Update app.py

app.py

@@ -1,8 +1,7 @@
 import gradio as gr
-from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
 import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
-from huggingface_hub import snapshot_download
+from huggingface_hub import snapshot_download 
 
 from src.about import (
     CITATION_BUTTON_LABEL,
@@ -26,8 +25,7 @@ from src.display.utils import (
 )
 from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REPO_ID, RESULTS_REPO, TOKEN
 from src.populate import get_evaluation_queue_df, get_leaderboard_df
-from src.submission.submit import add_new_eval
-
+from src.submission.submit import add_new_eval 
 
 def restart_space():
     API.restart_space(repo_id=REPO_ID)
@@ -36,19 +34,29 @@ def restart_space():
 try:
     print(EVAL_REQUESTS_PATH)
     snapshot_download(
-        repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
+        repo_id=QUEUE_REPO,
+        local_dir=EVAL_REQUESTS_PATH,
+        repo_type="dataset",
+        tqdm_class=None,
+        etag_timeout=30,
+        token=TOKEN
     )
 except Exception:
     restart_space()
+
 try:
     print(EVAL_RESULTS_PATH)
     snapshot_download(
-        repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
+        repo_id=RESULTS_REPO,
+        local_dir=EVAL_RESULTS_PATH,
+        repo_type="dataset",
+        tqdm_class=None,
+        etag_timeout=30,
+        token=TOKEN
     )
 except Exception:
     restart_space()
 
-
 LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
 
 (
@@ -57,39 +65,21 @@ LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS,
     pending_eval_queue_df,
 ) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
 
+# Replaced the problematic Leaderboard component with native Gradio Dataframe
 def init_leaderboard(dataframe):
     if dataframe is None or dataframe.empty:
-        raise ValueError("Leaderboard DataFrame is empty or None.")
-    return Leaderboard(
+        return gr.Markdown("### No data available in leaderboard.")
+    
+    # We use a standard Dataframe which is much more stable with websockets 15.0+
+    return gr.Dataframe(
         value=dataframe,
-        datatype=[c.type for c in fields(AutoEvalColumn)],
-        select_columns=SelectColumns(
-            default_selection=[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default],
-            cant_deselect=[c.name for c in fields(AutoEvalColumn) if c.never_hidden],
-            label="Select Columns to Display:",
-        ),
-        search_columns=[AutoEvalColumn.model.name, AutoEvalColumn.license.name],
-        hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden],
-        filter_columns=[
-            ColumnFilter(AutoEvalColumn.model_type.name, type="checkboxgroup", label="Model types"),
-            ColumnFilter(AutoEvalColumn.precision.name, type="checkboxgroup", label="Precision"),
-            ColumnFilter(
-                AutoEvalColumn.params.name,
-                type="slider",
-                min=0.01,
-                max=150,
-                label="Select the number of parameters (B)",
-            ),
-            ColumnFilter(
-                AutoEvalColumn.still_on_hub.name, type="boolean", label="Deleted/incomplete", default=True
-            ),
-        ],
-        bool_checkboxgroup_label="Hide models",
+        headers=[c.name for c in fields(AutoEvalColumn) if not c.hidden],
+        datatype=[c.type for c in fields(AutoEvalColumn) if not c.hidden],
         interactive=False,
     )
 
-
 demo = gr.Blocks(css=custom_css)
+
 with demo:
     gr.HTML(TITLE)
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
@@ -129,7 +119,6 @@ with demo:
                                 datatype=EVAL_TYPES,
                                 row_count=5,
                             )
-
                     with gr.Accordion(
                         f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})",
                         open=False,
@@ -141,52 +130,53 @@ with demo:
                                 datatype=EVAL_TYPES,
                                 row_count=5,
                             )
-            with gr.Row():
-                gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
 
-            with gr.Row():
-                with gr.Column():
-                    model_name_textbox = gr.Textbox(label="Model name")
-                    revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
-                    model_type = gr.Dropdown(
-                        choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
-                        label="Model type",
-                        multiselect=False,
-                        value=None,
-                        interactive=True,
-                    )
+                with gr.Row():
+                    gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
 
-                with gr.Column():
-                    precision = gr.Dropdown(
-                        choices=[i.value.name for i in Precision if i != Precision.Unknown],
-                        label="Precision",
-                        multiselect=False,
-                        value="float16",
-                        interactive=True,
-                    )
-                    weight_type = gr.Dropdown(
-                        choices=[i.value.name for i in WeightType],
-                        label="Weights type",
-                        multiselect=False,
-                        value="Original",
-                        interactive=True,
-                    )
-                    base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
-
-            submit_button = gr.Button("Submit Eval")
-            submission_result = gr.Markdown()
-            submit_button.click(
-                add_new_eval,
-                [
-                    model_name_textbox,
-                    base_model_name_textbox,
-                    revision_name_textbox,
-                    precision,
-                    weight_type,
-                    model_type,
-                ],
-                submission_result,
-            )
+                with gr.Row():
+                    with gr.Column():
+                        model_name_textbox = gr.Textbox(label="Model name")
+                        revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
+                        model_type = gr.Dropdown(
+                            choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
+                            label="Model type",
+                            multiselect=False,
+                            value=None,
+                            interactive=True,
+                        )
+
+                    with gr.Column():
+                        precision = gr.Dropdown(
+                            choices=[i.value.name for i in Precision if i != Precision.Unknown],
+                            label="Precision",
+                            multiselect=False,
+                            value="float16",
+                            interactive=True,
+                        )
+                        weight_type = gr.Dropdown(
+                            choices=[i.value.name for i in WeightType],
+                            label="Weights type",
+                            multiselect=False,
+                            value="Original",
+                            interactive=True,
+                        )
+                        base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
+
+                submit_button = gr.Button("Submit Eval")
+                submission_result = gr.Markdown()
+                submit_button.click(
+                    add_new_eval,
+                    [
+                        model_name_textbox,
+                        base_model_name_textbox,
+                        revision_name_textbox,
+                        precision,
+                        weight_type,
+                        model_type,
+                    ],
+                    submission_result,
+                )
 
     with gr.Row():
         with gr.Accordion("📙 Citation", open=False):
@@ -201,4 +191,5 @@ with demo:
 scheduler = BackgroundScheduler()
 scheduler.add_job(restart_space, "interval", seconds=1800)
 scheduler.start()
-demo.queue(default_concurrency_limit=40).launch()
+
+demo.queue(default_concurrency_limit=40).launch()