Update app.py

app.py

@@ -1,8 +1,46 @@
-import gradio as gr
 from transformers import pipeline
+import gradio as gr
+
+def coding(model, text, codetext):
+    classifier = pipeline("zero-shot-classification", model=model)
+    codelist = codetext.split(',')
+    output = classifier(text, codelist, multi_label=True)
+    return output
 
-def greet(name):
-    return "Hello " + name + "!!"
+iface = gr.Interface(
+    fn=coding, 
+    inputs=[
+        gr.Radio(
+            [
+                "facebook/bart-large-mnli",
+                "MoritzLaurer/multilingual-MiniLMv2-L6-mnli-xnli",
+                "MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7",
+                "MoritzLaurer/mDeBERTa-v3-base-mnli-xnli",
+                "MoritzLaurer/deberta-v3-large-zeroshot-v2.0",
+                #"joeddav/xlm-roberta-large-xnli"
+            ],
+            #min_width=200,
+            #scale=2,
+            value="facebook/bart-large-mnli",
+            label="Model"
+        ),
+        gr.TextArea(
+            label='Comment',
+            value='感覺性格溫和，適合香港人，特別係亞洲人的肌膚，不足之處就是感覺很少有優惠，價錢都比較貴'
+        ),
+        gr.Textbox(
+            label='Code list',
+            value='非常好/很好/好滿意,價錢合理/實惠/不太貴/親民/價格適中/價格便宜/價錢大眾化,價錢貴/不合理/比日本台灣貴/可以再平d/Sasa 卓悅買會平啲'
+        )
+    ],
+    outputs=[
+        #gr.Textbox(label='Result')
+        gr.JSON()
+        #gr.BarPlot()
+    ],
+    title="NuanceTree Coding Test",
+    description="Test Zero-Shot Classification",
+    allow_flagging='never'
+)
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+iface.launch()