Update app.py

app.py

@@ -9,12 +9,13 @@ from config import openai_api_key
 # Load the model
 llm = load_model(openai_api_key)
 
-
 def analyze_video(video_path, progress=gr.Progress()):
     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 {
+            "transcript": gr.Textbox(value="Please upload a video file.", label="Error"),
+            "execution_info": gr.Textbox(value="Analysis not started.", label="Execution Information")
+        }
 
     progress(0, desc="Starting analysis...")
     progress(0.2, desc="Starting transcription and diarization")
@@ -33,33 +34,54 @@ def analyze_video(video_path, progress=gr.Progress()):
     end_time = time.time()
     execution_time = end_time - start_time
 
-    output_components = []
+    output_components = {
+        "transcript": gr.Textbox(value=transcription, label="Transcript", lines=10),
+    }
 
-    # Add transcript
-    output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10, visible=True))
-    
-    for speaker_id, speaker_charts in charts.items():
+    for i, (speaker_id, speaker_charts) in enumerate(charts.items(), start=1):
         speaker_explanations = explanations[speaker_id]
         speaker_general_impression = general_impressions[speaker_id]
-        speaker_section = [
-            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["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)
-
-    # Add execution info
-    output_components.append(
-        gr.Textbox(value=f"Completed in {int(execution_time)} seconds.", label="Execution Information", visible=True))
+        output_components.update({
+            f"speaker_{i}_header": gr.Markdown(f"## {speaker_id}"),
+            f"speaker_{i}_impression": gr.Textbox(value=speaker_general_impression, label="General Impression", lines=3),
+            f"speaker_{i}_attachment": gr.Plot(value=speaker_charts["attachment"]),
+            f"speaker_{i}_attachment_exp": gr.Textbox(value=speaker_explanations["attachment"], label="Attachment Styles Explanation"),
+            f"speaker_{i}_dimensions": gr.Plot(value=speaker_charts["dimensions"]),
+            f"speaker_{i}_bigfive": gr.Plot(value=speaker_charts["bigfive"]),
+            f"speaker_{i}_bigfive_exp": gr.Textbox(value=speaker_explanations["bigfive"], label="Big Five Traits Explanation"),
+            f"speaker_{i}_personality": gr.Plot(value=speaker_charts["personality"]),
+            f"speaker_{i}_personality_exp": gr.Textbox(value=speaker_explanations["personality"], label="Personality Disorders Explanation"),
+        })
+
+    output_components["execution_info"] = gr.Textbox(value=f"Completed in {int(execution_time)} seconds.", label="Execution Information")
 
     return output_components
 
+def use_example():
+    return "examples/Scenes.From.A.Marriage.US.mp4"
+
+def update_output(components):
+    updates = []
+    updates.append(gr.update(value=components["transcript"].value, visible=True))
+    for i in range(1, 4):
+        if f"speaker_{i}_header" in components:
+            updates.append(gr.update(visible=True))
+            updates.extend([
+                gr.update(value=components[f"speaker_{i}_header"].value),
+                gr.update(value=components[f"speaker_{i}_impression"].value),
+                gr.update(value=components[f"speaker_{i}_attachment"].value),
+                gr.update(value=components[f"speaker_{i}_attachment_exp"].value),
+                gr.update(value=components[f"speaker_{i}_dimensions"].value),
+                gr.update(value=components[f"speaker_{i}_bigfive"].value),
+                gr.update(value=components[f"speaker_{i}_bigfive_exp"].value),
+                gr.update(value=components[f"speaker_{i}_personality"].value),
+                gr.update(value=components[f"speaker_{i}_personality_exp"].value),
+            ])
+        else:
+            updates.append(gr.update(visible=False))
+    updates.append(gr.update(value=components["execution_info"].value, visible=True))
+    return updates
+
 with gr.Blocks() as iface:
     gr.Markdown("# AI Personality Detection")
     
@@ -73,39 +95,33 @@ with gr.Blocks() as iface:
             example_video = gr.Video("examples/Scenes.From.A.Marriage.US.mp4", label="Example Video")
             use_example_button = gr.Button("Use Example Video")
 
-    # Create output components
-    output_components = []
-
-    execution_info_box = gr.Textbox(label="Execution Information", value="N/A", lines=1)
-    output_components.append(execution_info_box)
-
-    for _ in range(3):  # Assuming maximum of 3 speakers
-        output_components.extend([
-            gr.Markdown(visible=False),
-            gr.Textbox(label="General Impression", 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),
-        ])
-
-    # Add transcript output component
-    transcript_output = gr.Textbox(label="Transcript", lines=10, visible=False)
-    output_components.append(transcript_output)
-
-    def use_example():
-        return "examples/Scenes.From.A.Marriage.US.mp4"
-
-    output_container = gr.Column() 
+    # Create placeholder components for output
+    with gr.Column() as output_container:
+        transcript_output = gr.Textbox(label="Transcript", lines=10, visible=False)
+        speaker_outputs = []
+        for i in range(1, 4):  # Assuming a maximum of 3 speakers
+            with gr.Column(visible=False) as speaker_column:
+                gr.Markdown(f"## Speaker {i}")
+                gr.Textbox(label="General Impression", lines=3)
+                gr.Plot(label="Attachment Styles")
+                gr.Textbox(label="Attachment Styles Explanation")
+                gr.Plot(label="Attachment Dimensions")
+                gr.Plot(label="Big Five Traits")
+                gr.Textbox(label="Big Five Traits Explanation")
+                gr.Plot(label="Personality Disorders")
+                gr.Textbox(label="Personality Disorders Explanation")
+            speaker_outputs.append(speaker_column)
+        execution_info = gr.Textbox(label="Execution Information", visible=False)
 
     analyze_button.click(
         fn=analyze_video,
         inputs=[video_input],
-        outputs=output_container,
+        outputs=[transcript_output] + speaker_outputs + [execution_info],
         show_progress=True
+    ).then(
+        fn=update_output,
+        inputs=[gr.State(analyze_video)],
+        outputs=[transcript_output] + speaker_outputs + [execution_info],
     )
 
     use_example_button.click(
@@ -115,8 +131,12 @@ with gr.Blocks() as iface:
     ).then(
         fn=analyze_video,
         inputs=[video_input],
-        outputs=output_container,
+        outputs=[transcript_output] + speaker_outputs + [execution_info],
         show_progress=True
+    ).then(
+        fn=update_output,
+        inputs=[gr.State(analyze_video)],
+        outputs=[transcript_output] + speaker_outputs + [execution_info],
     )
 
 if __name__ == "__main__":