# filename: utils/cost_summary.py

def optimize_ai_costs():
    """AI cost optimization strategies ka summary."""
    
    tips = {
        '1_gemini_first': {
            'saving': '90% of Haiku calls',
            'how': 'Gemini (free) filters 200 markets to 15 candidates. Only 15 go to Haiku.'
        },
        '2_cache_analysis': {
            'saving': '80% of repeat calls', 
            'how': 'Skip markets analyzed <4h ago with <2% price change.'
        },
        '3_skip_cache': {
            'saving': '50% of Sonnet calls',
            'how': 'If Sonnet SKIPped a market, dont re-analyze for 6+ hours.'
        },
        '4_batch_analysis': {
            'saving': '60% token cost',
            'how': 'Send 5 candidates in one Haiku call instead of 5 separate calls.'
        },
        '5_no_opus': {
            'saving': '$3/day',
            'how': 'Use Sonnet for everything except sports exits. Opus is 5x more expensive.'
        }
    }
    
    total_daily_without = 15.0  # $15/day agar sab kuch full power pe chalao
    total_daily_with = 1.0     # $1/day hamari optimization ke saath
    
    print(f'Without optimization: ${total_daily_without}/day = ~PKR {total_daily_without*280}/day')
    print(f'With optimization: ${total_daily_with}/day = ~PKR {total_daily_with*280}/day')
    print(f'Monthly Savings: ~PKR {((total_daily_without-total_daily_with)*30)*280:,}')
    print("-" * 20)
    
    for name, tip in tips.items():
        print(f'Strategy -> {name}: saves {tip["saving"]} — {tip["how"]}')

# Run karke dekho
optimize_ai_costs()

Without optimization: $15.0/day = ~PKR 4200.0/day
With optimization: $1.0/day = ~PKR 280.0/day
Monthly Savings: ~PKR 117,600.0
--------------------
Strategy -> 1_gemini_first: saves 90% of Haiku calls — Gemini (free) filters 200 markets to 15 candidates. Only 15 go to Haiku.
Strategy -> 2_cache_analysis: saves 80% of repeat calls — Skip markets analyzed <4h ago with <2% price change.
Strategy -> 3_skip_cache: saves 50% of Sonnet calls — If Sonnet SKIPped a market, dont re-analyze for 6+ hours.
Strategy -> 4_batch_analysis: saves 60% token cost — Send 5 candidates in one Haiku call instead of 5 separate calls.
Strategy -> 5_no_opus: saves $3/day — Use Sonnet for everything except sports exits. Opus is 5x more expensive.

# filename: scanner.py (Simplified)
import time
from ai.gemini import is_market_a_potential_candidate # Assume this function exists

# Mock function to simulate fetching all markets from Polymarket
def fetch_all_markets():
    print("Fetching 200 markets from Polymarket...")
    # Example: PSL final, KSE index movement, new government policy etc.
    return [
        {'id': '1', 'question': 'Will Pakistan win the T20 World Cup 2024?'},
        {'id': '2', 'question': 'Will KSE-100 index cross 80,000 by end of June?'},
        {'id': '3', 'question': 'Who will win the toss in the PAK vs IND match?'},
        # ... and 197 other markets
    ]

# This is our mock Gemini filter. Asal mein ye API call hogi.
# Hum yahan simple keyword matching se simulate kar rahay hain.
def mock_gemini_filter(market):
    """Simulates Gemini's logic to find markets with an edge."""
    keywords = ['win', 'cross', 'exceed', 'pass']
    # Gemini ko hum prompt detay hain to find markets that are predictable
    # and not pure chance (like a toss).
    if any(keyword in market['question'] for keyword in keywords) and 'toss' not in market['question']:
        print(f"  [GEMINI] ✅ Found potential in: {market['question']}")
        return True
    print(f"  [GEMINI] ❌ Skipping random market: {market['question']}")
    return False


def run_scanner():
    print("--- Starting Market Scan ---")
    all_markets = fetch_all_markets()
    potential_candidates = []
    
    print("\n--- Phase 1: Gemini Free Screening ---")
    for market in all_markets:
        # Asal code mein yahan `is_market_a_potential_candidate(market)` call hoga
        if mock_gemini_filter(market):
            potential_candidates.append(market)
            
    print(f"\n--- Scan Complete ---")
    print(f"Gemini ne {len(all_markets)} markets ko filter karke {len(potential_candidates)} candidates nikalay.")
    print("Ab sirf in candidates ko paid AI (Haiku) pe bhejengay.")
    # Next step would be: analyze_with_haiku(potential_candidates)

# Chala ke dekho
run_scanner()