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from transformers import pipeline
import wikipedia
import random
import gradio as gr
model_name = "deepset/electra-base-squad2"
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
def get_wiki_article(topic):
topic=topic
try:
search = wikipedia.search(topic, results = 1)[0]
except wikipedia.DisambiguationError as e:
choices = [x for x in e.options if ('disambiguation' not in x) and ('All pages' not in x) and (x!=topic)]
search = random.choice(choices)
try:
p = wikipedia.page(search)
except wikipedia.exceptions.DisambiguationError as e:
choices = [x for x in e.options if ('disambiguation' not in x) and ('All pages' not in x) and (x!=topic)]
s = random.choice(choices)
p = wikipedia.page(s)
return p.content, p.url
def get_answer(topic, question):
w_art, w_url=get_wiki_article(topic)
qa = {'question': question, 'context': w_art}
res = nlp(qa)
return res['answer'], w_url, {'confidence':res['score']}
inputs = [
gr.inputs.Textbox(lines=2, label="Topic"),
gr.inputs.Textbox(lines=2, label="Question")
]
outputs = [
gr.outputs.Textbox(type='str',label="Answer"),
gr.outputs.Textbox(type='str',label="Wikipedia Reference Article"),
gr.outputs.Label(type="confidences",label="Confidence in answer (assuming the correct wikipedia article)"),
]
title = "AI Wikipedia Search"
description = 'Contextual Question and Answer'
article = ''
examples = [
['Quantum', 'What is quanta in physics?'],
['Cicero', 'What quotes did Marcus Tullius Cicero make?'],
['Alzheimers', 'What causes alzheimers?'],
['Neuropathy', 'With neuropathy and neuro-muskoskeletal issues, and what are the treatments available?'],
['Chemotherapy', 'What are possible care options for patients in chemotherapy?'],
['Health', 'What is mindfulness and how does it affect health?'],
['Medicine', 'In medicine what is the Hippocratic Oath?'],
['Insurance', 'What is Medicare?'],
['Financial Services', 'Does Medicaid offer financial assistance?'],
['Ontology', 'Why is an anthology different than ontology?'],
['Taxonomy', 'What is a biology taxonomy?'],
['Pharmacy', 'What does a pharmacist do?']
]
gr.Interface(get_answer, inputs, outputs, title=title, description=description, article=article, examples=examples, flagging_options=["strongly related","related", "neutral", "unrelated", "strongly unrelated"]).launch(share=False,enable_queue=False) |