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import wikipedia
import transformers
import spacy
from transformers import AutoModelWithLMHead, AutoTokenizer
import random
import gradio as gr
tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
model = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
nlp = spacy.load("en_core_web_sm")
def get_question(answer, context, max_length=64):
input_text = "answer: %s context: %s </s>" % (answer, context)
features = tokenizer([input_text], return_tensors='pt')
output = model.generate(input_ids=features['input_ids'],
attention_mask=features['attention_mask'],
max_length=max_length)
return tokenizer.decode(output[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)
import gradio as gr
def greet(topic):
print("Entered topic: ", topic)
topics = wikipedia.search(topic)
random.shuffle(topics)
for topic in topics:
try:
summary = wikipedia.summary(topic)
except wikipedia.DisambiguationError as e:
# print(e.options)
s = random.choice(e.options)
summary = wikipedia.summary(s)
except wikipedia.PageError as e:
continue
break
print("Selected topic: ", topic)
print("Summary: ", summary)
summary = summary.replace("\n", "")
doc = nlp(summary)
answers = doc.ents
filtered_answers = []
for answer in answers:
if(answer.text in topic or topic in answer.text):
pass
else:
filtered_answers.append(answer)
answer_1 = random.choice(filtered_answers)
question_1 = get_question(answer_1, summary)
question_1 = question_1[9:]
print("Question: ", question_1)
print("Answer: ", answer_1)
return [question_1, gr.update(visible=True), gr.update(value=answer_1, visible=False)]
def get_answer(input_answer, gold_answer):
print("Entered Answer: ", input_answer)
return gr.update(value=gold_answer, visible=True)
with gr.Blocks() as demo:
# with gr.Row():
topic = gr.Textbox(label="Topic")
greet_btn = gr.Button("Ask a Question")
question = gr.Textbox(label="Question")
input_answer = gr.Textbox(label="Your Answer", visible=False)
answer_btn = gr.Button("Show Answer")
gold_answer = gr.Textbox(label="Correct Answer", visible=False)
greet_btn.click(fn=greet, inputs=topic, outputs=[question, input_answer, gold_answer])
# with gr.Row():
answer_btn.click(fn=get_answer, inputs=[input_answer,gold_answer], outputs=gold_answer)
demo.launch()
# demo.launch(share=True) |