damjad opened a new pull request, #29217:
URL: https://github.com/apache/flink/pull/29217
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## What is the purpose of the change
Triton Inference Server's KServe V2 protocol treats tensor names as
**case-sensitive**. A model
configured with `input` / `output` tensors in its `config.pbtxt` rejects
requests that send
`INPUT` / `OUTPUT`, returning HTTP 400 `unexpected inference output
'OUTPUT'`.
`TritonInferenceModelFunction.buildInferenceRequest()` unconditionally
uppercased both tensor names:
```java
// Before (buggy):
inputNode.put("name", inputName.toUpperCase());
outputNode.put("name", outputName.toUpperCase());
```
This caused every request to a model with lowercase tensor names to fail at
the network layer.
## Brief change log
- Remove .toUpperCase() from the input tensor name assignment in
buildInferenceRequest()
- Remove .toUpperCase() from the output tensor name assignment in
buildInferenceRequest()
- Add TritonTensorNameCasingTest — two MockWebServer-backed integration
tests that capture the outgoing HTTP request and assert the name fields in
inputs and outputs match the column names declared in the model schema without
any case transformation
## Verifying this change
This change added tests and can be verified as follows:
- TritonTensorNameCasingTest#testLowercaseTensorNamesArePreserved — columns
named input/output produce "name":"input" / "name":"output" in the JSON body
- TritonTensorNameCasingTest#testMixedCaseTensorNamesArePreserved — columns
named myInput/myOutput are also sent unchanged
- Tests fail when .toUpperCase() is re-introduced (expected: "input" but
was: "INPUT")
- Manually verified against a live Triton endpoint (torch-model with
lowercase tensors): HTTP 400 → HTTP 200
## 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): no
- The serializers: no
- The runtime per-record code paths (performance sensitive): no
- Anything that affects how connectors interact with Flink: no
- The SQL / Table API: no
- Core ML / Model inference (flink-model-triton): yes
## Documentation
No public API or configuration changes. The fix aligns behaviour with the
KServe V2 specification,
which defines tensor names as opaque strings whose casing is determined by
the model's
config.pbtxt
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