[Workspace] Propagate workspace context through REST APIs#19282
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BenWilson2 merged 1 commit intomlflow:orgnization-supportfrom Dec 10, 2025
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[Workspace] Propagate workspace context through REST APIs#19282BenWilson2 merged 1 commit intomlflow:orgnization-supportfrom
BenWilson2 merged 1 commit intomlflow:orgnization-supportfrom
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| # Workspace mode relies on a workspace provider to resolve the default workspace and seed | ||
| # request context. Artifact-only servers never load that stack, so they cannot determine | ||
| # the active workspace safely. This decision can be revisited in the future. | ||
| raise click.UsageError("--enable-workspaces cannot be combined with --artifacts-only.") |
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I think this fine to leave for future work if requested. The very nature of this feature stack seems like running an artifacts-only server seems like it's not common for where users would run in this mode.
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Thanks for the work here, Matt! This looks great :)
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Add Flask and FastAPI middleware to resolve the active workspace and set the workspace context. This allows workspace aware stores to directly leverage this without resolving it themselves. Artifact serving is also isolated by workspace when enabled. Also enhance the server CLI with workspace configuration options. This also includes a few fixes after the rebase to the master branch. Signed-off-by: mprahl <mprahl@users.noreply.github.com>
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🛠 DevTools 🛠
Install mlflow from this PR
For Databricks, use the following command:
Related Issues/PRs
#1464
#5844
Design document: https://docs.google.com/document/d/1IbFfceCmWV3knJfc0ninn58EXLVbHUh1meV_pknOM40/edit
What changes are proposed in this pull request?
Add Flask and FastAPI middleware to resolve the active workspace and set the workspace context. This allows workspace aware stores to directly leverage this without resolving it themselves. Artifact serving is also isolated by workspace when enabled.
Also enhance the server CLI with workspace configuration options.
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
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?
Yesshould be selected for bug fixes, documentation updates, and other small changes.Noshould be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.What is a minor/patch release?
Bug fixes, doc updates and new features usually go into minor releases.
Bug fixes and doc updates usually go into patch releases.