Update app.py

app.py

@@ -1,7 +1,37 @@
+import torch
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-def greet(text):
-    return f"Hello {text}! Your Space is working."
+MODEL_NAME = "Manvtith/FoodExtract-gemma-3-270m-fine-tune-v1"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def extract_food(text):
+    prompt = f"Extract all food and drink items from this sentence:\n{text}\nAnswer:"
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=128,
+            temperature=0.2,
+            do_sample=False
+        )
+
+    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return result.split("Answer:")[-1].strip()
+
+demo = gr.Interface(
+    fn=extract_food,
+    inputs=gr.Textbox(lines=3, placeholder="Type a sentence with food..."),
+    outputs="text",
+    title="Food & Drink Extractor (Gemma SLM)",
+    description="Fine-tuned Gemma-3-270M to extract food and beverage items from text."
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()