> ## Documentation Index
> Fetch the complete documentation index at: https://docs.open-metadata.org/llms.txt
> Use this file to discover all available pages before exploring further.

# List ML Models

> List all ML models with optional filtering and pagination

# List ML Models

List all ML models with optional filtering and pagination.

## Query Parameters

<ParamField query="service" type="string">
  Filter by ML model service fully qualified name.
</ParamField>

<ParamField query="limit" type="integer" default="10">
  Maximum number of results to return (max: 1000000).
</ParamField>

<ParamField query="before" type="string">
  Cursor for backward pagination.
</ParamField>

<ParamField query="after" type="string">
  Cursor for forward pagination.
</ParamField>

<ParamField query="fields" type="string">
  Comma-separated list of fields to include: `owners`, `tags`, `followers`, `votes`, `extension`, `domains`, `sourceHash`. See [Supported Fields](#supported-fields) below.
</ParamField>

<ParamField query="include" type="string" default="non-deleted">
  Include `all`, `deleted`, or `non-deleted` entities.
</ParamField>

<RequestExample dropdown>
  ```python GET /v1/mlmodels theme={null}
  from metadata.sdk import configure
  from metadata.sdk.entities import MLModels

  configure(
      host="https://your-company.open-metadata.org/api",
      jwt_token="your-jwt-token"
  )

  # List first page
  models = MLModels.list(limit=50)
  for m in models.data:
      print(f"{m.fullyQualifiedName} ({m.algorithm})")

  # List all with auto-pagination
  for m in MLModels.list_all():
      print(f"{m.fullyQualifiedName}")

  # Filter by service
  models = MLModels.list(
      service="mlflow_svc",
      fields=["owners", "tags", "domains"],
      limit=50
  )

  for m in models.data:
      print(f"{m.fullyQualifiedName}")
      if m.owners:
          print(f"  Owners: {[o.name for o in m.owners]}")
      if m.tags:
          print(f"  Tags: {[t.tagFQN for t in m.tags]}")
  ```

  ```java GET /v1/mlmodels theme={null}
  import static org.openmetadata.sdk.fluent.MlModels.*;

  // List first page
  var result = MlModels.list()
      .limit(50)
      .execute();

  for (var m : result.getData()) {
      System.out.println(m.getFullyQualifiedName());
  }

  // Filter by service with fields
  var result = MlModels.list()
      .service("mlflow_svc")
      .fields("owners", "tags", "domains")
      .limit(50)
      .execute();

  for (var m : result.getData()) {
      System.out.println(m.getFullyQualifiedName());
  }
  ```

  ```bash GET /v1/mlmodels theme={null}
  # List all
  curl "{base_url}/api/v1/mlmodels?limit=50" \
    -H "Authorization: Bearer {access_token}"

  # Filter by service
  curl "{base_url}/api/v1/mlmodels?service=mlflow_svc&limit=50" \
    -H "Authorization: Bearer {access_token}"

  # With fields
  curl "{base_url}/api/v1/mlmodels?service=mlflow_svc&fields=owners,tags,domains&limit=50" \
    -H "Authorization: Bearer {access_token}"
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "data": [
      {
        "id": "6b04e1d8-b66d-4f78-ab21-beb5be2cf4f2",
        "name": "customer_segmentation",
        "fullyQualifiedName": "mlflow_svc.customer_segmentation",
        "displayName": "Customer Segmentation Model",
        "algorithm": "KMeans",
        "version": 0.1,
        "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": []
      }
    ],
    "paging": {
      "after": "...",
      "total": 5
    }
  }
  ```
</ResponseExample>

***

## Returns

Returns a paginated list of ML model objects. By default, only basic fields are included. Use the `fields` parameter to request additional data.

## Response

<ResponseField name="data" type="array">
  Array of ML model objects.

  <Expandable title="properties">
    <ResponseField name="id" type="string">
      Unique identifier for the ML model (UUID format).
    </ResponseField>

    <ResponseField name="name" type="string">
      ML model name.
    </ResponseField>

    <ResponseField name="fullyQualifiedName" type="string">
      Fully qualified name in format `service.modelName`.
    </ResponseField>

    <ResponseField name="displayName" type="string">
      Human-readable display name.
    </ResponseField>

    <ResponseField name="algorithm" type="string">
      Algorithm used by the ML model.
    </ResponseField>

    <ResponseField name="service" type="object">
      Reference to the parent ML model service.
    </ResponseField>

    <ResponseField name="serviceType" type="string">
      Type of ML model service (e.g., Mlflow, Sklearn, SageMaker).
    </ResponseField>

    <ResponseField name="owners" type="array" optional>
      List of owners assigned to the ML model. Only included when `fields` contains `owners`.
    </ResponseField>

    <ResponseField name="tags" type="array" optional>
      Classification tags applied. Only included when `fields` contains `tags`.
    </ResponseField>

    <ResponseField name="domains" type="array" optional>
      Domain assignments for governance. Only included when `fields` contains `domains`.
    </ResponseField>

    <ResponseField name="followers" type="array" optional>
      Users following this ML model. Only included when `fields` contains `followers`.
    </ResponseField>

    <ResponseField name="votes" type="object" optional>
      User votes and ratings. Only included when `fields` contains `votes`.
    </ResponseField>

    <ResponseField name="extension" type="object" optional>
      Custom properties. Only included when `fields` contains `extension`.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseField name="paging" type="object">
  Pagination information.

  <Expandable title="properties">
    <ResponseField name="total" type="integer">
      Total count of ML models matching the query.
    </ResponseField>

    <ResponseField name="after" type="string" optional>
      Cursor for the next page of results. Null if this is the last page.
    </ResponseField>

    <ResponseField name="before" type="string" optional>
      Cursor for the previous page of results. Null if this is the first page.
    </ResponseField>
  </Expandable>
</ResponseField>

***

## Supported Fields

The following fields can be requested via the `fields` query parameter:

| Field        | Description                        |
| ------------ | ---------------------------------- |
| `owners`     | Owner references (users and teams) |
| `tags`       | Classification tags                |
| `followers`  | Users following the ML model       |
| `votes`      | User votes and ratings             |
| `extension`  | Custom property values             |
| `domains`    | Domain assignments for governance  |
| `sourceHash` | Hash for change detection          |

***

## Error Handling

| Code  | Error Type     | Description                             |
| ----- | -------------- | --------------------------------------- |
| `401` | `UNAUTHORIZED` | Invalid or missing authentication token |
| `403` | `FORBIDDEN`    | User lacks permission to list ML models |