Update app.py

app.py

@@ -1,22 +1,27 @@
 ## app.py ##
 import gradio as gr
 import spacy
+import random
 from transformers import pipeline
 
 nlp = spacy.load('es_core_news_sm')
 text_generator = pipeline('text-generation', model='gpt2')
 
 pos_tags = ['ADJ', 'ADP', 'ADV', 'AUX', 'CONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'SYM', 'VERB', 'X']
+pos_tags_es = ['ADJ', 'ADP', 'ADV', 'AUX', 'CONJ', 'DET', 'INTJ', 'NOMBRE', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNT', 'SCONJ', 'SYM', 'VERBO', 'X']  # Spanish version
+pos_explanation = {  # Add explanations for each POS tag
+    # Add your own explanations here
+}
 
 sentence_state = {'sentence': '', 'tagged_words': []}
 
 def generate_sentence():
-    result = text_generator('', max_length=10)[0]  # Limiting max_length for simplicity
+    result = text_generator('Erase una vez', max_length=10)[0]
     sentence = result['generated_text']
     tagged_words = analyze_sentence(sentence)
     sentence_state['sentence'] = sentence
     sentence_state['tagged_words'] = tagged_words
-    return sentence, [word for word, _ in tagged_words]
+    return sentence, random.sample(tagged_words, 5)  # Only select 5 words to classify
 
 def analyze_sentence(sentence):
     doc = nlp(sentence)
@@ -26,20 +31,23 @@ def check_answer(*args):
     correct_answer = [tag for word, tag in sentence_state['tagged_words']]
     user_answer = list(args)
     if user_answer == correct_answer:
-        return 'Correcto!'
+        return '¡Correcto!'
     else:
-        return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer)
+        return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer) + '. ' + explain(correct_answer)
+
+def explain(tags):
+    return ' '.join(pos_explanation[tag] for tag in tags)
 
 def game_flow(start_game):
-    if start_game == 'Start':
+    if start_game == 'Iniciar':
         sentence, words = generate_sentence()
-        answer = check_answer(*gr.inputs)
-        return sentence, words, answer
+        answer = check_answer(*gr.inputs[1:])  # Skip the first input
+        return sentence, [word for word, _ in words], answer
 
 iface = gr.Interface(fn=game_flow, 
-                     inputs=[gr.inputs.Textbox(label='Type "Start" to generate sentence')] + 
-                            [gr.inputs.Dropdown(choices=pos_tags, label=f'Word {i+1}') for i in range(10)],  # Assumes sentences of 10 words
-                     outputs=[gr.outputs.Textbox(label='Sentence'),
-                              gr.outputs.Textbox(label='Words'),
-                              gr.outputs.Textbox(label='Result')])
-iface.launch()
+                     inputs=[gr.inputs.Textbox(label='Escribe "Iniciar" para generar una frase')] + 
+                            [gr.inputs.Dropdown(choices=pos_tags_es, label=f'Palabra {i+1}') for i in range(5)],  # Only 5 words to classify
+                     outputs=[gr.outputs.Textbox(label='Frase'),
+                              gr.outputs.Textbox(label='Palabras'),
+                              gr.outputs.Textbox(label='Resultado')])
+iface