Update app.py

app.py

@@ -1,37 +1,45 @@
-## app.py ##
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline,GPTNeoXForCausalLM, AutoConfig
-from gradio import Interface
+from transformers import pipeline
 import gradio as gr
-from accelerate import init_empty_weights
-import json 
-# Create a dictionary of models
-MODELS = {
-    "T5": "lmsys/fastchat-t5-3b-v1.0",
-    "LSpanishGPT2": "PlanTL-GOB-ES/gpt2-large-bne",
-    "GPT2": "datificate/gpt2-small-spanish",
-    "OpenAssistant": "OpenAssistant"
-}
-
-# Define your function
-def generate_and_analyze(model_name, input_text):
-    model= MODELS[model_name]
-    tokenizer = AutoTokenizer.from_pretrained(model)
-    if model == "OpenAssistant":
-        tokenizer = AutoTokenizer.from_pretrained("OpenAssistant")
-        model = AutoModelForCausalLM.from_pretrained("OpenAssistant")
-    
-    TOKENIZERS[model_name] = tokenizer
-    text_generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device=0) # Use GPU if available
-    result = text_generator(input_text, max_length=250, do_sample=True)[0]
-    return result['generated_text']
-
-# Define your interface
-iface = gr.Interface(
-    fn=generate_and_analyze, 
-    inputs=[
-        gr.inputs.Dropdown(choices=list(MODELS.keys()), label="Model"),
-        gr.inputs.Textbox(lines=2, label="Input Text")
-    ], 
-    outputs="text"
-)
-iface.launch()
+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()