Update app.py

app.py

@@ -13,7 +13,7 @@ llm = load_model(openai_api_key)
 def analyze_video(video_path, progress=gr.Progress()):
     start_time = time.time()
     if not video_path:
-        return [None] * 29  # Return None for all outputs
+        return [None] * 32  # Return None for all outputs
 
     progress(0, desc="Starting analysis...")
     progress(0.2, desc="Starting transcription and diarization")
@@ -37,32 +37,36 @@ def analyze_video(video_path, progress=gr.Progress()):
     output_components.append(f"Completed in {int(execution_time)} seconds.")
     output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10, visible=True))
 
-    for i, (speaker_id, speaker_charts) in enumerate(charts.items(), start=1):
-        speaker_explanations = explanations[speaker_id]
-        speaker_general_impression = general_impressions[speaker_id]
+    for i in range(3):  # Always process 3 speakers, even if some are empty
+        speaker_id = f"Speaker {i+1}"
+        speaker_charts = charts.get(speaker_id, {})
+        speaker_explanations = explanations.get(speaker_id, {})
+        speaker_general_impression = general_impressions.get(speaker_id, "")
         
         output_components.extend([
-            gr.Markdown(f"### {speaker_id}", visible=True),
-            gr.Textbox(value=speaker_general_impression, label="General Impression", visible=True, lines=10),
-            gr.Plot(value=speaker_charts.get("attachment", None), visible=True),
-            gr.Plot(value=speaker_charts.get("dimensions", None), visible=True),
-            gr.Textbox(value=speaker_explanations.get("attachment", ""), label="Attachment Styles Explanation", visible=True, lines=2),
-            gr.Plot(value=speaker_charts.get("bigfive", None), visible=True),
-            gr.Textbox(value=speaker_explanations.get("bigfive", ""), label="Big Five Traits Explanation", visible=True, lines=2),
-            gr.Plot(value=speaker_charts.get("personality", None), visible=True),
-            gr.Textbox(value=speaker_explanations.get("personality", ""), label="Personality Disorders Explanation", visible=True, lines=2)
+            gr.Markdown(f"### {speaker_id}", visible=bool(speaker_charts)),
+            gr.Textbox(value=speaker_general_impression, label="General Impression", visible=bool(speaker_charts), lines=10),
+            gr.Plot(value=speaker_charts.get("attachment", None), visible=bool(speaker_charts)),
+            gr.Plot(value=speaker_charts.get("dimensions", None), visible=bool(speaker_charts)),
+            gr.Textbox(value=speaker_explanations.get("attachment", ""), label="Attachment Styles Explanation", visible=bool(speaker_charts), lines=2),
+            gr.Plot(value=speaker_charts.get("bigfive", None), visible=bool(speaker_charts)),
+            gr.Textbox(value=speaker_explanations.get("bigfive", ""), label="Big Five Traits Explanation", visible=bool(speaker_charts), lines=2),
+            gr.Plot(value=speaker_charts.get("personality", None), visible=bool(speaker_charts)),
+            gr.Textbox(value=speaker_explanations.get("personality", ""), label="Personality Disorders Explanation", visible=bool(speaker_charts), lines=2)
         ])
 
-    # Pad with None for any missing speakers
-    while len(output_components) < 29:
+    # Ensure we always return 32 components
+    while len(output_components) < 32:
         output_components.append(None)
 
     return output_components
 
 def use_example_1():
     return "examples/Scenes.From.A.Marriage.US.mp4"
+
 def use_example_2():
     return "examples/Billie Eilish.mp4"
+
 def use_example_3():
     return "examples/Elliot Rodger.mp4"
 
@@ -80,7 +84,7 @@ def get_middle_frame(video_path):
     return None
 
 def clear_outputs():
-    return [None] * 29
+    return [None] * 32
 
 with gr.Blocks() as iface:
     gr.Markdown("# Multiple-Speakers-Personality-Analyzer")
@@ -93,14 +97,13 @@ with gr.Blocks() as iface:
             
     # Create output components
     output_components = []
-    # Add transcript output near the top
     execution_box = gr.Textbox(label="Execution Info", value="N/A", lines=1)
     output_components.append(execution_box)
 
     transcript = gr.Textbox(label="Transcript", lines=10, visible=False)
     output_components.append(transcript)
 
-    for n in range(3):  # Assuming maximum of 3 speakers
+    for n in range(3):  # Always create 3 speaker tabs
         with gr.Tab(label=f'Speaker {n + 1}', visible=False) as tab:
             gr.Markdown(visible=False)
             gr.Textbox(label="General Impression", visible=False)
@@ -113,14 +116,7 @@ with gr.Blocks() as iface:
             gr.Textbox(label="Personality Disorders Explanation", visible=False)
             output_components.extend([tab] + [component for component in tab.children])
 
-    with open('description.txt', 'r') as file:
-        description_txt = file.read()
-    with gr.Tab(label=f'Description', visible=True):
-        gr.Markdown(description_txt)
-        gr.HTML("<div style='height: 20px;'></div>")
-        gr.Image(value="appendix/AI Personality Detection flow - 1.png", label='Flowchart 1', width=1000)
-        gr.Image(value="appendix/AI Personality Detection flow - 2.png", label='Flowchart 2', width=1000)
-
+    
     gr.Markdown("### Example Videos")
     with gr.Row():
         with gr.Column(scale=1):
@@ -144,6 +140,15 @@ with gr.Blocks() as iface:
             example_video_3 = gr.Video(example_video_3_path, label="Example 3", visible=False)
             use_example_button_3 = gr.Button("Load Example 3")
             
+    with open('description.txt', 'r') as file:
+        description_txt = file.read()
+    with gr.Tab(label=f'Description', visible=True):
+        gr.Markdown(description_txt)
+        gr.HTML("<div style='height: 20px;'></div>")
+        gr.Image(value="appendix/AI Personality Detection flow - 1.png", label='Flowchart 1', width=1000)
+        gr.Image(value="appendix/AI Personality Detection flow - 2.png", label='Flowchart 2', width=1000)
+
+            
     analyze_button.click(
         fn=clear_outputs,
         inputs=[],