feat: revert the comments

app.py

@@ -1,30 +1,15 @@
 import gradio as gr
-import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
+from huggingface_hub import snapshot_download
 
 from src.about import (
-    INTRODUCTION_TEXT,
-    TITLE
+    INTRODUCTION_TEXT, TITLE, EVALUATION_QUEUE_TEXT, BENCHMARKS_TEXT
 )
 from src.benchmarks import (
     QABenchmarks,
     LongDocBenchmarks
 )
 from src.display.css_html_js import custom_css
-from src.envs import (
-    API,
-    EVAL_RESULTS_PATH,
-    REPO_ID, DEFAULT_METRIC_QA, DEFAULT_METRIC_LONG_DOC, METRIC_LIST, LATEST_BENCHMARK_VERSION, COL_NAME_RERANKING_MODEL, COL_NAME_RETRIEVAL_MODEL, BM25_LINK, BENCHMARK_VERSION_LIST
-)
-from src.loaders import (
-    load_eval_results
-)
-from src.utils import (
-    update_metric,
-    set_listeners,
-    reset_rank,
-    remove_html, upload_file, submit_results
-)
 from src.display.gradio_formatting import (
     get_version_dropdown,
     get_search_bar,
@@ -37,28 +22,40 @@ from src.display.gradio_formatting import (
     get_revision_and_ts_checkbox,
     get_leaderboard_table
 )
-
-from src.about import EVALUATION_QUEUE_TEXT, BENCHMARKS_TEXT
+from src.envs import (
+    API,
+    EVAL_RESULTS_PATH,
+    REPO_ID, DEFAULT_METRIC_QA, DEFAULT_METRIC_LONG_DOC, METRIC_LIST, LATEST_BENCHMARK_VERSION,
+    COL_NAME_RERANKING_MODEL, COL_NAME_RETRIEVAL_MODEL, BM25_LINK, BENCHMARK_VERSION_LIST, RESULTS_REPO, TOKEN
+)
+from src.loaders import load_eval_results
+from src.utils import (
+    update_metric,
+    set_listeners,
+    reset_rank,
+    remove_html, upload_file, submit_results
+)
 
 
 def restart_space():
     API.restart_space(repo_id=REPO_ID)
 
 
-# try:
-#     snapshot_download(
-#         repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30,
-#         token=TOKEN
-#     )
-# except Exception as e:
-#     print(f'failed to download')
-#     restart_space()
+try:
+    snapshot_download(
+        repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30,
+        token=TOKEN
+    )
+except Exception as e:
+    print(f'failed to download')
+    restart_space()
 
 global data
 data = load_eval_results(EVAL_RESULTS_PATH)
 global datastore
 datastore = data[LATEST_BENCHMARK_VERSION]
 
+
 def update_metric_qa(
         metric: str,
         domains: list,
@@ -68,7 +65,8 @@ def update_metric_qa(
         show_anonymous: bool,
         show_revision_and_timestamp: bool,
 ):
-    return update_metric(datastore, 'qa', metric, domains, langs, reranking_model, query, show_anonymous, show_revision_and_timestamp)
+    return update_metric(datastore, 'qa', metric, domains, langs, reranking_model, query, show_anonymous,
+                         show_revision_and_timestamp)
 
 
 def update_metric_long_doc(
@@ -80,7 +78,8 @@ def update_metric_long_doc(
         show_anonymous: bool,
         show_revision_and_timestamp,
 ):
-    return update_metric(datastore, "long-doc", metric, domains, langs, reranking_model, query, show_anonymous, show_revision_and_timestamp)
+    return update_metric(datastore, "long-doc", metric, domains, langs, reranking_model, query, show_anonymous,
+                         show_revision_and_timestamp)
 
 
 def update_datastore(version):
@@ -158,7 +157,7 @@ with demo:
 
                         selected_version.change(
                             update_datastore,
-                            [selected_version,],
+                            [selected_version, ],
                             [selected_domains, selected_langs, selected_rerankings, lb_table, hidden_lb_table]
                         )
 
@@ -198,19 +197,22 @@ with demo:
                             with gr.Column(scale=1):
                                 selected_noreranker = get_noreranking_dropdown()
 
-                        lb_df_retriever = datastore.leaderboard_df_qa[datastore.leaderboard_df_qa[COL_NAME_RERANKING_MODEL] == "NoReranker"]
+                        lb_df_retriever = datastore.leaderboard_df_qa[
+                            datastore.leaderboard_df_qa[COL_NAME_RERANKING_MODEL] == "NoReranker"]
                         lb_df_retriever = reset_rank(lb_df_retriever)
                         lb_table_retriever = get_leaderboard_table(
                             lb_df_retriever, datastore.types_qa)
 
                         # Dummy leaderboard for handling the case when the user uses backspace key
-                        hidden_lb_df_retriever = datastore.raw_df_qa[datastore.raw_df_qa[COL_NAME_RERANKING_MODEL] == "NoReranker"]
+                        hidden_lb_df_retriever = datastore.raw_df_qa[
+                            datastore.raw_df_qa[COL_NAME_RERANKING_MODEL] == "NoReranker"]
                         hidden_lb_df_retriever = reset_rank(hidden_lb_df_retriever)
-                        hidden_lb_table_retriever = get_leaderboard_table(hidden_lb_df_retriever, datastore.types_qa, visible=False)
+                        hidden_lb_table_retriever = get_leaderboard_table(hidden_lb_df_retriever, datastore.types_qa,
+                                                                          visible=False)
 
