app.py

from transformers import pipeline
import gradio as gr
import pygame

# Load the pre-trained Spanish language model using HuggingFace
nlp = pipeline("text2text-generation", model="datificate/gpt2-small-spanish")

# Define a function that generates a random Spanish sentence using the pre-trained model
def generate_sentence():
    sentence = nlp("Genera una oración en español")[0]["generated_text"]
    return sentence

# Define a function that checks if the child identifies the verb in the sentence
def check_answer(sentence, verb):
    words = sentence.split()
    if verb in words:
        return "¡Correcto! El verbo está en la oración."
    else:
        return "Lo siento, el verbo no está en la oración."

# Define a function that creates the chatbot interface using Gradio and adds fun animations or sound effects
def chatbot():
    # Initialize pygame mixer for sound effects
    pygame.mixer.init()

    # Load sound effect
    sound_effect = pygame.mixer.Sound("ding.wav")

    # Generate a random sentence
    sentence = generate_sentence()

    # Ask the child to identify the verb in the sentence
    verb = input("Identifica el verbo en la siguiente oración: " + sentence + "\n")

    # Check if the child's answer is correct
    result = check_answer(sentence, verb)

    # Play sound effect if the answer is correct
    if "Correcto" in result:
        sound_effect.play()

    return result

# Run the chatbot interface using Gradio
gr.Interface(fn=chatbot, inputs=None, outputs="text").launch()