gemini-code-assist[bot] commented on code in PR #37471:
URL: https://github.com/apache/beam/pull/37471#discussion_r2760685783
##########
sdks/java/ml/inference/remote/src/main/java/org/apache/beam/sdk/ml/inference/remote/RetryHandler.java:
##########
@@ -82,13 +77,12 @@ public <T> T execute(RetryableRequest<T> request) throws
Exception {
if (backoffMillis == BackOff.STOP) {
LOG.error("Request failed after {} retry attempts.", attempt);
throw new RuntimeException(
- "Request failed after exhausting retries. " +
- "Max retries: " + maxRetries + ", " ,
- lastException);
+ "Request failed after exhausting retries. " + "Max retries: " +
maxRetries + ", ",
+ lastException);
}
attempt++;
- LOG.warn("Retry request attempt {} failed with: {}. Retrying in {}
ms", attempt, e.getMessage(), backoffMillis);
+ LOG.warn("Retry request attempt {} failed. Retrying in {} ms",
attempt, backoffMillis, e);
Review Comment:
While logging the full exception is a great improvement for debugging, the
log message itself has lost some useful context by removing the exception
message. You can include both the message for quick scanning and the full stack
trace for deep dives.
```suggestion
LOG.warn("Retry request attempt {} failed with: {}. Retrying in {}
ms", attempt, e.getMessage(), backoffMillis, e);
```
##########
sdks/java/ml/inference/openai/src/test/java/org/apache/beam/sdk/ml/inference/openai/OpenAIModelHandlerIT.java:
##########
@@ -252,33 +292,40 @@ public void testWithDifferentModel() {
// Test with a different model
String input = "Explain quantum computing in one sentence.";
- PCollection<OpenAIModelInput> inputs = pipeline
- .apply("CreateInput", Create.of(input))
- .apply("MapToInput", MapElements
- .into(TypeDescriptor.of(OpenAIModelInput.class))
- .via(OpenAIModelInput::create));
-
- PCollection<Iterable<PredictionResult<OpenAIModelInput,
OpenAIModelResponse>>> results = inputs
- .apply("DifferentModelInference",
- RemoteInference.<OpenAIModelInput, OpenAIModelResponse>invoke()
- .handler(OpenAIModelHandler.class)
- .withParameters(OpenAIModelParameters.builder()
- .apiKey(apiKey)
- .modelName("gpt-5")
- .instructionPrompt("Respond concisely")
- .build()));
-
- PAssert.that(results).satisfies(batches -> {
- for (Iterable<PredictionResult<OpenAIModelInput, OpenAIModelResponse>>
batch : batches) {
- for (PredictionResult<OpenAIModelInput, OpenAIModelResponse> result :
batch) {
- assertNotNull("Output should not be null",
- result.getOutput().getModelResponse());
- assertFalse("Output should not be empty",
- result.getOutput().getModelResponse().trim().isEmpty());
- }
- }
- return null;
- });
+ PCollection<OpenAIModelInput> inputs =
+ pipeline
+ .apply("CreateInput", Create.of(input))
+ .apply(
+ "MapToInput",
+ MapElements.into(TypeDescriptor.of(OpenAIModelInput.class))
+ .via(OpenAIModelInput::create));
+
+ PCollection<Iterable<PredictionResult<OpenAIModelInput,
OpenAIModelResponse>>> results =
+ inputs.apply(
+ "DifferentModelInference",
+ RemoteInference.<OpenAIModelInput, OpenAIModelResponse>invoke()
+ .handler(OpenAIModelHandler.class)
+ .withParameters(
+ OpenAIModelParameters.builder()
+ .apiKey(apiKey)
+ .modelName("gpt-5")
Review Comment:
The `gpt-5` model does not exist, which will cause this test to fail with an
API error. However, the test asserts a successful outcome. To fix this, please
use a valid and available OpenAI model. For example, you could use
`gpt-4-turbo` if you want to test a different model from the default
`gpt-4o-mini`.
```suggestion
.modelName("gpt-4-turbo")
```
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