cleanup

app.py

@@ -108,7 +108,7 @@ def build_plot(min_score, max_models_per_month, toggle_annotations, set_selector
         hover_name="Model",
         hover_data=["Organization", "License", "Link"],
         trendline="ols",
-        title=f"Proprietary vs Open LLMs (LMSYS Arena ELO as of {date_updated})",
+        title=f"Open vs Proprietary LLMs by LMSYS Arena ELO Score (as of {date_updated})",
         labels={"rating": "Arena ELO", "Release Date": "Release Date"},
         height=800,
         template="seaborn",
@@ -161,13 +161,17 @@ with gr.Blocks(
 
     with gr.Row():
         with gr.Column():
-            toggle_annotations = gr.Radio(
-                choices=[True, False], label="Overlay Best Model Name", value=True
-            )
             set_selector = gr.Dropdown(
                 choices=list(CAT_NAME_TO_EXPLANATION.keys()),
-                label="Select Dataset",
+                label="Select Category",
                 value="Overall",
+                info="Select the category to visualize",
+            )
+            toggle_annotations = gr.Radio(
+                choices=[True, False],
+                label="Overlay Best Model Name",
+                value=True,
+                info="Toggle to overlay the name of the best model per month per license",
             )
         with gr.Column():
             min_score = gr.Slider(
@@ -176,6 +180,7 @@ with gr.Blocks(
                 value=(max_elo_score - min_elo_score) * 0.3 + min_elo_score,
                 step=50,
                 label="Minimum ELO Score",
+                info="Filter out low scoring models",
             )
             max_models_per_month = gr.Slider(
                 value=upper_models_per_month - 2,
@@ -183,6 +188,7 @@ with gr.Blocks(
                 maximum=upper_models_per_month,
                 step=1,
                 label="Max Models per Month (per License)",
+                info="Limit to N best models per month per license to reduce clutter",
             )
 
     # Show plot