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# -*- coding: utf-8 -*-
"""Job-coach-document-testing-site.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1ECyP45v5tfkn0I-0W24qWGQotWyqPIQS
"""
#! pip install gradio
#! pip install transformers
import gradio as gr
#import torch
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
from transformers import pipeline
def QA_function(context, queries):
#tokenizer = AutoTokenizer.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")
model = "bert-large-uncased-whole-word-masking-finetuned-squad"
question_answerer = pipeline("question-answering", model = model)
Answered=[]
NotAnswered=[]
queries=queries.split("?")
queries.pop(-1)
for query in queries:
query.strip()
result = question_answerer(question = query, context=context)
if result['score'] > 0.01:
Answered.append(query +"? Answer: " + result['answer'])
else:
NotAnswered.append(query)
#print("Question Answered: ")
#for answer in Answered:
#print(answer)
# print("Question Not Answered: ")
# for answer in NotAnswered:
# print(answer)
result1=''',
'''.join(Answered)
result1='''Question Answered:
'''+ result1
result2=''',
'''.join(NotAnswered)
result2='''
Question Not Answered:
'''+ result2
return result1 + result2
title = "Testing demo"
description = "A testing site for Job Coach Documents"
gradio_ui = gr.Interface(QA_function, [gr.inputs.Textbox(lines=10, label="Context"), gr.inputs.Textbox(lines=10, label="Question")], gr.outputs.Textbox(label="Answer"))
gradio_ui.launch(debug=True) |