Merge remote-tracking branch 'origin/main'

app.py

@@ -3,6 +3,7 @@ from huggingface_hub import HfApi
 from matchmaking import *
 from background_task import init_matchmaking, get_elo_data
 from apscheduler.schedulers.background import BackgroundScheduler
+from utils import *
 
 matchmaking = Matchmaking()
 api = HfApi()
@@ -21,24 +22,19 @@ def update_elos():
 
 with gr.Blocks() as block:
     gr.Markdown(f"""
-        # 🏆 The Deep Reinforcement Learning Course Leaderboard 🏆 
+        # 🏆 AI vs. AI SoccerTwos Leaderboard ⚽ 
 
-        This is the leaderboard of trained agents during the Deep Reinforcement Learning Course. A free course from beginner to expert.
+        In this leaderboard, you can find the ELO score and the rank of your trained model for the SoccerTwos environment.
 
-        This is the Soccer environment leaderboard, use Ctrl+F to find your rank 🏆
+        If you want to know more about a model, just **copy the username and model and paste them into the search bar**.
 
-        We use an ELO rating to sort the models.
-        You **can click on the model's name** to be redirected to its model card which includes documentation.
+        👀 To visualize your agents competing check this demo: https://huggingface.co/spaces/unity/ML-Agents-SoccerTwos
 
-        🤖 You want to try to train your agents? <a href="http://eepurl.com/ic5ZUD" target="_blank">Sign up to the Hugging Face free Deep Reinforcement Learning Course 🤗 </a>.
-
-        You want to compare two agents? <a href="https://huggingface.co/spaces/ThomasSimonini/Compare-Reinforcement-Learning-Agents" target="_blank">It's possible using this Spaces demo 👀 </a>.
-
-        🔧 There is an **environment missing?** Please open an issue.
+        🤖 For more information about this AI vs. AI challenge and to participate? Check: [ADD LINK].
         """)
     with gr.Row():
         output = gr.components.Dataframe(
-            value=get_elo_data(),
+            value=get_elo_data,
             headers=["Ranking 🏆", "User 🤗", "Model id 🤖", "ELO 🚀", "Games played 🎮"],
             datatype=["number", "markdown", "markdown", "number", "number"]
         )

background_task.py

@@ -4,6 +4,7 @@ import subprocess
 import pandas as pd
 from datetime import datetime
 from huggingface_hub import HfApi, Repository
+from utils import *
 
 DATASET_REPO_URL = "https://huggingface.co/datasets/huggingface-projects/bot-fight-data"
 DATASET_TEMP_REPO_URL = "https://huggingface.co/datasets/huggingface-projects/temp-match-results"
@@ -220,7 +221,8 @@ def get_elo_data() -> pd.DataFrame:
     :return: ELO data as a pandas DataFrame
     """
     repo.git_pull()
-    data = pd.read_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILENAME))
+    data = pd.read_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILENAME))    
+    
     return data
 
 

utils.py

@@ -0,0 +1,13 @@
+# Based on Omar Sanseviero work
+# Make model clickable link
+def make_clickable_model(model_name):
+    # remove user from model name
+    model_name_show = ' '.join(model_name.split('/')[1:])
+
+    link = "https://huggingface.co/" + model_name
+    return f'<a target="_blank" href="{link}">{model_name_show}</a>'
+
+# Make user clickable link
+def make_clickable_user(user_id):
+    link = "https://huggingface.co/" + user_id
+    return f'<a  target="_blank" href="{link}">{user_id}</a>'