chore: Update app.py to include select_columns and hide_columns in init_leaderboard function

app.py

@@ -19,30 +19,46 @@ from src.display.utils import (
     EVAL_COLS,
     EVAL_TYPES,
     AutoEvalColumn,
-    ModelType,
     fields,
-    WeightType,
-    Precision
 )
-from src.envs import API, EVAL_DETAILED_RESULTS_PATH, EVAL_RESULTS_PATH, EVAL_DETAILED_RESULTS_REPO, REPO_ID, RESULTS_REPO, TOKEN
+from src.envs import (
+    API,
+    EVAL_DETAILED_RESULTS_PATH,
+    EVAL_RESULTS_PATH,
+    EVAL_DETAILED_RESULTS_REPO,
+    REPO_ID,
+    RESULTS_REPO,
+    TOKEN,
+)
 from src.populate import get_leaderboard_df
 
 
 def restart_space():
     API.restart_space(repo_id=REPO_ID)
 
+
 ### Space initialisation
 try:
     print(EVAL_DETAILED_RESULTS_REPO)
     snapshot_download(
-        repo_id=EVAL_DETAILED_RESULTS_REPO, local_dir=EVAL_DETAILED_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
+        repo_id=EVAL_DETAILED_RESULTS_REPO,
+        local_dir=EVAL_DETAILED_RESULTS_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()
@@ -96,4 +112,4 @@ 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()

src/about.py

@@ -1,6 +1,7 @@
 from dataclasses import dataclass
 from enum import Enum
 
+
 @dataclass
 class Task:
     benchmark: str
@@ -16,11 +17,10 @@ class Tasks(Enum):
     further_insights = Task("Further Insights", "acc", "Further Insights")
 
 
-NUM_FEWSHOT = 0 # Change with your few shot
+NUM_FEWSHOT = 0  # Change with your few shot
 # ---------------------------------------------------
 
 
-
 # Your leaderboard name
 TITLE = """<h1 align="center" id="space-title">LiveBench</h1>"""
 

src/display/utils.py

@@ -5,6 +5,7 @@ import pandas as pd
 
 from src.about import Tasks
 
+
 def fields(raw_class):
     return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"]
 
@@ -20,12 +21,15 @@ class ColumnContent:
     hidden: bool = False
     never_hidden: bool = False
 
+
 ## Leaderboard columns
 auto_eval_column_dict = []
 # Init
 # auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
-auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model Name", "markdown", True, never_hidden=True)])
-#Scores
+auto_eval_column_dict.append(
+    ["model", ColumnContent, ColumnContent("Model Name", "markdown", True, never_hidden=True)]
+)
+# Scores
 auto_eval_column_dict.append(["Overall", ColumnContent, ColumnContent("Total", "number", True)])
 for task in Tasks:
     auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)])
@@ -33,6 +37,7 @@ for task in Tasks:
 # We use make dataclass to dynamically fill the scores from Tasks
 AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
 
+
 ## For the queue columns in the submission tab
 @dataclass(frozen=True)
 class EvalQueueColumn:  # Queue column
@@ -43,12 +48,13 @@ class EvalQueueColumn:  # Queue column
     weight_type = ColumnContent("weight_type", "str", "Original")
     status = ColumnContent("status", "str", True)
 
+
 ## All the model information that we might need
 @dataclass
 class ModelDetails:
     name: str
     display_name: str = ""
-    symbol: str = "" # emoji
+    symbol: str = ""  # emoji
 
 
 # Column selection

src/envs.py

@@ -4,9 +4,11 @@ from huggingface_hub import HfApi
 
 # Info to change for your repository
 # ----------------------------------
-TOKEN = os.environ.get("HF_TOKEN") # A read/write token for your org
+TOKEN = os.environ.get("HF_TOKEN")  # A read/write token for your org
 
-OWNER = "lmms-lab" # Change to your org - don't forget to create a results and request dataset, with the correct format!
+OWNER = (
+    "lmms-lab"  # Change to your org - don't forget to create a results and request dataset, with the correct format!
+)
 # ----------------------------------
 
 REPO_ID = f"{OWNER}/leaderboard"
@@ -14,7 +16,7 @@ EVAL_DETAILED_RESULTS_REPO = f"{OWNER}/LiveBenchDetailedResults"
 RESULTS_REPO = f"{OWNER}/LiveBenchResults"
 
 # If you setup a cache later, just change HF_HOME
-CACHE_PATH=os.getenv("HF_HOME", ".")
+CACHE_PATH = os.getenv("HF_HOME", ".")
 
 # Local caches
 EVAL_DETAILED_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-detailed-results")