Upload app.py with huggingface_hub

app.py

@@ -10,7 +10,7 @@ from huggingface_hub import hf_hub_download
 # Define the model and username
 MODEL_NAME = "XGBoost"
 HF_USERNAME = "Devishetty100"
-CUSTOM_MODEL_NAME = "neoguardianai"
+CUSTOM_MODEL_NAME = "NeoGuardianAI"
 REPO_ID = f"{HF_USERNAME}/{CUSTOM_MODEL_NAME.lower()}"
 
 # List of trusted domains that should always be considered safe
@@ -32,7 +32,18 @@ TRUSTED_DOMAINS = [
 def load_model_files():
     try:
         print(f"Attempting to download model from Hugging Face Hub: {REPO_ID}")
-        model_path = hf_hub_download(repo_id=REPO_ID, filename=f"{MODEL_NAME.lower()}_model.joblib")
+        # Try to list files in the repository to see what's available
+        try:
+            from huggingface_hub import list_repo_files
+            files = list_repo_files(repo_id=REPO_ID)
+            print(f"Files available in the repository: {files}")
+        except Exception as list_error:
+            print(f"Error listing repository files: {list_error}")
+
+        # Use lowercase 'xgboost' instead of MODEL_NAME.lower() to match the actual filename
+        model_path = hf_hub_download(repo_id=REPO_ID, filename="xgboost_model.joblib")
+        print(f"Downloaded model file to: {model_path}")
+
         scaler_path = hf_hub_download(repo_id=REPO_ID, filename="scaler.joblib")
         feature_names_path = hf_hub_download(repo_id=REPO_ID, filename="feature_names.json")
 
@@ -52,7 +63,9 @@ def load_model_files():
         # If downloading fails, try to load from local files
         try:
             print("Attempting to load model from local files...")
-            model = joblib.load(f"{MODEL_NAME.lower()}_model.joblib")
+            # Try with the correct lowercase name
+            model = joblib.load("xgboost_model.joblib")
+            print("Successfully loaded xgboost_model.joblib")
             scaler = joblib.load("scaler.joblib")
 
             with open("feature_names.json", 'r') as f: