define click event

app.py

@@ -5,7 +5,7 @@ import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
 
 from src.assets.text_content import TITLE, INTRODUCTION_TEXT, SINGLE_A100_TEXT, CITATION_BUTTON_LABEL, CITATION_BUTTON_TEXT
-from src.utils import restart_space, load_dataset_repo, make_clickable_model, make_clickable_score, extract_score_from_clickable
+from src.utils import restart_space, load_dataset_repo, make_clickable_model, make_clickable_score, submit_query
 from src.assets.css_html_js import custom_css
 
 
@@ -187,7 +187,15 @@ with demo:
         #         elem_id="1xA100-plot",
         #         show_label=False,
         #     )
-
+            # Callbacks
+            submit_button.click(
+                submit_query,
+                [
+                    search_bar, backend_checkboxes, datatype_checkboxes, threshold_slider,
+                    single_A100_for_search
+                ],
+                [single_A100_leaderboard]
+            )
     with gr.Row():
         with gr.Accordion("📙 Citation", open=False):
             citation_button = gr.Textbox(
@@ -197,32 +205,6 @@ with demo:
             ).style(show_copy_button=True)
 
 
-def submit_query(text, backends, datatypes, threshold, raw_df):
-    raw_df["H4 Score ⬆️"] = raw_df["H4 Score ⬆️"].apply(
-        extract_score_from_clickable)
-
-    filtered_df = raw_df[
-        raw_df["Model 🤗"].str.lower().str.contains(text.lower()) &
-        raw_df["Backend 🏭"].isin(backends) &
-        raw_df["Datatype 📥"].isin(datatypes) &
-        (raw_df["H4 Score ⬆️"] >= threshold)
-    ]
-
-    filtered_df["H4 Score ⬆️"] = filtered_df["H4 Score ⬆️"].apply(
-        make_clickable_score)
-    return filtered_df
-
-
-# Callbacks
-submit_button.click(
-    submit_query,
-    [
-        search_bar, backend_checkboxes, datatype_checkboxes, threshold_slider,
-        single_A100_for_search
-    ],
-    [single_A100_leaderboard]
-)
-
 # Restart space every hour
 scheduler = BackgroundScheduler()
 scheduler.add_job(restart_space, "interval", seconds=3600,

src/utils.py

@@ -70,3 +70,19 @@ def make_clickable_score(score):
 
 def extract_score_from_clickable(clickable_score) -> float:
     return float(re.findall(r"\d+\.\d+", clickable_score)[-1])
+
+
+def submit_query(text, backends, datatypes, threshold, raw_df):
+    raw_df["H4 Score ⬆️"] = raw_df["H4 Score ⬆️"].apply(
+        extract_score_from_clickable)
+
+    filtered_df = raw_df[
+        raw_df["Model 🤗"].str.lower().str.contains(text.lower()) &
+        raw_df["Backend 🏭"].isin(backends) &
+        raw_df["Datatype 📥"].isin(datatypes) &
+        (raw_df["H4 Score ⬆️"] >= threshold)
+    ]
+
+    filtered_df["H4 Score ⬆️"] = filtered_df["H4 Score ⬆️"].apply(
+        make_clickable_score)
+    return filtered_df