def ChatbotTester(FAQFilename,LogFilename):
print(__doc__.split('.')[0])
try:
chatbot = Chatbot.Chatbot(FAQFilename)
except FileNotFoundError:
print("Could not find FAQ.")
return 1
if LogFilename:
print("Loggin to file: "+LogFilename)
logFile = open(LogFilename,"a")
# loop
while(1):
try:
userInput = input('Input: ')
except KeyboardInterrupt:
# User hit ctrl-c
if LogFilename:
logFile.close()
return 1
# We open and close the file to avoid loosing data if we crash
if LogFilename:
logFile = open(LogFilename,"a")
Type,response = chatbot.InputOutput(userInput)
if LogFilename:
logFile.write("\nInput: "+userInput)
logFile.write("\nResponse: "+response)
logFile.write("\nType: "+str(Type))
logFile.write("\n")
logFile.close()
print()
print("Response: "+response)
if Type == True:
try:
chatbot.UserFeedback(input())
except KeyboardInterrupt:
# User hit ctrl-c
if LogFilename:
logFile.close()
return 1
else:
print()
print()
def ChatbotAutograder(script_filename, faq_filename, log_filename):
print(__doc__.split('.')[0])
try:
with open(script_filename, encoding='utf-8') as json_data:
autograder_test_script_as_list_of_dicts = json.load(json_data)
except:
print("Failure opening AutograderScript json file")
return 1
try:
chatbot = Chatbot.Chatbot(faq_filename)
except FileNotFoundError:
print("Could not find FAQ.")
return 1
if log_filename:
print("Loggin to file: "+log_filename)
log_file = open(log_filename, "w")
score = 0.0
for qa_dict in autograder_test_script_as_list_of_dicts:
response = chatbot.input_output(qa_dict["questions"][0]).split('\n')[0]
action = "0.0"
if "replace" in qa_dict:
replace = qa_dict["replace"]
else:
replace = ""
if response == qa_dict["response"]:
score += 1.0
action = "1.0"
chatbot.user_feedback(True, replace)
else:
score -= 0.5
action = "-0.5"
chatbot.user_feedback(False, replace)
if log_filename:
log_file.write("\nTest Question: "+qa_dict["questions"][0])
log_file.write("\nAgent Response: "+response)
log_file.write("\nTest Answer: "+qa_dict["response"])
log_file.write("\nTest Replace: "+replace)
log_file.write("\nAction: "+action)
log_file.write("\n")
log_file.close()
print("Score:", score)
import Chatbot
if __name__ == '__main__':
tokenTelegram = '1255840202:AAESK__tlVGY63FVPJOJufa70DLej8UfXrI'
ibm_apiKey = 'VZHzvjelK9YsjuYtBGOkXhFLhoDGruweoDcYIfKhE7hT'
ibm_url = 'https://api.us-east.assistant.watson.cloud.ibm.com/instances/1b62e879-1f7e-4e0b-9d72-5ab9c1d9328b'
ibm_assitantId = 'a8817251-2b48-47d0-a208-09f7fde9b369'
chatbot = Chatbot.Chatbot(tokenTelegram, ibm_apiKey, ibm_url,
ibm_assitantId)
def ChatbotAutograder(script_filename, faq_filename, log_filename):
print(__doc__.split('.')[0])
try:
with open(script_filename, encoding='utf-8') as json_data:
autograder_test_script_as_list_of_dicts = json.load(json_data)
except:
print("Failure opening AutograderScript json file")
return 1
try:
chatbot = Chatbot.Chatbot(faq_filename)
except FileNotFoundError:
print("Could not find FAQ.")
