def load_model_from_s3(model_dir, config):
try:
from rasa_nlu.persistor import Persistor
p = Persistor(config['path'], config['aws_region'], config['bucket_name'])
p.fetch_and_extract('{0}.tar.gz'.format(os.path.basename(model_dir)))
except Exception as e:
logging.warn("Using default interpreter, couldn't fetch model: {}".format(e.message))
def __create_interpreter(self):
model_dir = self.config.server_model_dir
metadata, backend = None, None
if model_dir is not None:
# download model from S3 if needed
if not os.path.isdir(model_dir):
try:
from rasa_nlu.persistor import Persistor
p = Persistor(self.config.path, self.config.aws_region,
self.config.bucket_name)
p.fetch_and_extract('{0}.tar.gz'.format(
os.path.basename(model_dir)))
except:
warnings.warn(
"using default interpreter, couldn't find model dir or fetch it from S3"
)
metadata = json.loads(
open(os.path.join(model_dir, 'metadata.json'), 'rb').read())
backend = metadata["backend"]
if backend is None:
from .interpreters.simple_interpreter import HelloGoodbyeInterpreter
return HelloGoodbyeInterpreter()
elif backend.lower() == 'mitie':
logging.info("using mitie backend")
from .interpreters.mitie_interpreter import MITIEInterpreter
return MITIEInterpreter(**metadata)
elif backend.lower() == 'spacy_sklearn':
logging.info("using spacy + sklearn backend")
from .interpreters.spacy_sklearn_interpreter import SpacySklearnInterpreter
return SpacySklearnInterpreter(**metadata)
else:
raise ValueError("unknown backend : {0}".format(backend))