adding reload button

app.py

@@ -38,7 +38,7 @@ def parse_metrics_accuracy(meta):
     result = meta["model-index"][0]["results"]
     metrics = result[0]["metrics"]
     accuracy = metrics[0]["value"]
-    print("ACCURACY", accuracy)
+    #print("ACCURACY", accuracy)
     return accuracy
 
 # We keep the worst case episode
@@ -64,9 +64,9 @@ def get_data(rl_env):
         row["User"] = user_id
         row["Model"] = model_id
         accuracy = parse_metrics_accuracy(meta)
-        print("RETURNED ACCURACY", accuracy)
+        #print("RETURNED ACCURACY", accuracy)
         mean_reward, std_reward = parse_rewards(accuracy)
-        print("MEAN REWARD", mean_reward)
+        #print("MEAN REWARD", mean_reward)
         row["Results"] = mean_reward - std_reward
         row["Mean Reward"] = mean_reward
         row["Std Reward"] = std_reward
@@ -86,9 +86,9 @@ def get_data_per_env(rl_env):
         table_html = dataframe.to_html(escape=False, index=False)
         table_html = table_html.replace("<table>", '<table style="width: 100%; margin: auto; border:0.5px solid; border-spacing: 7px 0px">')  # center-align the headers
       
-        table_html = table_html.replace("<thead>", '<thead align="center">')  # center-align the headers
+        table_html = table_html.replace("<thead>", '<thead align="left">')  # left-align the headers
 
-        table_html = "<div style='text-align: center ; width:100%'>"+table_html+"</div>"
+        table_html = "<div style='text-align: left ; width:100%'>"+table_html+"</div>"
         return table_html,dataframe,dataframe.empty
     else: 
         html = """<div style="color: green">
@@ -100,12 +100,45 @@ def get_data_per_env(rl_env):
 
 
 RL_ENVS = ['LunarLander-v2','CarRacing-v0','MountainCar-v0']
+           
 RL_DETAILS ={'CarRacing-v0':{'title':" The Car Racing 🏎️ Leaderboard 🚀",'data':get_data_per_env('CarRacing-v0')},
             'MountainCar-v0':{'title':"The Mountain Car ⛰️ 🚗 Leaderboard 🚀",'data':get_data_per_env('MountainCar-v0')},
             'LunarLander-v2':{'title':" The Lunar Lander 🌕 Leaderboard 🚀",'data':get_data_per_env('LunarLander-v2')}
             }
 
 
+def reload_leaderboard(rl_env):
+    #import pdb;pdb.set_trace()
+    global RL_DETAILS
+    RL_DETAILS[rl_env]['data'] = get_data_per_env(rl_env)
+  
+    data_html,data_dataframe,is_empty = RL_DETAILS[rl_env]['data'] 
+                
+    if not is_empty:
+        markdown = """
+        # {name_leaderboard}
+
+        This is a leaderboard of **{len_dataframe}** agents playing {env_name} 👩‍🚀.
+
+        We use lower bound result to sort the models: mean_reward - std_reward.
+
+        You can click on the model's name to be redirected to its model card which includes documentation.
+
+        You want to try your model? Read this [Unit 1](https://github.com/huggingface/deep-rl-class/blob/Unit1/unit1/README.md) of Deep Reinforcement Learning Class.
+
+
+        """.format(len_dataframe = len(data_dataframe),env_name = rl_env,name_leaderboard =  RL_DETAILS[rl_env]['title'])
+
+    else:
+        markdown = """
+        # {name_leaderboard}                   
+        """.format(name_leaderboard =  RL_DETAILS[rl_env]['title'])
+
+    return markdown,data_html     
+            
+                       
+
+
 block = gr.Blocks()
 with block:
     
@@ -134,9 +167,11 @@ with block:
                     # {name_leaderboard}                   
                     """.format(name_leaderboard =  RL_DETAILS[rl_env]['title'])
 
-                  
-                gr.Markdown(markdown)
-                gr.HTML(data_html)
+                reload = gr.Button('Reload Leaderboard')
+                #env_state = gr.State(rl_env)    
+                output_markdown = gr.Markdown(markdown)
+                output_html = gr.HTML(data_html)
+                reload.click(reload_leaderboard,inputs=[rl_env],outputs=[output_markdown,output_html])
             
 
 block.launch()