working_training_system.py

#!/usr/bin/env python3
"""
Working Training System
======================
Creates training data for matrix-enhanced models.
"""

import json
from datetime import datetime

def create_working_training_data():
    """Create working training data."""
    
    training_data = []
    
    # SQL examples
    sql_examples = [
        {
            "prompt": "Generate an optimized SQL query for finding customers with high-value orders",
            "completion": "SELECT c.customer_id, c.name, SUM(o.total) as total_spent FROM customers c JOIN orders o ON c.customer_id = o.customer_id WHERE o.total > 1000 GROUP BY c.customer_id, c.name HAVING total_spent > 5000 ORDER BY total_spent DESC; -- Matrix-enhanced query"
        },
        {
            "prompt": "Create a complex SQL query with multiple JOINs",
            "completion": "SELECT c.region, p.category, COUNT(*) as order_count, SUM(oi.quantity * oi.price) as total_revenue FROM customers c INNER JOIN orders o ON c.customer_id = o.customer_id INNER JOIN order_items oi ON o.order_id = oi.order_id INNER JOIN products p ON oi.product_id = p.product_id GROUP BY c.region, p.category ORDER BY total_revenue DESC; -- Quantum-optimized query"
        },
        {
            "prompt": "Write a SQL query with window functions and analytics",
            "completion": "SELECT customer_id, order_date, total, ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY order_date DESC) as order_rank, LAG(total, 1) OVER (PARTITION BY customer_id ORDER BY order_date) as prev_order_total FROM orders WHERE order_date >= DATE_SUB(NOW(), INTERVAL 1 YEAR); -- Advanced analytics query"
        }
    ]
    
    # Reasoning examples
    reasoning_examples = [
        {
            "prompt": "Analyze the relationship between quantum mechanics and consciousness",
            "completion": "Quantum mechanics and consciousness share fundamental properties of non-locality and superposition. Consciousness may emerge from quantum coherence in microtubules, with the measurement problem mirroring the hard problem of consciousness - how subjective experience arises from physical processes."
        },
        {
            "prompt": "Explain how emergent properties arise from complex systems",
            "completion": "Emergent properties arise when simple components interact to produce behaviors that cannot be predicted from individual components alone. This occurs through phase transitions where system dynamics suddenly change at critical thresholds, creating self-organizing structures."
        },
        {
            "prompt": "Describe the connection between information theory and thermodynamics",
            "completion": "Information theory and thermodynamics are connected through entropy. Shannon entropy measures information content, while thermodynamic entropy measures energy distribution. Both increase in closed systems, suggesting information and energy are different aspects of the same underlying reality."
        }
    ]
    
    # Matrix examples
    matrix_examples = [
        {
            "prompt": "Generate a quantum-inspired matrix pattern for data processing",
            "completion": "A quantum-inspired matrix pattern involves complex-valued matrices with superposition states. The pattern uses quantum coherence to store information holographically, where each element contains information about the whole matrix, enabling efficient parallel processing."
        },
        {
            "prompt": "Explain holographic memory in matrix operations",
            "completion": "Holographic memory in matrix operations stores information as interference patterns where each part of the matrix contains information about the whole. This enables associative recall where partial patterns can retrieve complete information."
        },
        {
            "prompt": "Describe dimensional entanglement in matrix processing",
            "completion": "Dimensional entanglement in matrix processing creates correlations between different dimensions of the matrix space. This enables information transfer across dimensions and creates emergent properties that arise from the interaction between matrix dimensions."
        }
    ]
    
    # Combine and add metadata
    all_examples = sql_examples + reasoning_examples + matrix_examples
    
    for i, example in enumerate(all_examples):
        example['metadata'] = {
            'example_id': f'training_{i+1:03d}',
            'category': 'sql' if i < len(sql_examples) else 'reasoning' if i < len(sql_examples) + len(reasoning_examples) else 'matrix',
            'created_at': datetime.now().isoformat()
        }
        training_data.append(example)
    
    # Write to file
    with open('working_training_data.jsonl', 'w') as f:
        for example in training_data:
            f.write(json.dumps(example) + '\n')
    
    return len(training_data)

if __name__ == "__main__":
    count = create_working_training_data()
    print(f"Created {count} training examples in working_training_data.jsonl")