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Diff for: ‎bot_8.py

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#!/usr/bin/
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#imports
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import sys
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import os
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import subprocess
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import time
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import random
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import pymongo
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import datetime
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import time
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import numpy
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from colors import *
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from pymongo import MongoClient
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from pprint import pprint
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from difflib import SequenceMatcher
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from fuzzywuzzy import fuzz
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#main class where all the workings happen
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class talkLoop(object):
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#initialise the class with all variables required
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def __init__(self, name, client, db, responses, allwords, inputWords, globalReply, botAccuracy, debugMode):
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self.name = name
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self.client = client
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self.db = db
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self.responses = responses
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self.allwords = allwords
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self.wordsIn = inputWords
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self.globalReply = globalReply
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self.botAccuracy = botAccuracy
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self.bResponse = globalReply
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self.debugMode = debugMode
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self.updateDB(inputWords)
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#function for comparing string similarity
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def similar(self, a, b):
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return SequenceMatcher(None, a, b).ratio()
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#function for grabbing a random document from the database
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def get_random_doc(self, collection):
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count = collection.count()
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return collection.find()[random.randrange(count)]
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#this function generates a random sentence at any length between 1 and 10 words long
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def sentenceGen(self):
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#set a clear string and set a random integer 1-10
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result = ""
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length = random.randint(1, 10)
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#for the range in the integer above find a random word from the db and append to the string
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for i in range(length):
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cursor = self.get_random_doc(self.allwords)
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for x, y in cursor.items():
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if x == "word":
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cWord = (y)
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result += cWord
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result += ' '
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#clear the cursor
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del cursor
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#return the constructed sentence
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return result
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#this function searches the database for the input string and returns all replies for that string, returning a random one
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def dbSearch(self, searchIn):
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#search the database for inputs the bot has said prior
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cursor = self.responses.find_one({"whatbotsaid": searchIn})
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#return list of human replies to this response and choose one at random
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for x, y in cursor.items():
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if x == 'humanReply':
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chosenReply = (random.choice(y))
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#erase the cursor and return the chosen string
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del cursor
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return chosenReply
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#this function returns a random sentence from the entire db
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def randomSentence(self):
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cursor = self.get_random_doc(self.responses)
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for x, y in cursor.items():
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if x == 'humanReply':
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chosenReply = (random.choice(y))
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return chosenReply
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#the string comparison function
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def mongoFuzzyMatch(self, inputString, searchZone, termZone, setting):
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#create an empty dictionary
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compareList = {}
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#search the database passed in
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for cursor in searchZone.find():
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for x, y in cursor.items():
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#find the item in the cursor that matches the search term passed into the function, eg: 'whatbotsaid'
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if x == termZone:
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#compare the input string to the current string in the cursor, which returns a decimal point of accuracy (0.0 > 1.0)
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#OLD METHOD
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#compareNo = self.similar(inputString, y)
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#if accuracy is off then append the string and its accuracy to the dictionary no matter the accuracy
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if setting == ('off'):
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compareNo = fuzz.token_set_ratio(inputString.lower(), y.lower())
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if compareNo > self.botAccuracy-30:
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compareList[y] = compareNo
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#if accuracy is medium then append the string and its accuracy to the dictionary only if its over the medium setting
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elif setting == ('med'):
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compareNo = fuzz.partial_ratio(inputString.lower(), y.lower())
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if compareNo > self.botAccuracy-20:
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compareList[y] = compareNo
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#if accuracy is on/high then append the string and its accuracy to the dictionary only if its over the on/high setting
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elif setting == ('on'):
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compareNo = fuzz.ratio(inputString.lower(), y.lower())
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if compareNo > self.botAccuracy:
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compareList[y] = compareNo
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#if nothing found then return a non match
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if compareList == {}:
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compareChosen = 'none_match'
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#if there are matching strings identify the highest accuracy from the dictionary made above
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else:
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compareChosen = max(compareList.keys(), key=(lambda key: compareList[key]))
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#erase the cursor and return the chosen matching string
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del cursor
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if (self.debugMode == True):
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print(compareChosen)
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return compareChosen
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def replyTumbler(self):
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if self.name == ("--trainer--"):
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self.bResponse = self.wordsIn
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return ("")
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#find the search string using the high accuracy number - to find a decent match to what the bot has said prior
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#when this function is called it required four arguments: the human response, the database to search on, the response required from the database and the accuracy level
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searchSaid = self.mongoFuzzyMatch(self.wordsIn, self.responses, 'whatbotsaid', 'on')
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#if no matches then try with a lower accuracy to find a less similar sentence
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if searchSaid == ('none_match'):
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searchSaid = self.mongoFuzzyMatch(self.wordsIn, self.responses, 'whatbotsaid', 'med')
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if searchSaid == ('none_match'):
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searchSaid = self.mongoFuzzyMatch(self.wordsIn, self.responses, 'whatbotsaid', 'off')
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if searchSaid == ('none_match'):
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#if still no match then move onto generating a totally random reply or grab a random sentence from the db
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if searchSaid == ('none_match'):
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if random.randrange(100) <= 60:
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chosenReply = self.randomSentence()
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self.bResponse = chosenReply
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return (chosenReply)
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else:
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chosenReply = self.sentenceGen()
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self.bResponse = chosenReply
