# Copyright 2023 Iguazio
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
__all__ = ["GraphServer", "create_graph_server", "GraphContext", "MockEvent"]
import asyncio
import json
import os
import socket
import traceback
import uuid
from typing import Optional, Union
from nuclio import Context as NuclioContext
from nuclio.request import Logger as NuclioLogger
import mlrun
import mlrun.common.constants
import mlrun.common.helpers
import mlrun.model_monitoring
import mlrun.utils
from mlrun.config import config
from mlrun.errors import err_to_str
from mlrun.secrets import SecretsStore
from ..common.helpers import parse_versioned_object_uri
from ..common.schemas.model_monitoring.constants import FileTargetKind
from ..datastore import get_stream_pusher
from ..datastore.store_resources import ResourceCache
from ..errors import MLRunInvalidArgumentError
from ..model import ModelObj
from ..utils import get_caller_globals
from .states import RootFlowStep, RouterStep, get_function, graph_root_setter
from .utils import event_id_key, event_path_key
class _StreamContext:
"""Handles the stream context for the events stream process. Includes the configuration for the output stream
that will be used for pushing the events from the nuclio model serving function"""
def __init__(self, enabled: bool, parameters: dict, function_uri: str):
"""
Initialize _StreamContext object.
:param enabled: A boolean indication for applying the stream context
:param parameters: Dictionary of optional parameters, such as `log_stream` and `stream_args`. Note that these
parameters might be relevant to the output source such as `kafka_brokers` if
the output source is from type Kafka.
:param function_uri: Full value of the function uri, usually it's <project-name>/<function-name>
"""
self.enabled = False
self.hostname = socket.gethostname()
self.function_uri = function_uri
self.output_stream = None
self.stream_uri = None
log_stream = parameters.get(FileTargetKind.LOG_STREAM, "")
if (enabled or log_stream) and function_uri:
self.enabled = True
project, _, _, _ = parse_versioned_object_uri(
function_uri, config.default_project
)
self.stream_uri = mlrun.model_monitoring.get_stream_path(project=project)
if log_stream:
# Update the stream path to the log stream value
self.stream_uri = log_stream.format(project=project)
stream_args = parameters.get("stream_args", {})
self.output_stream = get_stream_pusher(self.stream_uri, **stream_args)
[docs]class GraphServer(ModelObj):
kind = "server"
def __init__(
self,
graph=None,
parameters=None,
load_mode=None,
function_uri=None,
verbose=False,
version=None,
functions=None,
graph_initializer=None,
error_stream=None,
track_models=None,
tracking_policy=None,
secret_sources=None,
default_content_type=None,
):
self._graph = None
self.graph: Union[RouterStep, RootFlowStep] = graph
self.function_uri = function_uri
self.parameters = parameters or {}
self.verbose = verbose
self.load_mode = load_mode or "sync"
self.version = version or "v2"
self.context = None
self._current_function = None
self.functions = functions or {}
self.graph_initializer = graph_initializer
self.error_stream = error_stream
self.track_models = track_models
self.tracking_policy = tracking_policy
self._error_stream_object = None
self.secret_sources = secret_sources
self._secrets = SecretsStore.from_list(secret_sources)
self._db_conn = None
self.resource_cache = None
self.default_content_type = default_content_type
self.http_trigger = True
[docs] def set_current_function(self, function):
"""set which child function this server is currently running on"""
self._current_function = function
@property
def graph(self) -> Union[RootFlowStep, RouterStep]:
return self._graph
@graph.setter
def graph(self, graph):
graph_root_setter(self, graph)
[docs] def set_error_stream(self, error_stream):
"""set/initialize the error notification stream"""
self.error_stream = error_stream
if error_stream:
self._error_stream_object = get_stream_pusher(error_stream)
else:
self._error_stream_object = None
def _get_db(self):
return mlrun.get_run_db(secrets=self._secrets)
[docs] def init_states(
self,
context,
namespace,
resource_cache: ResourceCache = None,
logger=None,
is_mock=False,
monitoring_mock=False,
):
"""for internal use, initialize all steps (recursively)"""
if self.secret_sources:
self._secrets = SecretsStore.from_list(self.secret_sources)
