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Signed-off-by: Subodh Bansode <[email protected]>
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Install mlflow from this PR
Install mlflow from this PR# mlflow
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/26432/merge
# mlflow-skinny
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/26432/merge#subdirectory=libs/skinnyFor Databricks, use the following command: %sh curl -LsSf https://raw.githubusercontent.com/mlflow/mlflow/HEAD/dev/install-skinny.sh | sh -s pull/26432/mergePR author's recent activityIn the last 14 days, @Subodh-17 opened 17 PRs across 10 repos:
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This PR was automatically closed because #26387 is assigned to @Amazinghorseli, @aaronteo-db. If you believe this was done in error, please reach out to a maintainer. Please do not force-push to or delete the PR branch so this PR can be reopened. |
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Related Issues/PRs
Closes #26387
What changes are proposed in this pull request?
Fix MCP server version filter normalization so that occurrences of
versionLIKEandversionILIKEinside quoted string literals are not incorrectly rewritten as theversionidentifier.The fix moves the normalization to the token level in
SearchMCPServerVersionUtils, following the existing token-level handling used bySearchMCPAccessEndpointUtils. Quoted string literals are therefore left unchanged while the bareversionidentifier retains its existing normalization behavior.Regression coverage verifies single- and double-quoted literals, affected
versionLIKE/versionILIKEvalues, filter ordering, comparison operators, and both workspace modes.How is this PR tested?
Does this PR require documentation update?
Does this PR require updating the MLflow Skills repository?
Release Notes
Is this a user-facing change?
Fixes MCP server version searches when quoted server-name filter values contain
versionLIKEorversionILIKE; quoted literals are no longer rewritten during version-filter normalization.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 notesIs this PR a critical bugfix or security fix that should go into the next patch release?
What is a minor/patch release?