def main(args):
pre_load = args.pre_load
_endpoints = read_endpoints(args.endpoints)
router = DataRouter(
args.path,
args.max_training_processes,
args.response_log,
args.emulate,
args.storage,
model_server=_endpoints.model,
wait_time_between_pulls=args.wait_time_between_pulls,
)
if pre_load:
logger.debug("Preloading....")
if "all" in pre_load:
pre_load = router.project_store.keys()
router._pre_load(pre_load)
rasa = create_app(
router, args.loglevel, args.write, get_token(args.token), args.cors
)
rasa.add_task(configure_logging)
logger.info("Started http server on port %s" % args.port)
rasa.run(
host="0.0.0.0",
port=args.port,
workers=1,
access_log=logger.isEnabledFor(logging.DEBUG),
)
def main(args):
_endpoints = read_endpoints(args.endpoints)
loop = asyncio.get_event_loop()
if loop.is_closed():
loop = asyncio.new_event_loop()
router = loop.run_until_complete(
create_data_router(
args.model,
args.max_training_processes,
args.response_log,
args.emulate,
args.storage,
model_server=_endpoints.model,
wait_time_between_pulls=args.wait_time_between_pulls,
))
loop.close()
rasa = create_app(router, args.loglevel, args.write, get_token(args.token),
args.cors)
rasa.add_task(configure_logging)
logger.info("Started http server on port %s" % args.port)
rasa.run(
host="0.0.0.0",
port=args.port,
workers=1,
access_log=logger.isEnabledFor(logging.DEBUG),
)
# -*- coding: utf-8 -*- ''' @Author : Xu @Software: PyCharm @File : bot.py @Time : 2019-09-25 14:23 @Desc : 可用于代码断点调试 ''' from rasa.core.channels.socketio import SocketIOInput from rasa.core.agent import Agent import rasa import pathlib import os basedir = str(pathlib.Path(os.path.abspath(__file__)).parent) model = basedir + "/models" # model = "/home/xsq/nlp_code/Chatbot_RASA/models" endpoints = "config/endpoints.yml" credentials = "config/credentials.yml" # ss = rasa.run(model=model, endpoints=endpoints, credentials=credentials)
import logging
import rasa
logging.info("attempting to run rasa")
# Make necessary bindings
# Todo: Add to .env
model_path = "./rasa_folder/models/latest.tar.gz"
model_name = "latest"
domain_path = "./rasa_folder/domain.yml"
credentials_path = "./rasa_folder/credentials.yml"
endpoints_path = "./rasa_folder/endpoints.yml"
config_path = "./rasa_folder/config.yml"
training_data_path = "./rasa_folder/data"
output_path = "./rasa_folder/models"
# Train if needed
rasa.train(domain=domain_path,
config=config_path,
training_files=training_data_path,
output=output_path,
fixed_model_name=model_name)
# Run Rasa
rasa.run(model=model_path,
endpoints=endpoints_path,
port=5005,
cors="*",
connector="rest",
enable_api=True)
def run(args: argparse.Namespace) -> NoReturn:
"""Entrypoint for `rasa run`.
Args:
args: The CLI arguments.
"""
import rasa
args.endpoints = rasa.cli.utils.get_validated_path(args.endpoints,
"endpoints",
DEFAULT_ENDPOINTS_PATH,
True)
args.credentials = rasa.cli.utils.get_validated_path(
args.credentials, "credentials", DEFAULT_CREDENTIALS_PATH, True)
if args.enable_api:
if not args.remote_storage:
args.model = _validate_model_path(args.model, "model",
DEFAULT_MODELS_PATH)
rasa.run(**vars(args))
return
# if the API is not enable you cannot start without a model
# make sure either a model server, a remote storage, or a local model is
# configured
from rasa.model import get_model
from rasa.core.utils import AvailableEndpoints
# start server if remote storage is configured
if args.remote_storage is not None:
rasa.run(**vars(args))
return
# start server if model server is configured
endpoints = AvailableEndpoints.read_endpoints(args.endpoints)
model_server = endpoints.model if endpoints and endpoints.model else None
if model_server is not None:
rasa.run(**vars(args))
return
# start server if local model found
args.model = _validate_model_path(args.model, "model", DEFAULT_MODELS_PATH)
local_model_set = True
try:
get_model(args.model)
except ModelNotFound:
local_model_set = False
if local_model_set:
rasa.run(**vars(args))
return
rasa.shared.utils.cli.print_error(
f"No model found. You have three options to provide a model:\n"
f"1. Configure a model server in the endpoint configuration and provide "
f"the configuration via '--endpoints'.\n"
f"2. Specify a remote storage via '--remote-storage' to load the model "
f"from.\n"
f"3. Train a model before running the server using `rasa train` and "
f"use '--model' to provide the model path.\n"
f"For more information check {DOCS_BASE_URL}/model-storage.")
import os
import rasa
from rasa import version
from rasa.cli import scaffold, run, train, interactive, shell, test, visualize, data, x
from rasa.cli.arguments.default_arguments import add_logging_options
from rasa.cli.utils import parse_last_positional_argument_as_model_path
from rasa.utils.common import set_log_level
import rasa.core.visualize
import asyncio
if __name__ == "__main__":
os.chdir('/Users/lidayuan/Documents/edison/rasa/examples/concertbot')
# rasa.train(domain='domain.yml', config='config.yml', training_files='./data')
rasa.run(model="models", endpoints="endpoints.yml")
# loop = asyncio.get_event_loop()
# loop.run_until_complete(
# rasa.core.visualize(config_path="config.yml",
# domain_path="domain.yml",
# stories_path='./data/stories.md',
# nlu_data_path=None,
# output_path="./txt.html",
# max_history=100
# )
# )
def rasa_run():
"""rasa run """
# 创建路径上下文对象
path_context = PathContext()
run(model=path_context.model_directory, endpoints=path_context.endpoints_file_path,
credentials=path_context.credentials_file_path,log_file="./logs/wireless.log")
# -*- coding:utf-8 -*-
import rasa
from rasa.cli.shell import shell
from rasa.constants import DEFAULT_DOMAIN_PATH, DEFAULT_ENDPOINTS_PATH, DEFAULT_MODELS_PATH
from rasa.core.processor import MessageProcessor
from rasa.core.tracker_store import TrackerStore
from rasa.core.trackers import DialogueStateTracker
from rasa.nlu.registry import component_classes, registered_components
from small_projects.rasa_learn.ep2.train import PROJECT_PATH, CustomPipeline
# component_classes.append(CustomPipeline)
# registered_components[CustomPipeline.name] = CustomPipeline
# class O:
# model = "/Users/dustyposa/Documents/code/github/goSpider/small_projects/rasa_learn/ep2/models"
# endpoints = "/Users/dustyposa/Documents/code/github/goSpider/small_projects/rasa_learn/ep2/endpoints.yml"
# credentials = None
# enable_api = False
#
#
# shell(O())
from rasa.core.channels import RestInput
# rasa.run(model="/Users/dustyposa/Documents/code/github/goSpider/small_projects/rasa_learn/ep2/models",
# endpoints="/Users/dustyposa/Documents/code/github/goSpider/small_projects/rasa_learn/ep2/endpoints.yml")
rasa.run(model=str((PROJECT_PATH / DEFAULT_MODELS_PATH)),
endpoints=str((PROJECT_PATH / DEFAULT_ENDPOINTS_PATH)),
credentials="./credentials.yml")
from rasa.nlu.registry import Any
def run():
import rasa
rasa.run(model="models", endpoints="endpoints.yml")
