elasticstack.getElasticsearchIngestProcessorInference

elasticstack 0.15.0, May 14 26

Viewing docs for elasticstack 0.15.0
published on Thursday, May 14, 2026 by elastic

Helper data source which can be used to create the configuration for an inference ingest processor. The inference processor uses a pre-trained data frame analytics model or a model deployed for natural language processing tasks to infer against the data that is being ingested in the pipeline. See: https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-ingest-put-pipeline

Example Usage

import * as pulumi from "@pulumi/pulumi";
import * as elasticstack from "@pulumi/elasticstack";

const inference = elasticstack.getElasticsearchIngestProcessorInference({
    modelId: "example",
    inputOutput: {
        inputField: "body",
        outputField: "body_vector",
    },
});
const myIngestPipeline = new elasticstack.ElasticsearchIngestPipeline("my_ingest_pipeline", {
    name: "inference-ingest",
    processors: [inference.then(inference => inference.json)],
});

import pulumi
import pulumi_elasticstack as elasticstack

inference = elasticstack.get_elasticsearch_ingest_processor_inference(model_id="example",
    input_output={
        "input_field": "body",
        "output_field": "body_vector",
    })
my_ingest_pipeline = elasticstack.ElasticsearchIngestPipeline("my_ingest_pipeline",
    name="inference-ingest",
    processors=[inference.json])

package main

import (
	"github.com/pulumi/pulumi-terraform-provider/sdks/go/elasticstack/elasticstack"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		inference, err := elasticstack.GetElasticsearchIngestProcessorInference(ctx, &elasticstack.GetElasticsearchIngestProcessorInferenceArgs{
			ModelId: "example",
			InputOutput: elasticstack.GetElasticsearchIngestProcessorInferenceInputOutput{
				InputField:  "body",
				OutputField: pulumi.StringRef("body_vector"),
			},
		}, nil)
		if err != nil {
			return err
		}
		_, err = elasticstack.NewElasticsearchIngestPipeline(ctx, "my_ingest_pipeline", &elasticstack.ElasticsearchIngestPipelineArgs{
			Name: pulumi.String("inference-ingest"),
			Processors: pulumi.StringArray{
				pulumi.String(inference.Json),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Elasticstack = Pulumi.Elasticstack;

return await Deployment.RunAsync(() => 
{
    var inference = Elasticstack.GetElasticsearchIngestProcessorInference.Invoke(new()
    {
        ModelId = "example",
        InputOutput = new Elasticstack.Inputs.GetElasticsearchIngestProcessorInferenceInputOutputInputArgs
        {
            InputField = "body",
            OutputField = "body_vector",
        },
    });

    var myIngestPipeline = new Elasticstack.ElasticsearchIngestPipeline("my_ingest_pipeline", new()
    {
        Name = "inference-ingest",
        Processors = new[]
        {
            inference.Apply(getElasticsearchIngestProcessorInferenceResult => getElasticsearchIngestProcessorInferenceResult.Json),
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.elasticstack.ElasticstackFunctions;
import com.pulumi.elasticstack.inputs.GetElasticsearchIngestProcessorInferenceArgs;
import com.pulumi.elasticstack.inputs.GetElasticsearchIngestProcessorInferenceInputOutputArgs;
import com.pulumi.elasticstack.ElasticsearchIngestPipeline;
import com.pulumi.elasticstack.ElasticsearchIngestPipelineArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        final var inference = ElasticstackFunctions.getElasticsearchIngestProcessorInference(GetElasticsearchIngestProcessorInferenceArgs.builder()
            .modelId("example")
            .inputOutput(GetElasticsearchIngestProcessorInferenceInputOutputArgs.builder()
                .inputField("body")
                .outputField("body_vector")
                .build())
            .build());

        var myIngestPipeline = new ElasticsearchIngestPipeline("myIngestPipeline", ElasticsearchIngestPipelineArgs.builder()
            .name("inference-ingest")
            .processors(inference.json())
            .build());

    }
}

resources:
  myIngestPipeline:
    type: elasticstack:ElasticsearchIngestPipeline
    name: my_ingest_pipeline
    properties:
      name: inference-ingest
      processors:
        - ${inference.json}
variables:
  inference:
    fn::invoke:
      function: elasticstack:getElasticsearchIngestProcessorInference
      arguments:
        modelId: example
        inputOutput:
          inputField: body
          outputField: body_vector

Example coming soon!

