from huggingface_hub import from_pretrained_fastai

from fastai.text.all import *

import gradio as gr






# Cargamos el learner

learner = from_pretrained_fastai('osrojo/Emotion')


# Definimos las etiquetas de nuestro modelo

labels = ['0','1','2','3','4','5']


example1 = "I started crying when I saw that little cat standing in the middle of the forest. It reminded me of my poor kitten."

example2 = "I can't wait to see Coldplay's concert next week. It's gonna be great!"

example3 = "The moment I finished reading a Brief History of Time, I knew that my passion would be physics."

example4 = "The fact that I needed to create four Gmail accounts in order to finish this goddammn notebook is quite irritating."

example5 = "i feel agitated with myself that i did not foresee her frustrations earlier leading to the ending of our relationship"

example6 = "i feel like they bring the characters to life completely and I'm always kind of surprised what the actors do do together."

# Definimos una función que se encarga de llevar a cabo las predicciones

def predict(text): 
    pred,pred_idx, probs = learner.predict(text)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}


# Creamos la interfaz y la lanzamos. 

gr.Interface(fn=predict, inputs=gr.Textbox(), outputs=gr.Label(),examples=[example1,example2,example3,example4,example5,example6]).launch(share=False)