Update app.py

app.py

@@ -1,10 +1,36 @@
+# import gradio as gr
+
+# from transformers import pipeline
+# classifier = pipeline('text-classification', model='el-filatova/clasificador-tweet-sentiment')
+
+# def predict(text):
+#     return classifier(text)
+
+# iface = gr.Interface(fn=predict, inputs=[gr.Textbox(value="ah, what a pang of aching sharp surprise")], outputs="text")
+# iface.launch()
+
 import gradio as gr
 
 from transformers import pipeline
 classifier = pipeline('text-classification', model='el-filatova/clasificador-tweet-sentiment')
 
 def predict(text):
-    return classifier(text)
+    prediction = classifier(text)
+    score = int(round(prediction[0]['score'] * 100))
+    
+    if prediction[0]['label'] == "LABEL_0":
+        output = f"This tweet carries a negative sentiment with a confidence level of {score}%."
+    elif prediction[0]['label'] == "LABEL_1":
+        output = f"This tweet carries a neutral sentiment with a confidence level of {score}%."
+    else:
+        output = f"This tweet carries a positive sentiment with a confidence level of {score}%."
+
+    return output
+            
 
 iface = gr.Interface(fn=predict, inputs=[gr.Textbox(value="ah, what a pang of aching sharp surprise")], outputs="text")
-iface.launch()
+iface.launch()
+
+
+
+