Update app.py

app.py

@@ -35,39 +35,31 @@ def analyze_video(video_path, progress=gr.Progress()):
 
     output_components = []
 
-    # Add transcript near the beginning
+    # Add transcript
     output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10, visible=True))
     
     for speaker_id, speaker_charts in charts.items():
-        markdown_content = f"""
-        | {speaker_id} |
-        |-----------|
-        """
         speaker_explanations = explanations[speaker_id]
         speaker_general_impression = general_impressions[speaker_id]
         speaker_section = [
-            gr.Markdown(markdown_content, visible=True),
+            gr.Markdown(f"## {speaker_id}", visible=True),
             gr.Textbox(value=speaker_general_impression, label="General Impression", lines=3, visible=True),
-            gr.Plot(value=speaker_charts.get("attachment", None), visible=True),
-            gr.Textbox(value=speaker_explanations.get("attachment", ""), label="Attachment Styles Explanation", visible=True),
-            gr.Plot(value=speaker_charts.get("dimensions", None), visible=True),
-            gr.Plot(value=speaker_charts.get("bigfive", None), visible=True),
-            gr.Textbox(value=speaker_explanations.get("bigfive", ""), label="Big Five Traits Explanation", visible=True),
-            gr.Plot(value=speaker_charts.get("personality", None), visible=True),
-            gr.Textbox(value=speaker_explanations.get("personality", ""), label="Personality Disorders Explanation", visible=True),
+            gr.Plot(value=speaker_charts["attachment"], visible=True),
+            gr.Textbox(value=speaker_explanations["attachment"], label="Attachment Styles Explanation", visible=True),
+            gr.Plot(value=speaker_charts["dimensions"], visible=True),
+            gr.Plot(value=speaker_charts["bigfive"], visible=True),
+            gr.Textbox(value=speaker_explanations["bigfive"], label="Big Five Traits Explanation", visible=True),
+            gr.Plot(value=speaker_charts["personality"], visible=True),
+            gr.Textbox(value=speaker_explanations["personality"], label="Personality Disorders Explanation", visible=True),
         ]
         output_components.extend(speaker_section)
 
-    while len(output_components) < 49:
-        output_components.extend([gr.update(visible=False)] * 8)
-
     # Add execution info
     output_components.append(
         gr.Textbox(value=f"Completed in {int(execution_time)} seconds.", label="Execution Information", visible=True))
 
     return output_components
 
-
 with gr.Blocks() as iface:
     gr.Markdown("# AI Personality Detection")
     
@@ -107,10 +99,12 @@ with gr.Blocks() as iface:
     def use_example():
         return "examples/Scenes.From.A.Marriage.US.mp4"
 
+    output_container = gr.Column() 
+
     analyze_button.click(
         fn=analyze_video,
         inputs=[video_input],
-        outputs=output_components,
+        outputs=output_container,
         show_progress=True
     )
 
@@ -121,7 +115,7 @@ with gr.Blocks() as iface:
     ).then(
         fn=analyze_video,
         inputs=[video_input],
-        outputs=output_components,
+        outputs=output_container,
         show_progress=True
     )