Update app.py

app.py

@@ -1,30 +1,17 @@
-!pip install gradio
-!pip install transformers
-
+# gradio demo
 import gradio as gr
 from transformers import pipeline
-    
-def aspects(sentense):
-    sentense=[sentense]
-    sentimentdata=sentiment(sentense)
-    fit_score=process.default_scorer(sentense,fit)
-    mat_score=process.default_scorer(sentense,material)
-    price_score=process.default_scorer(sentense,price)
-    sentimentlabel=sentimentdata[0].get("label")
-    sentprobability=sentimentdata[0].get("score")    
-    return  sentimentlabel,sentprobability,fit_score,price_score,mat_score
 
 pipe = pipeline("sentiment-analysis")
-interface=gr.Interface(fn=aspects,inputs=gr.inputs.Textbox(lines=10,placeholder="please insert your text"),
-examples=[
-          ["this product and not fitting well to my body and feel scratchy"],
-        ["this fabric is super cool and feel very comfortable "]
-       
-    ],
-    title="Review Analyzer",
-                       outputs=[gr.outputs.Textbox(type="auto", label="Sentiment"),
-                                gr.outputs.Textbox(type="auto", label="Sentiment score"),
-                                gr.outputs.Textbox(type="auto", label="Fit related score"),
-                                gr.outputs.Textbox(type="auto", label="Price related score"),
-                                gr.outputs.Textbox(type="auto", label="Material related score")],live=True)
-interface.launch()
+
+def predict(text):
+  return pipe(text)[0]["label"]
+
+iface = gr.Interface(
+  fn=predict,
+  inputs='text',
+  outputs='text',
+  examples=[["The movie was amazing"]]
+)
+
+iface.launch()