Update app.py

app.py

@@ -27,7 +27,7 @@ def analyze_video(video_path, language_display_name, max_speakers, progress=gr.P
     start_time = time.time()
 
     if not video_path:
-        return [gr.Markdown("Please upload a video file.")], "Analysis not started."
+        return [gr.Markdown("Please upload a video file.")] + [gr.Markdown(visible=False) for _ in range(48)] + ["Analysis not started."]
 
     # Convert the display name to the language code
     language = LANGUAGE_MAP[language_display_name]
@@ -66,30 +66,28 @@ def analyze_video(video_path, language_display_name, max_speakers, progress=gr.P
     for speaker_id, speaker_charts in charts.items():
         speaker_explanations = explanations[speaker_id]
 
-        output_components.append(gr.Markdown(f"### {speaker_id}"))
-        
-        if "attachment" in speaker_charts:
-            output_components.append(gr.Plot(speaker_charts["attachment"]))
-            output_components.append(gr.Textbox(value=speaker_explanations.get("attachment", ""),
-                           label=f"Attachment Styles Explanation - {speaker_id}", lines=2))
-        
-        if "dimensions" in speaker_charts:
-            output_components.append(gr.Plot(speaker_charts["dimensions"]))
-        
-        if "bigfive" in speaker_charts:
-            output_components.append(gr.Plot(speaker_charts["bigfive"]))
-            output_components.append(gr.Textbox(value=speaker_explanations.get("bigfive", ""),
-                           label=f"Big Five Traits Explanation - {speaker_id}", lines=2))
-        
-        if "personality" in speaker_charts:
-            output_components.append(gr.Plot(speaker_charts["personality"]))
-            output_components.append(gr.Textbox(value=speaker_explanations.get("personality", ""),
-                           label=f"Personality Disorders Explanation - {speaker_id}", lines=2))
+        output_components.extend([
+            gr.Markdown(f"### {speaker_id}"),
+            gr.Plot(speaker_charts.get("attachment", None)) if "attachment" in speaker_charts else gr.Markdown(visible=False),
+            gr.Textbox(value=speaker_explanations.get("attachment", ""), label=f"Attachment Styles Explanation - {speaker_id}", lines=2) if "attachment" in speaker_charts else gr.Markdown(visible=False),
+            gr.Plot(speaker_charts.get("dimensions", None)) if "dimensions" in speaker_charts else gr.Markdown(visible=False),
+            gr.Plot(speaker_charts.get("bigfive", None)) if "bigfive" in speaker_charts else gr.Markdown(visible=False),
+            gr.Textbox(value=speaker_explanations.get("bigfive", ""), label=f"Big Five Traits Explanation - {speaker_id}", lines=2) if "bigfive" in speaker_charts else gr.Markdown(visible=False),
+            gr.Plot(speaker_charts.get("personality", None)) if "personality" in speaker_charts else gr.Markdown(visible=False),
+            gr.Textbox(value=speaker_explanations.get("personality", ""), label=f"Personality Disorders Explanation - {speaker_id}", lines=2) if "personality" in speaker_charts else gr.Markdown(visible=False),
+        ])
 
     # Add the transcript at the end
     output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10))
 
-    return output_components, f"Completed in {int(execution_time)} seconds."
+    # Pad the output with invisible components if necessary
+    while len(output_components) < 49:
+        output_components.append(gr.Markdown(visible=False))
+
+    # Add the execution time
+    output_components.append(f"Completed in {int(execution_time)} seconds.")
+
+    return output_components
 
 # Define the Gradio interface
 with gr.Blocks() as iface:
@@ -103,9 +101,7 @@ with gr.Blocks() as iface:
     analyze_button = gr.Button("Analyze")
 
     # Create placeholders for output components
-    output_components = [gr.Markdown(visible=False) for _ in range(50)]  # Adjust the number based on your maximum possible outputs
-    
-    # Execution time box
+    output_components = [gr.Markdown(visible=False) for _ in range(49)]
     execution_info_box = gr.Textbox(label="Execution Information", value="Waiting for analysis...", lines=2)
 
     analyze_button.click(