Upload folder using huggingface_hub

app.py

@@ -23,19 +23,38 @@ st.set_page_config(
 
 @st.cache_resource
 def load_artifacts():
-    repo_id = "SharleyK/predictive-maintenance-model"
+    try:
+        repo_id = "SharleyK/predictive-maintenance-model"
+        token = os.getenv("HF_TOKEN")
+
+        model_path = hf_hub_download(
+            repo_id=repo_id,
+            filename="best_model.pkl",
+            token=token
+        )
+        model = joblib.load(model_path)
+
+        scaler_path = hf_hub_download(
+            repo_id=repo_id,
+            filename="scaler.pkl",
+            token=token
+        )
+        scaler = joblib.load(scaler_path)
+
+        metadata_path = hf_hub_download(
+            repo_id=repo_id,
+            filename="metadata.json",
+            token=token
+        )
+        with open(metadata_path, "r") as f:
+            metadata = json.load(f)
+
+        return model, scaler, metadata, True
+
+    except Exception as e:
+        st.error(f"❌ Error loading model artifacts: {e}")
+        return None, None, {}, False
 
-    model = joblib.load(hf_hub_download( repo_id,
-    "best_model.pkl",
-    token=os.getenv("HF_TOKEN")))
-    scaler = joblib.load(hf_hub_download(repo_id, "scaler.pkl"),token=os.getenv("HF_TOKEN"))
-    metadata = json.load(open(hf_hub_download(repo_id, "metadata.json",token=os.getenv("HF_TOKEN"))))
-
-    return model, scaler, metadata
-
-
-model, scaler, metadata = load_artifacts()
-MODEL_NAME = metadata.get("model_name", "Unknown Model")
 
 # =============================================================================
 # FEATURE ENGINEERING