test_inference.py

#!/usr/bin/env python3
"""
Test script for Hugging Face compatible models
"""

import sys
import os
sys.path.append(os.path.dirname(os.path.abspath(__file__)))

from inference import StoxChaiStockPredictor

def test_models():
    """Test all models with sample data"""
    print("🧪 Testing Hugging Face Models")
    print("=" * 50)
    
    try:
        # Initialize predictor
        predictor = StoxChaiStockPredictor()
        
        # Check available models
        available_models = predictor.get_available_models()
        print(f"✅ Found {len(available_models)} models: {', '.join(available_models)}")
        
        # Sample features (16 features in order)
        sample_features = [
            100.0,  # OpnPric
            105.0,  # HghPric
            98.0,   # LwPric
            102.0,  # LastPric
            100.0,  # PrvsClsgPric
            7.0,    # Price_Range
            2.0,    # Price_Change
            2.0,    # Price_Change_Pct
            1.5,    # Volume_Price_Ratio
            101.0,  # SMA_5
            100.5,  # SMA_20
            0.01,   # Price_Momentum
            1000.0, # Volume_MA
            1.2,    # Volume_Ratio
            1200.0, # TtlTradgVol
            120000.0 # TtlTrfVal
        ]
        
        print(f"\n📊 Testing with sample features:")
        feature_names = predictor.get_feature_names()
        for i, (name, value) in enumerate(zip(feature_names, sample_features)):
            print(f"  {i+1:2d}. {name:20s}: {value:8.2f}")
        
        # Test individual models
        print(f"\n🎯 Testing individual models:")
        for model_name in available_models:
            try:
                pred = predictor.predict(sample_features, model_name, lookback_days=5)
                print(f"  ✅ {model_name:15s}: ₹{pred:8.2f}")
            except Exception as e:
                print(f"  ❌ {model_name:15s}: Error - {e}")
        
        # Test ensemble prediction
        print(f"\n🔮 Testing ensemble prediction:")
        all_preds = predictor.predict_all_models(sample_features, lookback_days=5)
        
        successful_predictions = []
        for model, pred in all_preds.items():
            if pred is not None and model != 'ensemble':
                successful_predictions.append(pred)
                print(f"  ✅ {model:15s}: ₹{pred:8.2f}")
        
        if 'ensemble' in all_preds and all_preds['ensemble'] is not None:
            print(f"  🎯 Ensemble:        ₹{all_preds['ensemble']:8.2f}")
        
        # Show model info
        print(f"\n📋 Model Information:")
        model_info = predictor.get_model_info()
        for model_name, info in model_info.items():
            print(f"  {model_name:15s}: {info['type']} with {info['features']} features")
        
        print(f"\n🎉 All tests completed successfully!")
        return True
        
    except Exception as e:
        print(f"❌ Test failed: {e}")
        import traceback
        traceback.print_exc()
        return False

if __name__ == "__main__":
    success = test_models()
    sys.exit(0 if success else 1)