if self.error_stream:
self._error_stream_object = get_stream_pusher(self.error_stream)
self.resource_cache = resource_cache or ResourceCache()
context = GraphContext(server=self, nuclio_context=context, logger=logger)
context.is_mock = is_mock
context.monitoring_mock = monitoring_mock
context.root = self.graph
context.stream = _StreamContext(
self.track_models, self.parameters, self.function_uri
)
context.current_function = self._current_function
context.get_store_resource = self.resource_cache.resource_getter(
self._get_db(), self._secrets
)
context.get_table = self.resource_cache.get_table
context.verbose = self.verbose
self.context = context
if self.graph_initializer:
if callable(self.graph_initializer):
handler = self.graph_initializer
else:
handler = get_function(self.graph_initializer, namespace or [])
handler(self)
context.root = self.graph
[docs] def init_object(self, namespace):
self.graph.init_object(self.context, namespace, self.load_mode, reset=True)
[docs] def test(
self,
path: str = "/",
body: Union[str, bytes, dict] = None,
method: str = "",
headers: Optional[str] = None,
content_type: Optional[str] = None,
silent: bool = False,
get_body: bool = True,
event_id: Optional[str] = None,
trigger: "MockTrigger" = None,
offset=None,
time=None,
):
"""invoke a test event into the server to simulate/test server behavior
example::
server = create_graph_server()
server.add_model("my", class_name=MyModelClass, model_path="{path}", z=100)
print(server.test("my/infer", testdata))
:param path: api path, e.g. (/{router.url_prefix}/{model-name}/..) path
:param body: message body (dict or json str/bytes)
:param method: optional, GET, POST, ..
:param headers: optional, request headers, ..
:param content_type: optional, http mime type
:param silent: don't raise on error responses (when not 20X)
:param get_body: return the body as py object (vs serialize response into json)
:param event_id: specify the unique event ID (by default a random value will be generated)
:param trigger: nuclio trigger info or mlrun.serving.server.MockTrigger class (holds kind and name)
:param offset: trigger offset (for streams)
:param time: event time Datetime or str, default to now()
"""
if not self.graph:
raise MLRunInvalidArgumentError(
"no models or steps were set, use function.set_topology() and add steps"
)
if not method:
method = "POST" if body else "GET"
event = MockEvent(
body=body,
path=path,
method=method,
headers=headers,
content_type=content_type,
event_id=event_id,
trigger=trigger,
offset=offset,
time=time,
)
resp = self.run(event, get_body=get_body)
if hasattr(resp, "status_code") and resp.status_code >= 300 and not silent:
raise RuntimeError(f"failed ({resp.status_code}): {resp.body}")
return resp
[docs] def run(self, event, context=None, get_body=False, extra_args=None):
server_context = self.context
context = context or server_context
event.content_type = event.content_type or self.default_content_type or ""
if event.headers:
if event_id_key in event.headers:
event.id = event.headers.get(event_id_key)
if event_path_key in event.headers:
event.path = event.headers.get(event_path_key)
if isinstance(event.body, (str, bytes)) and (
not event.content_type or event.content_type in ["json", "application/json"]
):
# assume it is json and try to load
try:
body = json.loads(event.body)
event.body = body
except (json.decoder.JSONDecodeError, UnicodeDecodeError) as exc:
if event.content_type in ["json", "application/json"]:
# if its json type and didnt load, raise exception
message = f"failed to json decode event, {err_to_str(exc)}"
context.logger.error(message)
server_context.push_error(event, message, source="_handler")
return context.Response(
body=message, content_type="text/plain", status_code=400
)
try:
response = self.graph.run(event, **(extra_args or {}))
except Exception as exc:
message = f"{exc.__class__.__name__}: {err_to_str(exc)}"
if server_context.verbose:
message += "\n" + str(traceback.format_exc())
context.logger.error(f"run error, {traceback.format_exc()}")
server_context.push_error(event, message, source="_handler")
return context.Response(
body=message, content_type="text/plain", status_code=400
)
if asyncio.iscoroutine(response):
return self._process_async_response(context, response, get_body)
else:
return self._process_response(context, response, get_body)
