Datasets - Braintrust

Dataset Structure

Each record has four top-level fields:

• input: Data to recreate the example in your application (required).
• expected: Ideal output or ground truth (optional but recommended for evaluation).
• metadata: Key-value pairs for filtering and grouping (optional).
• tags: Labels for organizing and filtering records (optional).

Where to go from here

• Create datasets from uploads, the SDK, production logs, user feedback, traces, or Loop.
• Build dataset pipelines to transform project logs into dataset rows in bulk.
• Manage datasets — tag and star, save snapshots, define schemas, customize table views, and edit records.
• Use in evaluations by passing datasets to Eval(), assigning them to environments, or converting experiment results.
• Track performance to see which experiments used a dataset and how each row performs.

For human review workflows on dataset records, see Human review and Custom views.