Oracle Cloud Infrastructure v3.9.0, Sep 24 25

Oracle Cloud Infrastructure v3.9.0 published on Wednesday, Sep 24, 2025 by Pulumi

oci.AiDocument.getModels

Oracle Cloud Infrastructure v3.9.0 published on Wednesday, Sep 24, 2025 by Pulumi

Example Usage

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

const testModels = oci.AiDocument.getModels({
    compartmentId: compartmentId,
    displayName: modelDisplayName,
    id: modelId,
    projectId: testProject.id,
    state: modelState,
});

import pulumi
import pulumi_oci as oci

test_models = oci.AiDocument.get_models(compartment_id=compartment_id,
    display_name=model_display_name,
    id=model_id,
    project_id=test_project["id"],
    state=model_state)

package main

import (
	"github.com/pulumi/pulumi-oci/sdk/v3/go/oci/aidocument"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := aidocument.GetModels(ctx, &aidocument.GetModelsArgs{
			CompartmentId: pulumi.StringRef(compartmentId),
			DisplayName:   pulumi.StringRef(modelDisplayName),
			Id:            pulumi.StringRef(modelId),
			ProjectId:     pulumi.StringRef(testProject.Id),
			State:         pulumi.StringRef(modelState),
		}, nil)
		if err != nil {
			return err
		}
		return nil
	})
}

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

return await Deployment.RunAsync(() => 
{
    var testModels = Oci.AiDocument.GetModels.Invoke(new()
    {
        CompartmentId = compartmentId,
        DisplayName = modelDisplayName,
        Id = modelId,
        ProjectId = testProject.Id,
        State = modelState,
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.oci.AiDocument.AiDocumentFunctions;
import com.pulumi.oci.AiDocument.inputs.GetModelsArgs;
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 testModels = AiDocumentFunctions.getModels(GetModelsArgs.builder()
            .compartmentId(compartmentId)
            .displayName(modelDisplayName)
            .id(modelId)
            .projectId(testProject.id())
            .state(modelState)
            .build());

    }
}

variables:
  testModels:
    fn::invoke:
      function: oci:AiDocument:getModels
      arguments:
        compartmentId: ${compartmentId}
        displayName: ${modelDisplayName}
        id: ${modelId}
        projectId: ${testProject.id}
        state: ${modelState}

Using getModels

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 getModels(args: GetModelsArgs, opts?: InvokeOptions): Promise<GetModelsResult>
function getModelsOutput(args: GetModelsOutputArgs, opts?: InvokeOptions): Output<GetModelsResult>

def get_models(compartment_id: Optional[str] = None,
               display_name: Optional[str] = None,
               filters: Optional[Sequence[GetModelsFilter]] = None,
               id: Optional[str] = None,
               project_id: Optional[str] = None,
               state: Optional[str] = None,
               opts: Optional[InvokeOptions] = None) -> GetModelsResult
def get_models_output(compartment_id: Optional[pulumi.Input[str]] = None,
               display_name: Optional[pulumi.Input[str]] = None,
               filters: Optional[pulumi.Input[Sequence[pulumi.Input[GetModelsFilterArgs]]]] = None,
               id: Optional[pulumi.Input[str]] = None,
               project_id: Optional[pulumi.Input[str]] = None,
               state: Optional[pulumi.Input[str]] = None,
               opts: Optional[InvokeOptions] = None) -> Output[GetModelsResult]

func GetModels(ctx *Context, args *GetModelsArgs, opts ...InvokeOption) (*GetModelsResult, error)
func GetModelsOutput(ctx *Context, args *GetModelsOutputArgs, opts ...InvokeOption) GetModelsResultOutput

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

public static class GetModels 
{
    public static Task<GetModelsResult> InvokeAsync(GetModelsArgs args, InvokeOptions? opts = null)
    public static Output<GetModelsResult> Invoke(GetModelsInvokeArgs args, InvokeOptions? opts = null)
}

public static CompletableFuture<GetModelsResult> getModels(GetModelsArgs args, InvokeOptions options)
public static Output<GetModelsResult> getModels(GetModelsArgs args, InvokeOptions options)

fn::invoke:
  function: oci:AiDocument/getModels:getModels
  arguments:
    # arguments dictionary

The following arguments are supported:

CompartmentId string: The ID of the compartment in which to list resources.
DisplayName string: A filter to return only resources that match the entire display name given.
Filters List<GetModelsFilter>
Id string: The filter to find the model with the given identifier.
ProjectId string: The ID of the project for which to list the objects.
State string: The filter to match models with the given lifecycleState.