                         selected_version.change(
                             update_datastore,
-                            [selected_version,],
+                            [selected_version, ],
                             [
                                 selected_domains,
                                 selected_langs,
@@ -254,9 +256,10 @@ with demo:
                                 datastore.leaderboard_df_qa[
                                     COL_NAME_RETRIEVAL_MODEL
                                 ] == BM25_LINK
-                            ]
+                                ]
                         lb_df_reranker = reset_rank(lb_df_reranker)
-                        reranking_models_reranker = lb_df_reranker[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
+                        reranking_models_reranker = lb_df_reranker[COL_NAME_RERANKING_MODEL].apply(
+                            remove_html).unique().tolist()
                         with gr.Row():
                             with gr.Column(scale=1):
                                 selected_rerankings_reranker = get_reranking_dropdown(reranking_models_reranker)
@@ -265,7 +268,8 @@ with demo:
                         lb_table_reranker = get_leaderboard_table(
                             lb_df_reranker, datastore.types_qa)
 
-                        hidden_lb_df_reranker = datastore.raw_df_qa[datastore.raw_df_qa[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK]
+                        hidden_lb_df_reranker = datastore.raw_df_qa[
+                            datastore.raw_df_qa[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK]
                         hidden_lb_df_reranker = reset_rank(hidden_lb_df_reranker)
                         hidden_lb_table_reranker = get_leaderboard_table(
                             hidden_lb_df_reranker,
@@ -274,7 +278,7 @@ with demo:
 
                         selected_version.change(
                             update_datastore,
-                            [selected_version,],
+                            [selected_version, ],
                             [
                                 selected_domains,
                                 selected_langs,
@@ -348,7 +352,7 @@ with demo:
 
                         selected_version.change(
                             update_datastore_long_doc,
-                            [selected_version,],
+                            [selected_version, ],
                             [
                                 selected_domains,
                                 selected_langs,
@@ -394,14 +398,14 @@ with demo:
                                 selected_noreranker = get_noreranking_dropdown()
                         lb_df_retriever_long_doc = datastore.leaderboard_df_long_doc[
                             datastore.leaderboard_df_long_doc[COL_NAME_RERANKING_MODEL] == "NoReranker"
-                        ]
+                            ]
                         lb_df_retriever_long_doc = reset_rank(lb_df_retriever_long_doc)
                         lb_table_retriever_long_doc = get_leaderboard_table(
                             lb_df_retriever_long_doc, datastore.types_long_doc)
 
                         hidden_lb_df_retriever_long_doc = datastore.raw_df_long_doc[
                             datastore.raw_df_long_doc[COL_NAME_RERANKING_MODEL] == "NoReranker"
-                        ]
+                            ]
                         hidden_lb_df_retriever_long_doc = reset_rank(hidden_lb_df_retriever_long_doc)
                         hidden_lb_table_retriever_long_doc = get_leaderboard_table(
                             hidden_lb_df_retriever_long_doc, datastore.types_long_doc, visible=False
@@ -409,7 +413,7 @@ with demo:
 
                         selected_version.change(
                             update_datastore_long_doc,
-                            [selected_version,],
+                            [selected_version, ],
                             [
                                 selected_domains,
                                 selected_langs,
@@ -452,16 +456,19 @@ with demo:
                                 datastore.leaderboard_df_long_doc[
                                     COL_NAME_RETRIEVAL_MODEL
                                 ] == BM25_LINK
-                            ]
+                                ]
                         lb_df_reranker_ldoc = reset_rank(lb_df_reranker_ldoc)
-                        reranking_models_reranker_ldoc = lb_df_reranker_ldoc[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
+                        reranking_models_reranker_ldoc = lb_df_reranker_ldoc[COL_NAME_RERANKING_MODEL].apply(
+                            remove_html).unique().tolist()
                         with gr.Row():
                             with gr.Column(scale=1):
-                                selected_rerankings_reranker_ldoc = get_reranking_dropdown(reranking_models_reranker_ldoc)
+                                selected_rerankings_reranker_ldoc = get_reranking_dropdown(
+                                    reranking_models_reranker_ldoc)
                             with gr.Column(scale=1):
                                 search_bar_reranker_ldoc = gr.Textbox(show_label=False, visible=False)
                         lb_table_reranker_ldoc = get_leaderboard_table(lb_df_reranker_ldoc, datastore.types_long_doc)
-                        hidden_lb_df_reranker_ldoc = datastore.raw_df_long_doc[datastore.raw_df_long_doc[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK]
+                        hidden_lb_df_reranker_ldoc = datastore.raw_df_long_doc[
+                            datastore.raw_df_long_doc[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK]
                         hidden_lb_df_reranker_ldoc = reset_rank(hidden_lb_df_reranker_ldoc)
                         hidden_lb_table_reranker_ldoc = get_leaderboard_table(
                             hidden_lb_df_reranker_ldoc, datastore.types_long_doc, visible=False
@@ -469,7 +476,7 @@ with demo:
 
                         selected_version.change(
                             update_datastore_long_doc,
-                            [selected_version,],
+                            [selected_version, ],
                             [
                                 selected_domains,
                                 selected_langs,
@@ -580,5 +587,3 @@ if __name__ == "__main__":
     scheduler.start()
     demo.queue(default_concurrency_limit=40)
     demo.launch()
-
-