Update app/model_loader.py

app/model_loader.py

@@ -1,34 +1,22 @@
+# app/model_loader.py
 import os
 import tensorflow as tf
 from huggingface_hub import hf_hub_download
 
-# ✅ Force Hugging Face cache to a writable directory
-os.environ["HF_HUB_CACHE"] = "/tmp/huggingface"
-
-# ✅ Model directory and path
-MODEL_DIR = "/tmp/model"
-MODEL_PATH = os.path.join(MODEL_DIR, "efficientnetv2s.h5")
-
+MODEL_PATH = "app/model/efficientnetv2s.h5"
 REPO_ID = "Miguel764/efficientnetv2s-skin-cancer-classifier"
 FILENAME = "efficientnetv2s.h5"
 
 def load_model():
-    # Create directories if not exist
-    os.makedirs(MODEL_DIR, exist_ok=True)
-    os.makedirs(os.environ["HF_HUB_CACHE"], exist_ok=True)
-
-    # ✅ Only download if the model is missing
     if not os.path.exists(MODEL_PATH):
         print("Model not found locally. Downloading from Hugging Face...")
-        downloaded_path = hf_hub_download(
+        os.makedirs(os.path.dirname(MODEL_PATH), exist_ok=True)
+        hf_hub_download(
             repo_id=REPO_ID,
             filename=FILENAME,
-            local_dir=MODEL_DIR,
-            local_dir_use_symlinks=False
+            local_dir="app/model"
         )
-        print(f"Model downloaded to: {downloaded_path}")
     else:
         print("Model already exists locally.")
 
-    # ✅ Load the model safely
     return tf.keras.models.load_model(MODEL_PATH)