Model Servers¶

See here for additional information regarding model servers.

class SpellClient.servers

class ModelServersService(client)¶

A class for managing Spell model servers.

list()¶

Lists model servers.

Parameters: name (str) – Model server name
Returns: A list of ModelServer objects.
Raises: ClientException – an error occured.

get(name)¶

Get a model server.

Parameters: name (str) – model server name
Returns: A ModelServer.
Raises: ClientException – an error occured.

rm(name)¶

Remove a model server.

Parameters: name (str) – Model server name
Raises: ClientException – an error occured.

serve(model, entrypoint, github_url, **kwargs)¶

Create a new model server using a model.

Parameters

model (str) – Targeted model, should be in MODEL:VERSION format
entrypoint (str) – Path to the file to be used as the model server entrypoint, e.g. serve.py or similar.
github_url (str) – a GitHub URL to a repository for code to include in the server.
github_ref (str, optional) – a reference to a commit, branch, or tag in the repository corresponding to github_url for code to include in the run (default: master).
commit_ref (str, optional) – git commit hash to use (default: HEAD).
name (str, optional) – Name of the model server. Defaults to the model name.
node_group (str, optional) – Name of the node group to serve from. Defaults to the default node group.
classname (str, optional) – Name of the Predictor class. Only required if more then one predictor exists in the entrypoint.
pip_packages (list of str, optional) – pip dependencies (default: None). For example: ["moviepy", "scikit-image"].
apt_packages (list of str, optional) – apt dependencies (default: None). For example: ["python-tk", "ffmpeg"]
requirements_file (str, optional) – a path to a pip requirements file.
envvars (dict of str -> str, optional) – name to value mapping of environment variables for the server (default: None).
attached_resources (dict of str -> str, optional) – resource name to mountpoint mapping of attached resouces for the run (default: None). For example: {"runs/42" : "/mnt/data"}
resource_requirements (dict of str -> str, optional) – configuration mapping for node resource requirements: CPU, GPU, RAM, etcetera. Has sane default values.
num_processes (int) – The number of processes to run the model server on. By default this is (2 * numberOfCores) + 1, or equal to the available GPUs if applicable.
pod_autoscale_config (dict of str -> str, optional) – configuration mapping for pod autoscaling: min_pods, max_pods, target_cpu_utilization, target_requests_per_second. Has sane default values.
enable_batching (bool, optional) – Whether or not to enable model server batching. Defaults to False.
batching_config (dict of str -> int, optional) – If model server batching is enabled, the values passed to this parameter are used to configure it. If left empty, the default batching parameter values will be used. Has two keys: max_batch_size and request_timeout.
description – (str, optional): Model server description, defaults to None.
debug (bool, optional) – Launches the model server in debug mode. Should not be used in production.

Raises

ClientException – an error occured.

ModelServer¶

class ModelServer¶

Object representing a Spell model server.

id¶

Model server id

Type: int

server_name¶

Model server name

Type: str

status¶

Model server status (e.g. Running, Stopped)

Type: str

url¶

Model server endpoint URL

Type: str

created_at¶

Model server creation timestamp

Type: datetime.datetime

updated_at¶

Timestamp for the last time an action was performed on this server.

Type: datetime.datetime

cluster¶

Model serving cluster configuration details such as provider, region, subnet, and cloud provider credentials.

Type: dict

model_version¶

A ModelVersion object containing information on the model being served. See the corresponding docs for more information.

Type: ModelVersion

entrypoint¶

The model server entrypoint (e.g. serve.py).

Type: str

workspace¶

Details describing the git repository the model server was launched from.

Type: dict

git_commit_hash¶

Commit hash fingerprinting the version of the code this server is running.

Type: str

pods¶

Lists current and historic Kubernetes pods that served or are serving this server.

Type: list of ModelServerPod

creator¶

The Spell user who created this model server initially.

Type: User

resource_requirements¶

The resource requirements and limits currently set for this model server. To learn more refer to the model server documentation.

Type: ContainerResourceRequirements

pod_autoscale_config¶

A mapping of server performance configuration values: min_pods, max_pods, target_cpu_utilization, target_requests_per_second.

