Fix litellm autolog for versions >= 1.78#19459
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harupy merged 1 commit intomlflow:masterfrom Dec 17, 2025
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Pull request overview
This PR fixes a compatibility issue with litellm versions >= 1.78 where the success_handler callback is wrapped in a function named "run" instead of being submitted directly to the thread pool executor. The fix ensures MLflow traces are captured correctly by updating the executor patch to recognize both function names.
- Updated function name detection to check for both "success_handler" (< 1.78) and "run" (>= 1.78)
- Added inline comments explaining the version-specific behavior
- Tested with both litellm 1.75.9 and 1.80.10
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In litellm >= 1.78, the success_handler callback is wrapped in a function named 'run' instead of being submitted directly. Update the executor patch to check for both function names to ensure callbacks are run synchronously in all supported versions. Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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WeichenXu123
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Dec 19, 2025
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
WeichenXu123
pushed a commit
that referenced
this pull request
Dec 19, 2025
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Fix litellm autolog compatibility with litellm >= 1.78.
In litellm >= 1.78, the
success_handlercallback is wrapped in a function namedruninstead of being submitted directly to the thread pool executor. MLflow's patch was only checking for"success_handler", causing callbacks to run asynchronously and traces to not be available immediately after completion calls.This PR updates the executor patch to check for both
"success_handler"(litellm < 1.78) and"run"(litellm >= 1.78) function names.How is this PR tested?
Tested with both litellm 1.75.9 and 1.80.10:
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
Fix litellm autolog compatibility with litellm versions >= 1.78, ensuring traces are correctly captured.
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.
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