CompartmentId string: The ID of the compartment in which to list resources.
DisplayName string: A filter to return only resources that match the entire display name given.
Filters []GetModelsFilter
Id string: The filter to find the model with the given identifier.
ProjectId string: The ID of the project for which to list the objects.
State string: The filter to match models with the given lifecycleState.

compartmentId String: The ID of the compartment in which to list resources.
displayName String: A filter to return only resources that match the entire display name given.
filters List<GetModelsFilter>
id String: The filter to find the model with the given identifier.
projectId String: The ID of the project for which to list the objects.
state String: The filter to match models with the given lifecycleState.

compartmentId string: The ID of the compartment in which to list resources.
displayName string: A filter to return only resources that match the entire display name given.
filters GetModelsFilter[]
id string: The filter to find the model with the given identifier.
projectId string: The ID of the project for which to list the objects.
state string: The filter to match models with the given lifecycleState.

compartment_id str: The ID of the compartment in which to list resources.
display_name str: A filter to return only resources that match the entire display name given.
filters Sequence[GetModelsFilter]
id str: The filter to find the model with the given identifier.
project_id str: The ID of the project for which to list the objects.
state str: The filter to match models with the given lifecycleState.

compartmentId String: The ID of the compartment in which to list resources.
displayName String: A filter to return only resources that match the entire display name given.
filters List<Property Map>
id String: The filter to find the model with the given identifier.
projectId String: The ID of the project for which to list the objects.
state String: The filter to match models with the given lifecycleState.

getModels Result

The following output properties are available:

ModelCollections List<GetModelsModelCollection>: The list of model_collection.
CompartmentId string: The lock compartment ID.
DisplayName string: A human-friendly name for the model, which can be changed.
Filters List<GetModelsFilter>
Id string: A unique identifier that is immutable after creation.
ProjectId string: The OCID of the project that contains the model.
State string: The current state of the model.

ModelCollections []GetModelsModelCollection: The list of model_collection.
CompartmentId string: The lock compartment ID.
DisplayName string: A human-friendly name for the model, which can be changed.
Filters []GetModelsFilter
Id string: A unique identifier that is immutable after creation.
ProjectId string: The OCID of the project that contains the model.
State string: The current state of the model.

modelCollections List<GetModelsModelCollection>: The list of model_collection.
compartmentId String: The lock compartment ID.
displayName String: A human-friendly name for the model, which can be changed.
filters List<GetModelsFilter>
id String: A unique identifier that is immutable after creation.
projectId String: The OCID of the project that contains the model.
state String: The current state of the model.

modelCollections GetModelsModelCollection[]: The list of model_collection.
compartmentId string: The lock compartment ID.
displayName string: A human-friendly name for the model, which can be changed.
filters GetModelsFilter[]
id string: A unique identifier that is immutable after creation.
projectId string: The OCID of the project that contains the model.
state string: The current state of the model.

model_collections Sequence[GetModelsModelCollection]: The list of model_collection.
compartment_id str: The lock compartment ID.
display_name str: A human-friendly name for the model, which can be changed.
filters Sequence[GetModelsFilter]
id str: A unique identifier that is immutable after creation.
project_id str: The OCID of the project that contains the model.
state str: The current state of the model.

modelCollections List<Property Map>: The list of model_collection.
compartmentId String: The lock compartment ID.
displayName String: A human-friendly name for the model, which can be changed.
filters List<Property Map>
id String: A unique identifier that is immutable after creation.
projectId String: The OCID of the project that contains the model.
state String: The current state of the model.

Supporting Types

GetModelsFilter

Name string
Values List<string>
Regex bool

Name string
Values []string
Regex bool

name String
values List<String>
regex Boolean

name string
values string[]
regex boolean

name str
values Sequence[str]
regex bool

name String
values List<String>
regex Boolean

GetModelsModelCollection

Items List<GetModelsModelCollectionItem>

Items []GetModelsModelCollectionItem

items List<GetModelsModelCollectionItem>

items GetModelsModelCollectionItem[]

items Sequence[GetModelsModelCollectionItem]

items List<Property Map>

GetModelsModelCollectionItem

CompartmentId string

The ID of the compartment in which to list resources.

