Create dataset

curl --request POST \
  --url https://console.sqwish.ai/v1/datasets \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "examples": [
    {
      "context": "<string>",
      "decisions": [
        {
          "id": "<string>",
          "question": "<string>",
          "kind": "single",
          "outcomes": "<unknown>",
          "rubric": [
            "<unknown>"
          ],
          "weights": {},
          "costs": {},
          "abstain": {
            "min_probability": 0.5,
            "cost": 123
          }
        }
      ],
      "model": "<string>",
      "independent": false,
      "store": true,
      "metadata": {},
      "targets": {},
      "rewards": {}
    }
  ]
}
'

import requests

url = "https://console.sqwish.ai/v1/datasets"

payload = {
    "name": "<string>",
    "examples": [
        {
            "context": "<string>",
            "decisions": [
                {
                    "id": "<string>",
                    "question": "<string>",
                    "kind": "single",
                    "outcomes": "<unknown>",
                    "rubric": ["<unknown>"],
                    "weights": {},
                    "costs": {},
                    "abstain": {
                        "min_probability": 0.5,
                        "cost": 123
                    }
                }
            ],
            "model": "<string>",
            "independent": False,
            "store": True,
            "metadata": {},
            "targets": {},
            "rewards": {}
        }
    ]
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: '<string>',
    examples: [
      {
        context: '<string>',
        decisions: [
          {
            id: '<string>',
            question: '<string>',
            kind: 'single',
            outcomes: '<unknown>',
            rubric: ['<unknown>'],
            weights: {},
            costs: {},
            abstain: {min_probability: 0.5, cost: 123}
          }
        ],
        model: '<string>',
        independent: false,
        store: true,
        metadata: {},
        targets: {},
        rewards: {}
      }
    ]
  })
};

fetch('https://console.sqwish.ai/v1/datasets', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "id": "<string>",
  "name": "<string>",
  "created_at": 123,
  "sha256": "<string>",
  "status": "validated",
  "rows": 123,
  "contexts": 123,
  "duplicates_removed": 123,
  "method": "sft",
  "augmentation": "none",
  "deleted_at": 123,
  "input": {
    "format": "json",
    "sha256": "<string>",
    "bytes": 123
  },
  "labeling": {
    "job_id": "<string>",
    "source_id": "<string>",
    "source_sha256": "<string>",
    "source_input_sha256": "<string>",
    "spec_sha256": "<string>",
    "prompt_version": "<string>",
    "teacher_models": [
      "<string>"
    ],
    "row_indices": [
      123
    ],
    "selection_sha256": "<string>",
    "target_method": "mean_one_hot_teacher_votes"
  },
  "source": "<string>",
  "metadata_filter": {}
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "retryable": true,
    "request_id": "<string>",
    "details": [
      {
        "path": [
          "<string>"
        ],
        "message": "<string>",
        "type": "<string>"
      }
    ]
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "retryable": true,
    "request_id": "<string>",
    "details": [
      {
        "path": [
          "<string>"
        ],
        "message": "<string>",
        "type": "<string>"
      }
    ]
  }
}