renatoh commented on code in PR #3426:
URL: https://github.com/apache/solr/pull/3426#discussion_r2198541560
##########
solr/modules/llm/src/java/org/apache/solr/llm/textvectorisation/model/SolrTextToVectorModel.java:
##########
@@ -80,41 +84,40 @@ public static SolrTextToVectorModel getInstance(
* support, some of them may require to be handled in here as
separate switch cases
*/
switch (paramName) {
- case TIMEOUT_PARAM:
+ case TIMEOUT_PARAM -> {
Duration timeOut = Duration.ofSeconds((Long)
params.get(paramName));
builder.getClass().getMethod(paramName,
Duration.class).invoke(builder, timeOut);
- break;
- case MAX_SEGMENTS_PER_BATCH_PARAM:
- builder
- .getClass()
- .getMethod(paramName, Integer.class)
- .invoke(builder, ((Long) params.get(paramName)).intValue());
- break;
- case MAX_RETRIES_PARAM:
- builder
- .getClass()
- .getMethod(paramName, Integer.class)
- .invoke(builder, ((Long) params.get(paramName)).intValue());
- break;
+ }
+ case MAX_SEGMENTS_PER_BATCH_PARAM, MAX_RETRIES_PARAM -> builder
+ .getClass()
+ .getMethod(paramName, Integer.class)
+ .invoke(builder, ((Long) params.get(paramName)).intValue());
+
/*
* For primitive params if there's only one setter available, we
call it.
* If there's choice we default to the string one
*/
- default:
+ default -> {
ArrayList<Method> paramNameMatches = new ArrayList<>();
for (var method : builder.getClass().getMethods()) {
if (paramName.equals(method.getName()) &&
method.getParameterCount() == 1) {
paramNameMatches.add(method);
}
}
if (paramNameMatches.size() == 1) {
- paramNameMatches.get(0).invoke(builder, params.get(paramName));
+ paramNameMatches.getFirst().invoke(builder,
params.get(paramName));
} else {
- builder
- .getClass()
- .getMethod(paramName, String.class)
- .invoke(builder, params.get(paramName).toString());
+ try {
+ builder
+ .getClass()
+ .getMethod(paramName, String.class)
+ .invoke(builder, params.get(paramName).toString());
+ } catch (NoSuchMethodException e) {
+ log.error("Parameter {} not supported by model {}",
paramName, className);
Review Comment:
Implementing my own DimensionAwareEmbeddingModel, I notice that if the
attribute is not supported by the model, the error was not logged at all and I
had to debug to see what the issue was
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