Update app.py

app.py

@@ -48,7 +48,26 @@ def load_leaderboard():
         print(f"Failed to load leaderboard from HF Hub: {e}")
         return {}
 
+def load_entries():
+    try:
+        # grab the CSV of all past plays
+        csv_path = hf_hub_download(
+            repo_id=HUB_REPO_ID,
+            repo_type="dataset",
+            filename="test/leaderboard_entries.csv",
+            token=HF_TOKEN
+        )
+        df = pd.read_csv(csv_path)
+
+        return df
+
+    except Exception as e:
+        print(f"Failed to load leaderboard from HF Hub: {e}")
+        # if anything goes wrong, fall back to empty
+        return pd.Dataframe(columns=["file_name","prompt","label","model","split","prediction","user","timestamp"])
+
 leaderboard_scores = load_leaderboard()
+leaderboard_entries = load_entries()
 
 def save_leaderboard():
     try:
@@ -176,8 +195,8 @@ def detect_with_model(image: Image.Image, prompt: str, username: str, model_name
     image.save(image_path)
 
     csv_path = os.path.join("test", "leaderboard_entries.csv")
-    header = "file_name,prompt,label,model,split,prediction,user,timestamp\n"
-    csv_line = f"test/{type_image}/{image_filename},\"{prompt}\",{type_image},{model_name.lower()},test,{prediction.lower()},{username},{datetime.now().isoformat()}\n"
+    df.loc[len(df)] = [f"test/{type_image}/{image_filename}", prompt, type_image, model_name.lower(), "test", prediction.lower(), username, datetime.now().isoformat()]
+    df.to_csv(csv_path, index=False)
     try:
         file_exists = os.path.exists(csv_path)
         with open(csv_path, "a", encoding="utf-8") as f: