[Workspace] Small improvements#20290
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B-Step62 merged 2 commits intomlflow:orgnization-supportfrom Jan 29, 2026
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Some references still used /api/2.0 even though they should be 3.0. Signed-off-by: mprahl <mprahl@users.noreply.github.com>
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Documentation preview for 546d173 is available at: Changed Pages (2)
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LGTM with a minor suggestion to field name
mlflow/utils/workspace_context.py
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| from mlflow.utils.workspace_utils import DEFAULT_WORKSPACE_NAME | ||
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| _WORKSPACE: ContextVar[str | None] = ContextVar("mlflow_active_workspace", default=None) | ||
| _WORKSPACE_RESOLVED: ContextVar[bool] = ContextVar("mlflow_workspace_resolved", default=False) |
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| _WORKSPACE_RESOLVED: ContextVar[bool] = ContextVar("mlflow_workspace_resolved", default=False) | |
| _IS_WORKSPACE_RESOLVED: ContextVar[bool] = ContextVar("mlflow_workspace_resolved", default=False) |
nit: the original name may be a bit confusing with resolved workspace name.
Prior to this, the FastAPI workspace middleware tried to detect if it was a Flask route. Rather than keep this list up to date, this just always has the FastAPI workspace middleware resolve it and the Flask handler only sets it when FastAPI is not enabled (e.g. gunicorn). Signed-off-by: mprahl <mprahl@users.noreply.github.com>
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Related Issues/PRs
#1464
#5844
Design document: https://docs.google.com/document/d/1IbFfceCmWV3knJfc0ninn58EXLVbHUh1meV_pknOM40/edit
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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?
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