Vedika8/image-processing-pipeline

1import sys
2import os
3sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
4from models.summarization_model import SummarizationModel
5
6def test_summarization_model():
7    # Initialize the summarization model
8    summarization_model = SummarizationModel()
9
10    # Define a sample text to summarize
11    sample_text = """
12    The recent advancements in artificial intelligence have been remarkable. 
13    With the advent of new models and techniques, AI has become increasingly proficient in tasks such as natural language processing, image recognition, and decision-making. 
14    However, challenges still remain, particularly in areas like ethical considerations, data privacy, and the interpretability of AI models. 
15    Moving forward, it is crucial to address these challenges to ensure that AI technology is developed responsibly and benefits society as a whole.
16    """
17
18    # Perform summarization
19    summarized_text = summarization_model.summarize(sample_text)
20
21    # Print the summarized text for inspection
22    print("Summarized Text:", summarized_text)
23
24    # Add assertions for testing (optional)
25    assert summarized_text is not None, "Summarization returned None."
26    assert isinstance(summarized_text, str), "Summarized text is not a string."
27    assert len(summarized_text) < len(sample_text), "Summarized text is not shorter than the original text."
28
29if __name__ == "__main__":
30    test_summarization_model()
31