Type: PodAutoscaleConfig

additional_resources¶

Lists additional files (besides the model) attached to this model server.

Type: list of Resource

batching_config¶

Batching configuration details. Refer to the corresponding section of the docs for more information.

Type: BatchingConfig

environment¶

A mapping of additional pip and apt dependencies installed onto this model server.

Type: Environment

healthcheck(**kwargs)¶

Query the model server HTTPS health check endpoint.

Parameters

**kwargs – additional keyword arguments to be passed to requests.get. For eaxmple,
timeout parameter may be helpful for the case that the server request hangs. (the) –

Returns

the server response. Use the ok field, status_code field, or raise_for_status object method to verify server health.

Return type

requests.Response

Raises

requests.exceptions.RequestException – an error occurred.

logs(pod, follow=False, offset=None)¶

Get long entries for a model server.

Parameters

pod (int) – the ID of the pod to get logs for. For a list of pods for this model server (and their associated IDs) refer to the attribute pods.
follow (bool, optional) – follow the log lines until the server reaches a final status (default: False).
offset (int, optional) – which log line to start from. Note that this value, if set, must be a positive integer value (default: None).

metrics(metric_name, follow=False, start=None)¶

Get a server metric. Metrics are sorted by tag.

Parameters: metric_name (str) – the name of the metric being fetched.
Raises: ClientException – an error occured.

predict(payload, **kwargs)¶

Query the model server HTTPS endpoint.

Parameters

payload (dict) – a JSON serializable dictionary containing query parameters understood by your model server.
**kwargs – additional keyword arguments to be passed to requests.post.

Returns

the server response.

Return type

requests.Response

Raises

requests.exceptions.RequestException – an error occurred.

refresh()¶

Refresh the model server state.

Refresh all of the server attributes with the latest information for the server from Spell.

Raises: ClientException – an error occurred.

start()¶

Starts the model server.

Raises: ClientException – an error occured.

stop()¶

Stops the model server.

Raises: ClientException – an error occured.

update(**kwargs)¶

Updates the model server.

Parameters

model (str, optional) – Targeted model, should be in MODEL:VERSION format
entrypoint (str, optional) – Path to the file to be used as the model server entrypoint, e.g. serve.py or similar.
github_url (str, optional) – a GitHub URL to a repository for code to include in the server.
github_ref (str, optional) – a reference to a commit, branch, or tag in the repository corresponding to the github_url for code to include in the run (default: master).
commit_ref (str, optional) – git commit hash to use (default: HEAD).
node_group (str, optional) – Name of the node group to serve from. Defaults to the default node group.
classname (str, optional) – Name of the Predictor class. Only required if more then one predictor exists in the entrypoint.
pip_packages (list of str, optional) – pip dependencies (default: None). For example: ["moviepy", "scikit-image"].
apt_packages (list of str, optional) – apt dependencies (default: None). For example: ["python-tk", "ffmpeg"]
requirements_file (str, optional) – a path to a requirements file
envvars (dict of str -> str, optional) – name to value mapping of environment variables for the server (default: None).
attached_resources (dict of str -> str, optional) – resource name to mountpoint mapping of attached resouces for the run (default: None). For example: {"runs/42" : "/mnt/data"}
resource_requirements (dict of str -> str, optional) – Configuration mapping for node resource requirements: cpu_limit, cpu_request, ram_limit, ram_request, gpu_limit. Has sane default values.
num_processes (int) – The number of processes to run the model server on. By default this is (2 * numberOfCores) + 1 or equal to the available GPUs if applicable.
pod_autoscale_config (dict of str -> str, optional) – configuration mapping for pod autoscaling: min_pods, max_pods, target_cpu_utilization, target_requests_per_second. Has sane default values.
enable_batching (bool, optional) – Whether or not to enable model server batching. Defaults to False.
batching_config (dict of str -> str, optional) – If model server batching is enabled, the values passed to this parameter are used to configure it. If left empty, the default batching parameter values will be used.
debug (bool, optional) – Launches the model server in debug mode. Should not be used in production.

Raises

ClientException – an error occured.