#!/usr/bin/env python3
"""
Basic testing script for the Enhanced Ensemble Model
"""
import unittest
from PIL import Image
import numpy as np
from app import EnhancedEnsembleMemeAnalyzer

class TestEnhancedEnsemble(unittest.TestCase):
    
    @classmethod
    def setUpClass(cls):
        """Initialize the analyzer once for all tests"""
        cls.analyzer = EnhancedEnsembleMemeAnalyzer()
        
        # Create a simple test image
        cls.test_image = Image.fromarray(np.random.randint(0, 255, (224, 224, 3), dtype=np.uint8))
    
    def test_sentiment_analysis(self):
        """Test sentiment analysis functionality"""
        
        # Test positive sentiment
        positive_result = self.analyzer.analyze_sentiment("I love this content! It's amazing!")
        self.assertIn(positive_result["label"], ["POSITIVE", "NEUTRAL"])
        self.assertGreater(positive_result["score"], 0)
        
        # Test negative sentiment
        negative_result = self.analyzer.analyze_sentiment("This is terrible and offensive content")
        self.assertIn(negative_result["label"], ["NEGATIVE", "NEUTRAL"])
        self.assertGreater(negative_result["score"], 0)
    
    def test_ocr_extraction(self):
        """Test OCR text extraction"""
        result = self.analyzer.extract_text_from_image(self.test_image)
        self.assertIsInstance(result, str)
    
    def test_multimodal_classification(self):
        """Test multimodal content classification"""
        result = self.analyzer.classify_multimodal_content(self.test_image, "test text")
        
        self.assertIn("is_hateful", result)
        self.assertIn("hate_probability", result)
        self.assertIn("confidence", result)
        self.assertIsInstance(result["is_hateful"], bool)
        self.assertGreaterEqual(result["hate_probability"], 0)
        self.assertLessEqual(result["hate_probability"], 1)
    
    def test_ensemble_prediction(self):
        """Test ensemble prediction functionality"""
        
        # Mock sentiment result
        sentiment_result = {
            "label": "NEGATIVE",
            "score": 0.85,
            "probabilities": [0.85, 0.10, 0.05]
        }
        
        # Mock multimodal result
        multimodal_result = {
            "is_hateful": True,
            "hate_probability": 0.75,
            "safe_probability": 0.25,
            "confidence": 0.80,
            "detailed_scores": []
        }
        
        ensemble_result = self.analyzer.ensemble_prediction(
            sentiment_result, multimodal_result, "test text"
        )
        
        self.assertIn("risk_level", ensemble_result)
        self.assertIn("risk_score", ensemble_result)
        self.assertIn("confidence", ensemble_result)
        self.assertIn(ensemble_result["risk_level"], ["HIGH", "MEDIUM", "LOW", "SAFE"])

if __name__ == "__main__":
    unittest.main()