Using getElasticsearchIngestProcessorInference

Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

function getElasticsearchIngestProcessorInference(args: GetElasticsearchIngestProcessorInferenceArgs, opts?: InvokeOptions): Promise<GetElasticsearchIngestProcessorInferenceResult>
function getElasticsearchIngestProcessorInferenceOutput(args: GetElasticsearchIngestProcessorInferenceOutputArgs, opts?: InvokeOptions): Output<GetElasticsearchIngestProcessorInferenceResult>

def get_elasticsearch_ingest_processor_inference(description: Optional[str] = None,
                                                 field_map: Optional[Mapping[str, str]] = None,
                                                 if_: Optional[str] = None,
                                                 ignore_failure: Optional[bool] = None,
                                                 input_output: Optional[GetElasticsearchIngestProcessorInferenceInputOutput] = None,
                                                 model_id: Optional[str] = None,
                                                 on_failures: Optional[Sequence[str]] = None,
                                                 tag: Optional[str] = None,
                                                 target_field: Optional[str] = None,
                                                 opts: Optional[InvokeOptions] = None) -> GetElasticsearchIngestProcessorInferenceResult
def get_elasticsearch_ingest_processor_inference_output(description: pulumi.Input[Optional[str]] = None,
                                                 field_map: pulumi.Input[Optional[Mapping[str, pulumi.Input[str]]]] = None,
                                                 if_: pulumi.Input[Optional[str]] = None,
                                                 ignore_failure: pulumi.Input[Optional[bool]] = None,
                                                 input_output: pulumi.Input[Optional[GetElasticsearchIngestProcessorInferenceInputOutputArgs]] = None,
                                                 model_id: pulumi.Input[Optional[str]] = None,
                                                 on_failures: pulumi.Input[Optional[Sequence[pulumi.Input[str]]]] = None,
                                                 tag: pulumi.Input[Optional[str]] = None,
                                                 target_field: pulumi.Input[Optional[str]] = None,
                                                 opts: Optional[InvokeOptions] = None) -> Output[GetElasticsearchIngestProcessorInferenceResult]

func GetElasticsearchIngestProcessorInference(ctx *Context, args *GetElasticsearchIngestProcessorInferenceArgs, opts ...InvokeOption) (*GetElasticsearchIngestProcessorInferenceResult, error)
func GetElasticsearchIngestProcessorInferenceOutput(ctx *Context, args *GetElasticsearchIngestProcessorInferenceOutputArgs, opts ...InvokeOption) GetElasticsearchIngestProcessorInferenceResultOutput

> Note: This function is named GetElasticsearchIngestProcessorInference in the Go SDK.

public static class GetElasticsearchIngestProcessorInference 
{
    public static Task<GetElasticsearchIngestProcessorInferenceResult> InvokeAsync(GetElasticsearchIngestProcessorInferenceArgs args, InvokeOptions? opts = null)
    public static Output<GetElasticsearchIngestProcessorInferenceResult> Invoke(GetElasticsearchIngestProcessorInferenceInvokeArgs args, InvokeOptions? opts = null)
}

public static CompletableFuture<GetElasticsearchIngestProcessorInferenceResult> getElasticsearchIngestProcessorInference(GetElasticsearchIngestProcessorInferenceArgs args, InvokeOptions options)
public static Output<GetElasticsearchIngestProcessorInferenceResult> getElasticsearchIngestProcessorInference(GetElasticsearchIngestProcessorInferenceArgs args, InvokeOptions options)

fn::invoke:
  function: elasticstack:index/getElasticsearchIngestProcessorInference:getElasticsearchIngestProcessorInference
  arguments:
    # arguments dictionary

data "elasticstack_getelasticsearchingestprocessorinference" "name" {
    # arguments
}

The following arguments are supported:

ModelId string: The ID or alias for the trained model, or the ID of the deployment.
Description string: Description of the processor.
FieldMap Dictionary<string, string>: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
If string: Conditionally execute the processor
IgnoreFailure bool: Ignore failures for the processor.
InputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
OnFailures List<string>: Handle failures for the processor.
Tag string: Identifier for the processor.
TargetField string: Field added to incoming documents to contain results objects.

ModelId string: The ID or alias for the trained model, or the ID of the deployment.
Description string: Description of the processor.
FieldMap map[string]string: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
If string: Conditionally execute the processor
IgnoreFailure bool: Ignore failures for the processor.
InputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
OnFailures []string: Handle failures for the processor.
Tag string: Identifier for the processor.
TargetField string: Field added to incoming documents to contain results objects.

model_id string: The ID or alias for the trained model, or the ID of the deployment.
description string: Description of the processor.
field_map map(string): Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if string: Conditionally execute the processor
ignore_failure bool: Ignore failures for the processor.
input_output object: Input and output field mappings for the inference processor.
on_failures list(string): Handle failures for the processor.
tag string: Identifier for the processor.
target_field string: Field added to incoming documents to contain results objects.

modelId String: The ID or alias for the trained model, or the ID of the deployment.
description String: Description of the processor.
fieldMap Map<String,String>: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if_ String: Conditionally execute the processor
ignoreFailure Boolean: Ignore failures for the processor.
inputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
onFailures List<String>: Handle failures for the processor.
tag String: Identifier for the processor.
targetField String: Field added to incoming documents to contain results objects.

modelId string: The ID or alias for the trained model, or the ID of the deployment.
description string: Description of the processor.
fieldMap {[key: string]: string}: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if string: Conditionally execute the processor
ignoreFailure boolean: Ignore failures for the processor.
inputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
onFailures string[]: Handle failures for the processor.
tag string: Identifier for the processor.
targetField string: Field added to incoming documents to contain results objects.

