Adding summarization

app.py

@@ -2,7 +2,7 @@ from transformers import pipeline
 import gradio as gr
 
 asr = pipeline("automatic-speech-recognition", "facebook/wav2vec2-base-960h")
-
+summarizer = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
 classifier = pipeline("text-classification", model="bhadresh-savani/distilbert-base-uncased-emotion")
 
 def transcribe(audio):
@@ -13,6 +13,10 @@ def speech_to_text(speech):
     text = asr(speech)["text"]
     return text
 
+def summarize_text(text):
+    stext = summarizer(text)
+    return stext
+
 def text_to_sentiment(text):
     sentiment = classifier(text)[0]["label"]
     return sentiment 
@@ -26,8 +30,12 @@ with demo:
     text = gr.Textbox()
     b1.click(speech_to_text, inputs=audio_file, outputs=text)
     
-    b2 = gr.Button("Classify Sentiment")
+    stext = gr.Textbox()
+    b2 = gr.Button("Summarize Text")
+    b3.click(summarize_text, inputs=text, outputs=stext)
+    
+    b3 = gr.Button("Classify Sentiment")
     label = gr.Label()
-    b2.click(text_to_sentiment, inputs=text, outputs=label)
+    b3.click(text_to_sentiment, inputs=stext, outputs=label)
     
 demo.launch(share=True)