| import gradio as gr | |
| import spacy | |
| from transformers import pipeline | |
| nlp = spacy.load('es_core_news_sm') | |
| text_generator = pipeline('text-generation', model='datificate/gpt-2-small-spanish') | |
| pos_tags = ['ADJ', 'ADP', 'ADV', 'AUX', 'CONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'SYM', 'VERB', 'X'] | |
| sentence = "" | |
| tagged_words = [] | |
| def generate_sentence(): | |
| global sentence, tagged_words | |
| result = text_generator('', max_length=50)[0] | |
| sentence = result['generated_text'] | |
| tagged_words = analyze_sentence(sentence) | |
| return sentence, [word for word, _ in tagged_words] | |
| def analyze_sentence(sentence): | |
| doc = nlp(sentence) | |
| tagged_words = [(token.text, token.pos_) for token in doc] | |
| return tagged_words | |
| def check_answer(*args): | |
| correct_answer = [tag for word, tag in tagged_words] | |
| user_answer = list(args) | |
| if user_answer == correct_answer: | |
| return 'Correcto!' | |
| else: | |
| return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer) | |
| iface = gr.Interface(fn=generate_sentence, inputs='button', outputs=['textbox', 'dynamic']) | |
| iface.add_interface(fn=check_answer, inputs=gr.inputs.Dynamic(type="dropdown", choices=pos_tags, label='Word Tags'), outputs='textbox') | |
| iface.launch() | |