ComponentModels List<GetModelsModelCollectionItemComponentModel>

The OCID collection of active custom Key Value models that need to be composed.

DefinedTags Dictionary<string, string>

Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: {"foo-namespace": {"bar-key": "value"}}

Description string

An optional description of the model.

DisplayName string

A filter to return only resources that match the entire display name given.

FreeformTags Dictionary<string, string>

A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: {"bar-key": "value"}

Id string

The filter to find the model with the given identifier.

InferenceUnits int

Number of replicas required for this model.

IsComposedModel bool

Set to true when the model is created by using multiple key value extraction models.

IsQuickMode bool

Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.

Labels List<string>

The collection of labels used to train the custom model.

Language string

The document language for model training, abbreviated according to the BCP 47 syntax.

LifecycleDetails string

A message describing the current state in more detail, that can provide actionable information if training failed.

Locks List<GetModelsModelCollectionItemLock>

Locks associated with this resource.

MaxTrainingTimeInHours double

The maximum model training time in hours, expressed as a decimal fraction.

Metrics List<GetModelsModelCollectionItemMetric>

Trained Model Metrics.

ModelId string

The OCID of active custom Key Value model that need to be composed.

ModelSubTypes List<GetModelsModelCollectionItemModelSubType>

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

ModelType string

The type of the Document model.

ModelVersion string

The version of the model.

ProjectId string

The ID of the project for which to list the objects.

State string

The filter to match models with the given lifecycleState.

SystemTags Dictionary<string, string>

Usage of system tag keys. These predefined keys are scoped to namespaces. For example: {"orcl-cloud": {"free-tier-retained": "true"}}

TenancyId string

The tenancy id of the model.

TestingDatasets List<GetModelsModelCollectionItemTestingDataset>

The base entity which is the input for creating and training a model.

TimeCreated string

When the model was created, as an RFC3339 datetime string.

TimeUpdated string

When the model was updated, as an RFC3339 datetime string.

TrainedTimeInHours double

The total hours actually used for model training.

TrainingDatasets List<GetModelsModelCollectionItemTrainingDataset>

The base entity which is the input for creating and training a model.

ValidationDatasets List<GetModelsModelCollectionItemValidationDataset>

The base entity which is the input for creating and training a model.

CompartmentId string

The ID of the compartment in which to list resources.

ComponentModels []GetModelsModelCollectionItemComponentModel

The OCID collection of active custom Key Value models that need to be composed.

DefinedTags map[string]string

Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: {"foo-namespace": {"bar-key": "value"}}

Description string

An optional description of the model.

DisplayName string

A filter to return only resources that match the entire display name given.

FreeformTags map[string]string

A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: {"bar-key": "value"}

Id string

The filter to find the model with the given identifier.

InferenceUnits int

Number of replicas required for this model.

IsComposedModel bool

Set to true when the model is created by using multiple key value extraction models.

IsQuickMode bool

Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.

Labels []string

The collection of labels used to train the custom model.

Language string

The document language for model training, abbreviated according to the BCP 47 syntax.

LifecycleDetails string

A message describing the current state in more detail, that can provide actionable information if training failed.

Locks []GetModelsModelCollectionItemLock

Locks associated with this resource.

MaxTrainingTimeInHours float64

The maximum model training time in hours, expressed as a decimal fraction.

Metrics []GetModelsModelCollectionItemMetric

Trained Model Metrics.

ModelId string

The OCID of active custom Key Value model that need to be composed.

ModelSubTypes []GetModelsModelCollectionItemModelSubType

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

ModelType string

The type of the Document model.

ModelVersion string

The version of the model.

ProjectId string

The ID of the project for which to list the objects.

State string

The filter to match models with the given lifecycleState.

SystemTags map[string]string

Usage of system tag keys. These predefined keys are scoped to namespaces. For example: {"orcl-cloud": {"free-tier-retained": "true"}}

TenancyId string

The tenancy id of the model.

TestingDatasets []GetModelsModelCollectionItemTestingDataset

The base entity which is the input for creating and training a model.

TimeCreated string

When the model was created, as an RFC3339 datetime string.

TimeUpdated string

When the model was updated, as an RFC3339 datetime string.

TrainedTimeInHours float64

The total hours actually used for model training.

TrainingDatasets []GetModelsModelCollectionItemTrainingDataset

The base entity which is the input for creating and training a model.

