Set result_paths_per_model as State

app.py

@@ -1,5 +1,3 @@
-from functools import partial
-
 import gradio as gr
 
 import src.constants as constants
@@ -19,18 +17,15 @@ from src.results import (
     display_loading_message_for_results,
     display_results,
     download_results,
-    fetch_result_paths,
+    load_result_paths_per_model,
     load_results,
     plot_results,
-    sort_result_paths_per_model,
     update_load_results_component,
     update_tasks_component,
 )
 
 
 # if __name__ == "__main__":
-result_paths_per_model = sort_result_paths_per_model(fetch_result_paths())
-load_results = partial(load_results, result_paths_per_model=result_paths_per_model)
 
 with gr.Blocks(fill_height=True, fill_width=True) as demo:
     gr.HTML("<h1 style='text-align: center;'>Compare Results of the 🤗 Open LLM Leaderboard</h1>")
@@ -43,7 +38,8 @@ with gr.Blocks(fill_height=True, fill_width=True) as demo:
         "Check out the [documentation](https://huggingface.co/docs/leaderboards/open_llm_leaderboard/about) 📄 to find explanations on the evaluations used, their configuration parameters and details on the input/outputs for the models."
     )
     with gr.Row():
-        model_ids = gr.Dropdown(choices=list(result_paths_per_model.keys()), label="Models", multiselect=True)
+        model_ids = gr.Dropdown(label="Models", multiselect=True)
+        result_paths_per_model = gr.State()
 
     with gr.Row():
         with gr.Tab("Results"):
@@ -113,6 +109,17 @@ with gr.Blocks(fill_height=True, fill_width=True) as demo:
             details = gr.HTML()
             details_dataframe = gr.State()
 
+    # DEMO:
+    demo.load(
+        fn=load_result_paths_per_model,
+        outputs=result_paths_per_model,
+    ).then(
+        fn=lambda x: gr.Dropdown(choices=list(x.keys())),
+        inputs=result_paths_per_model,
+        outputs=model_ids,
+    )
+
+    # RESULTS:
     gr.on(
         triggers=[model_ids.input],
         fn=update_load_results_component,
@@ -124,7 +131,7 @@ with gr.Blocks(fill_height=True, fill_width=True) as demo:
         outputs=[results, configs],
     ).then(
         fn=load_results,
-        inputs=model_ids,
+        inputs=[model_ids, result_paths_per_model],
         outputs=results_dataframe,
     ).then(
         fn=update_tasks_component,

src/results.py

@@ -10,6 +10,10 @@ import src.constants as constants
 from src.hub import glob, load_json_file
 
 
+def load_result_paths_per_model():
+    return sort_result_paths_per_model(fetch_result_paths())
+
+
 def fetch_result_paths():
     path = f"{constants.RESULTS_DATASET_ID}/**/**/*.json"
     return glob(path)