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Datasets

Start an augmentation run (or estimate cost)

client.datasets.run(stringdatasetID, DatasetRunParams { brand_controls, column_mapping, estimate, 2 more } body, RequestOptionsoptions?): DatasetRunResponse { estimate, estimatedCreditsConsumed, estimatedMinutes, run_id }
POST/api/v1/datasets/{dataset_id}/run

Validates column mapping and recipe configuration, reserves credits, and starts the augmentation pipeline. Set estimate=true to validate and get a cost quote without starting a run.

ParametersExpand Collapse
datasetID: string
body: DatasetRunParams { brand_controls, column_mapping, estimate, 2 more }
brand_controls?: BrandControls

Brand and quality controls for generated completions (length, safety, hallucination grounding).

hallucination_mitigation?: boolean

Enable web-search grounding to reduce hallucinations in generated completions

length?: "minimal" | "concise" | "detailed" | "extensive"

Target response length. Controls verbosity of generated completions.

One of the following:
"minimal"
"concise"
"detailed"
"extensive"
safety_categories?: Array<string>

Content safety categories to enforce. Completions violating these are filtered.

column_mapping?: ColumnMapping

Column role assignments for augmentation. Required for real runs, optional for estimate-only requests.

prompt: string

Column to use as the prompt/instruction field

chat?: string

Column containing chat/conversation data (alternative to prompt+completion)

completion?: string

Column to use as the completion/response field

context?: Array<string>

Columns to include as context

estimate?: boolean

When true, validates the request and returns the estimated credit cost without starting a run.

job_specification?: JobSpecification

Job execution parameters

idempotency_key?: string

Client-generated idempotency key for safe retries. If a launch with the same key already exists, the original response is returned.

max_rows?: number

Maximum number of rows to process in this run

minimum1
recipe_specification?: RecipeSpecification

Augmentation recipe configuration. Omitted recipes use backend defaults.

recipes?: Recipes { deduplication, preference_pairs, prompt_metadata_injection, 2 more }

Augmentation recipe toggles. Omitted recipes use backend defaults.

deduplication?: boolean

Remove near-duplicate rows

preference_pairs?: boolean

Generate DPO-style preference pairs (chosen/rejected) instead of instruction completions

prompt_metadata_injection?: boolean

Inject context and constraints into prompts

prompt_rephrase?: boolean

Rephrase prompts for variety and clarity

reasoning_traces?: boolean

Add reasoning traces (chain-of-thought) to completions

version?: string

Recipe schema version. Allows recipe options to evolve across releases.

ReturnsExpand Collapse
DatasetRunResponse { estimate, estimatedCreditsConsumed, estimatedMinutes, run_id }
estimate: boolean

Whether this was an estimate-only request (no run started)

estimatedCreditsConsumed: number

Estimated number of credits that will be consumed by this run

estimatedMinutes: number

Estimated processing time in minutes

run_id?: string | null

Unique identifier for this pipeline run. Null for estimate-only requests.

Start an augmentation run (or estimate cost)

import Adaption from 'adaption';

const client = new Adaption({
  apiKey: process.env['ADAPTION_API_KEY'], // This is the default and can be omitted
});

const response = await client.datasets.run('dataset_id');

console.log(response.run_id);
{
  "estimate": true,
  "estimatedCreditsConsumed": 0,
  "estimatedMinutes": 0,
  "run_id": "dataset-550e8400-e29b-41d4-a716-446655440000-1712234567890"
}
Returns Examples
{
  "estimate": true,
  "estimatedCreditsConsumed": 0,
  "estimatedMinutes": 0,
  "run_id": "dataset-550e8400-e29b-41d4-a716-446655440000-1712234567890"
}