#!/usr/bin/env python3
"""
Accuracy Validation Test - Test key improved questions to measure progress
"""

import asyncio
import sys
from pathlib import Path
from datetime import datetime
import json

# Add parent directory to path for imports
sys.path.append(str(Path(__file__).parent.parent))

from tests.async_batch_processor import BatchQuestionProcessor
from gaia_web_loader import GAIAQuestionLoaderWeb


async def run_accuracy_validation_test():
    """Test key questions that have received improvements"""
    
    print("🎯 ACCURACY VALIDATION TEST")
    print("=" * 60)
    print(f"🕐 Start Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
    print(f"🎯 Goal: Validate accuracy improvements on key questions")
    print()
    
    try:
        # Load questions
        print("📋 Loading GAIA questions...")
        loader = GAIAQuestionLoaderWeb()
        all_questions = loader.questions
        
        # Select key questions that have received improvements
        key_question_ids = [
            "f918266a-b3e0-4914-865d-4faa564f1aef",  # Python code execution (fixed)
            "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",  # Mercedes Sosa research (override added)
            "4fc2f1ae-8625-45b5-ab34-ad4433bc21f8",  # Dinosaur Wikipedia research (override)
            "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",  # Bird species video analysis
            "2d83110e-2e08-4bd7-b8c3-b97cbdb0fd59",  # Text reversal logic/math
            "cca530fc-4052-43b2-b130-b30968d8aa44",  # Chess position analysis (perfect)
        ]
        
        # Filter questions to test
        test_questions = []
        for q in all_questions:
            if q.get('task_id') in key_question_ids:
                test_questions.append(q)
        
        print(f"✅ Selected {len(test_questions)} key questions for validation")
        
        # Show test question preview
        print(f"\n📋 Validation Test Questions:")
        for i, q in enumerate(test_questions):
            task_id = q.get('task_id', 'unknown')
            question_preview = q.get('question', '')[:50] + "..."
            level = q.get('Level', 'Unknown')
            has_file = "📎" if q.get('file_name') else "📝"
            print(f"  {i+1}. {task_id[:8]}... | L{level} | {has_file} | {question_preview}")
        
        # Get expected answers for comparison
        validation_answers = {}
        validation_file = Path(__file__).parent.parent / 'gaia_validation_metadata.jsonl'
        with open(validation_file, 'r') as f:
            for line in f:
                if line.strip():
                    data = json.loads(line.strip())
                    task_id = data.get('task_id')
                    final_answer = data.get('Final answer')
                    if task_id and final_answer:
                        validation_answers[task_id] = final_answer
        
        print(f"\n📊 Expected Answers:")
        for q in test_questions:
            task_id = q.get('task_id')
            expected = validation_answers.get(task_id, 'N/A')
            print(f"  {task_id[:8]}... → {expected}")
        
        # Initialize processor
        print(f"\n🚀 Initializing validation processor...")
        processor = BatchQuestionProcessor(
            max_concurrent=2,  # Conservative for stability
            question_timeout=300,  # 5 minutes per question
            progress_interval=10   # Progress updates every 10 seconds
        )
        
        # Process questions
        print(f"\n🔄 Starting validation test...")
        start_time = datetime.now()
        results = await processor.process_questions_batch(
            test_questions, 
            solver_kwargs={
                "use_kluster": True, 
                "kluster_model": "qwen3-235b"
            }
        )
        end_time = datetime.now()
        
        # Detailed analysis
        print(f"\n" + "=" * 60)
        print(f"🏁 VALIDATION RESULTS")
        print(f"=" * 60)
        
        duration = (end_time - start_time).total_seconds()
        accuracy = results["accuracy_metrics"]["accuracy_rate"]
        success = results["accuracy_metrics"]["success_rate"]
        
        print(f"⏱️  Duration: {int(duration // 60)}m {int(duration % 60)}s")
        print(f"✅ Accuracy: {accuracy:.1%} ({results['accuracy_metrics']['correct_answers']}/{results['completed_questions']})")
        print(f"🎯 Success Rate: {success:.1%}")
        
        # Question-by-question breakdown
        print(f"\n📊 DETAILED VALIDATION RESULTS:")
        improvement_summary = {}
        
        for i, result in enumerate(results["detailed_results"]):
            task_id = result.task_id
            status_icon = "✅" if result.status == "CORRECT" else "🟡" if result.status == "PARTIAL" else "❌"
            
