|
import gradio as gr |
|
import numpy as np |
|
from transformers import pipeline |
|
|
|
|
|
pipeline_clf = pipeline("text-classification", model = "stinoco/beto-sentiment-analysis-finetuned", return_all_scores = True) |
|
pipeline_pos = pipeline("token-classification", model = "sagorsarker/codeswitch-spaeng-pos-lince") |
|
|
|
|
|
def predict(text: str): |
|
|
|
''' |
|
Funci贸n que recibe texto como input, devuelve la clasificaci贸n de texto para ser recibida por el demo. |
|
text: texto a clasificar (str) |
|
''' |
|
|
|
|
|
classes = pipeline_clf(text)[0] |
|
|
|
|
|
classes = {element['label']: element['score'] for element in classes} |
|
|
|
labeled_text = {'text': text, 'entities': pipeline_pos(text)} |
|
|
|
return classes, labeled_text |
|
|
|
demo = gr.Interface(fn = predict, |
|
inputs = [gr.Textbox(placeholder = "Ingresa el reclamo ac谩", label = 'Reclamo')], |
|
outputs = [gr.outputs.Label(label = 'Categor铆as'), |
|
gr.Highlightedtext(label = 'Part of Speech')], |
|
examples = [ |
|
['al ser de region simpre esta con quiebre de stock'], |
|
['que tienen que tener vendedores que conozcan el rubro y que sepan lo que estan vendiendo'], |
|
['un solo vendedor no pude estar encargado de miles de articulos debe especificarse en cerveza'], |
|
['no hay mercaderia'] |
|
], |
|
title = 'Demo Clasificaci贸n NPS' |
|
) |
|
|
|
demo.launch() |