NLU analysis with expert.ai

Text_Analysis_StD.py

#NLU Analysis
def text_analysis(transcript, language, audio_report, file, length):
    #Keyphrase extraction
    print("NLU analysis of " + file + " started.")
    client = ExpertAiClient()
    output = client.specific_resource_analysis(body={"document": {"text": transcript}}, 
             params={'language': language, 'resource': 'relevants'})
    
    today = date.today()
    report = f"REPORT\nFile name: {file}\nDate: {today}" \
         f"\nLength: {datetime.timedelta(seconds=round(length,0))}" \
         f"\nFile stored at: {os.path.join(audio_report, file)}.txt"
    
    report += "\n\nMAIN LEMMAS:\n"
    for lemma in output.main_lemmas:
        report += lemma.value + "\n"
    report += "\nMAIN PHRASES:\n"
    for lemma in output.main_phrases:
        report += lemma.value + "\n"
    report += '\nMAIN TOPICS:\n'
    for n,topic in enumerate(output.topics):
        if topic.winner:
            report += '#' + topic.label + '\n'   
            
    #Write the report to a text file
    filepath = os.path.join(audio_report,file)
    text = open(filepath + ".txt","w")
    text.write(report)
    text.close()
    print("\nReport stored at " + filepath + ".txt")
    return report