Update app.py

app.py

@@ -3,12 +3,16 @@ import spacy
 from transformers import pipeline
 
 nlp = spacy.load('es_core_news_sm')
-text_generator = pipeline('text-generation', model='gpt2')
+text_generator = pipeline('text-generation', model='microsoft/DialoGPT-large')
 
 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():
-    result = text_generator('')[0]
+    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]
@@ -18,8 +22,7 @@ def analyze_sentence(sentence):
     tagged_words = [(token.text, token.pos_) for token in doc]
     return tagged_words
 
-def check_answer(sentence, *args):
-    tagged_words = analyze_sentence(sentence)
+def check_answer(*args):
     correct_answer = [tag for word, tag in tagged_words]
     user_answer = list(args)
     if user_answer == correct_answer:
@@ -27,11 +30,6 @@ def check_answer(sentence, *args):
     else:
         return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer)
 
-iface = gr.Interface(fn=check_answer, 
-                     inputs=[gr.inputs.Button(label='Generate Sentence'), 
-                             gr.inputs.Dropdown(choices=pos_tags, label='Word 1'),
-                             gr.inputs.Dropdown(choices=pos_tags, label='Word 2'),
-                             # Add more dropdowns as needed
-                            ], 
-                     outputs=gr.outputs.Textbox())
+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()