Fix double callback injection issue with LangChain streaming #12037
Conversation
github-actions
bot
added
area/tracking
|
Documentation preview for d865263 will be available when this CircleCI job More info
|
| assert ( | ||
| sum(isinstance(handler, MlflowLangchainTracer) for handler in callbacks.handlers) == 1 | ||
| ) |
There was a problem hiding this comment.
This was previously 2, which was an error.
Technically, we shouldn't be mutating the list of callbacks that the user provides to the stream() call. In the interest of time, I'm adjusting this test for now and will file a ticket for fixing the erroneous modification of the user's callback list and adjust the test case
| if not _is_new_callback_already_in_original_callbacks( | ||
| callback, original_callbacks.handlers | ||
| ): | ||
| original_callbacks.add_handler(callback) |
There was a problem hiding this comment.
We shouldn't be modifying original_callbacks either. Filed a follow-up ticket to fix that (autologging patch safety tooling doesn't allow a copy of the object to be used; we need to add an exemption for that)
dbczumar
changed the title
Signed-off-by: Corey Zumar <39497902+dbczumar@users.noreply.github.com>
|
@mlflow-automation autoformat |
Signed-off-by: mlflow-automation <mlflow-automation@users.noreply.github.com>
|
Failures are unrelated. Merging. |
馃洜 DevTools 馃洜
Install mlflow from this PR
Checkout with GitHub CLI
Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Fix double callback injection issue with LangChain streaming
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/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrationsarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow 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.