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  6. getAiReasoningEngineQuery
Viewing docs for Google Cloud v9.23.0
published on Thursday, May 7, 2026 by Pulumi
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pulumi/pulumi-gcp

gcp.vertex.getAiReasoningEngineQuery

gcp logo
Viewing docs for Google Cloud v9.23.0
published on Thursday, May 7, 2026 by Pulumi
Schema (JSON)
pulumi/pulumi-gcp

    Get the output of a query sent to a Vertex AI Reasoning Engine agent.

    Example Usage

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
import * as std from "@pulumi/std";

const defaultAiReasoningEngine = new gcp.vertex.AiReasoningEngine("default", {
    displayName: "vertex-mds-_48153",
    description: "Retrieves tenant project number",
    region: "us-central1",
    spec: {
        sourceCodeSpec: {
            inlineSource: {
                sourceArchive: std.filebase64({
                    input: "./test-fixtures/mds_agent_src.tar.gz",
                }).then(invoke => invoke.result),
            },
            pythonSpec: {
                entrypointModule: "metadata_agent",
                entrypointObject: "root_agent",
            },
        },
    },
});
const _default = gcp.vertex.getAiReasoningEngineQueryOutput({
    reasoningEngineId: defaultAiReasoningEngine.name,
    region: "us-central1",
    classMethod: "query",
});

    import pulumi
import pulumi_gcp as gcp
import pulumi_std as std

default_ai_reasoning_engine = gcp.vertex.AiReasoningEngine("default",
    display_name="vertex-mds-_48153",
    description="Retrieves tenant project number",
    region="us-central1",
    spec={
        "source_code_spec": {
            "inline_source": {
                "source_archive": std.filebase64(input="./test-fixtures/mds_agent_src.tar.gz").result,
            },
            "python_spec": {
                "entrypoint_module": "metadata_agent",
                "entrypoint_object": "root_agent",
            },
        },
    })
default = gcp.vertex.get_ai_reasoning_engine_query_output(reasoning_engine_id=default_ai_reasoning_engine.name,
    region="us-central1",
    class_method="query")

    package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v9/go/gcp/vertex"
	"github.com/pulumi/pulumi-std/sdk/go/std"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		invokeFilebase64, err := std.Filebase64(ctx, &std.Filebase64Args{
			Input: "./test-fixtures/mds_agent_src.tar.gz",
		}, nil)
		if err != nil {
			return err
		}
		defaultAiReasoningEngine, err := vertex.NewAiReasoningEngine(ctx, "default", &vertex.AiReasoningEngineArgs{
			DisplayName: pulumi.String("vertex-mds-_48153"),
			Description: pulumi.String("Retrieves tenant project number"),
			Region:      pulumi.String("us-central1"),
			Spec: &vertex.AiReasoningEngineSpecArgs{
				SourceCodeSpec: &vertex.AiReasoningEngineSpecSourceCodeSpecArgs{
					InlineSource: &vertex.AiReasoningEngineSpecSourceCodeSpecInlineSourceArgs{
						SourceArchive: pulumi.String(invokeFilebase64.Result),
					},
					PythonSpec: &vertex.AiReasoningEngineSpecSourceCodeSpecPythonSpecArgs{
						EntrypointModule: pulumi.String("metadata_agent"),
						EntrypointObject: pulumi.String("root_agent"),
					},
				},
			},
		})
		if err != nil {
			return err
		}
		_ = vertex.GetAiReasoningEngineQueryOutput(ctx, vertex.GetAiReasoningEngineQueryOutputArgs{
			ReasoningEngineId: defaultAiReasoningEngine.Name,
			Region:            pulumi.String("us-central1"),
			ClassMethod:       pulumi.String("query"),
		}, nil)
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;
using Std = Pulumi.Std;

return await Deployment.RunAsync(() => 
{
    var defaultAiReasoningEngine = new Gcp.Vertex.AiReasoningEngine("default", new()
    {
        DisplayName = "vertex-mds-_48153",
        Description = "Retrieves tenant project number",
        Region = "us-central1",
        Spec = new Gcp.Vertex.Inputs.AiReasoningEngineSpecArgs
        {
            SourceCodeSpec = new Gcp.Vertex.Inputs.AiReasoningEngineSpecSourceCodeSpecArgs
            {
                InlineSource = new Gcp.Vertex.Inputs.AiReasoningEngineSpecSourceCodeSpecInlineSourceArgs
                {
                    SourceArchive = Std.Index.Filebase64.Invoke(new()
                    {
                        Input = "./test-fixtures/mds_agent_src.tar.gz",
                    }).Apply(invoke => invoke.Result),
                },
                PythonSpec = new Gcp.Vertex.Inputs.AiReasoningEngineSpecSourceCodeSpecPythonSpecArgs
                {
                    EntrypointModule = "metadata_agent",
                    EntrypointObject = "root_agent",
                },
            },
        },
    });

