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")