import gradio
import nltk
import pandas as pd
from transformers import pipeline

summarizer = pipeline('summarization', model='t5-base')

# classifier_model_name = 'bhadresh-savani/distilbert-base-uncased-emotion'
# classifier_emotions = ['anger', 'disgust', 'fear', 'joy', 'sadness', 'surprise']

classifier_model_name = 'ProsusAI/finbert'
classifier_emotions = ['positive', 'neutral', 'negative']

classifier = pipeline('text-classification', model=classifier_model_name)

def my_inference_function(name):
    return "Hello " + name + "!"

gr_interface = gradio.Interface(
    fn = my_inference_function,
    inputs = "text",
    outputs = "text"
)

gr_interface.launch()