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Sequence Pipeline

Example of sequence pipeline
In this example, you'll create the configuration for a server. The same as the previous example, you'll print the configuration to demonstrate the step in details that will help you see the difference and notice the configuration contents.
  • Let's create a configuration by adding logging step in a sequence pipeline and print the output to JSON:
SequencePipeline sequencePipelineWithLoggingStep = SequencePipeline
.builder()
.add(new LoggingStep()) //add logging step into pipeline
.build();
System.out.format("----------%n" +
"Pipeline with a Logging step output%n" +
"------------%n" +
"%s%n" +
"------------%n%n",
sequencePipelineWithLoggingStep.toJson());
  • Call for default or empty inference configuration and print the output to JSON:
InferenceConfiguration defaultInferenceConfiguration = new InferenceConfiguration();
System.out.format("----------%n" +
"Default inference configuration%n" +
"------------%n" +
"%s%n" +
"------------%n%n",
defaultInferenceConfiguration.toJson());
  • Combine both to create complete configuration for a server:
InferenceConfiguration inferenceConfigurationWithPipeline = new InferenceConfiguration();
inferenceConfigurationWithPipeline.pipeline(sequencePipelineWithLoggingStep);
// Printing InferenceConfiguration in YAML
System.out.format("----------%n" +
"Inference Configuration in YAML%n" +
"------------%n" +
"%s%n" +
"------------%n%n",
inferenceConfigurationWithPipeline.toYaml());
You'll see the output similar to:
----------
Pipeline with a Logging step output
------------
{
"steps" : [ {
"@type" : "LOGGING",
"logLevel" : "INFO",
"log" : "KEYS"
} ]
}
------------
----------
Default inference configuration
------------
{
"host" : "localhost",
"port" : 0,
"useSsl" : false,
"protocol" : "HTTP",
"staticContentRoot" : "static-content",
"staticContentUrl" : "/static-content",
"staticContentIndexPage" : "/index.html",
"kafkaConfiguration" : {
"startHttpServerForKafka" : true,
"httpKafkaHost" : "localhost",
"httpKafkaPort" : 0,
"consumerTopicName" : "inference-in",
"consumerKeyDeserializerClass" : "io.vertx.kafka.client.serialization.JsonObjectDeserializer",
"consumerValueDeserializerClass" : "io.vertx.kafka.client.serialization.JsonObjectDeserializer",
"consumerGroupId" : "konduit-serving-consumer-group",
"consumerAutoOffsetReset" : "earliest",
"consumerAutoCommit" : "true",
"producerTopicName" : "inference-out",
"producerKeySerializerClass" : "io.vertx.kafka.client.serialization.JsonObjectSerializer",
"producerValueSerializerClass" : "io.vertx.kafka.client.serialization.JsonObjectSerializer",
"producerAcks" : "1"
},
"mqttConfiguration" : { },
"customEndpoints" : [ ]
}
------------
----------
Inference Configuration in YAML
------------
---
host: "localhost"
port: 0
use_ssl: false
protocol: "HTTP"
static_content_root: "static-content"
static_content_url: "/static-content"
static_content_index_page: "/index.html"
kafka_configuration:
start_http_server_for_kafka: true
http_kafka_host: "localhost"
http_kafka_port: 0
consumer_topic_name: "inference-in"
consumer_key_deserializer_class: "io.vertx.kafka.client.serialization.JsonObjectDeserializer"
consumer_value_deserializer_class: "io.vertx.kafka.client.serialization.JsonObjectDeserializer"
consumer_group_id: "konduit-serving-consumer-group"
consumer_auto_offset_reset: "earliest"
consumer_auto_commit: "true"
producer_topic_name: "inference-out"
producer_key_serializer_class: "io.vertx.kafka.client.serialization.JsonObjectSerializer"
producer_value_serializer_class: "io.vertx.kafka.client.serialization.JsonObjectSerializer"
producer_acks: "1"
mqtt_configuration: {}
custom_endpoints: []
pipeline:
steps:
- '@type': "LOGGING"
logLevel: "INFO"
log: "KEYS"
------------
Process finished with exit code 0