Update app.py

app.py

@@ -12,7 +12,7 @@ llm = load_model(openai_api_key)
 def analyze_video(video_path, max_speakers, progress=gr.Progress()):
     start_time = time.time()
     if not video_path:
-        return [gr.Markdown("Please upload a video file.")] + [gr.update(visible=False)] * 25
+        return {"error": "Please upload a video file."}
 
     progress(0, desc="Starting analysis...")
     progress(0.2, desc="Starting transcription and diarization")
@@ -31,38 +31,44 @@ def analyze_video(video_path, max_speakers, progress=gr.Progress()):
     end_time = time.time()
     execution_time = end_time - start_time
 
-    output_components = []
-
-    # Add transcript
-    output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10))
+    return {
+        "transcript": transcription,
+        "charts": charts,
+        "explanations": explanations,
+        "execution_time": int(execution_time)
+    }
 
-    # Create components for up to 3 speakers
-    for i in range(3):
-        if i < len(charts):
-            speaker_id = list(charts.keys())[i]
-            speaker_charts = charts[speaker_id]
-            speaker_explanations = explanations[speaker_id]
-            output_components.extend([
-                gr.Markdown(f"## {speaker_id}", 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),
-            ])
-        else:
-            # Add placeholder components for unused speakers
-            output_components.extend([gr.update(visible=False)] * 8)
+def generate_output_components(results):
+    if "error" in results:
+        return [gr.Markdown(results["error"])]
 
+    output_components = []
+    
+    # Add transcript
+    output_components.append(gr.Textbox(value=results["transcript"], label="Transcript", lines=10))
+    
+    # Create tabs for each speaker
+    with gr.Tabs() as tabs:
+        for speaker_id, speaker_charts in results["charts"].items():
+            speaker_explanations = results["explanations"][speaker_id]
+            with gr.Tab(label=speaker_id):
+                speaker_section = [
+                    gr.Markdown(f"## {speaker_id}\n<hr style='height:2px;border-width:0;color:black;background-color:black'>"),
+                    gr.Plot(value=speaker_charts.get("attachment", None)),
+                    gr.Textbox(value=speaker_explanations.get("attachment", ""), label="Attachment Styles Explanation"),
+                    gr.Plot(value=speaker_charts.get("dimensions", None)),
+                    gr.Plot(value=speaker_charts.get("bigfive", None)),
+                    gr.Textbox(value=speaker_explanations.get("bigfive", ""), label="Big Five Traits Explanation"),
+                    gr.Plot(value=speaker_charts.get("personality", None)),
+                    gr.Textbox(value=speaker_explanations.get("personality", ""), label="Personality Disorders Explanation"),
+                ]
+                output_components.extend(speaker_section)
+    
     # Add execution info
     output_components.append(
-        gr.Textbox(value=f"Completed in {int(execution_time)} seconds.", label="Execution Information"))
-
+        gr.Textbox(value=f"Completed in {results['execution_time']} seconds.", label="Execution Information")
+    )
+    
     return output_components
 
 with gr.Blocks() as iface:
@@ -73,31 +79,17 @@ with gr.Blocks() as iface:
     max_speakers = gr.Slider(minimum=1, maximum=3, step=1, value=2, label="Maximum Number of Speakers")
     analyze_button = gr.Button("Analyze")
 
-    # Create output components
-    output_components = [
-        gr.Textbox(label="Transcript", lines=10, visible=True)
-    ]
-
-    # Create components for up to 3 speakers
-    for _ in range(3):
-        output_components.extend([
-            gr.Markdown(visible=False),
-            gr.Plot(visible=False),
-            gr.Textbox(label="Attachment Styles Explanation", visible=False),
-            gr.Plot(visible=False),
-            gr.Plot(visible=False),
-            gr.Textbox(label="Big Five Traits Explanation", visible=False),
-            gr.Plot(visible=False),
-            gr.Textbox(label="Personality Disorders Explanation", visible=False),
-        ])
+    output = gr.HTML()
 
-    # Add execution info component
-    output_components.append(gr.Textbox(label="Execution Information", visible=False))
+    def run_analysis(video_path, max_speakers):
+        results = analyze_video(video_path, max_speakers)
+        output_components = generate_output_components(results)
+        return gr.HTML.update(value=gr.components.render(output_components))
 
     analyze_button.click(
-        fn=analyze_video,
+        fn=run_analysis,
         inputs=[video_input, max_speakers],
-        outputs=output_components,
+        outputs=[output],
         show_progress=True
     )