summarize updated

app.py

@@ -12,7 +12,7 @@ def process_inputs(audio, option, question=None):
       return generated_text
    elif option == "Summarize":
       generated_text = generate_text_from_audio(audio)
-      return generate_summary_from_text(generated_text, minLength=50, maxLength=150), None
+      return generate_summary_from_text(generated_text, minLength=20, maxLength=150), None
    elif option == "text-classification":
       generated_text = generate_text_from_audio(audio)
       return "", text_classification(generated_text)
@@ -49,9 +49,9 @@ def generate_text_from_audio(audio):
    audio_text_result = pipe(audio_data, generate_kwargs={"task": "translate", "forced_decoder_ids": [[1, None], [2, 50359]]})
    return audio_text_result["text"]
 
-def generate_summary_from_text(text):
+def generate_summary_from_text(text, minLength, maxLength):
    summarizer = pipeline("summarization", model="Falconsai/text_summarization")
-   return summarizer(text, max_length=100, min_length=15, do_sample=False)
+   return summarizer(text, max_length=maxLength, min_length=minLength, do_sample=False)[0]['summary_text']
 
 def text_classification(text):
    classifier = pipeline(task="text-classification", model="SamLowe/roberta-base-go_emotions", top_k=None)