def __init__(self):
self.frame = Frame()
self.condition = Condition()
self.port = 8080
self.connected = False
self.sample = ""
self.max_sockets = 1024
self.stream_id = b'12345'
self.threads = []
def make_frame(self, code, callargs={}, global_names=None, local_names=None):
"""
make frame
:rtype: object
"""
if global_names is not None and local_names is not None:
local_names = global_names
elif self.frames:
global_names = self.current_frame.global_names
local_names = {}
else:
global_names = local_names = {
'__builtins__': __builtins__,
'__name__': '__main__',
'__doc__': None,
'__package__': None,
}
local_names.update(callargs)
frame = Frame(code, global_names, local_names, self.current_frame)
return frame
def __init__(self):
super().__init__()
self.setMenuBar(QMenuBar())
self.deploy_files_action = QAction(QIcon('resources/deploy.png'), "Deploy selected", self)
self.backup_files_action = QAction(QIcon('resources/backup.png'), "Backup selected", self)
self.settings_action = QAction(QIcon('resources/settings.png'), "Settings", self)
self.exit_action = QAction(QIcon('resources/exit.png'), "Exit", self)
self.deploy_files_action.connect(self.deploy_files_action, SIGNAL("triggered()"), self.deploy_files)
self.backup_files_action.connect(self.backup_files_action, SIGNAL("triggered()"), self.backup_files)
self.settings_action.connect(self.settings_action, SIGNAL("triggered()"), self.show_settings)
self.exit_action.connect(self.exit_action, SIGNAL("triggered()"), self.exit)
self.file_menu = self.menuBar().addMenu("File")
self.file_menu.addAction(self.settings_action)
self.file_menu.addAction(self.exit_action)
self.actions_menu = self.menuBar().addMenu("Actions")
self.actions_menu.addAction(self.backup_files_action)
self.actions_menu.addAction(self.deploy_files_action)
"""
##################################################
"""
# outer frame. this is the central widget for the application
self.outer_frame = Frame(QVBoxLayout(), QFrame.StyledPanel)
# inner top frame. holds list widget and tab widget
self.inner_top_frame = Frame(QHBoxLayout(), QFrame.StyledPanel)
# inner btm frame.
self.inner_btm_frame = Frame(QVBoxLayout(), QFrame.StyledPanel)
# text area
self.display_area = TextDisplay()
# status bar. shows hover actions and status
self.status_bar = QStatusBar()
self.setStatusBar(self.status_bar)
self.status_bar.showMessage("Status Bar Message...")
# tab widget. holds description and powershell tabs. they both have text boxes inside to display text
self.tab_container = TabContainer()
tabs = (Tab("Description", TextDisplay(), QVBoxLayout()),
Tab("Powershell", TextDisplay(), QVBoxLayout()))
self.tab_container.set_tabs(tabs)
# list widget. holds selectable items
self.list_widget = ListWidget()
self.list_items = [ListItem("PXSurveyAPI"),
ListItem("PXWeb"),
ListItem("PXReporting"),
ListItem("PXNotification"),
ListItem("SampleUI"),
ListItem("SampleEngine"),
ListItem("PXClientMGMT"),
ListItem("InsightsOnline"),
ListItem("TEST"),
ListItem("PXSurveyMGMT"),
ListItem("PXVerintSurveyACL")]
self.list_widget.add_sort_list_items(self.list_items)
self.list_widget.connect(self.list_widget, SIGNAL("itemClicked(QListWidgetItem*)"), self.selected)
