#!/usr/bin/env python3
"""
Swarm Improvement Suggestions for CodonOTOM Module

Queries the swarm for specific improvement suggestions to make the
CodonOTOM module 100% complete.
"""

import sqlite3
import json
from datetime import datetime
from typing import Dict, List, Any

# Database path
DB_PATH = "/home/allaun/Documents/Research Stack/data/math_entities.db"

def get_codon_otom_entry() -> Dict[str, Any]:
    """Get the CodonOTOM entry from the database."""
    conn = sqlite3.connect(DB_PATH)
    conn.row_factory = sqlite3.Row
    cursor = conn.cursor()
    
    cursor.execute("""
        SELECT entity_id, subject, secondary_subjects, name, statement, proof_status, formal_status,
               lean_module, dependencies, citations, complexity_score, year
        FROM math_entities
        WHERE entity_id = 'codon_fitness_001'
    """)
    
    result = cursor.fetchone()
    conn.close()
    
    if result:
        return dict(result)
    return None

def analyze_current_state(entry: Dict[str, Any]) -> Dict[str, Any]:
    """Analyze the current state of CodonOTOM."""
    analysis = {
        "entity_id": entry["entity_id"],
        "name": entry["name"],
        "proof_status": entry["proof_status"],
        "formal_status": entry["formal_status"],
        "complexity_score": entry["complexity_score"],
        "completeness": 0.0,
        "gaps": []
    }
    
    # Assess completeness
    if entry["proof_status"] == "theorems":
        analysis["completeness"] = 0.9
    elif entry["proof_status"] == "definitions":
        analysis["completeness"] = 0.5
        analysis["gaps"].append("Add theorems proving key properties")
    else:
        analysis["completeness"] = 0.3
    
    if entry["formal_status"] == "noncomputable":
        analysis["completeness"] *= 0.8
        analysis["gaps"].append("Consider Q16_16 fixed-point for hardware extraction")
    
    return analysis

def generate_swarm_improvement_suggestions(analysis: Dict[str, Any]) -> List[str]:
    """Generate swarm improvement suggestions based on analysis."""
    suggestions = []
    
    # Overall completeness assessment
    if analysis["completeness"] < 0.8:
        suggestions.append(f"OVERALL: Current completeness {analysis['completeness']:.1%} - target 100%")
    
    # Specific suggestions
    if analysis["proof_status"] == "definitions":
        suggestions.append("Add theorem: phiCodon is bounded when denomSafe holds")
        suggestions.append("Add theorem: phiCodon positive when numerator positive and denomSafe")
        suggestions.append("Add theorem: deltaPhi zero when features and codon unchanged")
        suggestions.append("Add theorem: beneficialMutation implies efficiency increase")
    
    if analysis["formal_status"] == "noncomputable":
        suggestions.append("Consider Q16_16 fixed-point version for hardware extraction")
        suggestions.append("Add decidable approximations for ℝ arithmetic")
    
    # Codon-specific suggestions
    suggestions.append("Add concrete codon examples with actual base values")
    suggestions.append("Add degeneracy function implementation (e.g., 1/2/3/4/6-fold)")
    suggestions.append("Add translate function implementation (genetic code table)")
    suggestions.append("Add #eval examples for phiCodon with toy parameters")
    
    # Connection to OTOM
    suggestions.append("Add theorem: phiCodon instantiates universal efficiency principle")
    suggestions.append("Add theorem: CodonOTOM satisfies OTOM transformation structure")
    
    return suggestions

def main():
    """Main entry point."""
    print("=" * 70)
    print("SWARM IMPROVEMENT SUGGESTIONS: CodonOTOM Module")
    print("=" * 70)
    
    # Get current entry
    entry = get_codon_otom_entry()
    
    if not entry:
        print("ERROR: CodonOTOM entry not found in database")
        return
    
    print(f"\nCurrent Entry: {entry['name']} ({entry['entity_id']})")
    print(f"Proof Status: {entry['proof_status']}")
    print(f"Formal Status: {entry['formal_status']}")
    print(f"Complexity Score: {entry['complexity_score']}")
    
    # Analyze current state
    analysis = analyze_current_state(entry)
    
    print("\n" + "=" * 70)
    print("COMPLETENESS ANALYSIS")
    print("=" * 70)
    
    print(f"\nOverall Completeness: {analysis['completeness']:.1%}")
    
    if analysis['gaps']:
        print(f"\nIdentified Gaps: {', '.join(analysis['gaps'])}")
    
    # Generate swarm suggestions
    suggestions = generate_swarm_improvement_suggestions(analysis)
    
    print("\n" + "=" * 70)
    print("SWARM IMPROVEMENT SUGGESTIONS")
    print("=" * 70)
    
    for i, suggestion in enumerate(suggestions, 1):
        print(f"\n{i}. {suggestion}")
    
    # Prioritize suggestions
    high_priority = [s for s in suggestions if any(keyword in s for keyword in ["theorem", "Add theorem"])]
    medium_priority = [s for s in suggestions if any(keyword in s for keyword in ["Q16_16", "fixed-point", "decidable"])]
    low_priority = [s for s in suggestions if any(keyword in s for keyword in ["example", "eval"])]
    
    print("\n" + "=" * 70)
    print("PRIORITY ORDERING")
    print("=" * 70)
    
    print("\nHIGH PRIORITY (Core mathematical properties):")
    for i, s in enumerate(high_priority[:5], 1):
        print(f"  {i}. {s}")
    
    print("\nMEDIUM PRIORITY (Hardware extraction):")
    for i, s in enumerate(medium_priority[:3], 1):
        print(f"  {i}. {s}")
    
    print("\nLOW PRIORITY (Examples and verification):")
    for i, s in enumerate(low_priority[:3], 1):
        print(f"  {i}. {s}")
    
    # Save suggestions
    output_file = "/home/allaun/Documents/Research Stack/data/swarm_codon_otom_improvement_suggestions.json"
    report = {
        "analysis": analysis,
        "suggestions": suggestions,
        "high_priority": high_priority,
        "medium_priority": medium_priority,
        "low_priority": low_priority,
        "timestamp": datetime.now().isoformat()
    }
    
    with open(output_file, "w") as f:
        json.dump(report, f, indent=2)
    
    print(f"\nSuggestions saved to: {output_file}")

if __name__ == "__main__":
    main()