Update app.py

app.py

@@ -12,7 +12,7 @@ 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 [{"value": None, "visible": False}] * 29  # Return None for all outputs
 
     progress(0, desc="Starting analysis...")
     progress(0.2, desc="Starting transcription and diarization")
@@ -36,32 +36,35 @@ def analyze_video(video_path, progress=gr.Progress()):
     execution_time = end_time - start_time
 
     output_components = [
-        transcription,  # transcript
+        {"value": transcription, "visible": True},  # transcript
     ]
 
     for i, (speaker_id, speaker_charts) in enumerate(charts.items(), start=1):
         speaker_explanations = explanations[speaker_id]
         speaker_general_impression = general_impressions[speaker_id]
         output_components.extend([
-            f"## {speaker_id}",  # speaker header
-            speaker_general_impression,  # speaker impression
-            speaker_charts["attachment"],  # attachment plot
-            speaker_explanations["attachment"],  # attachment explanation
-            speaker_charts["dimensions"],  # dimensions plot
-            speaker_charts["bigfive"],  # bigfive plot
-            speaker_explanations["bigfive"],  # bigfive explanation
-            speaker_charts["personality"],  # personality plot
-            speaker_explanations["personality"],  # personality explanation
+            {"value": f"## {speaker_id}", "visible": True},  # speaker header
+            {"value": speaker_general_impression, "visible": True},  # speaker impression
+            {"value": speaker_charts["attachment"], "visible": True},  # attachment plot
+            {"value": speaker_explanations["attachment"], "visible": True},  # attachment explanation
+            {"value": speaker_charts["dimensions"], "visible": True},  # dimensions plot
+            {"value": speaker_charts["bigfive"], "visible": True},  # bigfive plot
+            {"value": speaker_explanations["bigfive"], "visible": True},  # bigfive explanation
+            {"value": speaker_charts["personality"], "visible": True},  # personality plot
+            {"value": speaker_explanations["personality"], "visible": True},  # personality explanation
         ])
 
     # Pad with None for any missing speakers
     while len(output_components) < 28:
-        output_components.extend([None] * 9)
+        output_components.extend([{"value": None, "visible": False}] * 9)
 
-    output_components.append(f"Completed in {int(execution_time)} seconds.")  # execution info
+    output_components.append({"value": f"Completed in {int(execution_time)} seconds.", "visible": True})  # execution info
 
     return output_components
 
+def update_output(outputs):
+    return [gr.update(value=output["value"], visible=output["visible"]) for output in outputs]
+
 def use_example():
     return "examples/Scenes.From.A.Marriage.US.mp4"
 
@@ -107,6 +110,10 @@ with gr.Blocks() as iface:
         inputs=[video_input],
         outputs=all_outputs,
         show_progress=True
+    ).then(
+        fn=update_output,
+        inputs=gr.State(lambda: analyze_video(video_input.value)),
+        outputs=all_outputs
     )
 
     use_example_button.click(
@@ -118,6 +125,10 @@ with gr.Blocks() as iface:
         inputs=[video_input],
         outputs=all_outputs,
         show_progress=True
+    ).then(
+        fn=update_output,
+        inputs=gr.State(lambda: analyze_video(video_input.value)),
+        outputs=all_outputs
     )
 
 if __name__ == "__main__":