Add test for return_full_text when saving prompt_template#19148
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BenWilson2 merged 2 commits intomlflow:masterfrom Dec 4, 2025
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Add test for return_full_text when saving prompt_template#19148BenWilson2 merged 2 commits intomlflow:masterfrom
BenWilson2 merged 2 commits intomlflow:masterfrom
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@ingo-stallknecht Thank you for the contribution! Could you fix the following issue(s)? ⚠ DCO checkThe DCO check failed. Please sign off your commit(s) by following the instructions here. See https://github.com/mlflow/mlflow/blob/master/CONTRIBUTING.md#sign-your-work for more details. |
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Signed-off-by: Ingo Stallknecht <ingostallknecht@gmail.com>
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I’ve amended the last commit and force-pushed to retrigger CI. |
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Small nit - once addressed, we'll merge! Thanks for adding this :)
Co-authored-by: Ben Wilson <39283302+BenWilson2@users.noreply.github.com> Signed-off-by: Ingo Stallknecht <ingostallknecht@gmail.com>
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Done. |
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Signed-off-by: Ingo Stallknecht <ingostallknecht@gmail.com> Co-authored-by: Ben Wilson <39283302+BenWilson2@users.noreply.github.com>
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Signed-off-by: Ingo Stallknecht <ingostallknecht@gmail.com> Co-authored-by: Ben Wilson <39283302+BenWilson2@users.noreply.github.com>
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Related Issues/PRs
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What changes are proposed in this pull request?
This PR adds a small unit test to
tests/transformers/test_transformers_model_export.py.The test verifies that calling
mlflow.transformers.log_modelwith aprompt_templatecorrectly setsreturn_full_text=Falsefor text-generation pipelines.This mirrors the documented behavior and protects against regressions.
Only one file is touched and the change is minimal by design.
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?