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import whisper
from .compute_fluency import compute_fluency_score
def main(file_path: str, model_size: str = "base", filler_count = None) -> dict:
try:
whisper_model = whisper.load_model(model_size)
results = compute_fluency_score(file_path, whisper_model, filler_count)
# Structure response
response = {
"fluency_score": round(results['fluency_score'], 2)
# "insight": results["insight"],
# "SRS": round(results["SRS"], 2),
# "PAS": round(results["PAS"], 2),
# "transcript": results["transcript"]
}
return response
except Exception as e:
raise RuntimeError(f"Error during analysis: {str(e)}")
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