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Datasets are PromptLayer’s versioned system of record for evaluation inputs and historical examples. Use them when you want a reusable set of test cases for evaluations, backtests, regression checks, or batch workflows. A Dataset Group is the container for one dataset over time. Inside that group, you edit a draft dataset, save numbered versions, and reuse those versions across evaluations. You can create data by uploading a CSV or JSON file, building from request history, or turning evaluation outputs back into a dataset for the next iteration.

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What you can do

  • Create datasets from files, request history, or evaluation results.
  • Edit draft datasets before publishing a version, including adding rows, renaming or deleting columns, updating values, and converting columns to JSON.
  • Organize dataset groups with folders, tags, changelog history, and archive controls.
  • Reuse a specific dataset version in an evaluation blueprint, or update a blueprint to a different dataset later.
  • Export datasets to CSV and use report outputs to seed the next round of testing.

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How it fits together

  1. Create a dataset group and populate a draft.
  2. Edit the draft and save a version.
  3. Attach that version to an evaluation blueprint.
  4. Run full batches, review results and history, and feed outputs into the next dataset iteration.

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Next steps

Evaluations

Learn how datasets power evaluation blueprints, scoring, and batch runs.

Programmatic Evals

Build datasets and evaluations from code or CI workflows.

Create from File

Upload a CSV or JSON file to create a new dataset version.

Create from History

Build a dataset version from filtered request history.