PATCH /v1/mlmodels/{id}

from metadata.sdk import configure
from metadata.sdk.entities import MLModels

configure(
    host="https://your-company.getcollate.io/api",
    jwt_token="your-jwt-token"
)

# Retrieve, modify, and update
model = MLModels.retrieve("6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2")
model.description = "Updated: Customer segmentation using KMeans with 5 clusters"
model.mlHyperParameters = [
    {"name": "n_clusters", "value": "7"},
    {"name": "max_iter", "value": "500"}
]
updated = MLModels.update(model)

print(f"Updated to version {updated.version}")

{
  "id": "6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2",
  "name": "customer_segmentation",
  "fullyQualifiedName": "mlflow_svc.customer_segmentation",
  "displayName": "Customer Segmentation Model",
  "description": "Updated: Customer segmentation using KMeans with 5 clusters",
  "algorithm": "KMeans",
  "version": 0.2,
  "updatedAt": 1769982669247,
  "updatedBy": "admin",
  "service": {
    "id": "ca22d46e-81b9-4e48-85b5-0adc44980da9",
    "type": "mlmodelService",
    "name": "mlflow_svc",
    "fullyQualifiedName": "mlflow_svc",
    "deleted": false
  },
  "serviceType": "Mlflow",
  "href": "http://localhost:8585/api/v1/mlmodels/6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2",
  "deleted": false,
  "owners": [],
  "tags": [],
  "followers": [],
  "votes": {
    "upVotes": 0,
    "downVotes": 0
  },
  "domains": []
}

PATCH

mlmodels

{id}

PATCH /v1/mlmodels/{id}

from metadata.sdk import configure
from metadata.sdk.entities import MLModels

configure(
    host="https://your-company.getcollate.io/api",
    jwt_token="your-jwt-token"
)

# Retrieve, modify, and update
model = MLModels.retrieve("6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2")
model.description = "Updated: Customer segmentation using KMeans with 5 clusters"
model.mlHyperParameters = [
    {"name": "n_clusters", "value": "7"},
    {"name": "max_iter", "value": "500"}
]
updated = MLModels.update(model)

print(f"Updated to version {updated.version}")

{
  "id": "6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2",
  "name": "customer_segmentation",
  "fullyQualifiedName": "mlflow_svc.customer_segmentation",
  "displayName": "Customer Segmentation Model",
  "description": "Updated: Customer segmentation using KMeans with 5 clusters",
  "algorithm": "KMeans",
  "version": 0.2,
  "updatedAt": 1769982669247,
  "updatedBy": "admin",
  "service": {
    "id": "ca22d46e-81b9-4e48-85b5-0adc44980da9",
    "type": "mlmodelService",
    "name": "mlflow_svc",
    "fullyQualifiedName": "mlflow_svc",
    "deleted": false
  },
  "serviceType": "Mlflow",
  "href": "http://localhost:8585/api/v1/mlmodels/6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2",
  "deleted": false,
  "owners": [],
  "tags": [],
  "followers": [],
  "votes": {
    "upVotes": 0,
    "downVotes": 0
  },
  "domains": []
}

Update an ML Model

Update an ML model’s properties using JSON Merge Patch. You can update by ID or by fully qualified name.

Update by ID

string

required

UUID of the ML model to update.

Update by Name

Use PATCH /v1/mlmodels/name/{fqn} to update by fully qualified name.

fqn

string

required

Fully qualified name of the ML model (e.g., mlflow_svc.customer_segmentation).

Body Parameters

Send a JSON object with the fields to update. Only provided fields are changed.

description

string

Updated description in Markdown format.

displayName

string

Updated display name.

algorithm

string

Updated algorithm name.

mlFeatures

array

Updated list of ML features.

Show properties

name

string

Name of the feature.

dataType

string

Data type of the feature (e.g., numerical, categorical).

mlHyperParameters

array

Updated list of hyperparameters.

Show properties

name

string

Name of the hyperparameter.

value

string

Value of the hyperparameter.

target

string

Updated target variable.

owners

array

Updated list of owner references.

Show properties

string

UUID of the owner entity.

type

string

Type of owner entity (e.g., user, team).

tags

array

Updated classification tags.

Show properties

tagFQN

string

required

Fully qualified name of the tag.

labelType

string

Type of label (e.g., Manual, Derived, Propagated).

state

string

State of the tag (e.g., Suggested, Confirmed).

domain

string

Updated domain FQN.

extension

object

Updated custom property values.

PATCH /v1/mlmodels/{id}

from metadata.sdk import configure
from metadata.sdk.entities import MLModels

configure(
    host="https://your-company.getcollate.io/api",
    jwt_token="your-jwt-token"
)

# Retrieve, modify, and update
model = MLModels.retrieve("6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2")
model.description = "Updated: Customer segmentation using KMeans with 5 clusters"
model.mlHyperParameters = [
    {"name": "n_clusters", "value": "7"},
    {"name": "max_iter", "value": "500"}
]
updated = MLModels.update(model)

print(f"Updated to version {updated.version}")

{
  "id": "6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2",
  "name": "customer_segmentation",
  "fullyQualifiedName": "mlflow_svc.customer_segmentation",
  "displayName": "Customer Segmentation Model",
  "description": "Updated: Customer segmentation using KMeans with 5 clusters",
  "algorithm": "KMeans",
  "version": 0.2,
  "updatedAt": 1769982669247,
  "updatedBy": "admin",
  "service": {
    "id": "ca22d46e-81b9-4e48-85b5-0adc44980da9",
    "type": "mlmodelService",
    "name": "mlflow_svc",
    "fullyQualifiedName": "mlflow_svc",
    "deleted": false
  },
  "serviceType": "Mlflow",
  "href": "http://localhost:8585/api/v1/mlmodels/6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2",
  "deleted": false,
  "owners": [],
  "tags": [],
  "followers": [],
  "votes": {
    "upVotes": 0,
    "downVotes": 0
  },
  "domains": []
}

Returns

Returns the updated ML model object with the new version number.

Response

string

Unique identifier for the ML model (UUID format).

name

string

ML model name.

fullyQualifiedName

string

Fully qualified name in format service.modelName.

description

string

Updated description.

version

number

Incremented version number.

Error Handling

Code	Error Type	Description
`400`	`BAD_REQUEST`	Invalid JSON patch or malformed request
`401`	`UNAUTHORIZED`	Invalid or missing authentication token
`403`	`FORBIDDEN`	User lacks permission to update this ML model
`404`	`NOT_FOUND`	ML model with given ID or FQN does not exist
`409`	`CONFLICT`	Concurrent modification detected

Retrieve an ML Model

Delete an ML Model

Introduction

AI SDK

OpenMetadata Standards

Python SDK

Data Assets

Discovery

Lineage

Data Contracts

Teams & Users

Data Governance

Data Quality

Update an ML Model

Update an ML Model

Update by ID

Update by Name

Body Parameters

Returns

Response

Error Handling

Introduction

AI SDK

OpenMetadata Standards

Python SDK

Data Assets

Discovery

Lineage

Data Contracts

Teams & Users

Data Governance

Data Quality

​Update an ML Model

​Update by ID

​Update by Name

​Body Parameters

​Returns

​Response

​Error Handling

Update an ML Model

Update by ID

Update by Name

Body Parameters

Returns

Response

Error Handling