model_id str: The ID or alias for the trained model, or the ID of the deployment.
description str: Description of the processor.
field_map Mapping[str, str]: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if_ str: Conditionally execute the processor
ignore_failure bool: Ignore failures for the processor.
input_output GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
on_failures Sequence[str]: Handle failures for the processor.
tag str: Identifier for the processor.
target_field str: Field added to incoming documents to contain results objects.

modelId String: The ID or alias for the trained model, or the ID of the deployment.
description String: Description of the processor.
fieldMap Map<String>: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if String: Conditionally execute the processor
ignoreFailure Boolean: Ignore failures for the processor.
inputOutput Property Map: Input and output field mappings for the inference processor.
onFailures List<String>: Handle failures for the processor.
tag String: Identifier for the processor.
targetField String: Field added to incoming documents to contain results objects.

getElasticsearchIngestProcessorInference Result

The following output properties are available:

Id string: Internal identifier of the resource
IgnoreFailure bool: Ignore failures for the processor.
Json string: JSON representation of this data source.
ModelId string: The ID or alias for the trained model, or the ID of the deployment.
Description string: Description of the processor.
FieldMap Dictionary<string, string>: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
If string: Conditionally execute the processor
InputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
OnFailures List<string>: Handle failures for the processor.
Tag string: Identifier for the processor.
TargetField string: Field added to incoming documents to contain results objects.

Id string: Internal identifier of the resource
IgnoreFailure bool: Ignore failures for the processor.
Json string: JSON representation of this data source.
ModelId string: The ID or alias for the trained model, or the ID of the deployment.
Description string: Description of the processor.
FieldMap map[string]string: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
If string: Conditionally execute the processor
InputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
OnFailures []string: Handle failures for the processor.
Tag string: Identifier for the processor.
TargetField string: Field added to incoming documents to contain results objects.

id string: Internal identifier of the resource
ignore_failure bool: Ignore failures for the processor.
json string: JSON representation of this data source.
model_id string: The ID or alias for the trained model, or the ID of the deployment.
description string: Description of the processor.
field_map map(string): Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if string: Conditionally execute the processor
input_output object: Input and output field mappings for the inference processor.
on_failures list(string): Handle failures for the processor.
tag string: Identifier for the processor.
target_field string: Field added to incoming documents to contain results objects.

id String: Internal identifier of the resource
ignoreFailure Boolean: Ignore failures for the processor.
json String: JSON representation of this data source.
modelId String: The ID or alias for the trained model, or the ID of the deployment.
description String: Description of the processor.
fieldMap Map<String,String>: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if_ String: Conditionally execute the processor
inputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
onFailures List<String>: Handle failures for the processor.
tag String: Identifier for the processor.
targetField String: Field added to incoming documents to contain results objects.

id string: Internal identifier of the resource
ignoreFailure boolean: Ignore failures for the processor.
json string: JSON representation of this data source.
modelId string: The ID or alias for the trained model, or the ID of the deployment.
description string: Description of the processor.
fieldMap {[key: string]: string}: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if string: Conditionally execute the processor
inputOutput GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
onFailures string[]: Handle failures for the processor.
tag string: Identifier for the processor.
targetField string: Field added to incoming documents to contain results objects.

id str: Internal identifier of the resource
ignore_failure bool: Ignore failures for the processor.
json str: JSON representation of this data source.
model_id str: The ID or alias for the trained model, or the ID of the deployment.
description str: Description of the processor.
field_map Mapping[str, str]: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if_ str: Conditionally execute the processor
input_output GetElasticsearchIngestProcessorInferenceInputOutput: Input and output field mappings for the inference processor.
on_failures Sequence[str]: Handle failures for the processor.
tag str: Identifier for the processor.
target_field str: Field added to incoming documents to contain results objects.

id String: Internal identifier of the resource
ignoreFailure Boolean: Ignore failures for the processor.
json String: JSON representation of this data source.
modelId String: The ID or alias for the trained model, or the ID of the deployment.
description String: Description of the processor.
fieldMap Map<String>: Maps the document field names to the known field names of the model. Maps the document fields to the model's expected input fields.
if String: Conditionally execute the processor
inputOutput Property Map: Input and output field mappings for the inference processor.
onFailures List<String>: Handle failures for the processor.
tag String: Identifier for the processor.
targetField String: Field added to incoming documents to contain results objects.

Supporting Types

GetElasticsearchIngestProcessorInferenceInputOutput

InputField string: The field name from which the inference processor reads its input value.
OutputField string: The field name to which the inference processor writes its output.

InputField string: The field name from which the inference processor reads its input value.
OutputField string: The field name to which the inference processor writes its output.

input_field string: The field name from which the inference processor reads its input value.
output_field string: The field name to which the inference processor writes its output.

inputField String: The field name from which the inference processor reads its input value.
outputField String: The field name to which the inference processor writes its output.

inputField string: The field name from which the inference processor reads its input value.
outputField string: The field name to which the inference processor writes its output.

input_field str: The field name from which the inference processor reads its input value.
output_field str: The field name to which the inference processor writes its output.

inputField String: The field name from which the inference processor reads its input value.
outputField String: The field name to which the inference processor writes its output.