Update app.py

app.py

@@ -107,15 +107,15 @@ def get_metadata(model_id):
 #     return mean_reward, std_reward
 
 
-def rank_dataframe(dataframe):
-    dataframe = dataframe.sort_values(
-        by=["Cumulative Reward", "User", "Model"], ascending=False
-    )
-    if not "Ranking" in dataframe.columns:
-        dataframe.insert(0, "Ranking", [i for i in range(1, len(dataframe) + 1)])
-    else:
-        dataframe["Ranking"] = [i for i in range(1, len(dataframe) + 1)]
-    return dataframe
+# def rank_dataframe(dataframe):
+#     dataframe = dataframe.sort_values(
+#         by=["Cumulative Reward", "User", "Model"], ascending=False
+#     )
+#     if not "Ranking" in dataframe.columns:
+#         dataframe.insert(0, "Ranking", [i for i in range(1, len(dataframe) + 1)])
+#     else:
+#         dataframe["Ranking"] = [i for i in range(1, len(dataframe) + 1)]
+#     return dataframe
 
 
 def update_leaderboard_dataset_parallel(hivex_env, path):
@@ -146,8 +146,9 @@ def update_leaderboard_dataset_parallel(hivex_env, path):
     # Filter out None results (models with no metadata)
     data = [row for row in data if row is not None]
 
-    ranked_dataframe = rank_dataframe(pd.DataFrame.from_records(data))
-    new_history = ranked_dataframe
+    # ranked_dataframe = rank_dataframe(pd.DataFrame.from_records(data))
+    # new_history = ranked_dataframe
+    new_history = pd.DataFrame.from_records(data)
     file_path = path + "/" + hivex_env + ".csv"
     new_history.to_csv(file_path, index=False)
 
@@ -170,8 +171,8 @@ def run_update_dataset():
 
 def get_data(rl_env, task, path) -> pd.DataFrame:
     """
-    Get data from rl_env and filter by the given task.
-    :return: filtered data as a pandas DataFrame
+    Get data from rl_env, filter by the given task, and drop the Task column.
+    :return: filtered data as a pandas DataFrame without the Task column
     """
     csv_path = path + "/" + rl_env + ".csv"
     data = pd.read_csv(csv_path)
@@ -179,6 +180,9 @@ def get_data(rl_env, task, path) -> pd.DataFrame:
     # Filter the data to only include rows where the "Task" column matches the given task
     filtered_data = data[data["Task"] == task]
 
+    # Drop the "Task" column
+    filtered_data = filtered_data.drop(columns=["Task"])
+
     # Convert User and Model columns to clickable links
     for index, row in filtered_data.iterrows():
         user_id = row["User"]
@@ -189,17 +193,6 @@ def get_data(rl_env, task, path) -> pd.DataFrame:
     return filtered_data
 
 
-def get_data_no_html(rl_env, path) -> pd.DataFrame:
-    """
-    Get data from rl_env
-    :return: data as a pandas DataFrame
-    """
-    csv_path = path + "/" + rl_env + ".csv"
-    data = pd.read_csv(csv_path)
-
-    return data
-
-
 run_update_dataset()
 
 block = gr.Blocks()
@@ -220,8 +213,7 @@ with block:
                     task = "Task " + str(j + 1)
                     with gr.TabItem(f"Task {j}"):
                         with gr.Row():
-                            # gr_dataframe = gr.components.Dataframe(value=get_data(hivex_env["hivex_env"], path_), headers=["User", "Model", "Cumulative Reward"], datatype=["markdown", "markdown", "number"],  row_count=(100, 'fixed'))
-                            gr_dataframe = gr.components.Dataframe(value=get_data(hivex_env["hivex_env"], j,path_), headers=["Ranking", "User", "Model"], datatype=["number", "markdown", "markdown"], row_count=(100, 'fixed'))
+                            gr_dataframe = gr.components.Dataframe(value=get_data(hivex_env["hivex_env"], j, path_), headers=["User", "Model"], datatype=["markdown", "markdown"], row_count=(100, 'fixed'))
                  
 
 scheduler = BackgroundScheduler()