def train_classificator():
trainer = Trainer(RasaNLUConfig(CONF.get_value('nlu-config-file-path')))
training_data = load_data(CONF.get_value('nlu-training-data-path'))
trainer.train(training_data)
trainer.persist(
CONF.get_value('models-directory'),
fixed_model_name=CONF.get_value('classification-model-name'))
def _auth(*args, **kw):
event = request.get_json()
logger.debug("received %s", event)
logger.debug("configuratioon token: %s",
CONF.get_value("hangouts-api-key"))
if event.get('token') != CONF.get_value("hangouts-api-key"):
return get_error_response('Wrong token', 401)
return func(*args, **kw)
def get_leave_entitlement(employee, year):
request_body = {
'employeeId': employee.get('employeeId'),
'year': year,
'homeOffice': employee.get('homeOffice').get('name')
}
jwt_token = jwt.encode(request_body,
CONF.get_value('leave-api-key'),
algorithm='HS256')
return requests.get(
CONF.get_value('leave-api-url') + 'leave-entitlement',
headers={'Authorization': 'Bearer %s' % jwt_token.decode("utf-8")})
def background_task():
while 1:
logger.debug("loading agent ...")
dialog.get_agent()
interval = int(CONF.get_value('warming-up-agent-interval'))
time.sleep(interval)
def get_leaves(employee_id, start_date=None):
url = BASE_API_URL + 'leave?employee_ids=' + employee_id
if start_date:
url += '&start_date=' + start_date
return requests.get(
url, headers={'Authorization': CONF.get_value('backend-api-token')})
def post_leave(leave):
url = BASE_API_URL + 'leave'
response = requests.post(
url,
json=leave,
headers={'Authorization': CONF.get_value('backend-api-token')})
return response.status_code == 201
def run():
output_file = "/tmp/graph.png"
stories_file = CONF.get_value('stories-file')
agent = dialog.get_agent()
agent.visualize(stories_file, output_file=output_file, max_history=2)
print("File generated: {}".format(output_file))
def send_bot_message(msg, sender_id=None):
logger.debug('Send bot message to chatbase msg=%s sender_id=%s', msg,
sender_id)
_add_message(
Message(
api_key=CONF.get_value('chatbase-api-key'),
message=msg,
type='agent',
platform='chatbot',
user_id=sender_id,
))
def send_not_handled_message(msg, sender_id=None):
logger.debug('Send not handled message to chatbase msg=%s sender_id=%s',
msg, sender_id)
_add_message(
Message(
api_key=CONF.get_value('chatbase-api-key'),
message=msg,
user_id=sender_id,
type='user',
platform='chatbot',
not_handled=True,
))
def send_user_message(msg, intent, sender_id):
logger.debug('Send user message to chatbase msg=%s intent=%s sender_id=%s',
msg, intent, sender_id)
_add_message(
Message(
api_key=CONF.get_value('chatbase-api-key'),
message=msg,
type='user',
platform='chatbot',
intent=intent,
user_id=sender_id,
))
def background_task():
interval = int(CONF.get_value('analytics-send-period'))
while 1:
logger.debug(
"send a batch of %d messages to chatbase and then sleep for %ds",
len(_MESSAGES.messages), interval)
with _MESSAGES_LOCK:
if _MESSAGES.messages:
response = _MESSAGES.send()
logger.debug("chatbat returned %s -> %s",
response.status_code, response.content)
_MESSAGES.messages = []
time.sleep(interval)
def train_dialog_online(classificator, input_channel):
agent = Agent(CONF.get_value('domain-file'),
policies=[MemoizationPolicy(),
KerasPolicy()],
interpreter=classificator)
agent.train_online(CONF.get_value('stories-file'),
input_channel=input_channel,
max_history=CONF.get_value('dialog-model-max-history'),
batch_size=CONF.get_value('dialog-model-batch-size'),
epochs=CONF.get_value('dialog-model-epochs'),
