[feat]: upgrade code deployment

.github/workflows/sync_ahf.yaml

@@ -25,6 +25,11 @@ jobs:
           git config --global user.email "$EMAIL_USER"
           git config --global user.name "tph-kds"
 
+      # Xóa file .pth trước khi push (để tránh bị Hugging Face chặn)
+      - name: Remove local model checkpoints
+        run: |
+          rm -f checkpoints/**/*.pth || true
+          
       - name: Force push to Hugging Face Space
         run: |
           git remote add hf https://$HF_USERNAME:$HF_TOKEN@huggingface.co/spaces/$HF_USERNAME/$SPACE_NAME || true

deployment/gradio/{main.py → app.py}

@@ -1,7 +1,8 @@
 import gradio as gr
 from src.infer import inference_pipeline
 
-model_path = "checkpoints/ckpt_23_10_2025/best_cat_dog_classifier_model_20251019_122336.pth"
+# model_path = "checkpoints/ckpt_23_10_2025/best_cat_dog_classifier_model_20251019_122336.pth"
+
 
 def classify_image(
         image_path: str
@@ -14,7 +15,8 @@ def classify_image(
     try:
         prediction = inference_pipeline(
             image_path=image_path, 
-            model_path=model_path
+            model_path=model_path,
+            hf=True
         )
         return f"Prediction: {prediction.capitalize()}"
     except Exception as e:

requirements.txt

@@ -1,4 +1,5 @@
 scikit-learn==1.6.1
 gradio==4.44.1
 pydantic==2.10.6
+huggingface_hub==0.36.0
 # torch torchvision --index-url https://download.pytorch.org/whl/cu126

src/infer.py

@@ -1,10 +1,12 @@
 import torch
+from huggingface_hub import hf_hub_download
 from src.model import CatDogClassifier
 from src.config import CatDogClassifierConfigs
 
 def inference_pipeline(
     image_path: str = "datasets/single_prediction/cat_or_dog_1.jpg",
-    model_path: str = "checkpoints/ckpt_23_10_2025/best_cat_dog_classifier_model_20251019_122336.pth"
+    model_path: str = "checkpoints/ckpt_23_10_2025/best_cat_dog_classifier_model_20251019_122336.pth",
+    hf: bool = False
 ):
 
     # Initialize model
@@ -21,7 +23,21 @@ def inference_pipeline(
     )
     # Load state_dict
     model = CatDogClassifier(configs=model_configs)
-    model.load_state_dict(torch.load(model_path, map_location="cpu"))
+    # Load weights
+    if hf:
+        # Download from Hugging Face Model Hub (not from Spaces)
+        model_path = hf_hub_download(
+            repo_id="vikenkd/catdog-model",  
+            filename="best_cat_dog_classifier_model_20251019_122336.pth",
+            repo_type="model"
+        )
+
+    # Load state_dict (both local & remote)
+    state_dict = torch.load(model_path, map_location=model_configs.device)
+    model.load_state_dict(state_dict)
+    model.eval()
+
+
     y_pred = model.predict(
         model=model, 
         image_path=image_path