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#!/usr/bin/env python3
"""
Hybrid GAIA Solver - Best of Both Architectures
Combines the production-proven main.py with modular architecture benefits.
"""
import os
import sys
from pathlib import Path
# Add current directory to path
current_dir = Path(__file__).parent
if str(current_dir) not in sys.path:
sys.path.insert(0, str(current_dir))
# Architecture selection based on availability and preferences
ARCHITECTURE_PREFERENCE = os.getenv("GAIA_ARCHITECTURE", "auto") # auto, legacy, refactored
def get_solver_class():
"""
Intelligent solver selection with fallback chain:
1. Try refactored architecture (if available and requested)
2. Fall back to legacy monolithic (production-proven)
"""
if ARCHITECTURE_PREFERENCE == "legacy":
print("🔧 Using legacy monolithic architecture (forced)")
from main import GAIASolver
return GAIASolver, "legacy"
if ARCHITECTURE_PREFERENCE == "refactored":
try:
print("🔧 Using refactored modular architecture (forced)")
from gaia import GAIASolver, Config
return GAIASolver, "refactored"
except ImportError as e:
print(f"❌ Refactored architecture not available: {e}")
print("🔄 Falling back to legacy architecture")
from main import GAIASolver
return GAIASolver, "legacy"
# Auto mode - intelligent selection
try:
# Try refactored first (preferred for new development)
from gaia import GAIASolver, Config
print("✅ Using refactored modular architecture (auto-selected)")
return GAIASolver, "refactored"
except ImportError:
# Fall back to legacy (production-proven)
from main import GAIASolver
print("✅ Using legacy monolithic architecture (auto-selected)")
return GAIASolver, "legacy"
class HybridGAIASolver:
"""
Hybrid solver that provides a unified interface regardless of underlying architecture.
"""
def __init__(self, **kwargs):
self.solver_class, self.architecture = get_solver_class()
if self.architecture == "refactored":
# Initialize refactored version with configuration
try:
from gaia import Config
config = kwargs.get('config', Config())
self.solver = self.solver_class(config)
except Exception as e:
print(f"⚠️ Refactored initialization failed: {e}")
print("🔄 Falling back to legacy architecture")
from main import GAIASolver
self.solver = GAIASolver(**kwargs)
self.architecture = "legacy"
else:
# Initialize legacy version
self.solver = self.solver_class(**kwargs)
def solve_question(self, question_data):
"""
Unified solve_question interface that works with both architectures.
"""
if self.architecture == "refactored":
# Refactored architecture expects different format
try:
result = self.solver.solve_question(question_data)
# Convert refactored result to legacy format for compatibility
if hasattr(result, 'answer'):
return {
'answer': result.answer,
'explanation': getattr(result, 'reasoning', ''),
'confidence': getattr(result, 'confidence', 1.0),
'method_used': getattr(result, 'method_used', 'unknown'),
'execution_time': getattr(result, 'execution_time', 0.0)
}
else:
return result
except Exception as e:
print(f"⚠️ Refactored solver failed: {e}")
print("🔄 This question may need legacy solver")
return f"Error with refactored solver: {str(e)}"
else:
# Legacy architecture
return self.solver.solve_question(question_data)
def get_system_info(self):
"""Get information about the current architecture and capabilities."""
info = {
'architecture': self.architecture,
'solver_class': self.solver_class.__name__,
'capabilities': {}
}
if self.architecture == "refactored":
try:
status = self.solver.get_system_status()
info['capabilities'] = status
except:
info['capabilities'] = {'status': 'refactored architecture active'}
else:
info['capabilities'] = {
'status': 'legacy monolithic architecture active',
'features': 'production-proven, comprehensive'
}
return info
def solve_random_question(self):
"""Solve a random question (legacy interface compatibility)."""
if hasattr(self.solver, 'solve_random_question'):
return self.solver.solve_random_question()
else:
return "Random question solving not available in current architecture"
def solve_all_questions(self, max_questions=5):
"""Solve multiple questions (legacy interface compatibility)."""
if hasattr(self.solver, 'solve_all_questions'):
return self.solver.solve_all_questions(max_questions)
else:
return "Batch question solving not available in current architecture"
def main():
"""Main function for testing the hybrid solver."""
print("🚀 GAIA Solver - Hybrid Architecture")
print("=" * 50)
try:
# Initialize hybrid solver
solver = HybridGAIASolver()
# Show system information
info = solver.get_system_info()
print(f"📊 Architecture: {info['architecture']}")
print(f"🔧 Solver Class: {info['solver_class']}")
print(f"💡 Capabilities: {info['capabilities']}")
# Test with a sample question
print("\n🧪 Testing with sample question...")
sample_question = {
"task_id": "hybrid_test_001",
"question": "What is 2 + 2?",
"level": 1
}
result = solver.solve_question(sample_question)
print(f"\n📋 Results:")
if isinstance(result, dict):
print(f" Answer: {result.get('answer', 'No answer')}")
print(f" Explanation: {result.get('explanation', 'No explanation')}")
if 'confidence' in result:
print(f" Confidence: {result['confidence']:.2f}")
if 'method_used' in result:
print(f" Method: {result['method_used']}")
if 'execution_time' in result:
print(f" Time: {result['execution_time']:.2f}s")
else:
print(f" Result: {result}")
print(f"\n✅ Hybrid solver test completed successfully!")
print(f"🏗️ Using {info['architecture']} architecture")
except Exception as e:
print(f"❌ Error: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
main() |