import gradio as gr
from transformers import pipeline

classifier = pipeline("text-classification",model='bhadresh-savani/distilbert-base-uncased-emotion', return_all_scores=True)

def detect_emotions(emotion_input):
  prediction = classifier(emotion_input,)
  output = {}
  for emotion in prediction[0]:
    output[emotion["label"]] = emotion["score"]
  return output

examples = [["I am excited to announce that I have been promoted"], ["Sorry for the late reply"]]

demo = gr.Interface(fn=detect_emotions, inputs=gr.Textbox(placeholder="Enter text here", label="Input"), outputs=gr.Label(label="Emotion"), examples=examples)
demo.launch()