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



# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
repo_id = "vop020506/entregable3"

learner = from_pretrained_fastai(repo_id)
labels = ['admiration','amusement', 'anger', 'annoyance', 'approval', 'caring','confusion','curiosity','desire', 'disappointment',
          'disapproval', 'disgust',	'embarrassment', 'excitement',	'fear',	'gratitude', 'grief', 'joy', 'love', 'nervousness', 'optimism', 'pride', 
          'realization','relief', 'remorse', 'sadness', 'surprise', 'neutral']
# 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)).launch(share=False)