ValidationDatasets []GetModelsModelCollectionItemValidationDataset

The base entity which is the input for creating and training a model.

compartmentId String

The ID of the compartment in which to list resources.

componentModels List<GetModelsModelCollectionItemComponentModel>

The OCID collection of active custom Key Value models that need to be composed.

definedTags Map<String,String>

Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: {"foo-namespace": {"bar-key": "value"}}

description String

An optional description of the model.

displayName String

A filter to return only resources that match the entire display name given.

freeformTags Map<String,String>

A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: {"bar-key": "value"}

id String

The filter to find the model with the given identifier.

inferenceUnits Integer

Number of replicas required for this model.

isComposedModel Boolean

Set to true when the model is created by using multiple key value extraction models.

isQuickMode Boolean

Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.

labels List<String>

The collection of labels used to train the custom model.

language String

The document language for model training, abbreviated according to the BCP 47 syntax.

lifecycleDetails String

A message describing the current state in more detail, that can provide actionable information if training failed.

locks List<GetModelsModelCollectionItemLock>

Locks associated with this resource.

maxTrainingTimeInHours Double

The maximum model training time in hours, expressed as a decimal fraction.

metrics List<GetModelsModelCollectionItemMetric>

Trained Model Metrics.

modelId String

The OCID of active custom Key Value model that need to be composed.

modelSubTypes List<GetModelsModelCollectionItemModelSubType>

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

modelType String

The type of the Document model.

modelVersion String

The version of the model.

projectId String

The ID of the project for which to list the objects.

state String

The filter to match models with the given lifecycleState.

systemTags Map<String,String>

Usage of system tag keys. These predefined keys are scoped to namespaces. For example: {"orcl-cloud": {"free-tier-retained": "true"}}

tenancyId String

The tenancy id of the model.

testingDatasets List<GetModelsModelCollectionItemTestingDataset>

The base entity which is the input for creating and training a model.

timeCreated String

When the model was created, as an RFC3339 datetime string.

timeUpdated String

When the model was updated, as an RFC3339 datetime string.

trainedTimeInHours Double

The total hours actually used for model training.

trainingDatasets List<GetModelsModelCollectionItemTrainingDataset>

The base entity which is the input for creating and training a model.

validationDatasets List<GetModelsModelCollectionItemValidationDataset>

The base entity which is the input for creating and training a model.

compartmentId string

The ID of the compartment in which to list resources.

componentModels GetModelsModelCollectionItemComponentModel[]

The OCID collection of active custom Key Value models that need to be composed.

definedTags {[key: string]: string}

Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: {"foo-namespace": {"bar-key": "value"}}

description string

An optional description of the model.

displayName string

A filter to return only resources that match the entire display name given.

freeformTags {[key: string]: string}

A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: {"bar-key": "value"}

id string

The filter to find the model with the given identifier.

inferenceUnits number

Number of replicas required for this model.

isComposedModel boolean

Set to true when the model is created by using multiple key value extraction models.

isQuickMode boolean

Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.

labels string[]

The collection of labels used to train the custom model.

language string

The document language for model training, abbreviated according to the BCP 47 syntax.

lifecycleDetails string

A message describing the current state in more detail, that can provide actionable information if training failed.

locks GetModelsModelCollectionItemLock[]

Locks associated with this resource.

maxTrainingTimeInHours number

The maximum model training time in hours, expressed as a decimal fraction.

metrics GetModelsModelCollectionItemMetric[]

Trained Model Metrics.

modelId string

The OCID of active custom Key Value model that need to be composed.

modelSubTypes GetModelsModelCollectionItemModelSubType[]

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

modelType string

The type of the Document model.

modelVersion string

The version of the model.

projectId string

The ID of the project for which to list the objects.

state string

The filter to match models with the given lifecycleState.

systemTags {[key: string]: string}

Usage of system tag keys. These predefined keys are scoped to namespaces. For example: {"orcl-cloud": {"free-tier-retained": "true"}}

tenancyId string

The tenancy id of the model.

testingDatasets GetModelsModelCollectionItemTestingDataset[]

The base entity which is the input for creating and training a model.

timeCreated string

When the model was created, as an RFC3339 datetime string.

timeUpdated string

When the model was updated, as an RFC3339 datetime string.

trainedTimeInHours number

The total hours actually used for model training.

trainingDatasets GetModelsModelCollectionItemTrainingDataset[]

The base entity which is the input for creating and training a model.

validationDatasets GetModelsModelCollectionItemValidationDataset[]

The base entity which is the input for creating and training a model.

