[Fix] plot visibility

app.py

@@ -5,21 +5,26 @@ from src.dataloading import get_leaderboard_models_cached, get_leaderboard_datas
 
 def create_heatmap(selected_models, selected_dataset):
     if not selected_models or not selected_dataset:
-        return None, gr.update(visible=False)   # Hide the plot if no models or dataset selected
+        return None  # ✅ Just return None to hide the plot
     
     # Generate random similarity matrix
     size = len(selected_models)
     similarities = np.random.rand(size, size)
     similarities = (similarities + similarities.T) / 2  # Make symmetric
+    similarities = np.round(similarities, 2)  # Round for clarity
     
-    # Create plot
-    fig = go.Figure()
-    fig.add_trace(go.Heatmap(
-        z=similarities,
-        x=selected_models,
-        y=selected_models,
-        colorscale='Viridis'
-    ))
+    # Create the heatmap figure
+    fig = go.Figure(
+        data=go.Heatmap(
+            z=similarities,  # ✅ Ensure it's a NumPy array
+            x=selected_models,
+            y=selected_models,
+            colorscale='Viridis',
+            zmin=0, zmax=1,  # Normalize scale
+            text=similarities,  # ✅ Show values in heatmap
+            hoverinfo="text"
+        )
+    )
     
     # Improve axis readability
     fig.update_layout(
@@ -28,12 +33,12 @@ def create_heatmap(selected_models, selected_dataset):
         yaxis_title="Models",
         xaxis=dict(tickangle=45, automargin=True),
         yaxis=dict(automargin=True),
-        width=800 + 20*len(selected_models),
-        height=800 + 20*len(selected_models),
-        margin=dict(b=100, l=100)  # Add bottom/left margin for labels
+        width=800 + 20 * len(selected_models),
+        height=800 + 20 * len(selected_models),
+        margin=dict(b=100, l=100),  # Add bottom/left margin for labels
     )
 
-    return fig, gr.update(visible=True)  # Show the plot
+    return fig  # ✅ Return only the figure
 
 
 def validate_inputs(selected_models, selected_dataset):
@@ -64,7 +69,7 @@ with gr.Blocks(title="LLM Similarity Analyzer") as demo:
         )
     
     generate_btn = gr.Button("Generate Heatmap", variant="primary")
-    heatmap = gr.Plot(label="Similarity Heatmap", visible=False)
+    heatmap = gr.Plot(label="Similarity Heatmap", visible=True)  # ✅ Ensure visible=True
     
     # Event handling
     generate_btn.click(
@@ -74,7 +79,7 @@ with gr.Blocks(title="LLM Similarity Analyzer") as demo:
     ).then(
         fn=create_heatmap,
         inputs=[model_dropdown, dataset_dropdown],
-        outputs=[heatmap, heatmap]
+        outputs=heatmap  # ✅ Only one output (gr.Plot)
     )
     
     # Clear button
@@ -86,4 +91,4 @@ with gr.Blocks(title="LLM Similarity Analyzer") as demo:
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()