update readme and server .env references

README.md

@@ -25,6 +25,10 @@ An application to explore and discover all leaderboards from the Hugging Face co
 - 🌓 Dark/Light mode
 - 🔄 Automatic data updates
 
+## Data Source
+
+The application fetches data from the [leaderboard-explorer/leaderboard_explorer](https://huggingface.co/datasets/leaderboard-explorer/leaderboard_explorer) dataset on Hugging Face Hub. This dataset contains the consolidated leaderboard data in the `final_leaderboards.json` file.
+
 ## Configuration
 
 ### Environment Variables
@@ -35,13 +39,18 @@ Create a `.env` file in the server directory with the following variables:
 # Hugging Face API token (required)
 HF_TOKEN=your_token_here
 
-# Server configuration (optional)
+# Hugging Face dataset repository ID
+HF_REPO_ID=OpenEvals/find-a-leaderboard
+
+# Server configuration
 API_HOST=0.0.0.0
 API_PORT=3002
 ```
 
 The `HF_TOKEN` is required to access private datasets on Hugging Face. You can get your token from your [Hugging Face account settings](https://huggingface.co/settings/tokens).
 
+The `HF_REPO_ID` specifies which dataset repository to use. By default, it points to the main leaderboard explorer dataset.
+
 ## Local Development
 
 1. Install client dependencies:

server/server.py

@@ -16,7 +16,8 @@ load_dotenv()
 # API configuration
 API_HOST = os.getenv("API_HOST", "0.0.0.0")
 API_PORT = int(os.getenv("API_PORT", "3002"))
-HF_TOKEN = os.getenv("HF_TOKEN")
+HUGGING_FACE_HUB_TOKEN = os.getenv("HUGGING_FACE_HUB_TOKEN")
+HUGGING_FACE_STORAGE_REPO = os.getenv("HUGGING_FACE_STORAGE_REPO")
 CACHE_DIR = "cache"
 CACHE_DURATION = timedelta(seconds=10)
 
@@ -71,9 +72,9 @@ async def get_leaderboards():
             
         # If no cache or expired, download from HF
         file_path = hf_hub_download(
-            repo_id="leaderboard-explorer/leaderboard_explorer",
+            repo_id=HUGGING_FACE_STORAGE_REPO,
             filename="final_leaderboards.json",
-            token=HF_TOKEN,
+            token=HUGGING_FACE_HUB_TOKEN,
             repo_type="dataset"
         )