Upload inference.py with huggingface_hub

inference.py

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+"""
+Simple inference script for the weight predictor model.
+Usage:
+    python inference.py "cheeseburger with fries" menu_item
+    python inference.py "chocolate bar 100g" grocery
+    python inference.py "wireless mouse" non_food
+"""
+import sys
+import joblib
+from huggingface_hub import hf_hub_download
+
+# Import predictor classes so pickling works
+import weight_predictor
+
+
+def load_model():
+    print("Loading model from HF Hub...")
+    model_path = hf_hub_download(
+        repo_id="ZZandro/weight-predictor",
+        filename="unified_predictor.pkl",
+        repo_type="model"
+    )
+    return joblib.load(model_path)
+
+
+def predict(text, item_type="grocery"):
+    predictor = load_model()
+    weight = predictor.predict(text, item_type=item_type)
+    return weight
+
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        print("Usage: python inference.py '<item description>' <item_type>")
+        print("  item_type: menu_item | grocery | non_food")
+        sys.exit(1)
+
+    description = sys.argv[1]
+    item_type = sys.argv[2] if len(sys.argv) > 2 else "grocery"
+
+    # Auto-prepend tag if not present
+    if not description.startswith("["):
+        description = f"[{item_type.upper()}] {description}"
+
+    weight = predict(description, item_type)
+    print(f"\nItem: {sys.argv[1]}")
+    print(f"Type: {item_type}")
+    print(f"Predicted weight: {weight:.1f} grams")