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FEAT GUI: Accept exact seed selections in scenario requests

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
35/100
Tipo de issue
Nueva funcionalidad
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
python
Área
api, backend, databases

Línea de trabajo

Start with pyrit\models\catalog\scenario.py, pyrit\backend\services\scenario_configuration_resolver.py, the scenario estimate/run services, and pyrit\scenario\core\dataset_configuration.py. Trace how shared estimate and run inputs are resolved, then use the existing framework/model/scenario/database tests to cover exact selections, stale or conflicting references, provenance, read-only estimates, and SQLite/Azure SQL-compatible access.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

feature-request GUI not ready yet
Is your feature request related to a problem? Please describe.

A user selecting a few examples in the explorer must run exactly those examples. Current scenario requests expose dataset names, caps, and a small filter set, not an explicit selected-example contract. Reconstructing a selection from broad filters could run different data.

Work item 13 of 17 in #2744. Technical prerequisites: item 2's stable seed/group IDs and the scorer-preset contract from item 12. Release sequencing: keep not ready yet until both #2756 (the main explorer/provider-loading track) and #2755 (the parallel scorer API) are complete and the maintainer promotes this item. Completing #2755 early does not release this item ahead of the remaining explorer work.

Describe the solution you'd like

Extend the shared estimate/run models and configuration resolver with a bounded, typed explicit-selection input resolved from existing memory.

  • Select complete logical examples by stable references. Resolve canonical content on the backend; do not trust arbitrary browser-supplied file paths or rebuild membership from a dataset name alone.
  • Preserve group membership, roles, order, source seed IDs, and existing provenance. Reuse DatasetAttackConfiguration's explicit seed/seed-group input where appropriate.
  • Make explicit selection mutually exclusive with conflicting dataset-name/filter/sampling overrides. Do not silently apply a scenario's default cap or random sample to an explicit selection.
  • Include the selected configured scorer reference and explicit objective inputs needed by the later scenario adapter, without serializing arbitrary component instances in the request.
  • Use the same effective selection/configuration for preview, estimate, and launch. Detect missing, changed, or invalid examples and ask the user to refresh rather than silently dropping rows or expanding to a whole dataset.
  • Preserve selected-input provenance using existing scenario/result mechanisms; do not create a new persistent dataset per selection.

Acceptance criteria:

  • Selecting N examples yields those same N logical examples in resolution, with linked media intact.
  • Invalid/duplicate/missing references and conflicting selection modes have defined, tested behavior.
  • Default dataset caps and filters cannot silently change an explicit selection.
  • Estimate resolution is read-only and does not fetch providers, persist seeds, or invoke models.
  • Existing named-dataset request behavior remains compatible.
  • Contract/resolver tests cover mixed examples, stale selection, provenance, and SQLite/Azure SQL-compatible memory access.
Describe alternatives you've considered, if relevant

Do not send an entire dataset to the browser, encode selections as arbitrary Python/opaque dataset_config objects, duplicate selected seeds into a new dataset, or add memory migrations. This item defines/resolves inputs; the scenario implementation is item 14.

Additional context

Start with pyrit\models\catalog\scenario.py, pyrit\backend\services\scenario_configuration_resolver.py, scenario estimate/run services, and pyrit\scenario\core\dataset_configuration.py. DATASET_FILTERS currently exposes harm_categories and data_types; exact selection needs an intentional shared contract. Follow framework/model/scenario/database/test instructions.

Lenguaje dominante
Python
Estrellas
4.5k
Forks
896
Merge medio
2 d 19 h
PR fusionados (30 d)
206

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