    var @default = Gcp.Vertex.GetAiReasoningEngineQuery.Invoke(new()
    {
        ReasoningEngineId = defaultAiReasoningEngine.Name,
        Region = "us-central1",
        ClassMethod = "query",
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiReasoningEngine;
import com.pulumi.gcp.vertex.AiReasoningEngineArgs;
import com.pulumi.gcp.vertex.inputs.AiReasoningEngineSpecArgs;
import com.pulumi.gcp.vertex.inputs.AiReasoningEngineSpecSourceCodeSpecArgs;
import com.pulumi.gcp.vertex.inputs.AiReasoningEngineSpecSourceCodeSpecInlineSourceArgs;
import com.pulumi.gcp.vertex.inputs.AiReasoningEngineSpecSourceCodeSpecPythonSpecArgs;
import com.pulumi.std.StdFunctions;
import com.pulumi.std.inputs.Filebase64Args;
import com.pulumi.gcp.vertex.VertexFunctions;
import com.pulumi.gcp.vertex.inputs.GetAiReasoningEngineQueryArgs;
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) {
        var defaultAiReasoningEngine = new AiReasoningEngine("defaultAiReasoningEngine", AiReasoningEngineArgs.builder()
            .displayName("vertex-mds-_48153")
            .description("Retrieves tenant project number")
            .region("us-central1")
            .spec(AiReasoningEngineSpecArgs.builder()
                .sourceCodeSpec(AiReasoningEngineSpecSourceCodeSpecArgs.builder()
                    .inlineSource(AiReasoningEngineSpecSourceCodeSpecInlineSourceArgs.builder()
                        .sourceArchive(StdFunctions.filebase64(Filebase64Args.builder()
                            .input("./test-fixtures/mds_agent_src.tar.gz")
                            .build()).result())
                        .build())
                    .pythonSpec(AiReasoningEngineSpecSourceCodeSpecPythonSpecArgs.builder()
                        .entrypointModule("metadata_agent")
                        .entrypointObject("root_agent")
                        .build())
                    .build())
                .build())
            .build());

        final var default = VertexFunctions.getAiReasoningEngineQuery(GetAiReasoningEngineQueryArgs.builder()
            .reasoningEngineId(defaultAiReasoningEngine.name())
            .region("us-central1")
            .classMethod("query")
            .build());

    }
}

    resources:
  defaultAiReasoningEngine:
    type: gcp:vertex:AiReasoningEngine
    name: default
    properties:
      displayName: vertex-mds-_48153
      description: Retrieves tenant project number
      region: us-central1
      spec:
        sourceCodeSpec:
          inlineSource:
            sourceArchive:
              fn::invoke:
                function: std:filebase64
                arguments:
                  input: ./test-fixtures/mds_agent_src.tar.gz
                return: result
          pythonSpec:
            entrypointModule: metadata_agent
            entrypointObject: root_agent
variables:
  default:
    fn::invoke:
      function: gcp:vertex:getAiReasoningEngineQuery
      arguments:
        reasoningEngineId: ${defaultAiReasoningEngine.name}
        region: us-central1
        classMethod: query

    Example coming soon!

    Using getAiReasoningEngineQuery

    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 getAiReasoningEngineQuery(args: GetAiReasoningEngineQueryArgs, opts?: InvokeOptions): Promise<GetAiReasoningEngineQueryResult>
function getAiReasoningEngineQueryOutput(args: GetAiReasoningEngineQueryOutputArgs, opts?: InvokeOptions): Output<GetAiReasoningEngineQueryResult>
    def get_ai_reasoning_engine_query(class_method: Optional[str] = None,
                                  input: Optional[str] = None,
                                  project: Optional[str] = None,
                                  reasoning_engine_id: Optional[str] = None,
                                  region: Optional[str] = None,
                                  opts: Optional[InvokeOptions] = None) -> GetAiReasoningEngineQueryResult
def get_ai_reasoning_engine_query_output(class_method: pulumi.Input[Optional[str]] = None,
                                  input: pulumi.Input[Optional[str]] = None,
                                  project: pulumi.Input[Optional[str]] = None,
                                  reasoning_engine_id: pulumi.Input[Optional[str]] = None,
                                  region: pulumi.Input[Optional[str]] = None,
                                  opts: Optional[InvokeOptions] = None) -> Output[GetAiReasoningEngineQueryResult]
    func GetAiReasoningEngineQuery(ctx *Context, args *GetAiReasoningEngineQueryArgs, opts ...InvokeOption) (*GetAiReasoningEngineQueryResult, error)
func GetAiReasoningEngineQueryOutput(ctx *Context, args *GetAiReasoningEngineQueryOutputArgs, opts ...InvokeOption) GetAiReasoningEngineQueryResultOutput