return 1
if log_filename:
print("Logging to file: "+log_filename)
log_file = open(log_filename, "w")
score = 0.0
total_questions = 0
total_correct = 0
total_wrong = 0
wrong_answers = []
for qa_dict in autograder_test_script_as_list_of_dicts:
response = chatbot.input_output(qa_dict["questions"][0]).split('\n')[0]
action = "0.0"
total_questions += 1
if "replace" in qa_dict:
replace = qa_dict["replace"]
else:
replace = ""
if response == qa_dict["response"]:
score += 1.0
action = "1.0"
total_correct += 1
chatbot.user_feedback(True, replace)
else:
score -= 0.5
action = "-0.5"
total_wrong += 1
chatbot.user_feedback(False, replace)
wrong_answers.append({'1_question': qa_dict["questions"][0], '2_expected_answer': qa_dict["response"],
'3_actual_answer': response.split('\n')[0]})
if log_filename:
log_file.write("\nTest Question: "+qa_dict["questions"][0])
log_file.write("\nAgent Response: "+response)
log_file.write("\nTest Answer: "+qa_dict["response"])
log_file.write("\nTest Replace: "+replace)
log_file.write("\nAction: "+action)
log_file.write("\n")
if log_filename:
# log_file = open(log_filename,"a")
log_file.write("\nScore: " + str(score))
log_file.write("\nTotal Questions: " + str(total_questions))
log_file.write("\nTotal Correct: " + str(total_correct))
log_file.write("\nTotal Wrong: " + str(total_wrong))
if total_wrong > 0:
log_file.write("\nWrong Answer Breakdown:\n")
pprint.pprint(wrong_answers, log_file)
log_file.write("\n")
log_file.close()
print("Score:", str(score))
print("Total Questions: " + str(total_questions))
print("Total Correct: " + str(total_correct))
print("Total Wrong: " + str(total_wrong))
def ChatbotAutograder(script_filename, verbose):
print(__doc__.split('.')[0])
print("Opening script: " + script_filename)
try:
with open(script_filename, encoding='utf-8') as json_data:
autograder_test_script = json.load(json_data)
except Exception as e:
print("Failure opening or reading script: " + str(e))
return 1
if 'version' in autograder_test_script:
print("Script version: " + autograder_test_script['version'])
else:
print("Version not identified")
return 1
if 'script' not in autograder_test_script:
print("Test script not identified")
return 1
if 'faq' not in autograder_test_script:
print("FAQ filename not identified")
return 1
try:
logit = Logger(autograder_test_script)
except:
print("Failed to open log file")
return 1
print("Redirecting to file: " + autograder_test_script['log'] + ".out")
try:
redirect = open(autograder_test_script['log'] + ".out", "w")
except:
print("Failed to open redirection file")
return 1
feedback = False
if autograder_test_script['feedback'] == 'on':
feedback = True
regrade_list_of_dicts = []
print("Opening FAQ: " + autograder_test_script['faq'])
print("Instantiating Chatbot")
try:
chatbot = Chatbot.Chatbot(autograder_test_script['faq'])
except FileNotFoundError:
print("Could not find FAQ.")
return 1
try:
grader = Grader()
print("Running script")
for qa_dict in autograder_test_script['script']:
question = qa_dict['questions'][0]
with redirect_stdout(redirect):
agent_response = chatbot.input_output(question).split('\n')[0]
try:
feedback_to_agent = grader.grade(agent_response,
qa_dict['type'],
qa_dict['response'])
except ValueError as e:
print("Grader Error: {0}".format(e))
logit.logmsg("Grader Error: {0}".format(e))
raise
if not verbose:
if feedback_to_agent:
print('+', end='')
else:
print('-', end='')
if len(qa_dict['questions']
) > 1 and feedback and not feedback_to_agent:
qa_dict_copy = qa_dict.copy()
qa_dict_copy['type'] = '2nd'
regrade_list_of_dicts.append(qa_dict_copy)
if verbose: print("Added to re-ask")
if 'replace' in qa_dict:
replace = qa_dict['replace']
else:
replace = ""
if feedback:
with redirect_stdout(redirect):
chatbot.user_feedback(feedback_to_agent, replace)
logmsg = logit.logformat(replace, qa_dict['type'], question,
agent_response, qa_dict['response'],
grader.result_string(feedback))
logit.logmsg(logmsg)
if verbose: print(logmsg)
if not verbose: print('|', end='')
# Ask questions in regrade_list_of_dicts again
for qa_dict in regrade_list_of_dicts:
question = qa_dict['questions'][1]
with redirect_stdout(redirect):
agent_response = chatbot.input_output(question).split('\n')[0]
try:
feedback_to_agent = grader.grade(agent_response,
qa_dict['type'],
qa_dict['response'])
except ValueError as e:
print("Grader Error: {0}".format(e))
raise
if not verbose:
if feedback_to_agent:
print('+', end='')
else:
print('-', end='')
logmsg = logit.logformat("", qa_dict['type'], question,
agent_response, qa_dict['response'],
grader.result_string(feedback))
logit.logmsg(logmsg)
if verbose: print(logmsg)
logit.logmsg("\n\n\nScript version: " +
autograder_test_script['version'])
logit.logmsg("\nFAQ: " + autograder_test_script['faq'])
if feedback:
logit.logmsg("\nFeedback: ON")
logit.logmsg("\n" + grader.header_string(feedback))
logit.logmsg("\nResult: " + grader.result_string(feedback))
print("\n\nResults")
print(grader.header_string(feedback))
print(grader.result_string(feedback))
except Exception as e:
logit.logmsg("Error during grading: " + str(e))
print("Error during grading: " + str(e))
print(traceback.print_exc(file=sys.stdout))
finally:
logit.logclose()
return 1
# -*- coding: utf-8 -*-
"""
Inicio de chatbot
Primeiramente deve ler o nome e reconhecer o nome da pessoa
"""
"""
Imports
"""
from Chatbot import * # Separação das funcões principais do chatbot
from chat_funcoes import *
"""
Globais
"""
chatbot = Chatbot("Teste")
"""
##########
"""
def main():
while True:
frase = normalizar_frase(chatbot.escutar())
resposta = chatbot.pensar(frase)
if (frase == "sair"):
break
else:
chatbot.fala(resposta)
pass
pass
print("Até mais %s" % (chatbot.nome_pessoa))
def ChatbotAutograder(ScriptFilename, FAQFilename, LogFilename):
print(__doc__.split('.')[0])
try:
with open(ScriptFilename, "r", encoding="utf-8") as f:
scriptFileasList = f.readlines()
except FileNotFoundError:
print("Could not find script.")
