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import gradio as gr
from gradio import Interface, inputs, outputs
import spacy
from transformers import GPT2LMHeadModel, GPT2Tokenizer
nlp = spacy.load('es_core_news_sm')
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("gpt2")
pos_map = {
'sustantivo': 'NOUN',
'verbo': 'VERB',
'adjetivo': 'ADJ',
'artículo': 'DET'
}
def identify_pos(sentence: str):
doc = nlp(sentence)
pos_tags = [(token.text, token.pos_) for token in doc]
return pos_tags
def game_logic(sentence: str, user_word: str, user_pos: str):
correct_answers = identify_pos(sentence)
user_pos = pos_map.get(user_pos.lower(), '')
for word, pos in correct_answers:
if word == user_word:
if pos.lower() == user_pos.lower():
return True, f'¡Correcto! "{user_word}" es un {user_pos}.'
else:
return False, f'Incorrecto. "{user_word}" no es un {user_pos}, es un {pos}.'
return False, f'La palabra "{user_word}" no se encuentra en la frase.'
def generate_hint(sentence: str, user_word: str, user_pos: str):
inputs = tokenizer.encode(f'Give a hint about the {user_pos} in the sentence "{sentence}"', return_tensors='pt')
outputs = model.generate(inputs, max_length=150, num_return_sequences=1, no_repeat_ngram_size=2)
hint = tokenizer.decode(outputs[0], skip_special_tokens=True)
return hint
def main(sentence: str, user_word: str, user_pos: str):
if sentence and user_word and user_pos and user_pos != 'Selecciona una función gramatical...':
correct, message = game_logic(sentence, user_word, user_pos)
hint = generate_hint(sentence, user_word, user_pos)
return message, hint
else:
return 'Por favor, introduce una frase, una palabra y selecciona una función gramatical válida (sustantivo, verbo, adjetivo, artículo).', ''
iface = Interface(fn=main,
inputs=[
inputs.Textbox(lines=2, placeholder='Introduce una frase aquí...'),
inputs.Textbox(lines=1, placeholder='Introduce una palabra aquí...'),
inputs.Dropdown(choices=['Selecciona una función gramatical...', 'sustantivo', 'verbo', 'adjetivo', 'artículo'])
],
outputs=[outputs.Textbox(), outputs.Textbox()])
iface.launch()
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