## Create a new Evaluation

`ai_gateway.evaluations.create(strgateway_id, EvaluationCreateParams**kwargs)  -> EvaluationCreateResponse`

**post** `/accounts/{account_id}/ai-gateway/gateways/{gateway_id}/evaluations`

Creates a new AI Gateway.

### Parameters

- `account_id: str`

- `gateway_id: str`

  gateway id

- `dataset_ids: SequenceNotStr[str]`

- `evaluation_type_ids: SequenceNotStr[str]`

- `name: str`

### Returns

- `class EvaluationCreateResponse: …`

  - `id: str`

  - `created_at: datetime`

  - `datasets: List[Dataset]`

    - `id: str`

    - `account_id: str`

    - `account_tag: str`

    - `created_at: datetime`

    - `enable: bool`

    - `filters: List[DatasetFilter]`

      - `key: Literal["created_at", "request_content_type", "response_content_type", 10 more]`

        - `"created_at"`

        - `"request_content_type"`

        - `"response_content_type"`

        - `"success"`

        - `"cached"`

        - `"provider"`

        - `"model"`

        - `"cost"`

        - `"tokens"`

        - `"tokens_in"`

        - `"tokens_out"`

        - `"duration"`

        - `"feedback"`

      - `operator: Literal["eq", "contains", "lt", "gt"]`

        - `"eq"`

        - `"contains"`

        - `"lt"`

        - `"gt"`

      - `value: List[Union[str, float, bool]]`

        - `str`

        - `float`

        - `bool`

    - `gateway_id: str`

      gateway id

    - `modified_at: datetime`

    - `name: str`

  - `gateway_id: str`

    gateway id

  - `modified_at: datetime`

  - `name: str`

  - `processed: bool`

  - `results: List[Result]`

    - `id: str`

    - `created_at: datetime`

    - `evaluation_id: str`

    - `evaluation_type_id: str`

    - `modified_at: datetime`

    - `result: str`

    - `status: float`

    - `status_description: str`

    - `total_logs: float`

  - `total_logs: float`

### Example

```python
import os
from cloudflare import Cloudflare

client = Cloudflare(
    api_token=os.environ.get("CLOUDFLARE_API_TOKEN"),  # This is the default and can be omitted
)
evaluation = client.ai_gateway.evaluations.create(
    gateway_id="my-gateway",
    account_id="3ebbcb006d4d46d7bb6a8c7f14676cb0",
    dataset_ids=["string"],
    evaluation_type_ids=["string"],
    name="name",
)
print(evaluation.id)
```

#### Response

```json
{
  "result": {
    "id": "id",
    "created_at": "2019-12-27T18:11:19.117Z",
    "datasets": [
      {
        "id": "id",
        "account_id": "account_id",
        "account_tag": "account_tag",
        "created_at": "2019-12-27T18:11:19.117Z",
        "enable": true,
        "filters": [
          {
            "key": "created_at",
            "operator": "eq",
            "value": [
              "string"
            ]
          }
        ],
        "gateway_id": "my-gateway",
        "modified_at": "2019-12-27T18:11:19.117Z",
        "name": "name"
      }
    ],
    "gateway_id": "my-gateway",
    "modified_at": "2019-12-27T18:11:19.117Z",
    "name": "name",
    "processed": true,
    "results": [
      {
        "id": "id",
        "created_at": "2019-12-27T18:11:19.117Z",
        "evaluation_id": "evaluation_id",
        "evaluation_type_id": "evaluation_type_id",
        "modified_at": "2019-12-27T18:11:19.117Z",
        "result": "result",
        "status": 0,
        "status_description": "status_description",
        "total_logs": 0
      }
    ],
    "total_logs": 0
  },
  "success": true
}
```