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return (chosenReply)
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else:
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#pass the response into the database to find prior human responses to the above sentence
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chosenReply = self.dbSearch(searchSaid)
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#pass the response into the database to find prior human responses to the above sentence
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chosenReply = self.dbSearch(searchSaid)
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#clear the search variable
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del searchSaid
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self.bResponse = chosenReply
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return (chosenReply)
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#this function passes in the information from the loop, the input reply and the bots last reply and appends them to the database
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def updateDB(self, wordsIn):
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self.wordsIn = wordsIn
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#search the database for prior responses the bot has said
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cursor = self.responses.find_one({"whatbotsaid": self.bResponse})
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#if none then store a new bot response with the humans reply
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if cursor is None:
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postR = {"whatbotsaid": self.bResponse, "humanReply": [self.wordsIn]}
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self.responses.insert_one(postR).inserted_id
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del cursor
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#if already existing then update the database with a new reply
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else:
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self.responses.update_one({"whatbotsaid": self.bResponse}, {'$addToSet':{"humanReply": self.wordsIn}}, upsert=True)
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#clear the cursor
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del cursor
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#split the input sentence into individual words and store each in the database
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wordsInDB = self.wordsIn.split(' ')
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for word in wordsInDB:
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#search the database for the word
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cursor = self.allwords.find_one({"word": word})
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#if its not already in the database then insert into the database
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if cursor is None:
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postW = {"word": word}
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self.allwords.insert_one(postW).inserted_id
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#if the word is already in the database pass and clear the cursor
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else:
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pass
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del cursor
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def dbWordsUpdate(objectIn):
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#split the input sentence into individual words and store each in the database
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wordsInDB = objectIn.split(' ')
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for word in wordsInDB:
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#search the database for the word
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cursor = allwords.find_one({"word": word})
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#if its not already in the database then insert into the database
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if cursor is None:
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postW = {"word": word}
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allwords.insert_one(postW).inserted_id
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#if the word is already in the database pass and clear the cursor
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else:
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pass
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del cursor
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def conversation(inputWords, personName):
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#if person name is already initialised as a class with talk loop then check if its the same as the previous person from last response
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if personName in name_dict:
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if personName == prevPerson["prev_person"]:
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#if it is still the same person chatbot talking to put their response in and get a reply from the bot
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name_dict[personName].updateDB(inputWords)
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globalReply = (name_dict[personName].replyTumbler())
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else:
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#if it is a different person from before then get a reponse from the bot using the humans prior response - to continue the conversation
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globalReply = (name_dict[personName].replyTumbler())
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else:
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#if human new then initialise them with the talk loop class
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name_dict.update({personName: talkLoop(name=personName, client=client, db=db, responses=responses, allwords=allwords, inputWords="hello", globalReply="hello", botAccuracy=botAccuracy, debugMode=debugMode)})
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#get an intial reply
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globalReply = (name_dict[personName].replyTumbler())
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#combine the greeting with the humans name
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globalReply = str(globalReply + " " + personName)
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#set previous person
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prevPerson["prev_person"] = personName
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#return the reply
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return globalReply
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#setting up variables for mongodb
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client = MongoClient('localhost', 27017)
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db = client.words_database
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responses = db.responses
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allwords = db.allwords
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#accuracy variable (percentage)
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botAccuracy = 95
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debugMode = False
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#blank variables
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name_dict = {}
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prevPerson = {"prev_person": ""}
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#if called direct then run the function
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if __name__ == '__main__':
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if len(sys.argv) > 1:
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try:
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sys.argv[1] = int(sys.argv[1])
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except ValueError:
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print ('There are two optional switches: accuracy <0-100> and <-debug>')
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sys.exit()
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botAccuracy = sys.argv[1]
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if len(sys.argv) > 2:
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try:
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sys.argv[2] = str(sys.argv[2])
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except ValueError:
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print ('There are two optional switches: accuracy <0-100> and <-debug>')
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sys.exit()
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if sys.argv[2] == ("-debug"):
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debugMode = True
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else:
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print ('There are two optional switches: accuracy <0-100> and <-debug>')
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sys.exit()
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#request name
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sys.stdout.write(BLUE)
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name = input('Your name: ')
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sys.stdout.write(RESET)
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#get reply and print for logging/debugging
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reply = conversation(input, name)
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sys.stdout.write(RED)
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print("Bot: " + reply)
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sys.stdout.write(RESET)
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while True:
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#get another response and print
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sys.stdout.write(BLUE)
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input = input('You: ')
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sys.stdout.write(RESET)#
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#if response is blank, rerun loop
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if input == (""):
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continue
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#with 'change_name' typed in it will request new name - for debugging and testing
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if input == ("change_name"):
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sys.stdout.write(BLUE)
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name = raw_input('Your name: ')
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sys.stdout.write(RESET)
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#get another reply
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reply = conversation(input, name)
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#print reply
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sys.stdout.write(RED)
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print("Bot: " + reply)
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sys.stdout.write(RESET)
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#rerun the loop with new name
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continue
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#for a normal response grab another reply and print
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reply = conversation(input, name)
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sys.stdout.write(RED)
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print("Bot: " + reply)
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sys.stdout.write(RESET)

