Enable running scorers/judges from trace details drawer in UI#20518
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danielseong1 merged 1 commit intomlflow:masterfrom Feb 2, 2026
Merged
Enable running scorers/judges from trace details drawer in UI#20518danielseong1 merged 1 commit intomlflow:masterfrom
danielseong1 merged 1 commit intomlflow:masterfrom
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Enable the `isEvaluatingTracesInDetailsViewEnabled` feature flag to allow users to run evaluation scorers directly from the trace details drawer in the traces UI. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> Signed-off-by: Daniel Seong <daniel.leem.seong@gmail.com>
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Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Enable the
isEvaluatingTracesInDetailsViewEnabledfeature flag to allow users to run evaluation scorers directly from the trace details drawer in the traces UI.This change enables the "Run Judge" button in the assessments pane of the trace details drawer, allowing users to evaluate individual traces using configured scorers without navigating away from the trace view.
How is this PR tested?
Manually verified that the "Run Judge" button appears in the trace details drawer when viewing traces.
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
Users can now run evaluation scorers directly from the trace details drawer in the traces UI, enabling quick evaluation of individual traces without navigating to the scorers page.
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/tracking: Tracking Service, tracking client APIs, autologgingarea/models: MLmodel format, model serialization/deserialization, flavorsarea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflowsarea/gateway: MLflow AI Gateway client APIs, server, and third-party integrationsarea/prompts: MLflow prompt engineering features, prompt templates, and prompt managementarea/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionalityarea/projects: MLproject format, project running backendsarea/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesHow should the PR be classified in the release notes? Choose one:
rn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notesShould this PR be included in the next patch release?
🤖 Generated with Claude Code