async def load_agent_on_start(core_model, endpoints, nlu_model, app, loop):
"""Load an agent.
Used to be scheduled on server start
(hence the `app` and `loop` arguments)."""
from rasa_core import broker
from rasa_core.agent import Agent
_interpreter = NaturalLanguageInterpreter.create(nlu_model, endpoints.nlu)
_broker = broker.from_endpoint_config(endpoints.event_broker)
_tracker_store = TrackerStore.find_tracker_store(None,
endpoints.tracker_store,
_broker)
if endpoints and endpoints.model:
from rasa_core import agent
app.agent = Agent(interpreter=_interpreter,
generator=endpoints.nlg,
tracker_store=_tracker_store,
action_endpoint=endpoints.action)
await agent.load_from_server(app.agent, model_server=endpoints.model)
else:
app.agent = Agent.load(core_model,
interpreter=_interpreter,
generator=endpoints.nlg,
tracker_store=_tracker_store,
action_endpoint=endpoints.action)
return app.agent
def create_agent(model: Text, endpoints: Text = None) -> 'Agent':
from rasa_core.interpreter import RasaNLUInterpreter
from rasa_core.tracker_store import TrackerStore
from rasa_core import broker
from rasa_core.utils import AvailableEndpoints
core_path, nlu_path = get_model_subdirectories(model)
_endpoints = AvailableEndpoints.read_endpoints(endpoints)
_interpreter = None
if os.path.exists(nlu_path):
_interpreter = RasaNLUInterpreter(model_directory=nlu_path)
else:
_interpreter = None
logging.info("No NLU model found. Running without NLU.")
_broker = broker.from_endpoint_config(_endpoints.event_broker)
_tracker_store = TrackerStore.find_tracker_store(None,
_endpoints.tracker_store,
_broker)
return Agent.load(core_path,
generator=_endpoints.nlg,
tracker_store=_tracker_store,
action_endpoint=_endpoints.action)
def test_file_broker_from_config():
cfg = utils.read_endpoint_config(
"data/test_endpoints/event_brokers/"
"file_endpoint.yml", "event_broker")
actual = broker.from_endpoint_config(cfg)
assert isinstance(actual, FileProducer)
assert actual.path == "rasa_event.log"
def test_pika_broker_from_config():
cfg = utils.read_endpoint_config(
'data/test_endpoints/event_brokers/'
'pika_endpoint.yml', "event_broker")
actual = broker.from_endpoint_config(cfg)
assert isinstance(actual, PikaProducer)
assert actual.host == "localhost"
assert actual.credentials.username == "username"
assert actual.queue == "queue"
def test_file_broker_logs_to_file(tmpdir):
fname = tmpdir.join("events.log").strpath
actual = broker.from_endpoint_config(
EndpointConfig(**{
"type": "file",
"path": fname
}))
for e in TEST_EVENTS:
actual.publish(e.as_dict())
# reading the events from the file one event per line
recovered = []
with open(fname, "r") as f:
for l in f:
recovered.append(Event.from_parameters(json.loads(l)))
assert recovered == TEST_EVENTS
def test_file_broker_properly_logs_newlines(tmpdir):
fname = tmpdir.join("events.log").strpath
actual = broker.from_endpoint_config(
EndpointConfig(**{
"type": "file",
"path": fname
}))
event_with_newline = UserUttered("hello \n there")
actual.publish(event_with_newline.as_dict())
# reading the events from the file one event per line
recovered = []
with open(fname, "r") as f:
for l in f:
recovered.append(Event.from_parameters(json.loads(l)))
assert recovered == [event_with_newline]
def do_interactive_learning(cmdline_args, stories, additional_arguments=None):
_endpoints = AvailableEndpoints.read_endpoints(cmdline_args.endpoints)
_interpreter = NaturalLanguageInterpreter.create(cmdline_args.nlu,
_endpoints.nlu)
from rasa_core.agent import Agent
from rasa_core.training import interactive
if cmdline_args.core:
if cmdline_args.finetune:
raise ValueError("--core can only be used without "
"--finetune flag.")
logger.info("Loading a pre-trained model. This means that "
"all training-related parameters will be ignored.")
