Update app.py

app.py

@@ -21,40 +21,38 @@ def clear_chat(state):
 
 from datasets import load_dataset
 import requests
+import os
 
 def get_user_elo_ratings():
     dataset = load_dataset("rwitz/mistral-elo-ratings", streaming=True)
     elo_ratings = dataset['train']  # or the relevant split
-
-    # Check and assign default ELO rating
-    default_elo = 1200
-    for bot in list(chatbots.keys()):
-        if bot not in elo_ratings:
-            elo_ratings[bot] = default_elo
-
     return elo_ratings
 
 def update_elo_rating(player_id, new_rating):
     # Fetch the current dataset
     elo_ratings = get_user_elo_ratings()
 
-    # Update the rating
-    elo_ratings = elo_ratings.map(lambda x: {'rating': new_rating})
+    # Function to update the rating of a specific player
+    def update_rating(example):
+        return {'rating': new_rating}
+
+    # Update the dataset
+    updated_dataset = elo_ratings.map(update_rating)
+
+    # Convert updated dataset to a dictionary for pushing
+    updated_data = updated_dataset.to_dict()
 
     # Push the updated dataset back to Hugging Face
-    # This part is more complex as it involves using Hugging Face's dataset push API.
-    # You'll need to use the `requests` library to make a POST request to Hugging Face's API.
-    # This is a simplified example:
-    updated_data = elo_ratings.to_dict()
     response = requests.post(
         "https://huggingface.co/datasets/rwitz/mistral-elo-ratings",
-        headers={"Authorization": f"Bearer {os.environ.get('huggingface_token')}"},
+        headers={"Authorization": f"Bearer {os.environ.get('HUGGINGFACE_TOKEN')}"},
         json=updated_data
     )
+
     if response.status_code == 200:
         print("Successfully updated the dataset")
     else:
-        print("Failed to update the dataset")
+        print("Failed to update the dataset. Response code:", response.status_code)
 
 # Function to get bot response
 def format_alpaca_prompt(state):