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

    public static class GetAiReasoningEngineQuery 
{
    public static Task<GetAiReasoningEngineQueryResult> InvokeAsync(GetAiReasoningEngineQueryArgs args, InvokeOptions? opts = null)
    public static Output<GetAiReasoningEngineQueryResult> Invoke(GetAiReasoningEngineQueryInvokeArgs args, InvokeOptions? opts = null)
}
    public static CompletableFuture<GetAiReasoningEngineQueryResult> getAiReasoningEngineQuery(GetAiReasoningEngineQueryArgs args, InvokeOptions options)
public static Output<GetAiReasoningEngineQueryResult> getAiReasoningEngineQuery(GetAiReasoningEngineQueryArgs args, InvokeOptions options)

    fn::invoke:
  function: gcp:vertex/getAiReasoningEngineQuery:getAiReasoningEngineQuery
  arguments:
    # arguments dictionary
    data "gcp_vertex_getaireasoningenginequery" "name" {
    # arguments
}

    The following arguments are supported:

    ReasoningEngineId string
    The ID of the Vertex AI Reasoning Engine to query.

    Region string
    The location of the resource.
    ClassMethod string
    Class method to be used for the query. It is optional and defaults to "query" if unspecified.
    Input string
    Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc..
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider default project is used.
    ReasoningEngineId string
    The ID of the Vertex AI Reasoning Engine to query.

    Region string
    The location of the resource.
    ClassMethod string
    Class method to be used for the query. It is optional and defaults to "query" if unspecified.
    Input string
    Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc..
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider default project is used.
    reasoning_engine_id string
    The ID of the Vertex AI Reasoning Engine to query.

    region string
    The location of the resource.
    class_method string
    Class method to be used for the query. It is optional and defaults to "query" if unspecified.
    input string
    Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc..
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider default project is used.
    reasoningEngineId String
    The ID of the Vertex AI Reasoning Engine to query.

    region String
    The location of the resource.
    classMethod String
    Class method to be used for the query. It is optional and defaults to "query" if unspecified.
    input String
    Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc..
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider default project is used.
    reasoningEngineId string
    The ID of the Vertex AI Reasoning Engine to query.

    region string
    The location of the resource.
    classMethod string
    Class method to be used for the query. It is optional and defaults to "query" if unspecified.
    input string
    Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc..
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider default project is used.
    reasoning_engine_id str
    The ID of the Vertex AI Reasoning Engine to query.

    region str
    The location of the resource.
    class_method str
    Class method to be used for the query. It is optional and defaults to "query" if unspecified.
    input str
    Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc..
    project str
    The ID of the project in which the resource belongs. If it is not provided, the provider default project is used.
    reasoningEngineId String
    The ID of the Vertex AI Reasoning Engine to query.

    region String
    The location of the resource.
    classMethod String
    Class method to be used for the query. It is optional and defaults to "query" if unspecified.
    input String
    Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc..
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider default project is used.

    getAiReasoningEngineQuery Result

    The following output properties are available:

    Id string
    The provider-assigned unique ID for this managed resource.
    Output string
    The JSON-serialized output resulting from the query.
    ReasoningEngineId string
    Region string
    ClassMethod string
    Input string
    Project string
    Id string
    The provider-assigned unique ID for this managed resource.
    Output string
    The JSON-serialized output resulting from the query.
    ReasoningEngineId string
    Region string
    ClassMethod string
    Input string
    Project string
    id string
    The provider-assigned unique ID for this managed resource.
    output string
    The JSON-serialized output resulting from the query.
    reasoning_engine_id string
    region string
    class_method string
    input string
    project string
    id String
    The provider-assigned unique ID for this managed resource.
    output String
    The JSON-serialized output resulting from the query.
    reasoningEngineId String
    region String
    classMethod String
    input String
    project String
    id string
    The provider-assigned unique ID for this managed resource.
    output string
    The JSON-serialized output resulting from the query.
    reasoningEngineId string
    region string
    classMethod string
    input string
    project string
    id str
    The provider-assigned unique ID for this managed resource.
    output str
    The JSON-serialized output resulting from the query.
    reasoning_engine_id str
    region str
    class_method str
    input str
    project str
    id String
    The provider-assigned unique ID for this managed resource.
    output String
    The JSON-serialized output resulting from the query.
    reasoningEngineId String
    region String
    classMethod String
    input String
    project String

    Package Details

    Repository
    Google Cloud (GCP) Classic pulumi/pulumi-gcp
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the google-beta Terraform Provider.
    gcp logo
    Viewing docs for Google Cloud v9.23.0
    published on Thursday, May 7, 2026 by Pulumi
    Schema (JSON)
    pulumi/pulumi-gcp
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