max_training_samples=CONF.get_value(
'dialog-model-max-training-samples'))
return agent
def get_employee(email):
url = BASE_API_URL + 'people/' + _login_name(email)
return requests.get(
url, headers={'Authorization': CONF.get_value('backend-api-token')})
def load_agent(classificator):
logger.info('loading context model from: %s',
CONF.get_value('dialog-model-path'))
return Agent.load(CONF.get_value('dialog-model-path'),
interpreter=classificator)
def load_classificator():
return RasaNLUInterpreter(CONF.get_value('classification-model-path'))
def _get_client():
global _CLIENT
if not _CLIENT:
_CLIENT = redis.from_url(CONF.get_value('redis-url'))
return _CLIENT
def set_employee(id, info):
info = json.dumps(info)
_get_client().set(_get_key(id), info, ex=CONF.get_value('redis-expire-time'))
#!/usr/bin/env python
import pprint
from chatbot.config import CONF
from rasa_core.interpreter import RasaNLUInterpreter
interpreter = RasaNLUInterpreter(CONF.get_value('classification-model-path'))
while 1:
text = input('Enter text: ')
pprint.pprint(interpreter.parse(text))
def test_load_config_from_file():
with _setup_environ('HANGOUTS_API_KEY', ''):
assert "secret-api-key" == CONF.get_value("hangouts-api-key")
def train_dialog():
train_dialogue_model(CONF.get_value('domain-file'),
CONF.get_value('stories-file'),
CONF.get_value('dialog-model-path'))
def test_load_config_from_environment_value():
with _setup_environ('HANGOUTS_API_KEY', 'foobar'):
assert "foobar" == CONF.get_value("hangouts-api-key")
import logging
import requests
from chatbot.backend import decorators
from chatbot.config import CONF
logger = logging.getLogger(__name__)
BASE_API_URL = CONF.get_value('backend-api-base-url')
def _login_name(email):
return email.split('@')[0]
@decorators.valid_response
def get_employee(email):
url = BASE_API_URL + 'people/' + _login_name(email)
return requests.get(
url, headers={'Authorization': CONF.get_value('backend-api-token')})
@decorators.valid_response
def get_leaves(employee_id, start_date=None):
url = BASE_API_URL + 'leave?employee_ids=' + employee_id
if start_date:
url += '&start_date=' + start_date
return requests.get(
url, headers={'Authorization': CONF.get_value('backend-api-token')})
},
},
"thread": {
"type": "object",
"required": ["name"],
"properties": {
"name": {"type": "string"},
}
}
}
}
}
}
@app.route("/" + CONF.get_value("messenger-endpoint"), methods=['POST'])
@middlewares.is_json
@middlewares.authenticate
@middlewares.validate(SCHEMA)
@middlewares.fill_session
def on_event():
"""Handles an event from Hangouts Chat."""
event = request.get_json()
if event.get('type') == 'ADDED_TO_SPACE':
logger.debug('Retrieve and send welcome text')
message = dialog.get_welcome_message(
dialog.get_agent(),
)
response = get_success_response(message)
import logging
import time
import threading
from chatbase.base_message import Message, MessageSet
from chatbot.config import CONF
logger = logging.getLogger(__name__)
_MESSAGES = MessageSet(api_key=CONF.get_value('chatbase-api-key'), )
_MESSAGES_LOCK = threading.RLock()
def _add_message(msg):
with _MESSAGES_LOCK:
_MESSAGES.append_message(msg)
def start_batch_sender():
def background_task():
interval = int(CONF.get_value('analytics-send-period'))
while 1:
logger.debug(
"send a batch of %d messages to chatbase and then sleep for %ds",
len(_MESSAGES.messages), interval)
with _MESSAGES_LOCK:
if _MESSAGES.messages:
response = _MESSAGES.send()
logger.debug("chatbat returned %s -> %s",
response.status_code, response.content)