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 = "rodrigomiranda98/tweet-eval-emotion"

learner = from_pretrained_fastai(repo_id)
labels = ['anger', 'joy', 'optimism', 'sadness']

# Definimos una función que se encarga de llevar a cabo las predicciones
def predict(text):
    pred, pred_idx, probs = learner.predict(text)
    print(f'pred: {pred}')
    print(f'probs: {probs}')
    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(lines=5, placeholder="Inserta el texto aquí"),
    outputs=gr.outputs.Label(num_top_classes=4),
    examples=["Everything will be fine, you'll see!", "My favorite team did not qualify, I'm sad."]
).launch(share=False)