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API Reference
Datasets

Start an augmentation run (or estimate cost)

datasets.run(strdataset_id, DatasetRunParams**kwargs) -> DatasetRunResponse
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
dataset_id: str
brand_controls: Optional[BrandControls]

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

hallucination_mitigation: Optional[bool]

Enable web-search grounding to reduce hallucinations in generated completions

length: Optional[Literal["minimal", "concise", "detailed", "extensive"]]

Target response length. Controls verbosity of generated completions.

One of the following:
"minimal"
"concise"
"detailed"
"extensive"
safety_categories: Optional[SequenceNotStr[str]]

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

column_mapping: Optional[ColumnMapping]

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

prompt: str

Column to use as the prompt/instruction field

chat: Optional[str]

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

completion: Optional[str]

Column to use as the completion/response field

context: Optional[SequenceNotStr[str]]

Columns to include as context

estimate: Optional[bool]

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

job_specification: Optional[JobSpecification]

Job execution parameters

idempotency_key: Optional[str]

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

max_rows: Optional[float]

Maximum number of rows to process in this run

minimum1
recipe_specification: Optional[RecipeSpecification]

Augmentation recipe configuration. Omitted recipes use backend defaults.

recipes: Optional[RecipeSpecificationRecipes]

Augmentation recipe toggles. Omitted recipes use backend defaults.

deduplication: Optional[bool]

Remove near-duplicate rows

preference_pairs: Optional[bool]

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

prompt_metadata_injection: Optional[bool]

Inject context and constraints into prompts

prompt_rephrase: Optional[bool]

Rephrase prompts for variety and clarity

reasoning_traces: Optional[bool]

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

version: Optional[str]

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

ReturnsExpand Collapse
class DatasetRunResponse: …
estimate: bool

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

estimated_credits_consumed: float

Estimated number of credits that will be consumed by this run

estimated_minutes: float

Estimated processing time in minutes

run_id: Optional[str]

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

Start an augmentation run (or estimate cost)

import os
from adaption import Adaption

client = Adaption(
    api_key=os.environ.get("ADAPTION_API_KEY"),  # This is the default and can be omitted
)
response = client.datasets.run(
    dataset_id="dataset_id",
)
print(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"
}