# pull everything together.
self.inner_top_frame.get_layout().addWidget(self.list_widget)
self.inner_btm_frame.get_layout().addWidget(self.tab_container)
self.outer_frame.get_layout().addWidget(self.inner_top_frame)
self.outer_frame.get_layout().addWidget(self.inner_btm_frame)
self.inner_top_frame.get_layout().addWidget(self.display_area)
self.setWindowIcon(QIcon('resources\conan.png'))
self.setCentralWidget(self.outer_frame)
self.show()
"""
class Window(QMainWindow):
def __init__(self):
super().__init__()
self.setMenuBar(QMenuBar())
self.deploy_files_action = QAction(QIcon('resources/deploy.png'), "Deploy selected", self)
self.backup_files_action = QAction(QIcon('resources/backup.png'), "Backup selected", self)
self.settings_action = QAction(QIcon('resources/settings.png'), "Settings", self)
self.exit_action = QAction(QIcon('resources/exit.png'), "Exit", self)
self.deploy_files_action.connect(self.deploy_files_action, SIGNAL("triggered()"), self.deploy_files)
self.backup_files_action.connect(self.backup_files_action, SIGNAL("triggered()"), self.backup_files)
self.settings_action.connect(self.settings_action, SIGNAL("triggered()"), self.show_settings)
self.exit_action.connect(self.exit_action, SIGNAL("triggered()"), self.exit)
self.file_menu = self.menuBar().addMenu("File")
self.file_menu.addAction(self.settings_action)
self.file_menu.addAction(self.exit_action)
self.actions_menu = self.menuBar().addMenu("Actions")
self.actions_menu.addAction(self.backup_files_action)
self.actions_menu.addAction(self.deploy_files_action)
"""
##################################################
"""
# outer frame. this is the central widget for the application
self.outer_frame = Frame(QVBoxLayout(), QFrame.StyledPanel)
# inner top frame. holds list widget and tab widget
self.inner_top_frame = Frame(QHBoxLayout(), QFrame.StyledPanel)
# inner btm frame.
self.inner_btm_frame = Frame(QVBoxLayout(), QFrame.StyledPanel)
# text area
self.display_area = TextDisplay()
# status bar. shows hover actions and status
self.status_bar = QStatusBar()
self.setStatusBar(self.status_bar)
self.status_bar.showMessage("Status Bar Message...")
# tab widget. holds description and powershell tabs. they both have text boxes inside to display text
self.tab_container = TabContainer()
tabs = (Tab("Description", TextDisplay(), QVBoxLayout()),
Tab("Powershell", TextDisplay(), QVBoxLayout()))
self.tab_container.set_tabs(tabs)
# list widget. holds selectable items
self.list_widget = ListWidget()
self.list_items = [ListItem("PXSurveyAPI"),
ListItem("PXWeb"),
ListItem("PXReporting"),
ListItem("PXNotification"),
ListItem("SampleUI"),
ListItem("SampleEngine"),
ListItem("PXClientMGMT"),
ListItem("InsightsOnline"),
ListItem("TEST"),
ListItem("PXSurveyMGMT"),
ListItem("PXVerintSurveyACL")]
self.list_widget.add_sort_list_items(self.list_items)
self.list_widget.connect(self.list_widget, SIGNAL("itemClicked(QListWidgetItem*)"), self.selected)
# pull everything together.
self.inner_top_frame.get_layout().addWidget(self.list_widget)
self.inner_btm_frame.get_layout().addWidget(self.tab_container)
self.outer_frame.get_layout().addWidget(self.inner_top_frame)
self.outer_frame.get_layout().addWidget(self.inner_btm_frame)
self.inner_top_frame.get_layout().addWidget(self.display_area)
self.setWindowIcon(QIcon('resources\conan.png'))
self.setCentralWidget(self.outer_frame)
self.show()
"""
Call powershell function and pass parameters:
script_path = "c:\\users\\cherbison\\desktop\\test-function.ps1"
posh_path = "C:\\WINDOWS\\system32\\WindowsPowerShell\\v1.0\\powershell.exe"
posh2 = subprocess.call([posh_path, ". \"" + script_path + "\";", "&test-function(\" test \")"])
script call
def call_script(self, type_, btn_pushed):
posh = "C:\\WINDOWS\\system32\\WindowsPowerShell\\v1.0\\powershell.exe"
script = self.script_path + type_ + "_" + btn_pushed + ".ps1"
try:
subprocess.Popen([posh, "Start-Process", '-Verb', "runAs", posh, [script]])
except subprocess.CalledProcessError as e:
print(e.output, "There was an error.")
