Update app.py

app.py

@@ -2,20 +2,29 @@ import gradio as gr
 import spacy
 from transformers import pipeline
 
+# Load the Spanish language model
 nlp = spacy.load('es_core_news_sm')
+
+# Load the text generation pipeline
 text_generator = pipeline('text-generation', model='gpt2')
 
 def generate_sentence():
-    result = text_generator('')[0]
-    sentence = result['generated_text']
-    return sentence
+    # Generate a sentence
+    try:
+        result = text_generator('', max_length=50)[0]
+        sentence = result['generated_text']
+        return sentence
+    except Exception as e:
+        return str(e)
 
 def analyze_sentence(sentence):
+    # Analyze the sentence
     doc = nlp(sentence)
     tagged_words = [(token.text, token.pos_) for token in doc]
     return tagged_words
 
 def check_answer(sentence, answer):
+    # Check the user's answer
     tagged_words = analyze_sentence(sentence)
     correct_answer = [tag for word, tag in tagged_words]
     if answer == correct_answer:
@@ -23,6 +32,18 @@ def check_answer(sentence, answer):
     else:
         return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer)
 
-sentence = generate_sentence()
-iface = gr.Interface(fn=check_answer, inputs=['text', 'list'], outputs='text')
+# Define the Gradio interface
+iface = gr.Interface(
+    fn={
+        "generate_sentence": generate_sentence,
+        "check_answer": check_answer
+    }, 
+    inputs={
+        "sentence": "text", 
+        "answer": "list"
+    }, 
+    outputs="text"
+)
+
+# Launch the interface
 iface.launch()