feat: Add semantic naming engine using validated mixing formula

demo_semantic_naming.py

@@ -0,0 +1,229 @@
+#!/usr/bin/env python3
+"""
+Demo: How semantic naming helps the Harmonizer
+Shows practical application of the validated mixing formula
+"""
+
+from harmonizer.divine_invitation_engine_V2 import DivineInvitationSemanticEngine, Coordinates
+from harmonizer.semantic_naming import SemanticNamingEngine
+
+
+def demo_1_detect_and_suggest():
+    """Demo 1: Detect bad name and suggest better ones"""
+    print("=" * 70)
+    print("DEMO 1: DETECT BAD NAME + SUGGEST IMPROVEMENTS")
+    print("=" * 70)
+
+    # Analyze a disharmonious function name
+    engine = DivineInvitationSemanticEngine()
+    namer = SemanticNamingEngine()
+
+    # Bad example: function name says "get" but does "delete"
+    print("\n❌ BAD CODE:")
+    print("def get_user(user_id):")
+    print("    database.delete(user_id)")
+    print("    return True")
+
+    # Analyze intent vs execution
+    intent_result = engine.analyze_text("get user")
+    execution_result = engine.analyze_text("delete")
+
+    print(f"\nIntent (function name):  {intent_result.coordinates}")
+    print(f"Execution (body):        {execution_result.coordinates}")
+
+    distance = engine.get_distance(intent_result.coordinates, execution_result.coordinates)
+    print(f"Disharmony distance:     {distance:.3f} ⚠️ HIGH!")
+
+    # Suggest better names based on actual execution
+    print("\n✅ SUGGESTED FIXES based on execution semantics:")
+    suggestions = namer.suggest_names(execution_result.coordinates, context="user", top_n=5)
+
+    for name, score in suggestions:
+        print(f"  • {name:25s} (match: {score:.1%})")
+
+
+def demo_2_generate_from_intent():
+    """Demo 2: Generate function structure from semantic intent"""
+    print("\n" + "=" * 70)
+    print("DEMO 2: GENERATE FUNCTION FROM SEMANTIC INTENT")
+    print("=" * 70)
+
+    engine = DivineInvitationSemanticEngine()
+    namer = SemanticNamingEngine()
+
+    # User describes what they want
+    intent = "validate user input compassionately"
+    print(f"\n📝 User intent: '{intent}'")
+
+    # Analyze semantic profile
+    result = engine.analyze_text(intent)
+    print(f"Semantic profile: {result.coordinates}")
+    print(f"Explanation: {namer.explain_coordinates(result.coordinates)}")
+
+    # Suggest function names
+    print("\n💡 Suggested function names:")
+    suggestions = namer.suggest_names(result.coordinates, context="input", top_n=3)
+    for name, score in suggestions:
+        print(f"  • {name} (match: {score:.1%})")
+
+    # Show what the function should do
+    print("\n📋 Generated function skeleton:")
+    print(f"""
+def {suggestions[0][0]}(user_input):
+    '''
+    {namer.explain_coordinates(result.coordinates)}
+    '''
+    # Justice component: Validation logic
+    if not user_input:
+        # Love component: Helpful error message
+        raise ValueError("Please provide valid input")
+
+    # Wisdom component: Check against rules
+    if not meets_requirements(user_input):
+        # Love component: Explain what's wrong
+        return ValidationResult(
+            valid=False,
+            message="Your input needs: [specific guidance]"
+        )
+
+    return ValidationResult(valid=True)
+""")
+
+
+def demo_3_refactoring_suggestion():
+    """Demo 3: Suggest refactoring with semantic names"""
+    print("=" * 70)
+    print("DEMO 3: SEMANTIC-AWARE REFACTORING")
+    print("=" * 70)
+
+    engine = DivineInvitationSemanticEngine()
+    namer = SemanticNamingEngine()
+
+    # Analyze a multi-purpose function
+    print("\n⚠️  PROBLEMATIC CODE (does too much):")
+    print("""
+def process_user(user_data):
+    # Validation (Justice)
+    if not user_data.is_valid:
+        raise ValueError("Invalid data")
+
+    # Data transformation (Power)
+    transformed = transform_data(user_data)
+
+    # Storage (Power)
+    save_to_database(transformed)
+
+    # Notification (Love)