compartment_id str

The ID of the compartment in which to list resources.

component_models Sequence[GetModelsModelCollectionItemComponentModel]

The OCID collection of active custom Key Value models that need to be composed.

defined_tags Mapping[str, str]

Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: {"foo-namespace": {"bar-key": "value"}}

description str

An optional description of the model.

display_name str

A filter to return only resources that match the entire display name given.

freeform_tags Mapping[str, str]

A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: {"bar-key": "value"}

id str

The filter to find the model with the given identifier.

inference_units int

Number of replicas required for this model.

is_composed_model bool

Set to true when the model is created by using multiple key value extraction models.

is_quick_mode bool

Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.

labels Sequence[str]

The collection of labels used to train the custom model.

language str

The document language for model training, abbreviated according to the BCP 47 syntax.

lifecycle_details str

A message describing the current state in more detail, that can provide actionable information if training failed.

locks Sequence[GetModelsModelCollectionItemLock]

Locks associated with this resource.

max_training_time_in_hours float

The maximum model training time in hours, expressed as a decimal fraction.

metrics Sequence[GetModelsModelCollectionItemMetric]

Trained Model Metrics.

model_id str

The OCID of active custom Key Value model that need to be composed.

model_sub_types Sequence[GetModelsModelCollectionItemModelSubType]

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

model_type str

The type of the Document model.

model_version str

The version of the model.

project_id str

The ID of the project for which to list the objects.

state str

The filter to match models with the given lifecycleState.

system_tags Mapping[str, str]

Usage of system tag keys. These predefined keys are scoped to namespaces. For example: {"orcl-cloud": {"free-tier-retained": "true"}}

tenancy_id str

The tenancy id of the model.

testing_datasets Sequence[GetModelsModelCollectionItemTestingDataset]

The base entity which is the input for creating and training a model.

time_created str

When the model was created, as an RFC3339 datetime string.

time_updated str

When the model was updated, as an RFC3339 datetime string.

trained_time_in_hours float

The total hours actually used for model training.

training_datasets Sequence[GetModelsModelCollectionItemTrainingDataset]

The base entity which is the input for creating and training a model.

validation_datasets Sequence[GetModelsModelCollectionItemValidationDataset]

The base entity which is the input for creating and training a model.

compartmentId String

The ID of the compartment in which to list resources.

componentModels List<Property Map>

The OCID collection of active custom Key Value models that need to be composed.

definedTags Map<String>

Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: {"foo-namespace": {"bar-key": "value"}}

description String

An optional description of the model.

displayName String

A filter to return only resources that match the entire display name given.

freeformTags Map<String>

A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: {"bar-key": "value"}

id String

The filter to find the model with the given identifier.

inferenceUnits Number

Number of replicas required for this model.

isComposedModel Boolean

Set to true when the model is created by using multiple key value extraction models.

isQuickMode Boolean

Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.

labels List<String>

The collection of labels used to train the custom model.

language String

The document language for model training, abbreviated according to the BCP 47 syntax.

lifecycleDetails String

A message describing the current state in more detail, that can provide actionable information if training failed.

locks List<Property Map>

Locks associated with this resource.

maxTrainingTimeInHours Number

The maximum model training time in hours, expressed as a decimal fraction.

metrics List<Property Map>

Trained Model Metrics.

modelId String

The OCID of active custom Key Value model that need to be composed.

modelSubTypes List<Property Map>

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

modelType String

The type of the Document model.

modelVersion String

The version of the model.

projectId String

The ID of the project for which to list the objects.

state String

The filter to match models with the given lifecycleState.

systemTags Map<String>

Usage of system tag keys. These predefined keys are scoped to namespaces. For example: {"orcl-cloud": {"free-tier-retained": "true"}}

tenancyId String

The tenancy id of the model.

testingDatasets List<Property Map>

The base entity which is the input for creating and training a model.

timeCreated String

When the model was created, as an RFC3339 datetime string.

timeUpdated String

When the model was updated, as an RFC3339 datetime string.

trainedTimeInHours Number

The total hours actually used for model training.

trainingDatasets List<Property Map>

The base entity which is the input for creating and training a model.

validationDatasets List<Property Map>

The base entity which is the input for creating and training a model.

GetModelsModelCollectionItemComponentModel

ModelId string: The OCID of active custom Key Value model that need to be composed.

