def main(args):
utils.configure_colored_logging(args.loglevel)
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 = RasaNLU(router,
args.loglevel,
args.write,
args.num_threads,
get_token(cmdline_args.token),
args.cors,
default_config_path=args.config)
logger.info('Started http server on port %s' % args.port)
rasa.app.run('0.0.0.0', args.port)
def main(args):
utils.configure_colored_logging(args.loglevel)
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 = RasaNLU(
router,
args.loglevel,
args.write,
args.num_threads,
get_token(cmdline_args.token),
args.cors,
default_config_path=args.config
)
logger.info('Started http server on port %s' % args.port)
rasa.app.run('0.0.0.0', args.port)
)
return simplejson.dumps(response)
except Exception as e:
request.setResponseCode(500)
logger.exception(e)
return simplejson.dumps({"error": "{}".format(e)})
if __name__ == '__main__':
# Running as standalone python application
cmdline_args = create_argument_parser().parse_args()
utils.configure_colored_logging(cmdline_args.loglevel)
pre_load = cmdline_args.pre_load
_endpoints = read_endpoints(cmdline_args.endpoints)
router = DataRouter(
cmdline_args.path,
cmdline_args.max_training_processes,
cmdline_args.response_log,
cmdline_args.emulate,
cmdline_args.storage,
model_server=_endpoints.model,
wait_time_between_pulls=cmdline_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)
interpreter = trainer.train(training_data, **kwargs)
if path:
persisted_path = trainer.persist(path, persistor, project,
fixed_model_name)
else:
persisted_path = None
return trainer, interpreter, persisted_path
if __name__ == '__main__':
cmdline_args = create_argument_parser().parse_args()
utils.configure_colored_logging(cmdline_args.loglevel)
if cmdline_args.url:
data_endpoint = EndpointConfig(cmdline_args.url)
else:
data_endpoint = read_endpoints(cmdline_args.endpoints).data
do_train(config.load(cmdline_args.config),
cmdline_args.data,
cmdline_args.path,
cmdline_args.project,
cmdline_args.fixed_model_name,
cmdline_args.storage,
data_endpoint=data_endpoint,
num_threads=cmdline_args.num_threads)
logger.info("Finished training")
if path:
persisted_path = trainer.persist(path,
persistor,
project,
fixed_model_name)
else:
persisted_path = None
return trainer, interpreter, persisted_path
if __name__ == '__main__':
cmdline_args = create_argument_parser().parse_args()
utils.configure_colored_logging(cmdline_args.loglevel)
if cmdline_args.url:
data_endpoint = EndpointConfig(cmdline_args.url)
else:
data_endpoint = read_endpoints(cmdline_args.endpoints).data
train(cmdline_args.config,
cmdline_args.data,
cmdline_args.path,
cmdline_args.project,
cmdline_args.fixed_model_name,
cmdline_args.storage,
training_data_endpoint=data_endpoint,
num_threads=cmdline_args.num_threads)
logger.info("Finished training")