def build_function():
try:
data = request.get_json(force=True)
except ValueError:
return json_error(HTTPStatus.BAD_REQUEST, reason='bad JSON body')
logger.info('build_function:\n{}'.format(data))
function = data.get('function')
with_mlrun = strtobool(data.get('with_mlrun', 'on'))
try:
fn = new_function(runtime=function)
fn.set_db_connection(_db)
fn.save(versioned=False)
ready = build_runtime(fn, with_mlrun)
fn.save(versioned=False)
logger.info('Fn:\n %s', fn.to_yaml())
except Exception as err:
logger.error(traceback.format_exc())
return json_error(
HTTPStatus.BAD_REQUEST,
reason='runtime error: {}'.format(err),
)
return jsonify(ok=True, data=fn.to_dict(), ready=ready)
def _build_function(
db_session,
auth_info: mlrun.api.schemas.AuthInfo,
function,
with_mlrun,
skip_deployed,
mlrun_version_specifier,
):
fn = None
ready = None
try:
fn = new_function(runtime=function)
run_db = get_run_db_instance(db_session, auth_info.session)
fn.set_db_connection(run_db)
fn.save(versioned=False)
if fn.kind in RuntimeKinds.nuclio_runtimes():
mlrun.api.api.utils.ensure_function_has_auth_set(fn, auth_info)
deploy_nuclio_function(fn)
# deploy only start the process, the get status API is used to check readiness
ready = False
else:
ready = build_runtime(fn, with_mlrun, mlrun_version_specifier,
skip_deployed)
fn.save(versioned=True)
logger.info("Fn:\n %s", fn.to_yaml())
except Exception as err:
logger.error(traceback.format_exc())
log_and_raise(HTTPStatus.BAD_REQUEST.value,
reason=f"runtime error: {err}")
return fn, ready
def _build_function(db_session, function, with_mlrun):
fn = None
ready = None
try:
fn = new_function(runtime=function)
run_db = get_run_db_instance(db_session)
fn.set_db_connection(run_db)
fn.save(versioned=False)
ready = build_runtime(fn, with_mlrun)
fn.save(versioned=False)
logger.info("Fn:\n %s", fn.to_yaml())
except Exception as err:
logger.error(traceback.format_exc())
log_and_raise(HTTPStatus.BAD_REQUEST,
reason="runtime error: {}".format(err))
return fn, ready
def _build_function(db_session, function, with_mlrun):
fn = None
ready = None
try:
fn = new_function(runtime=function)
run_db = get_run_db_instance(db_session)
fn.set_db_connection(run_db)
fn.save(versioned=False)
if fn.kind in RuntimeKinds.nuclio_runtimes():
deploy_nuclio_function(fn)
# deploy only start the process, the get status API is used to check readiness
ready = False
else:
ready = build_runtime(fn, with_mlrun)
fn.save(versioned=True)
logger.info("Fn:\n %s", fn.to_yaml())
except Exception as err:
logger.error(traceback.format_exc())
log_and_raise(HTTPStatus.BAD_REQUEST.value,
reason="runtime error: {}".format(err))
return fn, ready
def _build_function(
db_session,
auth_info: mlrun.api.schemas.AuthInfo,
function,
with_mlrun=True,
skip_deployed=False,
mlrun_version_specifier=None,
builder_env=None,
):
fn = None
ready = None
try:
fn = new_function(runtime=function)
except Exception as err:
logger.error(traceback.format_exc())
log_and_raise(HTTPStatus.BAD_REQUEST.value,
reason=f"runtime error: {err}")
try:
run_db = get_run_db_instance(db_session)
fn.set_db_connection(run_db)
fn.save(versioned=False)
if fn.kind in RuntimeKinds.nuclio_runtimes():
mlrun.api.api.utils.ensure_function_has_auth_set(fn, auth_info)
mlrun.api.api.utils.process_function_service_account(fn)
if fn.kind == RuntimeKinds.serving:
# Handle model monitoring
try:
if fn.spec.track_models:
logger.info(
"Tracking enabled, initializing model monitoring")
_init_serving_function_stream_args(fn=fn)
model_monitoring_access_key = _process_model_monitoring_secret(
db_session,
fn.metadata.project,
"MODEL_MONITORING_ACCESS_KEY",
)
_create_model_monitoring_stream(
project=fn.metadata.project)
mlrun.api.crud.ModelEndpoints(
).deploy_monitoring_functions(
project=fn.metadata.project,
model_monitoring_access_key=
model_monitoring_access_key,
db_session=db_session,
auth_info=auth_info,
)
except Exception as exc:
logger.warning(
"Failed deploying model monitoring infrastructure for the project",
project=fn.metadata.project,
exc=exc,
traceback=traceback.format_exc(),
)
deploy_nuclio_function(fn, auth_info=auth_info)
# deploy only start the process, the get status API is used to check readiness
ready = False
else:
ready = build_runtime(
auth_info,
fn,
with_mlrun,
mlrun_version_specifier,
skip_deployed,
builder_env=builder_env,
)
fn.save(versioned=True)
logger.info("Fn:\n %s", fn.to_yaml())
except Exception as err:
logger.error(traceback.format_exc())
log_and_raise(HTTPStatus.BAD_REQUEST.value,
reason=f"runtime error: {err}")
return fn, ready