def _init_model_from_server(model_server):
# type: (EndpointConfig) -> Optional[(Domain, PolicyEnsemble, Text)]
"""Initialise a Rasa Core model from a URL."""
if not is_url(model_server.url):
raise InvalidURL(model_server.url)
model_directory = tempfile.mkdtemp()
fingerprint = _pull_model_and_fingerprint(model_server,
model_directory,
fingerprint=None)
return fingerprint, model_directory
def download_file_from_url(url: Text) -> Text:
"""Download a story file from a url and persists it into a temp file.
Returns the file path of the temp file that contains the
downloaded content."""
if not nlu_utils.is_url(url):
raise InvalidURL(url)
response = requests.get(url)
response.raise_for_status()
filename = nlu_utils.create_temporary_file(response.content, mode="w+b")
return filename
def load_data_from_url(url, language='en'):
# type: (Text, Optional[Text]) -> TrainingData
"""Load training data from a URL."""
if not utils.is_url(url):
raise requests.exceptions.InvalidURL(url)
try:
response = requests.get(url)
response.raise_for_status()
temp_data_file = utils.create_temporary_file(response.content)
return _load(temp_data_file, language)
except Exception as e:
logger.warning("Could not retrieve training data "
"from URL:\n{}".format(e))
def _init_model_from_server(model_server):
# type: (EndpointConfig) -> Optional[(Domain, PolicyEnsemble, Text)]
"""Initialise a Rasa Core model from a URL."""
if not is_url(model_server.url):
raise InvalidURL(model_server.url)
model_directory = tempfile.mkdtemp()
fingerprint = _pull_model_and_fingerprint(model_server,
model_directory,
fingerprint=None)
return fingerprint, model_directory
def load_data_from_url(url, language='en'):
# type: (Text, Optional[Text]) -> TrainingData
"""Load training data from a URL."""
if not utils.is_url(url):
raise requests.exceptions.InvalidURL(url)
try:
response = requests.get(url)
response.raise_for_status()
temp_data_file = utils.create_temporary_file(response.content)
return _load(temp_data_file, language)
except Exception as e:
logger.warning("Could not retrieve training data "
"from URL:\n{}".format(e))
def _init_model_from_server(model_server: EndpointConfig
) -> Optional[typing.Tuple[Text, Text]]:
"""Initialise a Rasa Core model from a URL."""
if not is_url(model_server.url):
raise InvalidURL(model_server.url)
model_directory = tempfile.mkdtemp()
fingerprint = _pull_model_and_fingerprint(model_server,
model_directory,
fingerprint=None)
return fingerprint, model_directory
async def _update_model_from_server(model_server: EndpointConfig,
agent: 'Agent') -> None:
"""Load a zipped Rasa Core model from a URL and update the passed agent."""
if not is_url(model_server.url):
raise aiohttp.InvalidURL(model_server.url)
model_and_fingerprint = await _pull_model_and_fingerprint(
model_server, agent.fingerprint)
if model_and_fingerprint:
model_directory, new_model_fingerprint = model_and_fingerprint
_load_and_set_updated_model(agent, model_directory,
new_model_fingerprint)
else:
logger.debug("No new model found at "
"URL {}".format(model_server.url))
def load_data_from_endpoint(data_endpoint, language='en'):
# type: (EndpointConfig, Optional[Text]) -> TrainingData
"""Load training data from a URL."""
if not utils.is_url(data_endpoint.url):
raise requests.exceptions.InvalidURL(data_endpoint.url)
try:
response = data_endpoint.request("get")
response.raise_for_status()
temp_data_file = utils.create_temporary_file(response.content,
mode="w+b")
return _load(temp_data_file, language)
except Exception as e:
logger.warning("Could not retrieve training data "
"from URL:\n{}".format(e))
async def download_file_from_url(url: Text) -> Text:
"""Download a story file from a url and persists it into a temp file.
Returns the file path of the temp file that contains the
downloaded content."""
from rasa_nlu import utils as nlu_utils
if not nlu_utils.is_url(url):
raise InvalidURL(url)
async with aiohttp.ClientSession() as session:
async with session.get(url, raise_for_status=True) as resp:
filename = nlu_utils.create_temporary_file(await resp.read(),
mode="w+b")
return filename
def download_file_from_url(url):
# type: (Text) -> Text
"""Download a story file from a url and persists it into a temp file.
