Update app.py

app.py

@@ -52,22 +52,16 @@ speech_to_text = partial(
     whisper_device=whisper_device
     )
 
-def summarize(diarized, check, summarization_pipeline):
+def summarize(diarized, summarization_pipeline):
     """
     diarized: a list of tuples. Each tuple has a string to be displayed and a label for highlighting.
         The start/end times are not highlighted [(speaker text, speaker id), (start time/end time, None)]
     check is a list of speaker ids whose speech will get summarized
     """
 
-    if len(check) == 0:
-        return ""
-
     text = ""
     for d in diarized:
-        if len(check) == 2 and d[1] is not None:
-            text += f"\n{d[1]}: {d[0]}"
-        elif d[1] in check:
-            text += f"\n{d[0]}"
+        text += f"\n{d[1]}: {d[0]}"
 
     # inner function cached because outer function cannot be cached
     @functools.lru_cache(maxsize=128)
@@ -122,10 +116,8 @@ with gr.Blocks() as demo:
 
             gr.Markdown("**Call Transcript:**")
             diarized = gr.HighlightedText(label="Call Transcript")
-            gr.Markdown("Choose speaker to summarize:")
-            check = gr.CheckboxGroup(
-                choices=["Customer", "Support"], show_label=False, type="value"
-            )
+            gr.Markdown("Summarize Speaker")
+            sum_btn = gr.Button("Get Summary")
             summary = gr.Textbox(lines=4)
             sentiment_btn = gr.Button("Get Customer Sentiment")
             analyzed = gr.HighlightedText(color_map=color_map)
@@ -146,7 +138,7 @@ with gr.Blocks() as demo:
         outputs=diarized,
     )
     # when summarize checkboxes are changed, create summary
-    check.change(fn=partial(summarize, summarization_pipeline=summarization_pipeline), inputs=[diarized, check], outputs=summary)
+    sum_btn.click(fn=partial(summarize, summarization_pipeline=summarization_pipeline), inputs=[diarized], outputs=summary)
 
     # when sentiment button clicked, display highlighted text and plot
     sentiment_btn.click(fn=partial(sentiment, emotion_pipeline=emotion_pipeline), inputs=diarized, outputs=[analyzed])