Update app.py

app.py

@@ -166,29 +166,45 @@ def process_and_visualize(file_content):
     
     output_text = f"Average Performance per Model:\n{averages.sort_values(by='Average Performance').to_string()}"
         
-    return output_text, image_avg, image_line, image_heatmap, image_boxplot, plotly_avg, list(plotly_tasks.values())
+    return output_text, image_avg, image_line, image_heatmap, image_boxplot, plotly_avg, plotly_tasks
 
 if __name__ == "__main__":
     
     task_names = ['tinyArc', 'tinyHellaswag', 'tinyMMLU', 'tinyTruthfulQA', 'tinyTruthfulQA_mc1', 'tinyWinogrande']
     
-    iface = gr.Interface(
-        fn=process_and_visualize,
-        inputs=gr.Textbox(lines=10, label="Paste your data here"),
-        outputs=[
-            gr.Textbox(label="Average Performance per Model"),
-            gr.Image(label="Matplotlib Average Performance Chart"),
-            gr.Image(label="Matplotlib Task Performance Line Chart"),
-            gr.Image(label="Matplotlib Task Performance Heatmap"),
-            gr.Image(label="Matplotlib Performance Distribution Boxplot"),
-            gr.HTML(label="Plotly Average Performance Chart"),
-           gr.TabbedInterface(
-               [gr.HTML(f"Plotly {task} Chart") for task in task_names]
-           )
+    with gr.Blocks(title="LLM Benchmark Visualizer") as demo:
+        gr.Markdown("Upload your LLM benchmark data and visualize the results.")
+        
+        with gr.Row():
+           input_text = gr.Textbox(lines=10, label="Paste your data here")
+            
+        with gr.Row():
+             output_text = gr.Textbox(label="Average Performance per Model")
 
-        ],
-        title="LLM Benchmark Visualizer",
-        description="Upload your LLM benchmark data and visualize the results."
-    )
-    
-    iface.launch(share=True)
+        with gr.Row():
+            with gr.Column():
+                image_avg = gr.Image(label="Matplotlib Average Performance Chart")
+                image_line = gr.Image(label="Matplotlib Task Performance Line Chart")
+            with gr.Column():
+                 image_heatmap = gr.Image(label="Matplotlib Task Performance Heatmap")
+                 image_boxplot = gr.Image(label="Matplotlib Performance Distribution Boxplot")
+        with gr.Row():
+              plotly_avg = gr.HTML(label="Plotly Average Performance Chart")
+       
+        with gr.Row():
+            with gr.TabbedInterface([gr.HTML(value=f"", label=f"Plotly {task} Chart") for task in task_names], label="Task Charts"):
+                pass
+
+        input_text.change(
+            fn=process_and_visualize,
+            inputs=input_text,
+            outputs=[output_text, image_avg, image_line, image_heatmap, image_boxplot, plotly_avg],
+        )
+
+        def update_tabs(file_content):
+            _, _, _, _, _, _, plotly_tasks = process_and_visualize(file_content)
+            return {task: gr.HTML(value=html) for task, html in plotly_tasks.items()}
+
+        input_text.change(fn=update_tabs, inputs=input_text, outputs=[])
+            
+    demo.launch(share=True)