# Models

## List

`agents.evaluation_metrics.models.list(ModelListParams**kwargs)  -> ModelListResponse`

**get** `/v2/gen-ai/models`

To list all models, send a GET request to `/v2/gen-ai/models`.

### Parameters

- `page: Optional[int]`

  Page number.

- `per_page: Optional[int]`

  Items per page.

- `public_only: Optional[bool]`

  Only include models that are publicly available.

- `usecases: Optional[List[Literal["MODEL_USECASE_UNKNOWN", "MODEL_USECASE_AGENT", "MODEL_USECASE_FINETUNED", 4 more]]]`

  Include only models defined for the listed usecases.

  - MODEL_USECASE_UNKNOWN: The use case of the model is unknown
  - MODEL_USECASE_AGENT: The model maybe used in an agent
  - MODEL_USECASE_FINETUNED: The model maybe used for fine tuning
  - MODEL_USECASE_KNOWLEDGEBASE: The model maybe used for knowledge bases (embedding models)
  - MODEL_USECASE_GUARDRAIL: The model maybe used for guardrails
  - MODEL_USECASE_REASONING: The model usecase for reasoning
  - MODEL_USECASE_SERVERLESS: The model usecase for serverless inference

  - `"MODEL_USECASE_UNKNOWN"`

  - `"MODEL_USECASE_AGENT"`

  - `"MODEL_USECASE_FINETUNED"`

  - `"MODEL_USECASE_KNOWLEDGEBASE"`

  - `"MODEL_USECASE_GUARDRAIL"`

  - `"MODEL_USECASE_REASONING"`

  - `"MODEL_USECASE_SERVERLESS"`

### Returns

- `class ModelListResponse: …`

  A list of models

  - `links: Optional[APILinks]`

    Links to other pages

    - `pages: Optional[Pages]`

      Information about how to reach other pages

      - `first: Optional[str]`

        First page

      - `last: Optional[str]`

        Last page

      - `next: Optional[str]`

        Next page

      - `previous: Optional[str]`

        Previous page

  - `meta: Optional[APIMeta]`

    Meta information about the data set

    - `page: Optional[int]`

      The current page

    - `pages: Optional[int]`

      Total number of pages

    - `total: Optional[int]`

      Total amount of items over all pages

  - `models: Optional[List[APIModel]]`

    The models

    - `id: Optional[str]`

      Human-readable model identifier

    - `agreement: Optional[APIAgreement]`

      Agreement Description

      - `description: Optional[str]`

      - `name: Optional[str]`

      - `url: Optional[str]`

      - `uuid: Optional[str]`

    - `created_at: Optional[datetime]`

      Creation date / time

    - `is_foundational: Optional[bool]`

      True if it is a foundational model provided by do

    - `name: Optional[str]`

      Display name of the model

    - `parent_uuid: Optional[str]`

      Unique id of the model, this model is based on

    - `updated_at: Optional[datetime]`

      Last modified

    - `upload_complete: Optional[bool]`

      Model has been fully uploaded

    - `url: Optional[str]`

      Download url

    - `uuid: Optional[str]`

      Unique id

    - `version: Optional[APIModelVersion]`

      Version Information about a Model

      - `major: Optional[int]`

        Major version number

      - `minor: Optional[int]`

        Minor version number

      - `patch: Optional[int]`

        Patch version number

### Example

```python
from gradient import Gradient

client = Gradient()
models = client.agents.evaluation_metrics.models.list()
print(models.links)
```