async def _process_async_response(self, context, response, get_body):
return self._process_response(context, await response, get_body)
def _process_response(self, context, response, get_body):
body = response.body
if isinstance(body, context.Response) or get_body:
return body
if body and not isinstance(body, (str, bytes)):
body = json.dumps(body)
return context.Response(
body=body, content_type="application/json", status_code=200
)
return body
[docs] def wait_for_completion(self):
"""wait for async operation to complete"""
return self.graph.wait_for_completion()
def v2_serving_init(context, namespace=None):
"""hook for nuclio init_context()"""
context.logger.info("Initializing server from spec")
spec = mlrun.utils.get_serving_spec()
server = GraphServer.from_dict(spec)
if config.log_level.lower() == "debug":
server.verbose = True
if hasattr(context, "trigger"):
server.http_trigger = getattr(context.trigger, "kind", "http") == "http"
context.logger.info_with(
"Setting current function",
current_function=os.getenv("SERVING_CURRENT_FUNCTION", ""),
)
server.set_current_function(os.getenv("SERVING_CURRENT_FUNCTION", ""))
context.logger.info_with(
"Initializing states", namespace=namespace or get_caller_globals()
)
kwargs = {}
if hasattr(context, "is_mock"):
kwargs["is_mock"] = context.is_mock
server.init_states(
context,
namespace or get_caller_globals(),
**kwargs,
)
context.logger.info("Initializing graph steps")
server.init_object(namespace or get_caller_globals())
# set the handler hook to point to our handler
setattr(context, "mlrun_handler", v2_serving_handler)
setattr(context, "_server", server)
context.logger.info_with("Serving was initialized", verbose=server.verbose)
if server.verbose:
context.logger.info(server.to_yaml())
_set_callbacks(server, context)
def _set_callbacks(server, context):
if not server.graph.supports_termination() or not hasattr(context, "platform"):
return
if hasattr(context.platform, "set_termination_callback"):
context.logger.info(
"Setting termination callback to terminate graph on worker shutdown"
)
async def termination_callback():
context.logger.info("Termination callback called")
server.wait_for_completion()
context.logger.info("Termination of async flow is completed")
context.platform.set_termination_callback(termination_callback)
if hasattr(context.platform, "set_drain_callback"):
context.logger.info(
"Setting drain callback to terminate and restart the graph on a drain event (such as rebalancing)"
)
async def drain_callback():
context.logger.info("Drain callback called")
server.wait_for_completion()
context.logger.info(
"Termination of async flow is completed. Rerunning async flow."
)
# Rerun the flow without reconstructing it
server.graph._run_async_flow()
context.logger.info("Async flow restarted")
context.platform.set_drain_callback(drain_callback)
def v2_serving_handler(context, event, get_body=False):
"""hook for nuclio handler()"""
if context._server.http_trigger:
# Workaround for a Nuclio bug where it sometimes passes b'' instead of None due to dirty memory
if event.body == b"":
event.body = None
# original path is saved in stream_path so it can be used by explicit ack, but path is reset to / as a
# workaround for NUC-178
# nuclio 1.12.12 added the topic attribute, and we must use it as part of the fix for NUC-233
# TODO: Remove fallback on event.path once support for nuclio<1.12.12 is dropped
event.stream_path = getattr(event, "topic", event.path)
if hasattr(event, "trigger") and event.trigger.kind in (
"kafka",
"kafka-cluster",
"v3ioStream",
"v3io-stream",
"rabbit-mq",
"rabbitMq",
):
event.path = "/"
return context._server.run(event, context, get_body)
[docs]def create_graph_server(
parameters=None,
load_mode=None,
graph=None,
verbose=False,
current_function=None,
**kwargs,
) -> GraphServer:
"""create graph server host/emulator for local or test runs
Usage example::
server = create_graph_server(graph=RouterStep(), parameters={})
server.init(None, globals())
server.graph.add_route("my", class_name=MyModelClass, model_path="{path}", z=100)
print(server.test("/v2/models/my/infer", testdata))
"""
parameters = parameters or {}
server = GraphServer(graph, parameters, load_mode, verbose=verbose, **kwargs)
server.set_current_function(
current_function or os.getenv("SERVING_CURRENT_FUNCTION", "")
)
return server
class MockTrigger:
"""mock nuclio event trigger"""
