Update the connector pipeline

PUT /_connector/{connector_id}/_pipeline

Api key auth Basic auth Bearer auth

When you create a new connector, the configuration of an ingest pipeline is populated with default settings.

Path Parameters

connector_id string Id required: The unique identifier of the connector to be updated

Request

pipeline {} IngestPipelineParams required

Response

application/json

Examples

Request Console 1 / 7 languages

Console Kibana Dev Tools

PUT _connector/my-connector/_pipeline
{
    "pipeline": {
        "extract_binary_content": true,
        "name": "my-connector-pipeline",
        "reduce_whitespace": true,
        "run_ml_inference": true
    }
}

JavaScript Elasticsearch JavaScript Client

const response = await client.connector.updatePipeline({
  connector_id: "my-connector",
  pipeline: {
    extract_binary_content: true,
    name: "my-connector-pipeline",
    reduce_whitespace: true,
    run_ml_inference: true,
  },
});

Python Elasticsearch Python Client

resp = client.connector.update_pipeline(
    connector_id="my-connector",
    pipeline={
        "extract_binary_content": True,
        "name": "my-connector-pipeline",
        "reduce_whitespace": True,
        "run_ml_inference": True
    },
)

curl Shell

curl -X PUT "$ELASTICSEARCH_URL/_connector/my-connector/_pipeline" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "pipeline": {
      "extract_binary_content": true,
      "name": "my-connector-pipeline",
      "reduce_whitespace": true,
      "run_ml_inference": true
    }
  }'

Java Elasticsearch Java Client

client.connector().updatePipeline(u -> u
    .connectorId("my-connector")
    .pipeline(p -> p
        .extractBinaryContent(true)
        .name("my-connector-pipeline")
        .reduceWhitespace(true)
        .runMlInference(true)
    )
);

PHP Elasticsearch PHP Client

$resp = $client->connector()->updatePipeline([
    "connector_id" => "my-connector",
    "body" => [
        "pipeline" => [
            "extract_binary_content" => true,
            "name" => "my-connector-pipeline",
            "reduce_whitespace" => true,
            "run_ml_inference" => true,
        ],
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.connector.update_pipeline(
  connector_id: "my-connector",
  body: {
    "pipeline": {
      "extract_binary_content": true,
      "name": "my-connector-pipeline",
      "reduce_whitespace": true,
      "run_ml_inference": true
    }
  }
)

Response

{
  "result": "updated"
}