Returns the file path of the temp file that contains the
downloaded content."""
if not nlu_utils.is_url(url):
raise InvalidURL(url)
response = requests.get(url)
response.raise_for_status()
filename = nlu_utils.create_temporary_file(response.content,
mode="w+b")
return filename
def load_data_from_endpoint(data_endpoint: EndpointConfig,
language: Optional[Text] = 'en') -> 'TrainingData':
"""Load training data from a URL."""
if not utils.is_url(data_endpoint.url):
raise requests.exceptions.InvalidURL(data_endpoint.url)
try:
response = data_endpoint.request("get")
response.raise_for_status()
temp_data_file = utils.create_temporary_file(response.content,
mode="w+b")
training_data = _load(temp_data_file, language)
return training_data
except Exception as e:
logger.warning("Could not retrieve training data "
"from URL:\n{}".format(e))
def _update_model_from_server(model_server: EndpointConfig,
project: 'Project') -> None:
"""Load a zipped Rasa NLU model from a URL and update the passed
project."""
if not is_url(model_server.url):
raise InvalidURL(model_server)
model_directory = tempfile.mkdtemp()
new_model_fingerprint, filename = _pull_model_and_fingerprint(
model_server, model_directory, project.fingerprint)
if new_model_fingerprint:
model_name = _get_remote_model_name(filename)
project.fingerprint = new_model_fingerprint
project.update_model_from_dir_and_unload_others(model_directory,
model_name)
else:
logger.debug("No new model found at URL {}".format(model_server.url))
def _update_model_from_server(model_server: EndpointConfig,
project: 'Project') -> None:
"""Load a zipped Rasa NLU model from a URL and update the passed
project."""
if not is_url(model_server.url):
raise InvalidURL(model_server)
model_directory = tempfile.mkdtemp()
new_model_fingerprint, filename = _pull_model_and_fingerprint(
model_server, model_directory, project.fingerprint)
if new_model_fingerprint:
model_name = _get_remote_model_name(filename)
project.fingerprint = new_model_fingerprint
project.update_model_from_dir_and_unload_others(
model_directory, model_name)
else:
logger.debug("No new model found at URL {}".format(model_server.url))
def _update_model_from_server(model_server: EndpointConfig,
agent: 'Agent') -> None:
"""Load a zipped Rasa Core model from a URL and update the passed agent."""
if not is_url(model_server.url):
raise InvalidURL(model_server.url)
model_directory = tempfile.mkdtemp()
new_model_fingerprint = _pull_model_and_fingerprint(
model_server, model_directory, agent.fingerprint)
if new_model_fingerprint:
domain_path = os.path.join(os.path.abspath(model_directory),
"domain.yml")
domain = Domain.load(domain_path)
policy_ensemble = PolicyEnsemble.load(model_directory)
agent.update_model(domain, policy_ensemble, new_model_fingerprint)
else:
logger.debug("No new model found at "
"URL {}".format(model_server.url))
def _update_model_from_server(
model_server, # type: EndpointConfig
agent, # type: Agent
):
# type: (...) -> None
"""Load a zipped Rasa Core model from a URL and update the passed agent."""
if not is_url(model_server.url):
raise InvalidURL(model_server.url)
model_directory = tempfile.mkdtemp()
new_model_fingerprint = _pull_model_and_fingerprint(
model_server, model_directory, agent.fingerprint)
if new_model_fingerprint:
domain_path = os.path.join(os.path.abspath(model_directory),
"domain.yml")
domain = Domain.load(domain_path)
policy_ensemble = PolicyEnsemble.load(model_directory)
agent.update_model(domain, policy_ensemble, new_model_fingerprint)
else:
logger.debug("No new model found at "
"URL {}".format(model_server.url))
def test_is_url():
assert not is_url('./some/file/path')
assert is_url('https://rasa.com/')
def test_is_url():
assert not is_url('./some/file/path')
assert is_url('https://rasa.com/')
