def test_socketio_channel():
from rasa_core.channels.socketio import SocketIOInput
from rasa_core.agent import Agent
from rasa_core.interpreter import RegexInterpreter
# load your trained agent
agent = Agent.load(MODEL_PATH, interpreter=RegexInterpreter())
input_channel = SocketIOInput(
# event name for messages sent from the user
user_message_evt="user_uttered",
# event name for messages sent from the bot
bot_message_evt="bot_uttered",
# socket.io namespace to use for the messages
namespace=None)
# set serve_forever=True if you want to keep the server running
s = agent.handle_channels([input_channel], 5004, serve_forever=False)
# END DOC INCLUDE
# the above marker marks the end of the code snipped included
# in the docs
try:
assert s.started
routes_list = utils.list_routes(s.application)
assert routes_list.get("/webhooks/socketio/").startswith(
'socketio_webhook.health')
finally:
s.stop()
def run(core_dir, nlu_dir):
input_channel = SocketIOInput(user_message_evt="user_uttered",
bot_message_evt="bot_uttered",
session_persistence=True,
namespace=None)
_endpoints = AvailableEndpoints.read_endpoints('endpoints.yml')
_interpreter = NaturalLanguageInterpreter.create(nlu_dir)
elastic_user = os.getenv('ELASTICSEARCH_USER')
if elastic_user is None:
_tracker_store = ElasticTrackerStore(
domain=os.getenv('ELASTICSEARCH_URL', 'elasticsearch:9200'))
else:
_tracker_store = ElasticTrackerStore(
domain=os.getenv('ELASTICSEARCH_URL', 'elasticsearch:9200'),
user=os.getenv('ELASTICSEARCH_USER', 'user'),
password=os.getenv('ELASTICSEARCH_PASSWORD', 'password'),
scheme=os.getenv('ELASTICSEARCH_HTTP_SCHEME', 'http'),
scheme_port=os.getenv('ELASTICSEARCH_PORT', '80'))
_agent = load_agent(core_dir,
interpreter=_interpreter,
tracker_store=_tracker_store,
endpoints=_endpoints)
WEBCHAT_PORT = os.getenv('WEBCHAT_PORT', 3000)
http_server = start_server([input_channel], "", "", int(WEBCHAT_PORT),
_agent)
try:
http_server.serve_forever()
except Exception as exc:
logger.exception(exc)
def run():
agent = Agent.load("models/current/dialogue")
#agent.handle_channels();
# agent.predict_next()
input_channel = SocketIOInput(
# event name for messages sent from the user
user_message_evt="user_uttered",
# event name for messages sent from the bot
bot_message_evt="bot_uttered",
# socket.io namespace to use for the messages
namespace=None)
s = agent.handle_channels([input_channel], 5500, serve_forever=True)
def start_server_local(dialogue_model_path, server_endpoints):
"""Start a server which serve a local model.
Environment variables:
----------
SOCKET_PORT: int
Set the port, the server should listen on
(default: 5005)
Parameters:
----------
dialogue_model_path: str
Path to the local model directiory
server_endpoints: AvailableEndpoints
tuple with the endpoints nlg, nlu, action and model
"""
# Check SOCKET_PORT
socket_port = int(
os.environ['SOCKET_PORT']) if "SOCKET_PORT" in os.environ else 5005
# define nlu-server
rasaNLU = RasaNLUHttpInterpreter(project_name="damage_report_1.0.0",
endpoint=server_endpoints.nlu)
# initialize the agent
agent = Agent.load(dialogue_model_path,
interpreter=rasaNLU,
action_endpoint=server_endpoints.action)
# define all channels the server should listen to.
# SocketIOInput - socketIO for the webchat
# RestInput - Rest-Api for other services
channels = [
SocketIOInput(
# event name for messages sent from the user
user_message_evt="user_uttered",
# event name for messages sent from the bot
bot_message_evt="bot_uttered",
# socket.io namespace to use for the messages
namespace=None),
RestInput()
]
# Start the server
agent.handle_channels(channels, socket_port)
from rasa_core.agent import Agent
from rasa_core.channels.socketio import SocketIOInput
from rasa_core.agent import Agent
# load your trained agent
agent = Agent.load('models/dialogue', interpreter='models/current/nlu')
input_channel = SocketIOInput(
# event name for messages sent from the user
user_message_evt="user_uttered",
# event name for messages sent from the bot
bot_message_evt="bot_uttered",
# socket.io namespace to use for the messages
namespace=None)
# set serve_forever=False if you want to keep the server running
s = agent.handle_channels([input_channel], 5500, serve_forever=True)
from rasa_core.channels.socketio import SocketIOInput
from rasa_core.agent import Agent
from rasa_core.interpreter import RasaNLUInterpreter
interpreter = RasaNLUInterpreter("models/six/nlu/")
agent = Agent.load("models/six/dialogue", interpreter=interpreter)
agent.handle_channels([SocketIOInput()], 5500, serve_forever=True)