Add BackgroundScheduler()

app.py

@@ -3,10 +3,15 @@ import json
 import requests
 
 from datasets import load_dataset
+
 import gradio as gr
+from apscheduler.schedulers.background import BackgroundScheduler
+
+
 from huggingface_hub import HfApi, hf_hub_download
 from huggingface_hub.repocard import metadata_load
 import pandas as pd
+
 from utils import *
 
 
@@ -75,6 +80,24 @@ rl_envs = [
 "global": None
 },
 {
+"rl_env_beautiful": "PongNoFrameskip-v4 🎾",
+"rl_env": "PongNoFrameskip-v4",
+"video_link": "",
+"global": None
+},
+{
+"rl_env_beautiful": "BreakoutNoFrameskip-v4 🧱",
+"rl_env": "BreakoutNoFrameskip-v4",
+"video_link": "",
+"global": None
+},
+{
+"rl_env_beautiful": "QbertNoFrameskip-v4 🐦",
+"rl_env": "QbertNoFrameskip-v4",
+"video_link": "",
+"global": None
+},
+{
 "rl_env_beautiful": "BipedalWalker-v3",
 "rl_env": "BipedalWalker-v3",
 "video_link": "",
@@ -146,13 +169,13 @@ def get_model_ids(rl_env):
     api = HfApi()
     models = api.list_models(filter=rl_env)
     model_ids = [x.modelId for x in models]
-    print(model_ids)
+    #print(model_ids)
     return model_ids
 
 def get_model_dataframe(rl_env):
     # Get model ids associated with rl_env
     model_ids = get_model_ids(rl_env)
-    print(model_ids)
+    #print(model_ids)
     data = []
     for model_id in model_ids:
         """
@@ -175,13 +198,14 @@ def get_model_dataframe(rl_env):
         row["Mean Reward"] = mean_reward
         row["Std Reward"] = std_reward
         data.append(row)
+    print("DATA", data)
     ranked_dataframe = rank_dataframe(pd.DataFrame.from_records(data))
     print("RANKED", ranked_dataframe)
     return ranked_dataframe
     
     
 def rank_dataframe(dataframe):
-    print("DATAFRAME", dataframe)
+    #print("DATAFRAME", dataframe)
     dataframe = dataframe.sort_values(by=['Results'], ascending=False)
     if not 'Ranking' in dataframe.columns:
         dataframe.insert(0, 'Ranking', [i for i in range(1,len(dataframe)+1)])
@@ -198,7 +222,7 @@ with block:
     
     Just choose which environment you trained your agent on and with Ctrl+F find your rank 🏆
 
-    **If you don't find your model, go to the bottom of the page and click on the refresh button**
+    **The leaderboard is updated every hour. If you don't find your model, go to the bottom of the page and click on the refresh button**
     
     We use **lower bound result to sort the models: mean_reward - std_reward.**
 
@@ -226,10 +250,26 @@ with block:
                 rl_env["global"] = gr.components.Dataframe(value= get_model_dataframe(rl_env["rl_env"]), headers=["Ranking 🏆", "User 🤗", "Model id 🤖", "Results", "Mean Reward", "Std Reward"], datatype=["number", "markdown", "markdown", "number", "number", "number"])
             with gr.Row():
                 data_run = gr.Button("Refresh")
-                print("rl_env", rl_env["rl_env"])
+                #print("rl_env", rl_env["rl_env"])
                 val = gr.Variable(value=[rl_env["rl_env"]])
                 data_run.click(get_model_dataframe, inputs=[val], outputs =rl_env["global"])
             
                        
 block.launch()
 
+def refresh_leaderboard():
+    """
+    Here we refresh the leaderboard:
+    we update the rl_env["global"] for each rl_envs in rl_env
+    """
+    for i in range(0, len(rl_envs)):
+        rl_env = rl_envs[i]
+        temp = get_model_dataframe(rl_env)
+        rl_env["global"] = temp
+    print("The leaderboard has been updated")
+
+scheduler = BackgroundScheduler()
+# Refresh every hour
+scheduler.add_job(func=refresh_leaderboard, trigger="interval", seconds=3600)
+scheduler.start()
+