@staticmethod
def read_file(file_path):
file = open(file_path)
return file.read()
"""
def deploy_files(self):
self.display_area.append("deploy files clicked")
def backup_files(self):
self.display_area.append("backup files clicked")
def show_settings(self):
self.display_area.append("settings clicked")
def selected(self):
selected_item = self.list_widget.currentItem().text
self.display_area.append(selected_item + " selected")
self.display_area.ensureCursorVisible()
def exit(self):
self.display_area.append("exit clicked")
def __init__(self):
# create default personalities
cm = Character_Manager()
cm.save("character_default")
cm.save("character_stable")
cm.save("character_empathetic")
cm.save("character_irascible")
# set up logging
logging.basicConfig(
level=logging.INFO,
filename='../logs/app.log',
filemode="w",
format='%(asctime)s %(name)s/%(levelname)s - - %(message)s',
datefmt='%d.%m.%y %H:%M:%S')
self.logger = logging.getLogger("controller")
self.logger.setLevel(logging.INFO)
# read config file and save values in variables
self.config = configparser.ConfigParser()
self.config.read("../config/config.ini")
self.botname = self.config.get("default", "botname")
self.username = self.config.get("default", "username")
self.classifier_data = [
self.config.get("net", "classifier_type"),
self.config.get("net", "dataset"),
self.config.get("net", "feature_set")
]
self.logger.info("Conifg loaded: {}, {}, {}".format(
self.botname, self.username, self.classifier_data))
# initialize emotional variables
self.lex_happiness = pd.read_csv("../lexica/clean_happiness.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.lex_sadness = pd.read_csv("../lexica/clean_sadness.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.lex_anger = pd.read_csv("../lexica/clean_anger.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.lex_fear = pd.read_csv("../lexica/clean_fear.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.LIST_OF_LEXICA = self.lex_happiness, self.lex_sadness, self.lex_anger, self.lex_fear
self.list_happiness = self.lex_happiness["stems"].tolist()
self.list_sadness = self.lex_sadness["stems"].tolist()
self.list_anger = pd.Series(self.lex_anger["stems"].tolist())
self.list_fear = self.lex_fear["stems"].tolist()
self.lex_happiness_adj = pd.read_csv(
"../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.lex_sadness_adj = pd.read_csv("../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.lex_anger_adj = pd.read_csv("../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.lex_fear_adj = pd.read_csv("../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.logger.info("Lexica loaded")
# initialize ml-variables
if self.config.getboolean("default", "firstlaunch"):
# das md-model ist ca 80mb, das lg ca 1g
# self.nlp = spacy.load("en_core_web_lg")
self.nlp = spacy.load("en_core_web_md")
else:
self.nlp = spacy.load("../models/spacy")
self.spell = SpellChecker()
# create bot, responsible for generating answers and classifier, for analysing the input
self.character = Character(
self.config.getboolean("default", "firstlaunch"))
self.classifier = Classifier(self.classifier_data, self.LIST_OF_LEXICA,
self.nlp)
self.bot = Bot(self.lex_happiness, self.lex_sadness, self.lex_anger,
self.lex_fear, self.list_happiness, self.list_sadness,
self.list_anger, self.list_fear, self.lex_happiness_adj,
self.lex_sadness_adj, self.lex_anger_adj,
self.lex_fear_adj, self.nlp)
if self.config.getboolean("default", "firstlaunch"): self.bot.train()
# create frame and update widgets with initial values
self.frame = Frame(self.botname, self.character.get_emotional_state(),
self.character.get_emotional_history())
self.frame.register_subscriber(self)
self.frame.show()
# save all session data after the frame is closed
self.save_session()
logging.shutdown()
class Controller:
def __init__(self):
# create default personalities
cm = Character_Manager()
cm.save("character_default")
cm.save("character_stable")
cm.save("character_empathetic")
cm.save("character_irascible")
# set up logging
logging.basicConfig(
level=logging.INFO,
filename='../logs/app.log',
filemode="w",
format='%(asctime)s %(name)s/%(levelname)s - - %(message)s',
datefmt='%d.%m.%y %H:%M:%S')
self.logger = logging.getLogger("controller")
self.logger.setLevel(logging.INFO)
# read config file and save values in variables
self.config = configparser.ConfigParser()
self.config.read("../config/config.ini")
self.botname = self.config.get("default", "botname")
self.username = self.config.get("default", "username")
self.classifier_data = [
self.config.get("net", "classifier_type"),
self.config.get("net", "dataset"),
self.config.get("net", "feature_set")
]
self.logger.info("Conifg loaded: {}, {}, {}".format(
self.botname, self.username, self.classifier_data))
# initialize emotional variables
self.lex_happiness = pd.read_csv("../lexica/clean_happiness.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.lex_sadness = pd.read_csv("../lexica/clean_sadness.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.lex_anger = pd.read_csv("../lexica/clean_anger.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.lex_fear = pd.read_csv("../lexica/clean_fear.csv",
