Temporarily pin pydantic in CI due to 2.5.0 breaking changes #10372
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Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
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Thanks Ben! This is related to CI failure like this right? https://github.com/mlflow/mlflow/actions/runs/6855589269/job/18640949043?pr=10362
precisely :D |
| # The pydantic pin below is temporary until FastAPI releases a compatible build for the | ||
| # changes introduced in the 2.5.0 pydantic release. |
| @@ -31,7 +31,10 @@ jobs: | |||
| - uses: ./.github/actions/untracked | |||
| - uses: ./.github/actions/setup-python | |||
| - name: Install dependencies | |||
| # The pydantic pin below is temporary until FastAPI releases a compatible build for the | |||
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That's where the actual Exception is raised from (including a type that is no longer supported in the fields module within pydantic)
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That's where the actual Exception is raised from
link?
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Is there an issue in the fastapi repo related to this?
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Merging to unblock other PRs. We can update the comment as a follow-up if necessary. |
…10372) Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com> Signed-off-by: swathi <konakanchi.swathi@gmail.com>
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#xxxWhat changes are proposed in this pull request?
Temporarily pins pydantic due to 2.5.0 breaking changes
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area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/gateway: AI Gateway service, Gateway client APIs, third-party Gateway integrationsarea/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 notes