TensorFlow Serving

Provide access to TensorFlow Serving model servers to run inference with TensorFlow saved models remotely

Metadata

Property	Value
Scheme	`tensorflow-serving`
Support Level	Preview
Labels	ai
Version	4.10.2

Maven Dependency

<dependency>
    <groupId>org.apache.camel</groupId>
    <artifactId>camel-tensorflow-serving</artifactId>
    <version>4.10.2</version>
</dependency>

Endpoint Properties

Name	Type	Required	Default	Description
`api`	string	✓		The TensorFlow Serving API
`modelName`	string			Required servable name.
`modelVersion`	integer			Optional choice of which version of the model to use. Use this specific version number.
`modelVersionLabel`	string			Optional choice of which version of the model to use. Use the version associated with the given label.
`signatureName`	string			A named signature to evaluate. If unspecified, the default signature will be used.
`target`	string		`localhost:8500`	The target URI of the client. See: https://grpc.github.io/grpc-java/javadoc/io/grpc/Grpc.html#newChannelBuilder%28java.lang.String,io.grpc.ChannelCredentials%29
`lazyStartProducer`	boolean		`false`	Whether the producer should be started lazy (on the first message). By starting lazy you can use this to allow CamelContext and routes to startup in situations where a producer may otherwise fail during starting and cause the route to fail being started. By deferring this startup to be lazy then the startup failure can be handled during routing messages via Camel's routing error handlers. Beware that when the first message is processed then creating and starting the producer may take a little time and prolong the total processing time of the processing.
`credentials`	object			The credentials of the client.