try new code

app.py

@@ -1,7 +1,44 @@
 import gradio as gr
+from fastai.learner import load_learner
+from fastai.vision.all import PILImage
+from huggingface_hub import hf_hub_download
+import torch
 
-def greet(name):
-    return "Hello " + name + "!!"
+def load_model():
+    # Download the model from your model repository
+    model_path = hf_hub_download(
+        repo_id="RamyKhorshed/Lesson2FastAi",
+        filename="model.pkl",
+        repo_type="model"
+    )
+    return load_learner(model_path)
+
+print("Loading model...")
+model = load_model()
+print("Model loaded!")
+
+def predict_image(image):
+    # Convert to FastAI format
+    img = PILImage.create(image)
+    
+    # Predict
+    pred, pred_idx, probs = model.predict(img)
+    
+    # Format output
+    confidence = float(probs[pred_idx])
+    return {
+        "Cat": confidence if str(pred).lower() == "cat" else 1 - confidence,
+        "Not Cat": confidence if str(pred).lower() != "cat" else 1 - confidence
+    }
+
+# Create interface
+demo = gr.Interface(
+    fn=predict_image,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=2),
+    title="🐱 Cat Detector",
+    description="Upload an image to check if it contains a cat!",
+    article="Upload any image and the model will predict whether it contains a cat or not."
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()