delimiter=",",
dtype={
"text": str,
"affect": str,
"stems": str
},
float_precision='round_trip')
self.LIST_OF_LEXICA = self.lex_happiness, self.lex_sadness, self.lex_anger, self.lex_fear
self.list_happiness = self.lex_happiness["stems"].tolist()
self.list_sadness = self.lex_sadness["stems"].tolist()
self.list_anger = pd.Series(self.lex_anger["stems"].tolist())
self.list_fear = self.lex_fear["stems"].tolist()
self.lex_happiness_adj = pd.read_csv(
"../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.lex_sadness_adj = pd.read_csv("../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.lex_anger_adj = pd.read_csv("../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.lex_fear_adj = pd.read_csv("../lexica/clean_happiness_adj.csv",
delimiter=",",
dtype={
"text": str,
"intensity": float
},
float_precision='round_trip')
self.logger.info("Lexica loaded")
# initialize ml-variables
if self.config.getboolean("default", "firstlaunch"):
# das md-model ist ca 80mb, das lg ca 1g
# self.nlp = spacy.load("en_core_web_lg")
self.nlp = spacy.load("en_core_web_md")
else:
self.nlp = spacy.load("../models/spacy")
self.spell = SpellChecker()
# create bot, responsible for generating answers and classifier, for analysing the input
self.character = Character(
self.config.getboolean("default", "firstlaunch"))
self.classifier = Classifier(self.classifier_data, self.LIST_OF_LEXICA,
self.nlp)
self.bot = Bot(self.lex_happiness, self.lex_sadness, self.lex_anger,
self.lex_fear, self.list_happiness, self.list_sadness,
self.list_anger, self.list_fear, self.lex_happiness_adj,
self.lex_sadness_adj, self.lex_anger_adj,
self.lex_fear_adj, self.nlp)
if self.config.getboolean("default", "firstlaunch"): self.bot.train()
# create frame and update widgets with initial values
self.frame = Frame(self.botname, self.character.get_emotional_state(),
self.character.get_emotional_history())
self.frame.register_subscriber(self)
self.frame.show()
# save all session data after the frame is closed
self.save_session()
logging.shutdown()
# takes the users intent (per gui interaction) and starts the corresponding methods
def handle_intent(self,
intent,
input_message=None,
character=None,
classifier_type=None,
dataset=None,
feature_set=None):
if intent == "load_character":
self.character.load(character)
self.frame.update_diagrams(self.character.get_emotional_state(),
self.character.get_emotional_history())
self.frame.update_log(
[{
"character ready": self.character.character_name
}],
clear=True)
elif intent == "get_response":
if input_message and input_message != "":
self.handle_input(input_message)
elif intent == "retrain_bot":
self.bot.train()
self.frame.update_log(["chatbot training completed"], clear=True)
elif intent == "reset_state":
self.character.reset_bot()
self.frame.update_diagrams(self.character.get_emotional_state(),
self.character.get_emotional_history())
self.frame.update_log(["chatbot internal state reset"], clear=True)
elif intent == "change_classifier":
self.classifier_data = [classifier_type, dataset, feature_set]
self.classifier.load_network(self.classifier_data)
self.frame.update_log([{
"classifier ready": self.classifier_data
}],
clear=True)
self.logger.info("classifier loaded: {}".format(" ".join(
self.classifier_data)))
# take user input, generate new data an update ui
def handle_input(self, user_input):
# user_input = self.correct_input(user_input)
# update all modules
response_package = self.bot.respond(user_input)
ml_package = self.classifier.get_emotions(user_input)
state_package = self.character.update_emotional_state(
ml_package.get("input_emotions"))
response_package = self.bot.modify_output(
response_package, state_package["highest_emotion"],
state_package["highest_score"])
# update gui
self.frame.update_chat_out(user_input,
response_package.get("response").__str__(),
self.botname, self.username)
self.frame.update_log([{
"classifier": " ".join(self.classifier_data),
"character": self.character.character_name
}, ml_package, state_package])
self.frame.update_diagrams(state_package.get("emotional_state"),
state_package.get("emotional_history"))
# corrects user input
def correct_input(self, user_input):
# make list of all words
words = user_input.split(" ")
unknown_words = self.spell.unknown(words)
# replace all unknown words
for word in unknown_words:
print("correction: ", word, self.spell.correction(word))
user_input = user_input.replace(word, self.spell.correction(word))
return user_input
# handles saving data when closing the program
def save_session(self):
# saves current character state
self.character.save()
# set the first launch variable to false
self.config.set("default", "firstlaunch", "NO")
self.config.set("net", "classifier_type", self.classifier_data[0])
self.config.set("net", "dataset", self.classifier_data[1])
self.config.set("net", "feature_set", self.classifier_data[2])
# save nlp model
print("saving spacy")
self.nlp.to_disk("../models/spacy")
# save new value in file
with open("../config/config.ini", "w") as f:
self.config.write(f)
self.logger.info(f"Session saved - end program")
