auroflow opened a new pull request, #29454:
URL: https://github.com/apache/flink/pull/29454

   ## What is the purpose of the change
   
   This PR implements the model provider management described by the DataFrame 
API FLIP for [FLINK-40439](https://issues.apache.org/jira/browse/FLINK-40439).
   
   ## Brief change log
   
   - Add `ModelProvider`, typed `OpenAIProvider` and `TritonProvider` 
configurations, and `GenericProvider` for other installed Java providers.
   - Add process-wide provider registration, listing, and default selection.
   - Register Triton's existing health-check and circuit-breaker options in its 
factory so these configurations pass factory validation.
   
   ## Verifying this change
   
   This change added tests and can be verified as follows:
   
   - Add 16 pure Python tests covering option conversion, validation, 
registration, replacement, default selection, and custom providers. These tests 
require no Java gateway or MiniCluster.
   - Extend the Triton factory tests to verify acceptance of all six existing 
health-check and circuit-breaker options.
   
   ## Does this pull request potentially affect one of the following parts:
   
   - Dependencies (does it add or upgrade a dependency): no
   - The public API, i.e., is any changed class annotated with 
`@Public(Evolving)`: yes
   - The serializers: no
   - The runtime per-record code paths (performance sensitive): no
   - Anything that affects deployment or recovery: JobManager (and its 
components), Checkpointing, Kubernetes/Yarn, ZooKeeper: no
   - The S3 file system connector: no
   
   ## Documentation
   
   - Does this pull request introduce a new feature? yes
   - If yes, how is the feature documented? PyFlink API docstrings, examples, 
and reference page.
   
   ---
   
   ##### Was generative AI tooling used to co-author this PR?
   
   - [X] Yes (please specify the tool below)
   
   Generated-by: Codex (GPT-6)


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