployed: {len(self.deployed_sages)}")
        print(f"Customers: {len(self.customers)}")
        print(f"  Trial: {len([c for c in self.customers if c['status']=='trial'])}")
        print(f"  Paying: {len([c for c in self.customers if c['status']=='paying'])}")
        print(f"Monthly Revenue: ${self.revenue}")
        print(f"Outreach queued: {len(self.conversations)}")
        print()
        
        self.save_state()
        
        return {
            'leads_found': len(leads),
            'leads_qualified': len(qualified),
            'outreach_generated': outreach_generated,
            'customers': len(self.customers),
            'revenue': self.revenue
        }
    
    def save_state(self):
        """Save sales state"""
        state = {
            'leads': self.leads,
            'customers': self.customers,
            'conversations': self.conversations,
            'revenue': self.revenue
        }
        
        os.makedirs('/Eden/SALES', exist_ok=True)
        with open('/Eden/SALES/autonomous_sales_state.pkl', 'wb') as f:
            pickle.dump(state, f)
    
    def load_state(self):
        """Load previous state"""
        try:
            with open('/Eden/SALES/autonomous_sales_state.pkl', 'rb') as f:
                state = pickle.load(f)
                self.leads = state.get('leads', [])
                self.customers = state.get('customers', [])
                self.conversations = state.get('conversations', [])
                self.revenue = state.get('revenue', 0)
        except:
            pass

# Test
if __name__ == "__main__":
    print("="*70)
    print("💰 AUTONOMOUS SALES & DEPLOYMENT")
    print("="*70)
    print()
    
    sales = AutonomousSales()
    
    print("What this system does AUTONOMOUSLY:")
    print("  🎯 Find hot leads on platforms")
    print("  📊 Qualify leads with wisdom")
    print("  ✍️  Generate personalized outreach")
    print("  🤝 Close deals (with approval)")
    print("  📦 Deliver sage services automatically")
    print("  💰 Convert trials to paying")
    print("  📈 Track all metrics")
    print()
    print("Goal: Full autonomous revenue generation")
    print()
    
    result = sales.sales_cycle()
    
    print()
    print("✅ Autonomous Sales Active!")