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from course_search.search_system.data_pipeline import DataPipeline | |
import logging | |
def test_pipeline(): | |
pipeline = DataPipeline() | |
# Run pipeline and save results | |
df = pipeline.run_pipeline(save_path='data/courses_with_embeddings.pkl') | |
# Print results | |
print("\nDataFrame Info:") | |
print(df.info()) | |
print("\nSample Course:") | |
print(df.iloc[0][['title', 'description']].to_dict()) | |
print("\nSample Embedding Shape:", df.iloc[0]['embeddings'].shape) | |
if __name__ == "__main__": | |
logging.basicConfig(level=logging.INFO) | |
test_pipeline() |