Update app.py

app.py

@@ -1,7 +1,28 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+pipe = pipeline("text-classification", model="peter2000/xlm-roberta-base-finetuned-ecoicop")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def predict(text):
+    preds = pipe(text)[0]
+    return preds["label"].split('_')[1],preds["label"].split('_')[0], round(preds["score"], 5)
+
+gradio_ui = gr.Interface(
+    fn=predict,
+    title="Predicting E-Coicop Product Categories",
+    description="Enter some product text (trained on name, category and url) from an online supermarket and predict the corresponding ECOICOP (level 5) product category for food and baverages.",
+    inputs=[
+        gr.inputs.Textbox(lines=5, label="Paste some text here"),
+    ],
+    outputs=[
+        gr.outputs.Textbox(label="Label"),
+        gr.outputs.Textbox(label="Score"),
+    ],
+    examples=[
+        ["Tiefkühl Eiscreme & Eiswürfel Bechereis <sep> rewe beste wahl peanut butter eiscreme <sep> REWE Beste Wahl Peanut Butter Eiscreme 500ml"], 
+        ["epicerie-sucree <sep> cereales chocolat fraise nat <sep> Céréales chocolat & fraise NAT"],
+        ["Pelati e passate <sep> unknown <sep> Mutti Polpa di Pomodoro 3 x 400 g"]
+    ],
+)
+
+gradio_ui.launch(debug=True)