Update app.py

app.py

@@ -25,7 +25,7 @@ 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.")] + [gr.update(visible=False)] * 49 + ["Analysis not started."]
+        return [gr.Markdown("Please upload a video file.")] + [gr.update(visible=False)] * 48 + ["Analysis not started."]
 
     # Convert the display name to the language code
     language = LANGUAGE_MAP[language_display_name]
@@ -65,6 +65,8 @@ def analyze_video(video_path, language_display_name, max_speakers, progress=gr.P
 
     # Prepare outputs for each speaker
     output_components = []
+    speaker_count = len(charts)
+
     for speaker_id, speaker_charts in charts.items():
         speaker_explanations = explanations[speaker_id]
 
@@ -81,6 +83,19 @@ def analyze_video(video_path, language_display_name, max_speakers, progress=gr.P
 
         output_components.extend(speaker_section)
 
+    # Add empty placeholders for remaining outputs if fewer speakers than expected
+    while len(output_components) < 48:
+        output_components.extend([
+            gr.Markdown(visible=False),
+            gr.Plot(visible=False),
+            gr.Textbox(visible=False),
+            gr.Plot(visible=False),
+            gr.Plot(visible=False),
+            gr.Textbox(visible=False),
+            gr.Plot(visible=False),
+            gr.Textbox(visible=False),
+        ])
+
     # Add the transcript at the end
     output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10, visible=True))
 
@@ -89,6 +104,7 @@ def analyze_video(video_path, language_display_name, max_speakers, progress=gr.P
 
     return output_components
 
+
 # Define the Gradio interface
 with gr.Blocks() as iface:
     gr.Markdown("# AI Personality Detection")