summarize updated

app.py

@@ -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, minLength, maxLength):
+def generate_summary_from_text(text):
    summarizer = pipeline("summarization", model="Falconsai/text_summarization")
-   return summarizer(text, max_length=maxLength, min_length=minLength, do_sample=False)
+   return summarizer(text, max_length=100, min_length=15, do_sample=False)
 
 def text_classification(text):
    classifier = pipeline(task="text-classification", model="SamLowe/roberta-base-go_emotions", top_k=None)