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ai_intelligence_layer/test_components.py

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+#!/usr/bin/env python3
+"""
+Simple test to verify the AI Intelligence Layer is working.
+This tests the data models and validation logic without requiring Gemini API.
+"""
+import json
+from models.input_models import (
+    EnrichedTelemetryWebhook,
+    RaceContext,
+    RaceInfo,
+    DriverState,
+    Competitor,
+    Strategy
+)
+from models.output_models import BrainstormResponse
+from utils.validators import StrategyValidator, TelemetryAnalyzer
+
+
+def test_models():
+    """Test that Pydantic models work correctly."""
+    print("Testing Pydantic models...")
+    
+    # Load sample data
+    with open('sample_data/sample_enriched_telemetry.json') as f:
+        telemetry_data = json.load(f)
+    
+    with open('sample_data/sample_race_context.json') as f:
+        context_data = json.load(f)
+    
+    # Parse enriched telemetry
+    telemetry = [EnrichedTelemetryWebhook(**t) for t in telemetry_data]
+    print(f"✓ Parsed {len(telemetry)} telemetry records")
+    
+    # Parse race context
+    race_context = RaceContext(**context_data)
+    print(f"✓ Parsed race context for {race_context.driver_state.driver_name}")
+    
+    return telemetry, race_context
+
+
+def test_validators(telemetry, race_context):
+    """Test validation logic."""
+    print("\nTesting validators...")
+    
+    # Test telemetry analysis
+    tire_rate = TelemetryAnalyzer.calculate_tire_degradation_rate(telemetry)
+    print(f"✓ Tire degradation rate: {tire_rate:.4f} per lap")
+    
+    aero_avg = TelemetryAnalyzer.calculate_aero_efficiency_avg(telemetry)
+    print(f"✓ Aero efficiency average: {aero_avg:.3f}")
+    
+    ers_pattern = TelemetryAnalyzer.analyze_ers_pattern(telemetry)
+    print(f"✓ ERS pattern: {ers_pattern}")
+    
+    tire_cliff = TelemetryAnalyzer.project_tire_cliff(telemetry, race_context.race_info.current_lap)
+    print(f"✓ Projected tire cliff: Lap {tire_cliff}")
+    
+    # Test strategy validation
+    test_strategy = Strategy(
+        strategy_id=1,
+        strategy_name="Test Strategy",
+        stop_count=1,
+        pit_laps=[32],
+        tire_sequence=["medium", "hard"],
+        brief_description="Test strategy",
+        risk_level="low",
+        key_assumption="Test assumption"
+    )
+    
+    is_valid, error = StrategyValidator.validate_strategy(test_strategy, race_context)
+    if is_valid:
+        print(f"✓ Strategy validation working correctly")
+    else:
+        print(f"✗ Strategy validation failed: {error}")
+    
+    # Test telemetry summary
+    summary = TelemetryAnalyzer.generate_telemetry_summary(telemetry)
+    print(f"\n✓ Telemetry Summary:\n{summary}")
+
+
+def test_prompts(telemetry, race_context):
+    """Test prompt generation."""
+    print("\nTesting prompt generation...")
+    
+    from prompts.brainstorm_prompt import build_brainstorm_prompt
+    
+    prompt = build_brainstorm_prompt(telemetry, race_context)
+    print(f"✓ Generated brainstorm prompt ({len(prompt)} characters)")
+    print(f"  Contains 'Monaco': {('Monaco' in prompt)}")
+    print(f"  Contains 'Hamilton': {('Hamilton' in prompt)}")
+    print(f"  Contains telemetry data: {('aero_efficiency' in prompt)}")
+
+
+if __name__ == "__main__":
+    print("=" * 60)
+    print("AI Intelligence Layer - Component Tests")
+    print("=" * 60)
+    
+    try:
+        # Test models
+        telemetry, race_context = test_models()
+        
+        # Test validators
+        test_validators(telemetry, race_context)
+        
+        # Test prompts
+        test_prompts(telemetry, race_context)
+        
+        print("\n" + "=" * 60)
+        print("✓ All component tests passed!")
+        print("=" * 60)
+        print("\nNext steps:")
+        print("1. Add your Gemini API key to .env")
+        print("2. Start the service: python main.py")
+        print("3. Test with: ./test_api.sh")
+        
+    except Exception as e:
+        print(f"\n✗ Test failed: {e}")
+        import traceback
+        traceback.print_exc()