Introduction In the just released Apache Camel 4.10 LTS, AI-related components have been further enhanced. Among others, three new components related to AI model serving have been added. 1 TorchServe component TensorFlow Serving component KServe component My previous article Apache Camel AI: Leverage power of AI with DJL component demonstrated how the DJL component can be used to perform AI model inference within the Camel routes. Starting from 4.10, in addition to the in-route inference by DJL, these new components will allow the Camel routes to invoke external model servers to perform inference.

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CAMELAI

Apache Camel 4.10 LTS has just been released. This release introduces a set of new features and noticeable improvements that we will cover in this blog post. Camel Core Added customize to RouteBuilder to make it easier to configure a specific Camel component / dataformat, service in a Java lambda style, such as follows: @Override public void configure() throws Exception { customize(KServeComponent.class, k -> { k.getConfiguration().setTarget("localhost:8888"); }); from("timer:kserve?repeatCount=1") .to("kserve:model/metadata?modelName=myModel") .log("${body}"); } This makes it possible for low-code users that want to have a single Java file with the Camel route and all the Java based configuration done entirely from the same configure method.

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RELEASES

The Camel community announces the immediate availability of the Camel 4.10.0 LTS release with 214 new features and improvements. The artifacts are published and ready for you to download from the Central Maven repository. For more details please take a look at the release notes. Many thanks to all who made this release possible. On behalf of the Camel PMC, Gregor Zurowski

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RELEASES