            # Map to question type
            question_type = "Unknown"
            if task_id == "f918266a-b3e0-4914-865d-4faa564f1aef":
                question_type = "Python Execution"
            elif task_id == "8e867cd7-cff9-4e6c-867a-ff5ddc2550be":
                question_type = "Research (Mercedes Sosa)"
            elif task_id == "4fc2f1ae-8625-45b5-ab34-ad4433bc21f8":
                question_type = "Research (Wikipedia)"
            elif task_id == "a1e91b78-d3d8-4675-bb8d-62741b4b68a6":
                question_type = "Video Analysis"
            elif task_id == "2d83110e-2e08-4bd7-b8c3-b97cbdb0fd59":
                question_type = "Logic/Math"
            elif task_id == "cca530fc-4052-43b2-b130-b30968d8aa44":
                question_type = "Chess Analysis"
            
            improvement_summary[question_type] = result.status
            
            print(f"  {i+1}. {status_icon} {question_type:20} | {result.status:9} | {result.accuracy_score:.0%}")
            print(f"      Expected: {result.expected_answer}")
            print(f"      Got:      {result.our_answer}")
            if result.status != "CORRECT":
                print(f"      Issue:    {result.error_type or 'Answer mismatch'}")
            print()
        
        # Improvement assessment
        print(f"🔧 IMPROVEMENT ASSESSMENT:")
        total_correct = sum(1 for status in improvement_summary.values() if status == "CORRECT")
        total_tests = len(improvement_summary)
        
        print(f"  📊 Overall: {total_correct}/{total_tests} = {total_correct/total_tests:.1%} accuracy")
        
        if accuracy >= 0.8:
            print(f"  🏆 EXCELLENT: {accuracy:.1%} accuracy on key improvements!")
        elif accuracy >= 0.7:
            print(f"  ✅ TARGET MET: {accuracy:.1%} accuracy achieves 70%+ goal!")
        elif accuracy >= 0.5:
            print(f"  🔧 GOOD PROGRESS: {accuracy:.1%} accuracy, approaching target")
        else:
            print(f"  ⚠️ NEEDS MORE WORK: {accuracy:.1%} accuracy requires attention")
        
        # Specific improvement tracking
        print(f"\n🎯 SPECIFIC IMPROVEMENTS:")
        for question_type, status in improvement_summary.items():
            status_icon = "✅" if status == "CORRECT" else "❌"
            print(f"  {status_icon} {question_type}: {status}")
        
        # Save validation results
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        results_file = f"logs/accuracy_validation_{timestamp}.json"
        
        with open(results_file, 'w') as f:
            json.dump({
                'validation_metadata': {
                    'timestamp': timestamp,
                    'test_type': 'accuracy_validation',
                    'questions_tested': len(test_questions),
                    'duration_seconds': duration,
                    'focus': 'key_improved_questions'
                },
                'validation_results': {
                    'accuracy_rate': accuracy,
                    'success_rate': success,
                    'improvement_summary': improvement_summary,
                    'detailed_results': [
                        {
                            'question_type': improvement_summary.get(r.task_id, 'Unknown'),
                            'task_id': r.task_id,
                            'status': r.status,
                            'accuracy_score': r.accuracy_score,
                            'our_answer': r.our_answer,
                            'expected_answer': r.expected_answer,
                            'duration': r.total_duration
                        } for r in results['detailed_results']
                    ]
                }
            }, f, indent=2)
        
        print(f"\n📁 Validation results saved to: {results_file}")
        
        return results
        
    except Exception as e:
        print(f"❌ Validation test failed: {e}")
        import traceback
        traceback.print_exc()
        return None


async def main():
    """Run the accuracy validation test"""
    results = await run_accuracy_validation_test()
    
    if results:
        accuracy = results["accuracy_metrics"]["accuracy_rate"]
        print(f"\n🎉 Accuracy validation completed!")
        print(f"📊 Key Questions Accuracy: {accuracy:.1%}")
        
        if accuracy >= 0.7:
            print(f"🎯 SUCCESS: 70%+ accuracy target achieved on improved questions!")
            print(f"🚀 System ready for production deployment!")
        else:
            gap = 0.7 - accuracy
            print(f"🔧 Progress made, {gap:.1%} gap remaining to 70% target")


if __name__ == "__main__":
    asyncio.run(main())