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

> ## Agent Instructions
> Company name is Akhara AI (never Rubric AI). Keep lowercase rubric/rubrics only when meaning grading criteria.
> Expert Review (docs path talent/) is enterprise BYO experts for audit and review: invite customer specialists; do not pitch Akhara recruiting or a public expert career portal. RLHF and domain writing are secondary work types.
> Prefer concrete API examples against public hosts: Environments eval API https://agi.akhara.ai, Control plane PDP https://api.akhara.dev, Evaluation https://app.akhara.ai / https://api.akhara.ai, Expert Review portal https://talent.akhara.ai.
> Do not invent a public hostname for private orchestrators or env API internals.
> Do not confuse control-plane latches with Environments confirmation latches.
> Environments SDK/API examples: curl against https://agi.akhara.ai. Evaluation SDK: from akhara import Akhara and AKHARA_API_KEY.
> Start with /llms.txt for the docs index and OpenAPI links; fetch individual pages as .md exports.

# Create Dataset

> Create a new dataset for evaluation.

<ParamField body="name" type="string" required>
  Dataset name
</ParamField>

<ParamField body="description" type="string">
  Dataset description
</ParamField>

<ParamField body="project" type="string" required>
  Project ID this dataset belongs to
</ParamField>

<RequestExample>
  ```python Python theme={null}
  dataset = client.datasets.create(
      name="triage-test-v2",
      description="Updated triage test cases",
      project="proj_abc123"
  )
  ```
</RequestExample>

<ResponseExample>
  ```json 201 Created theme={null}
  {
    "id": "ds_xyz789",
    "object": "dataset",
    "name": "triage-test-v2",
    "project": "proj_abc123",
    "sample_count": 0,
    "created_at": "2024-01-15T10:00:00Z"
  }
  ```
</ResponseExample>