import gradio as gr
import pickle
from transformers import pipeline

def load_model(selected_model):
    with open(selected_model, 'rb') as file:
        loaded_model = pickle.load(file)
    return loaded_model

encoder = {
        'negative':'assets/negative.jpg',
        'neutral':'assets/neutral.jpg',
        'positive':'assets/positive.jpeg'
    }

classifier = pipeline(task="zero-shot-classification", model="facebook/bart-large-mnli")
def analyze_sentiment(text):
  results = classifier(text,["positive","negative",'neutral'],multi_label=True)
  mx = max(results['scores'])
  ind = results['scores'].index(mx)
  result = results['labels'][ind]
  return encoder[result]

demo = gr.Interface(fn=analyze_sentiment, 
                    inputs=gr.Textbox(lines=2, placeholder="Escrbe algo para comenzar", label='Escribe algo para comenzar'), 
                    outputs="image", 
                    title="Analizador de Sentimientos") 

demo.launch(share=True)