client.models.deploy

client.models.deploy(self, container_image, model_name, model_version, sample_input_file=None, architecture="amd64" credentials=None, model_id=None, run_timeout=None, status_timeout=None, short_description=None, tags=[],cpu_count=None, memory=None, gpu=False, long_description=None, technical_details=None, performance_summary=None, performance_metrics=None, input_details=None, output_details=None, model_picture=None)

Deploy new model or new version for existing model to your private model library.

🚧
Note: This method only supports deployment of container images stored in Docker registries that adhere to the HTTP API v2 protocol.

Parameters

Parameter	Type	Description	Example
`container_image`	`str`	Docker container image to be deployed. This string should represent what follows a `docker pull` command	`'modzy/grpc-echo-model:1.0.0'`
`model_name`	`str`	Name of model to be deployed	`'Echo Model'`
`model_version`	`str`	Version of model to be deployed	`'0.0.1'`
`sample_input_file`	`str`	Path to local file to be used for sample inference	`'./test-input.txt'`
`architecture`	`str`	``{'amd64', 'arm64', 'arm'}` If set to `arm64` or `arm`, deploy method will expedite the deployment process and bypass some Modzy tests that are only available for models compiled for amd64 chips.
`credentials`	`dict`	Dictionary containing credentials if the container image is private. The keys in this dictionary must be `["user", "pass"]`	`Dockerhub Example`: `{"user": "<Dockerhub account username>", "pass": "<Dockerhub account password>"}` `AWS ECR Example`: `{"user": "<AWS Access Key ID>", "pass": "<AWS Secret Access Key>"}`
`model_id`	`str`	Model identifier if deploying a new version to a model that already exists	`'y79drwaozn'`
`run_timeout`	`str`	Timeout threshold for container `run` route	`'60'`
`status_timeout`	`str`	Timeout threshold for container `status` route	`'60'`
`short_description`	`str`	Short description to appear on model biography page	`'This model returns the same text passed through as input, similar to an "echo".'`
`long_description`	`str`	Description to appear on model biography page	`"Long Description"`
`tags`	`List`	List of tags to make model more discoverable in model library	`["Text", "Language"]`
`cpu_count`	`Union[float, int]`	Number of CPU cores needed by model container	`1`
`memory`	`Union[float, int]`	RAM needed by model container in GB (e.g., 1 = 1GB, 0.5 = 500MB)	`2`
`gpu`	`bool`	Flag for whether or not model requires GPU to run	`False`
`technical_details`	`str`	Technical details to appear on model biography page. Markdown is accepted	`"Technical Details`"
`performance_summary`	`str`	Description providing model performance to appear on model biography page	`"Performance Summary`"
`performance_metrics`	`List`	List of arrays describing model performance statistics	`[ { "label": "Accuracy", "category": "numeric", "type": "percentage", "description": "The average of the classification accuracies across all classes.", "order": 1, "value": 0.96 } ]`
`input_details`	`List`	List of dictionaries describing details of model inputs	`[ { "name": "input", "acceptedMediaTypes": "application/json", "maximumSize": 1000000, "description": "Default input data" } ]`
`output_details`	`List`	List of dictionaries describing details of model outputs	`[ { "name": "results.json", "mediaType": "application/json", "maximumSize": 1000000, "description": "Default output data" } ]`
`model_picture`	`str`	Filepath to image for model card page	`"path-to-image.jpg"`

Returns

{
    "model_data": {
        "version": "0.0.1",
        "createdAt": "2022-08-16T01:10:52.821+00:00",
        "updatedAt": "2022-08-16T01:10:53.498+00:00",
        "inputValidationSchema": "",
        "timeout": {
            "status": 60000,
            "run": 60000
        },
        "requirement": {
            "requirementId": 1
        },
        "containerImage": {
            "uploadStatus": "IN_PROGRESS",
            "loadStatus": "IN_PROGRESS",
            "uploadPercentage": 0,
            "loadPercentage": 0,
            "containerImageSize": 0,
            "repositoryName": "thjg0zuntf"
        },
        "inputs": [
            {
                "name": "input",
                "acceptedMediaTypes": "application/json",
                "maximumSize": 1000000,
                "description": "Default input data"
            }
        ],
        "outputs": [
            {
                "name": "results.json",
                "mediaType": "application/json",
                "maximumSize": 1000000,
                "description": "Default output data"
            }
        ],
        "statistics": [],
        "isActive": false,
        "longDescription": "Long Description",
        "technicalDetails": "Techincal Details",
        "isAvailable": true,
        "status": "partial",
        "performanceSummary": "Performance summary",
        "model": {
            "modelId": "thjg0zuntf",
            "latestVersion": "0.0.1",
            "latestActiveVersion": "",
            "versions": [
                "0.0.1"
            ],
            "author": "Integration",
            "name": "Echo Model",
            "description": "Short Description",
            "permalink": "thjg0zuntf-integration-echo-model",
            "features": [],
            "isActive": false,
            "isRecommended": false,
            "isCommercial": false,
            "tags": [],
            "createdByEmail": "[email protected]",
            "createdByFullName": "First Last",
            "visibility": {
                "scope": "PRIVATE"
            }
        },
        "processing": {
            "minimumParallelCapacity": 0,
            "maximumParallelCapacity": 1
        },
        "originSidecar": false
    },
    "container_url": "https://modzy-instance.app.modzy.com/models/thjg0zuntf/0.0.1"
}

Examples

model_data = client.models.deploy(
    container_image="modzy/grpc-echo-model:1.0.0",
    model_name="Echo Model",
    model_version="0.0.1",
    sample_input_file="./test.txt",
    run_timeout="60",
    status_timeout="60",
    short_description="This model returns the same text passed through as input, similar to an 'echo.'",
    long_description="This model returns the same text passed through as input, similar to an 'echo.'",
    technical_details="This section can include any technical information abot your model. Include information about how your model was trained, any underlying architecture details, or other pertinant information an end-user would benefit from learning.",
    performance_summary="This is the performance summary."
)