Update app.py
Browse files
app.py
CHANGED
@@ -1,27 +1,24 @@
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## app.py ##
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import gradio as gr
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import spacy
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import random
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from transformers import pipeline
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nlp = spacy.load('es_core_news_sm')
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text_generator = pipeline('text-generation', model='gpt2')
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pos_tags = ['ADJ', 'ADP', 'ADV', 'AUX', 'CONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'SYM', 'VERB', 'X']
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pos_tags_es = ['ADJ', 'ADP', 'ADV', 'AUX', 'CONJ', 'DET', 'INTJ', 'NOMBRE', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNT', 'SCONJ', 'SYM', 'VERBO', 'X'] # Spanish version
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pos_explanation = { # Add explanations for each POS tag
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# Add your own explanations here
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}
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sentence_state = {'sentence': '', 'tagged_words': []}
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def generate_sentence():
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result = text_generator('
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sentence = result['generated_text']
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tagged_words = analyze_sentence(sentence)
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sentence_state['sentence'] = sentence
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sentence_state['tagged_words'] = tagged_words
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return sentence,
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def analyze_sentence(sentence):
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doc = nlp(sentence)
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correct_answer = [tag for word, tag in sentence_state['tagged_words']]
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user_answer = list(args)
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if user_answer == correct_answer:
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return '
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else:
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return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer)
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def explain(tags):
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return ' '.join(pos_explanation[tag] for tag in tags)
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def game_flow(start_game):
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if start_game == '
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sentence, words = generate_sentence()
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answer = check_answer(*gr.inputs
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return sentence,
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iface =
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inputs=[
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[
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outputs=[
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iface
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## app.py ##
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import gradio as gr
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import spacy
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from transformers import pipeline
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from gradio import Interface
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from gradio.components import Textbox, Dropdown
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nlp = spacy.load('es_core_news_sm')
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text_generator = pipeline('text-generation', model='gpt2')
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pos_tags = ['ADJ', 'ADP', 'ADV', 'AUX', 'CONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'SYM', 'VERB', 'X']
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sentence_state = {'sentence': '', 'tagged_words': []}
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def generate_sentence():
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result = text_generator('', max_length=10)[0] # Limiting max_length for simplicity
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sentence = result['generated_text']
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tagged_words = analyze_sentence(sentence)
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sentence_state['sentence'] = sentence
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sentence_state['tagged_words'] = tagged_words
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return sentence, [word for word, _ in tagged_words]
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def analyze_sentence(sentence):
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doc = nlp(sentence)
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correct_answer = [tag for word, tag in sentence_state['tagged_words']]
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user_answer = list(args)
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if user_answer == correct_answer:
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return 'Correcto!'
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else:
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return 'Incorrecto. La respuesta correcta es: ' + str(correct_answer)
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def game_flow(start_game):
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if start_game == 'Start':
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sentence, words = generate_sentence()
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answer = check_answer(*gr.inputs)
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return sentence, words, answer
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iface = Interface(fn=game_flow,
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inputs=[Textbox(label='Type "Start" to generate sentence')] +
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[Dropdown(choices=pos_tags, label=f'Word {i+1}') for i in range(10)], # Assumes sentences of 10 words
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outputs=[Textbox(label='Sentence'),
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Textbox(label='Words'),
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Textbox(label='Result')])
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iface.launch()
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