fix: Bugs related to filtering, change theme, add descriptions

app.py

@@ -9,6 +9,7 @@ import pandas as pd
 from pydantic import BaseModel
 import gradio as gr
 import requests
+import random
 
 
 class Task(BaseModel):
@@ -179,9 +180,13 @@ def main() -> None:
         for model_id in df.index
     })
 
-    with gr.Blocks() as demo:
+    with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
         gr.Markdown("# Radial Plot Generator")
-        gr.Markdown("### Select the models and languages to include in the plot")
+        gr.Markdown(
+            "This demo allows you to generate a radial plot comparing the performance "
+            "of different language models on different tasks. It is based on the "
+            "generative results from the [ScandEval benchmark](https://scandeval.com)."
+        )
         with gr.Row():
             with gr.Column():
                 language_names_dropdown = gr.Dropdown(
@@ -203,6 +208,10 @@ def main() -> None:
                     value=True,
                     interactive=True,
                 )
+                gr.Markdown(
+                    "<center>Produced with ❤️ by the <a href=\"https://alexandra.dk\">"
+                    "Alexandra Institute</a>.</center>"
+                )
             with gr.Column():
                 plot = gr.Plot(
                     value=produce_radial_plot(
@@ -263,17 +272,28 @@ def update_model_ids_dropdown(
     if results_dfs is None or len(language_names) == 0:
         return gr.update(choices=[], value=[])
 
-    filtered_models = list({
-        model_id
+    filtered_results_dfs = {
+        language: df
         for language, df in results_dfs.items()
-        for model_id in df.index
         if language.name in language_names
-    })
+    }
+
+    unique_models = {
+        model_id
+        for df in filtered_results_dfs.values()
+        for model_id in df.index
+    }
+
+    filtered_models = [
+        model_id
+        for model_id in unique_models
+        if all(model_id in df.index for df in filtered_results_dfs.values())
+    ]
 
     if len(filtered_models) == 0:
         return gr.update(choices=[], value=[])
 
-    return gr.update(choices=filtered_models, value=filtered_models[0])
+    return gr.update(choices=filtered_models, value=random.sample(filtered_models, k=1))
 
 
 def produce_radial_plot(