return 1
try:
chatbot = Chatbot.Chatbot(FAQFilename)
except FileNotFoundError:
print("Could not find FAQ.")
return 1
if LogFilename:
print("Loggin to file: " + LogFilename)
logFile = open(LogFilename, "a")
score = 0.0
total_questions = 0
total_correct = 0
total_skipped = 0
total_meant_to_skip = 0
total_correctly_skipped = 0
total_wrong = 0
wrong_answers = []
for qa in scriptFileasList:
question = qa.split('?')[0]
answer = qa.split('?')[1] #.strip()
# We open and close the file to avoid loosing data if we crash
if LogFilename:
logFile = open(LogFilename, "a")
Type, response = chatbot.InputOutput(question)
action = "0.0"
total_questions += 1
if Type == True:
if answer.split('\n')[0] == "I do not know.":
total_meant_to_skip += 1
score -= 0.1
action = "-0.1"
total_wrong += 1
wrong_answers.append({
'1_question': question,
'2_expected_answer': answer.split('\n')[0],
'3_actual_answer': response.split('\n')[0]
})
chatbot.UserFeedback("no")
elif response.split('\n')[0] == answer.split('\n')[0]:
score += 1.0
action = "1.0"
total_correct += 1
chatbot.UserFeedback("yes")
else:
score -= 0.1
action = "-0.1"
total_wrong += 1
wrong_answers.append({
'1_question': question,
'2_expected_answer': answer.split('\n')[0],
'3_actual_answer': response.split('\n')[0]
})
chatbot.UserFeedback("no")
else:
if not question.startswith("Who are you"):
if answer.split('\n')[0] == "I do not know.":
total_meant_to_skip += 1
if response.split('\n')[0] == answer.split('\n')[0]:
total_correctly_skipped += 1
else:
wrong_answers.append({
'1_question':
question,
'2_expected_answer':
answer.split('\n')[0],
'3_actual_answer':
response.split('\n')[0]
})
total_skipped += 1
if LogFilename:
logFile.write("\nInput: " + question)
logFile.write("\nResponse: " + response)
logFile.write("\nCorrect: " + answer)
logFile.write("\nType: " + str(Type))
logFile.write("\nAction: " + action)
logFile.write("\n")
logFile.close()
print()
print("Response: " + response)
if not Type: print()
print()
if LogFilename:
logFile = open(LogFilename, "a")
logFile.write("\nScore: " + str(score))
logFile.write("\nTotal Questions: " + str(total_questions))
logFile.write("\nTotal Correct: " + str(total_correct))
logFile.write("\nTotal Skipped: " + str(total_skipped))
logFile.write("\nTotal Meant to Skip: " + str(total_meant_to_skip))
logFile.write("\nTotal Correctly Skipped: " +
str(total_correctly_skipped))
logFile.write("\nTotal Wrong: " + str(total_wrong))
if total_wrong > 0:
logFile.write("\nWrong Answer Breakdown:\n")
pprint.pprint(wrong_answers, logFile)
logFile.write("\n")
logFile.close()
print("Score:", str(score))
print("Total Questions: " + str(total_questions))
print("Total Correct: " + str(total_correct))
print("Total Skipped: " + str(total_skipped))
print("Total Meant to Skip: " + str(total_meant_to_skip))
print("Total Correctly Skipped: " + str(total_correctly_skipped))
print("Total Wrong: " + str(total_wrong))
if total_wrong > 0:
print("(Wrong Answer Breakdown in logfile)")
print("\n")
secondSymptom.addCat("Throat")
secondSymptom.addSeverity(4)
# Creating first patient
patient1 = patient("Bob", 29, "Male")
# Adding symptom objects to Patient
patient1.addSymptom(first)
patient1.addSymptom(secondSymptom)
# Get patient info(Auto prints)
patient1.patientInfo()
# Creating Second Patient
patient2 = patient("Joe", 29, "Male")
# Adding symptom object to patient
patient2.addSymptom(first)
# Creating third Symptom
third = Symptom("Fatigue")
third.addCat("neurological")
third.addSeverity(10)
# Adding symptom to patient
patient2.addSymptom(third)
# Get patient info(Auto prints)
patient2.patientInfo()
print()
# Start Chatbot
chatbot1 = Chatbot()
chatbot1.startChat()
