Update app.py

app.py

@@ -215,8 +215,7 @@ def update_leaderboard_dataset(rl_env, path):
     return ranked_dataframe
 
 def download_leaderboard_dataset():
-    path = snapshot_download(repo_id=DATASET_REPO_ID, repo_type="dataset")
-    return path
+    global path_ = snapshot_download(repo_id=DATASET_REPO_ID, repo_type="dataset")
 
 def get_data(rl_env, path) -> pd.DataFrame:
     """
@@ -286,6 +285,7 @@ def filter_data(rl_env, path, user_id):
 
 run_update_dataset()
 
+
 with block:
     gr.Markdown(f"""
     # 🏆 The Deep Reinforcement Learning Course Leaderboard 🏆 
@@ -307,7 +307,7 @@ with block:
         
     🔧 There is an **environment missing?** Please open an issue.
     """)
-    path_ = download_leaderboard_dataset()
+    
 
     for i in range(0, len(rl_envs)):
         rl_env = rl_envs[i]
@@ -331,17 +331,16 @@ with block:
                 search_btn = gr.Button("Search my models 🔎")
                 reset_btn = gr.Button("Clear my search")
                 env = gr.Variable(rl_env["rl_env"])
-                grpath = gr.Variable(path_)
             with gr.Row():
                 gr_dataframe = gr.components.Dataframe(value=get_data(rl_env["rl_env"], path_), headers=["Ranking 🏆", "User 🤗", "Model id 🤖", "Results", "Mean Reward", "Std Reward"], datatype=["number", "markdown", "markdown", "number", "number", "number"],  row_count=(100, 'fixed'))
              
             with gr.Row():
                 #gr_search_dataframe = gr.components.Dataframe(headers=["Ranking 🏆", "User 🤗", "Model id 🤖", "Results", "Mean Reward", "Std Reward"], datatype=["number", "markdown", "markdown", "number", "number", "number"], visible=False)
-                search_btn.click(fn=filter_data, inputs=[env, grpath, user_id], outputs=gr_dataframe, api_name="filter_data")
+                search_btn.click(fn=filter_data, inputs=[env, path_, user_id], outputs=gr_dataframe, api_name="filter_data")
 
             with gr.Row():
-                search_btn.click(fn=filter_data, inputs=[env, grpath, user_id], outputs=gr_dataframe, api_name="filter_data")
-                reset_btn.click(fn=get_data, inputs=[env, grpath], outputs=gr_dataframe, api_name="get_data")
+                search_btn.click(fn=filter_data, inputs=[env, path_, user_id], outputs=gr_dataframe, api_name="filter_data")
+                reset_btn.click(fn=get_data, inputs=[env, path_], outputs=gr_dataframe, api_name="get_data")
 
 scheduler = BackgroundScheduler()
 # Refresh every hour