_broker = broker.from_endpoint_config(_endpoints.event_broker)
_tracker_store = TrackerStore.find_tracker_store(
None, _endpoints.tracker_store, _broker)
_agent = Agent.load(cmdline_args.core,
interpreter=_interpreter,
generator=_endpoints.nlg,
tracker_store=_tracker_store,
action_endpoint=_endpoints.action)
else:
if cmdline_args.out:
model_directory = cmdline_args.out
else:
model_directory = tempfile.mkdtemp(suffix="_core_model")
_agent = train(cmdline_args.domain, stories, model_directory,
_interpreter, _endpoints, cmdline_args.dump_stories,
cmdline_args.config[0], None, additional_arguments)
interactive.run_interactive_learning(
_agent,
stories,
finetune=cmdline_args.finetune,
skip_visualization=cmdline_args.skip_visualization)
def start_core(platform_token):
from rasa_core.utils import AvailableEndpoints
_endpoints = AvailableEndpoints(
# TODO: make endpoints more configurable, esp ports
model=EndpointConfig(
"http://localhost:5002"
"/api/projects/default/models/tags/production",
token=platform_token,
wait_time_between_pulls=1),
event_broker=EndpointConfig(**{"type": "file"}),
nlg=EndpointConfig("http://localhost:5002"
"/api/nlg",
token=platform_token))
from rasa_core import broker
_broker = broker.from_endpoint_config(_endpoints.event_broker)
from rasa_core.tracker_store import TrackerStore
_tracker_store = TrackerStore.find_tracker_store(None,
_endpoints.tracker_store,
_broker)
from rasa_core.run import load_agent
_agent = load_agent("models",
interpreter=None,
tracker_store=_tracker_store,
endpoints=_endpoints)
from rasa_core.run import serve_application
print_success("About to start core")
serve_application(
_agent,
"rasa",
5005,
"credentials.yml",
"*",
None, # TODO: configure auth token
True)
def test_load_non_existent_custom_broker_name():
config = EndpointConfig(**{"type": "rasa_core.broker.MyProducer"})
assert broker.from_endpoint_config(config) is None
def test_load_custom_broker_name():
config = EndpointConfig(**{"type": "rasa_core.broker.FileProducer"})
assert broker.from_endpoint_config(config)
def test_no_broker_in_config():
cfg = utils.read_endpoint_config(DEFAULT_ENDPOINTS_FILE, "event_broker")
actual = broker.from_endpoint_config(cfg)
assert actual is None
arg_parser = create_argument_parser()
cmdline_args = arg_parser.parse_args()
logging.getLogger('werkzeug').setLevel(logging.WARN)
logging.getLogger('engineio').setLevel(logging.WARN)
logging.getLogger('matplotlib').setLevel(logging.WARN)
logging.getLogger('socketio').setLevel(logging.ERROR)
logging.getLogger('pika').setLevel(logging.ERROR)
utils.configure_colored_logging(cmdline_args.loglevel)
utils.configure_file_logging(cmdline_args.loglevel, cmdline_args.log_file)
logger.info("Rasa process starting")
_endpoints = AvailableEndpoints.read_endpoints(cmdline_args.endpoints)
_interpreter = NaturalLanguageInterpreter.create(cmdline_args.nlu,
_endpoints.nlu)
_broker = broker.from_endpoint_config(_endpoints.event_broker)
_tracker_store = TrackerStore.find_tracker_store(None,
_endpoints.tracker_store,
_broker)
_agent = load_agent(cmdline_args.core,
interpreter=_interpreter,
tracker_store=_tracker_store,
endpoints=_endpoints)
serve_application(_agent, cmdline_args.connector, cmdline_args.port,
cmdline_args.credentials, cmdline_args.cors,
cmdline_args.auth_token, cmdline_args.enable_api,
cmdline_args.jwt_secret, cmdline_args.jwt_method)