Update app.py

app.py

@@ -2,42 +2,38 @@ 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')
 
+pos_tags = ['ADJ', 'ADP', 'ADV', 'AUX', 'CONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'SYM', 'VERB', 'X']
+
 def generate_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)
+    result = text_generator('')[0]
+    sentence = result['generated_text']
+    return sentence
 
 def analyze_sentence(sentence):
-    # Analyze the sentence
     doc = nlp(sentence)
     tagged_words = [(token.text, token.pos_) for token in doc]
     return tagged_words
 
-def game_handler(action, sentence, answer):
-    if action == 'generate':
-        return generate_sentence(), ''
-    elif action == 'check':
-        tagged_words = analyze_sentence(sentence)
-        correct_answer = [tag for word, tag in tagged_words]
-        if answer == correct_answer:
-            return sentence, 'Correcto!'
-        else:
-            return sentence, 'Incorrecto. La respuesta correcta es: ' + str(correct_answer)
+def check_answer(sentence, answer):
+    tagged_words = analyze_sentence(sentence)
+    correct_answer = [tag for word, tag in tagged_words]
+    if answer == correct_answer:
+        return 'Correcto!'
     else:
-        return sentence, 'Accion desconocida.'
+        return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer)
+
+def process_form(input_dict):
+    answer = [input_dict[word] for word in sorted(input_dict.keys())]
+    return check_answer(sentence, answer)
 
-iface = gr.Interface(fn=game_handler, 
-                     inputs=['dropdown', 'text', 'list'], 
-                     outputs=['text', 'text'])
+sentence = generate_sentence()
+tagged_words = analyze_sentence(sentence)
+inputs = {word: gr.inputs.Dropdown(choices=pos_tags) for word, tag in tagged_words}
+inputs['submit'] = gr.inputs.Button(label='Submit')
+outputs = gr.outputs.Textbox()
 
-iface.launch()
+iface = gr.Interface(fn=process_form, inputs=inputs, outputs=outputs)
+iface.launch()