def start_training() -> NoReturn:
"""Starts interactive learning session.
Starts interactive learning using command, `rasa interactive`.
Note: It will use the default Charlotte model,
`./models/charlotte.tar.gz` for training. Training will be skipped
if the training data and config have not changed.
"""
# You can find the reference code here:
# https://rasa.com/docs/rasa/user-guide/command-line-interface/
try:
# Checks if `charlotte.tar.gz` exists.
# Story visualization is disabled as a personal preference. You
# can enable it by removing `--skip-visualization` from the
# below code.
if model_check(ai_lower):
charlotte = model_check(ai_lower)
ep = ai_file['endpoints']
call(f'rasa interactive --model {charlotte} --skip-visualization '
f'--endpoints {ep} --e2e --dump-stories')
else:
# Similar to `test_nlu` function, it renders the model if it
# does not exist.
option = confirm(
f'Sorry {lower}, I could not find NLU model in "./models/" '
f'directory. Shall I create one now?')
if option is True:
render_model()
else:
show('Model not created.')
except Exception as error:
print('An error occured while performing this operation because of'
f' {error} in function "{stack()[0][3]}" on line'
f' {exc_info()[-1].tb_lineno}.')
def test_nlu() -> NoReturn:
"""Tests NLU model.
Runs NLU test session for testing the model. This function predicts
the intent of given statement and extracts the entities if present
in it.
Note: It will use the default Charlotte model,
`./models/charlotte.tar.gz` for testing.
"""
# You can find the reference code here:
# https://rasa.com/docs/rasa/user-guide/command-line-interface/
try:
# Checks if `charlotte.tar.gz` exists.
if model_check(ai_lower):
charlotte = model_check(ai_lower)
call(f'rasa shell nlu model-as-positional-argument "{charlotte}"')
else:
# Renders the model if it does not exist.
option = confirm(
f'Sorry {lower}, I could not find NLU model in "./models/" '
f'directory. Shall I create one now?')
if option is True:
render_model()
else:
show('Model not created.')
except Exception as error:
print('An error occured while performing this operation because of'
f' {error} in function "{stack()[0][3]}" on line'
f' {exc_info()[-1].tb_lineno}.')
def quit() -> NoReturn:
"""Terminates the code with a confirmation."""
from sys import exit
try:
option = confirm('Are you sure you want to leave?')
if option is True:
exit()
except Exception as error:
print('An error occured while performing this operation because of'
f' {error} in function "{stack()[0][3]}" on line'
f' {exc_info()[-1].tb_lineno}.')
def render_model() -> NoReturn:
"""Renders model.
Creates models using your NLU data and stories. The function renders
model by overwriting the previous model (if model has same name).
Note: This function trains a Rasa model that combines Rasa NLU and
Core models. If you only want to choose specific model, you can use
this function to do so.
"""
# You can find the reference code here:
# https://rasa.com/docs/rasa/user-guide/command-line-interface/
try:
# Asks which model to render.
type = choose(choice(cmdline_options['choose_model']),
nlu='NLU',
core='Core',
both='Both')
# Builds domain file with the my details.
_build_domain()
make_dir(ai_dir['models'])
rename = confirm(choice(cmdline_options['rename_model']))
# If the model is to be renamed, it will take input and render
# that model. Else, it will use `charlotte` as the default name.
if rename is True:
name = answer(f'{title}, what would you like to call it?').lower()
else:
name = ai_lower
show('This will overwrite the existing main model.')
# Appending model type to the name.
if type == 'nlu':
model = f'{type} --fixed-model-name "{name}_nlu"'
call(f'rasa train {model}')
elif type == 'core':
model = f'{type} --fixed-model-name "{name}_core"'
call(f'rasa train {model} --force --debug-plots --dump-stories')
else:
model = f'--fixed-model-name "{name}"'
call(f'rasa train {model} --force --debug-plots --dump-stories')
except Exception as error:
print('An error occured while performing this operation because of'
f' {error} in function "{stack()[0][3]}" on line'
f' {exc_info()[-1].tb_lineno}.')
clear_screen='Clear screen',
exit='Exit')
if option is 'render_model':
render_model()
elif option is 'start_training':
start_training()
elif option is 'evaluate_model':
evaluate_model()
elif option is 'test_nlu':
test_nlu()
elif option is 'get_nlu_stats':
get_nlu_stats()
elif option is 'start_action_server':
call(f'rasa run actions -p {ACTION_SERVER_PORT}', shell=True)
elif option is 'user_command':
option = confirm(choice(cmdline_options['user_command']))
if option is True:
call(answer(choice(cmdline_options['terminal_set'])),
shell=True)
elif option is 'clear_screen':
option = confirm(choice(cmdline_options['clear_screen']))
if option is True:
call('cls', shell=True)
elif option is 'exit':
option = confirm(choice(cmdline_options['confirm_quit']))
if option is True:
exit()
except Exception as error:
print('An error occurred while performing this operation because of'
f' {error} in function "{stack()[0][3]}" on line'
f' {exc_info()[-1].tb_lineno}.')
'this session.'
# Code starts here:
# Checks if all the necessary environment variables are present or not.
try:
if all([
os.environ.get(_MASTER_KEY),
os.environ.get(_ALIAS),
os.environ.get(_USERNAME),
os.environ.get(_MOBILE),
os.environ.get(_HOTWORD)
]) is False:
show('Key check failed! Creating user profile.')
# If no master key is detected.
if os.environ.get(_MASTER_KEY) is None:
start = confirm(_INITIAL_SETUP)
if start is False:
show(_PROFILE_SKIPPED)
exit()
else:
warning = confirm(_RESTART_REQUIRED)
if warning is True:
if os.environ.get(_MASTER_KEY) is None:
show(_TIP_1)
key = keygen(_MASTER_KEY,
secure(_GIVE_PASSWORD),
return_key=True)
else:
show(_PROFILE_SKIPPED)
exit()
else: