Update app.py

app.py

@@ -9,10 +9,12 @@ from config import openai_api_key
 # Load the model
 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)] * 13
+        return [gr.Markdown("Please upload a video file.")] + [gr.update(visible=False)] * 49 + [
+            "Analysis not started."]
 
     progress(0, desc="Starting analysis...")
     progress(0.2, desc="Starting transcription and diarization")
@@ -33,39 +35,40 @@ def analyze_video(video_path, max_speakers, progress=gr.Progress()):
 
     output_components = []
 
-    # Add transcript
+    # Add transcript near the beginning
     output_components.append(gr.Textbox(value=transcription, label="Transcript", lines=10, visible=True))
-
+    
     for speaker_id, speaker_charts in charts.items():
-        markdown_content = f"### {speaker_id}"
+        markdown_content = f"""
+        | {speaker_id} |
+        |-----------|
+        """
         speaker_explanations = explanations[speaker_id]
         speaker_section = [
             gr.Markdown(markdown_content, visible=True),
-            gr.Row([
-                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),
-            ]),
-            gr.Row([
-                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.Row([
-                gr.Plot(value=speaker_charts.get("personality", None), visible=True),
-                gr.Textbox(value=speaker_explanations.get("personality", ""), label="Personality Disorders Explanation", 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),
         ]
         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))
+    while len(output_components) < 49:
+        output_components.extend([gr.update(visible=False)] * 8)
 
-    # Pad with invisible components if necessary
-    while len(output_components) < 14:
-        output_components.append(gr.update(visible=False))
+    # Add execution info
+    output_components.append(
+        gr.Textbox(value=f"Completed in {int(execution_time)} seconds.", label="Execution Information", visible=True))
 
     return output_components
 
+
 with gr.Blocks() as iface:
     gr.Markdown("# AI Personality Detection")
     gr.Markdown("Upload a video")
@@ -75,24 +78,27 @@ with gr.Blocks() as iface:
     analyze_button = gr.Button("Analyze")
 
     # Create output components
-    output_components = [
-        gr.Textbox(label="Transcript", lines=10, visible=False),
-        gr.Markdown(visible=False),
-        gr.Row([gr.Plot(visible=False), gr.Plot(visible=False), gr.Textbox(label="Attachment Styles Explanation", visible=False)]),
-        gr.Row([gr.Plot(visible=False), gr.Textbox(label="Big Five Traits Explanation", visible=False)]),
-        gr.Row([gr.Plot(visible=False), gr.Textbox(label="Personality Disorders Explanation", visible=False)]),
-        gr.Markdown(visible=False),
-        gr.Row([gr.Plot(visible=False), gr.Plot(visible=False), gr.Textbox(label="Attachment Styles Explanation", visible=False)]),
-        gr.Row([gr.Plot(visible=False), gr.Textbox(label="Big Five Traits Explanation", visible=False)]),
-        gr.Row([gr.Plot(visible=False), gr.Textbox(label="Personality Disorders Explanation", visible=False)]),
-        gr.Markdown(visible=False),
-        gr.Row([gr.Plot(visible=False), gr.Plot(visible=False), gr.Textbox(label="Attachment Styles Explanation", visible=False)]),
-        gr.Row([gr.Plot(visible=False), gr.Textbox(label="Big Five Traits Explanation", visible=False)]),
-        gr.Row([gr.Plot(visible=False), gr.Textbox(label="Personality Disorders Explanation", visible=False)]),
-        
-    ]
-
-    gr.Textbox(label="Execution Information", visible=True)
+    output_components = []
+
+    # Add transcript output near the top
+    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.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 execution info component
+    transcript_output = gr.Textbox(label="Transcript", lines=10, visible=False)
+    output_components.append(transcript_output)
 
     analyze_button.click(
         fn=analyze_video,