beppe/question_answer
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Beppe Vanrolleghem
2022-11-30 14:47:11 +01:00
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The Amazon rainforest (Portuguese: Floresta Amazônica or Amazônia; Spanish: Selva Amazónica, Amazonía or usually Amazonia; French: Forêt amazonienne; Dutch: Amazoneregenwoud), also known in English as Amazonia or the Amazon Jungle, is a moist broadleaf forest that covers most of the Amazon basin of South America. This basin encompasses 7,000,000 square kilometres (2,700,000 sq mi), of which 5,500,000 square kilometres (2,100,000 sq mi) are covered by the rainforest. This region includes territory belonging to nine nations. The majority of the forest is contained within Brazil, with 60% of the rainforest, followed by Peru with 13%, Colombia with 10%, and with minor amounts in Venezuela, Ecuador, Bolivia, Guyana, Suriname and French Guiana. States or departments in four nations contain "Amazonas" in their names. The Amazon represents over half of the planet's remaining rainforests, and comprises the largest and most biodiverse tract of tropical rainforest in the world, with an estimated 390 billion individual trees divided into 16,000 species.

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import os
import cherrypy
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
model_name = "deepset/roberta-base-squad2"
path = os.path.abspath(os.path.dirname(__file__))
config = {
'global' : {
'server.socket_host' : '127.0.0.1',
'server.socket_port' : 8080,
'server.thread_pool' : 8,
},
}
class Root(object):
def answer_question(self, question, context):
question_answerer = pipeline('question-answering', model=model_name, tokenizer=model_name)
answer = question_answerer({'question': question, 'context': context})
print(answer)
return answer["answer"]
@cherrypy.expose
def index(self, *args, **kwargs):
answer = ""
with open('data.txt') as f:
context = f.read()
f.close()
if cherrypy.request.params.get('question'):
question_answerer = pipeline('question-answering', model=model_name, tokenizer=model_name)
temp = question_answerer({'question': cherrypy.request.params.get('question'), 'context': context})
answer = "<h1>answer</h1><p>{}</p>".format(temp["answer"])
return "<html><head><title>reinout project 1</title></head><body><h1>question</h1><form method=\"POST\" action=\"index\"><input type=\"text\" name=\"question\" size=\"50\"/><button type=\"submit\">send!</button></form>{}</body></html>".format(answer)
@cherrypy.expose
def question(self, *args,**kwargs):
with open('data.txt') as f:
alles = f.read()
f.close()
string=self.answer_question(cherrypy.request.params.get('the_link'), alles)
return string
if __name__ == '__main__':
cherrypy.quickstart(Root(), '/', config)

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# stappen
## requirements:
python 3.9
pip
## installation
pip install -r requirements.txt
python main.py
## access application
localhost:8080 in browser
## data.txt
fill data.txt with necessary context for question to be answered.

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cherrypy=18.8.0
tensorflow=2.10.1
transformers=4.24.0