from huggingface_hub import from_pretrained_fastai
import gradio as gr
from fastai.text.all import *



# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
repo_id = "ungonzal/tweet_eval"

learner = from_pretrained_fastai(repo_id)
labels = ["positive","negative"]

# Definimos una función que se encarga de llevar a cabo las predicciones
def predict(text):
    #img = PILImage.create(img)
    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.inputs.Textbox(), outputs=gr.outputs.Label(num_top_classes=3),examples=['Man these are the funniest kids ever!! That face! #HappyBirthdayBubb @ FLIPnOUT Xtreme']).launch(share=False)