+    send_welcome_email(user_data.email)
+
+    # Analytics (Wisdom)
+    log_user_metrics(user_data)
+""")
+
+    # Analyze each operation
+    operations = {
+        'validation': 'validate user data',
+        'transformation': 'transform data',
+        'storage': 'save database',
+        'notification': 'send email',
+        'analytics': 'log metrics'
+    }
+
+    print("\n🔍 SEMANTIC ANALYSIS OF OPERATIONS:")
+    coords_map = {}
+    for op_name, op_text in operations.items():
+        result = engine.analyze_text(op_text)
+        coords_map[op_name] = result.coordinates
+        dominant = namer._get_dominant_dimension(result.coordinates)
+        print(f"  {op_name:15s}: {result.coordinates} [{dominant.upper()}]")
+
+    # Suggest splitting
+    print("\n✅ SUGGESTED REFACTORING:")
+    print("\nSplit into semantically coherent functions:")
+
+    # Group by semantic similarity
+    groups = {
+        'validation': ['validation'],
+        'processing': ['transformation', 'storage'],
+        'notification': ['notification', 'analytics']
+    }
+
+    for group_name, ops in groups.items():
+        print(f"\n{group_name.upper()} GROUP:")
+        # Get average coordinates for this group
+        group_coords = Coordinates(
+            love=sum(coords_map[op].love for op in ops) / len(ops),
+            justice=sum(coords_map[op].justice for op in ops) / len(ops),
+            power=sum(coords_map[op].power for op in ops) / len(ops),
+            wisdom=sum(coords_map[op].wisdom for op in ops) / len(ops)
+        )
+
+        suggestions = namer.suggest_names(group_coords, context="user", top_n=3)
+        print(f"  Suggested names:")
+        for name, score in suggestions:
+            print(f"    • {name} (match: {score:.1%})")
+
+
+def demo_4_code_review():
+    """Demo 4: Automated semantic code review"""
+    print("\n" + "=" * 70)
+    print("DEMO 4: SEMANTIC CODE REVIEW")
+    print("=" * 70)
+
+    engine = DivineInvitationSemanticEngine()
+    namer = SemanticNamingEngine()
+
+    # Check if function name matches execution
+    functions_to_review = [
+        ("calculate_total", "sum values"),  # ✅ Good match
+        ("process_data", "delete records"),  # ❌ Mismatch
+        ("validate_input", "check rules"),  # ✅ Good match
+        ("get_user", "create user"),  # ❌ Mismatch
+    ]
+
+    print("\n📊 REVIEWING FUNCTION NAMES:\n")
+
+    for func_name, execution in functions_to_review:
+        intent = engine.analyze_text(func_name)
+        actual = engine.analyze_text(execution)
+        distance = engine.get_distance(intent.coordinates, actual.coordinates)
+
+        if distance < 0.3:
+            status = "✅ GOOD"
+            icon = "✅"
+        elif distance < 0.7:
+            status = "⚠️  REVIEW"
+            icon = "⚠️"
+        else:
+            status = "❌ BAD"
+            icon = "❌"
+
+        print(f"{icon} {func_name:20s} ({execution:20s})")
+        print(f"   Disharmony: {distance:.3f} - {status}")
+
+        if distance > 0.3:
+            # Suggest better name
+            suggestions = namer.suggest_names(actual.coordinates, top_n=1)
+            if suggestions:
+                print(f"   💡 Suggest: {suggestions[0][0]} (match: {suggestions[0][1]:.1%})")
+        print()
+
+
+if __name__ == "__main__":
+    print("\n🎯 SEMANTIC NAMING ENGINE DEMONSTRATIONS")
+    print("Showing how the validated mixing formula helps the Harmonizer\n")
+
+    demo_1_detect_and_suggest()
+    demo_2_generate_from_intent()
+    demo_3_refactoring_suggestion()
+    demo_4_code_review()
+
+    print("\n" + "=" * 70)
+    print("✅ DEMOS COMPLETE")
+    print("=" * 70)
+    print("\nThese demos show how the mixing formula enables:")
+    print("  1. Better refactoring suggestions")
+    print("  2. Function name generation from intent")
+    print("  3. Semantic-aware code splitting")
+    print("  4. Automated code review with suggestions")
+    print("\nAll powered by the validated LJWP mixing formula! 🚀")