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")