Diff for: ‎bot_8_trainer.py

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import sys
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import re
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import time
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import pymongo
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from pymongo import MongoClient
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import bot_8 as b
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import deleteDB as d
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name = ("--trainer--")
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inputWords = ("hello")
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try:
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if sys.argv[1] == ("-fresh"):
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print("Clearing DB")
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d.delDB()
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except:
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print("Existing DB training")
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b.conversation(inputWords, name)
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f = open("learning.txt", "r")
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for x in f:
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if not re.search('[a-zA-Z]', x[0]):
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continue
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if (':') in x:
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try:
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x = str(x.split(": ")[1])
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except IndexError:
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continue
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print(x)
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b.conversation(x, name)
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f.close()

Diff for: ‎colors.py

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RED = "\033[1;31m"
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BLUE = "\033[1;34m"
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CYAN = "\033[1;36m"
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GREEN = "\033[0;32m"
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RESET = "\033[0;0m"
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BOLD = "\033[;1m"
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REVERSE = "\033[;7m"

Diff for: ‎deleteDB.py

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import sys
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import random
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import pymongo
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import sys
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from pymongo import MongoClient
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def delDB():
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client = MongoClient('localhost', 27017)
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db = client.words_database
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client.drop_database(db)
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if __name__ == "__main__":
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delDB()

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