[Fix] rendering issues

app.py

@@ -1,23 +1,21 @@
 import gradio as gr
 import plotly.graph_objects as go
-import plotly.io as pio
 import numpy as np
 from src.dataloading import get_leaderboard_models_cached, get_leaderboard_datasets
 
+# Force the Plotly renderer to use an iframe-based output
+import plotly.io as pio
 pio.renderers.default = "iframe"
 
 def create_heatmap(selected_models, selected_dataset):
-    # Return nothing if no inputs are provided
     if not selected_models or not selected_dataset:
         return None
 
-    # Generate a random symmetric similarity matrix
     size = len(selected_models)
     similarities = np.random.rand(size, size)
     similarities = (similarities + similarities.T) / 2
     similarities = np.round(similarities, 2)
 
-    # Create a heatmap trace using go.Heatmap; we set x and y to the model names.
     fig = go.Figure(data=go.Heatmap(
         z=similarities,
         x=selected_models,
@@ -27,8 +25,7 @@ def create_heatmap(selected_models, selected_dataset):
         text=similarities,
         hoverinfo="text"
     ))
-
-    # Update layout: add title, axis titles, set fixed dimensions and margins
+    
     fig.update_layout(
         title=f"Similarity Matrix for {selected_dataset}",
         xaxis_title="Models",
@@ -37,7 +34,24 @@ def create_heatmap(selected_models, selected_dataset):
         height=800,
         margin=dict(l=100, r=100, t=100, b=100)
     )
-    return fig
+    
+    # (Optional) Force categorical ordering explicitly
+    fig.update_xaxes(
+        type="category",
+        categoryorder="array",
+        categoryarray=selected_models,
+        tickangle=45,
+        automargin=True
+    )
+    fig.update_yaxes(
+        type="category",
+        categoryorder="array",
+        categoryarray=selected_models,
+        automargin=True
+    )
+    
+    # Return a fully serializable dictionary
+    return fig.to_dict()
 
 def validate_inputs(selected_models, selected_dataset):
     if not selected_models:
@@ -47,7 +61,6 @@ def validate_inputs(selected_models, selected_dataset):
 
 with gr.Blocks(title="LLM Similarity Analyzer") as demo:
     gr.Markdown("## Model Similarity Comparison Tool")
-    
     with gr.Row():
         dataset_dropdown = gr.Dropdown(
             choices=get_leaderboard_datasets(),
@@ -66,10 +79,8 @@ with gr.Blocks(title="LLM Similarity Analyzer") as demo:
         )
     
     generate_btn = gr.Button("Generate Heatmap", variant="primary")
-    # Initialize the Plot component without a figure (it will be updated)
     heatmap = gr.Plot(label="Similarity Heatmap", visible=True)
     
-    # First validate inputs, then create the heatmap; note that we use a single output.
     generate_btn.click(
         fn=validate_inputs,
         inputs=[model_dropdown, dataset_dropdown],
@@ -80,7 +91,6 @@ with gr.Blocks(title="LLM Similarity Analyzer") as demo:
         outputs=heatmap
     )
     
-    # Clear button to reset selections and clear the plot
     clear_btn = gr.Button("Clear Selection")
     clear_btn.click(
         lambda: [None, None, None],
@@ -88,4 +98,4 @@ with gr.Blocks(title="LLM Similarity Analyzer") as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch(ssr_mode=False)
+    demo.launch(ssr_mode=False)

src/dataloading.py

@@ -6,7 +6,7 @@ def get_leaderboard_models():
     api = HfApi()
     
     # List all datasets in the open-llm-leaderboard organization
-    datasets = api.list_datasets(author="open-llm-leaderboard")
+    #datasets = api.list_datasets(author="open-llm-leaderboard")
     
     models = []
     #for dataset in datasets:

src/test.py

@@ -1,14 +0,0 @@
-import plotly.graph_objects as go
-import numpy as np
-
-models = ["model1", "model2", "model3"]
-size = len(models)
-sim = np.random.rand(size, size)
-sim = (sim + sim.T) / 2
-sim = np.round(sim, 2)
-fig = go.Figure(data=go.Heatmap(z=sim, x=models, y=models, colorscale="Viridis"))
-fig.update_layout(title="Test Heatmap", xaxis_title="Models", yaxis_title="Models", width=800, height=800)
-fig.show()
-
-# Save fig
-fig.write_html("heatmap.html")