def __init__(self, kind="", name=""):
self.kind = kind
self.name = name
class MockEvent:
"""mock basic nuclio event object"""
def __init__(
self,
body=None,
content_type=None,
headers=None,
method=None,
path=None,
event_id=None,
trigger: MockTrigger = None,
offset=None,
time=None,
):
self.id = event_id or uuid.uuid4().hex
self.key = ""
self.body = body
# optional
self.headers = headers or {}
self.method = method
self.path = path or "/"
self.content_type = content_type
self.error = None
self.trigger = trigger or MockTrigger()
self.offset = offset or 0
def __str__(self):
error = f", error={self.error}" if self.error else ""
return f"Event(id={self.id}, body={self.body}, method={self.method}, path={self.path}{error})"
class Response:
def __init__(self, headers=None, body=None, content_type=None, status_code=200):
self.headers = headers or {}
self.body = body
self.status_code = status_code
self.content_type = content_type or "text/plain"
def __repr__(self):
cls = self.__class__.__name__
items = self.__dict__.items()
args = (f"{key}={repr(value)}" for key, value in items)
args_str = ", ".join(args)
return f"{cls}({args_str})"
[docs]class GraphContext:
"""Graph context object"""
def __init__(
self,
level="info", # Unused argument
logger=None,
server=None,
nuclio_context: Optional[NuclioContext] = None,
) -> None:
self.state = None
self.logger = logger
self.worker_id = 0
self.Response = Response
self.verbose = False
self.stream = None
self.root = None
if nuclio_context:
self.logger: NuclioLogger = nuclio_context.logger
self.Response = nuclio_context.Response
if hasattr(nuclio_context, "trigger") and hasattr(
nuclio_context.trigger, "kind"
):
self.trigger = nuclio_context.trigger.kind
self.worker_id = nuclio_context.worker_id
if hasattr(nuclio_context, "platform"):
self.platform = nuclio_context.platform
elif not logger:
self.logger: mlrun.utils.Logger = mlrun.utils.logger
self._server = server
self.current_function = None
self.get_store_resource = None
self.get_table = None
self.is_mock = False
@property
def server(self):
return self._server
@property
def project(self) -> str:
"""current project name (for the current function)"""
project, _, _, _ = mlrun.common.helpers.parse_versioned_object_uri(
self._server.function_uri
)
return project
[docs] def push_error(self, event, message, source=None, **kwargs):
if self.verbose:
self.logger.error(
f"got error from {source} state:\n{event.body}\n{message}"
)
if self._server and self._server._error_stream_object:
try:
message = format_error(
self._server, self, source, event, message, kwargs
)
self._server._error_stream_object.push(message)
except Exception as ex:
message = traceback.format_exc()
self.logger.error(f"failed to write to error stream: {ex}\n{message}")
[docs] def get_param(self, key: str, default=None):
if self._server and self._server.parameters:
return self._server.parameters.get(key, default)
return default
[docs] def get_secret(self, key: str):
if self._server and self._server._secrets:
return self._server._secrets.get(key)
return None
[docs] def get_remote_endpoint(self, name, external=True):
"""return the remote nuclio/serving function http(s) endpoint given its name
:param name: the function name/uri in the form [project/]function-name[:tag]
:param external: return the external url (returns the external url by default)
"""
if "://" in name:
return name
project, uri, tag, _ = mlrun.common.helpers.parse_versioned_object_uri(
self._server.function_uri
)
if name.startswith("."):
name = f"{uri}-{name[1:]}"
else:
project, name, tag, _ = mlrun.common.helpers.parse_versioned_object_uri(
name, project
)
(
state,
fullname,
_,
_,
_,
function_status,
) = mlrun.runtimes.nuclio.function.get_nuclio_deploy_status(name, project, tag)
if state in ["error", "unhealthy"]:
raise ValueError(
f"Nuclio function {fullname} is in error state, cannot be accessed"
)
key = "externalInvocationUrls" if external else "internalInvocationUrls"
urls = function_status.get(key)
if not urls:
raise ValueError(f"cannot read {key} for nuclio function {fullname}")
return f"http://{urls[0]}"
def format_error(server, context, source, event, message, args):
return {
"function_uri": server.function_uri,
"worker": context.worker_id,
"host": socket.gethostname(),
"source": source,
"event": {"id": event.id, "body": event.body},
"message": message,
"args": args,
}
