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#!/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()) |