ModelId string: The OCID of active custom Key Value model that need to be composed.

modelId String: The OCID of active custom Key Value model that need to be composed.

modelId string: The OCID of active custom Key Value model that need to be composed.

model_id str: The OCID of active custom Key Value model that need to be composed.

modelId String: The OCID of active custom Key Value model that need to be composed.

GetModelsModelCollectionItemLock

CompartmentId string: The ID of the compartment in which to list resources.
Message string: A message added by the lock creator. The message typically gives an indication of why the resource is locked.
RelatedResourceId string: The resource ID that is locking this resource. Indicates that deleting this resource removes the lock.
TimeCreated string: When the model was created, as an RFC3339 datetime string.
Type string: Lock type.

CompartmentId string: The ID of the compartment in which to list resources.
Message string: A message added by the lock creator. The message typically gives an indication of why the resource is locked.
RelatedResourceId string: The resource ID that is locking this resource. Indicates that deleting this resource removes the lock.
TimeCreated string: When the model was created, as an RFC3339 datetime string.
Type string: Lock type.

compartmentId String: The ID of the compartment in which to list resources.
message String: A message added by the lock creator. The message typically gives an indication of why the resource is locked.
relatedResourceId String: The resource ID that is locking this resource. Indicates that deleting this resource removes the lock.
timeCreated String: When the model was created, as an RFC3339 datetime string.
type String: Lock type.

compartmentId string: The ID of the compartment in which to list resources.
message string: A message added by the lock creator. The message typically gives an indication of why the resource is locked.
relatedResourceId string: The resource ID that is locking this resource. Indicates that deleting this resource removes the lock.
timeCreated string: When the model was created, as an RFC3339 datetime string.
type string: Lock type.

compartment_id str: The ID of the compartment in which to list resources.
message str: A message added by the lock creator. The message typically gives an indication of why the resource is locked.
related_resource_id str: The resource ID that is locking this resource. Indicates that deleting this resource removes the lock.
time_created str: When the model was created, as an RFC3339 datetime string.
type str: Lock type.

compartmentId String: The ID of the compartment in which to list resources.
message String: A message added by the lock creator. The message typically gives an indication of why the resource is locked.
relatedResourceId String: The resource ID that is locking this resource. Indicates that deleting this resource removes the lock.
timeCreated String: When the model was created, as an RFC3339 datetime string.
type String: Lock type.

GetModelsModelCollectionItemMetric

DatasetSummaries List<GetModelsModelCollectionItemMetricDatasetSummary>: Summary of count of samples used during model training.
LabelMetricsReports List<GetModelsModelCollectionItemMetricLabelMetricsReport>: List of metrics entries per label.
ModelType string: The type of the Document model.
OverallMetricsReports List<GetModelsModelCollectionItemMetricOverallMetricsReport>: Overall Metrics report for Document Classification Model.

DatasetSummaries []GetModelsModelCollectionItemMetricDatasetSummary: Summary of count of samples used during model training.
LabelMetricsReports []GetModelsModelCollectionItemMetricLabelMetricsReport: List of metrics entries per label.
ModelType string: The type of the Document model.
OverallMetricsReports []GetModelsModelCollectionItemMetricOverallMetricsReport: Overall Metrics report for Document Classification Model.

datasetSummaries List<GetModelsModelCollectionItemMetricDatasetSummary>: Summary of count of samples used during model training.
labelMetricsReports List<GetModelsModelCollectionItemMetricLabelMetricsReport>: List of metrics entries per label.
modelType String: The type of the Document model.
overallMetricsReports List<GetModelsModelCollectionItemMetricOverallMetricsReport>: Overall Metrics report for Document Classification Model.

datasetSummaries GetModelsModelCollectionItemMetricDatasetSummary[]: Summary of count of samples used during model training.
labelMetricsReports GetModelsModelCollectionItemMetricLabelMetricsReport[]: List of metrics entries per label.
modelType string: The type of the Document model.
overallMetricsReports GetModelsModelCollectionItemMetricOverallMetricsReport[]: Overall Metrics report for Document Classification Model.

dataset_summaries Sequence[GetModelsModelCollectionItemMetricDatasetSummary]: Summary of count of samples used during model training.
label_metrics_reports Sequence[GetModelsModelCollectionItemMetricLabelMetricsReport]: List of metrics entries per label.
model_type str: The type of the Document model.
overall_metrics_reports Sequence[GetModelsModelCollectionItemMetricOverallMetricsReport]: Overall Metrics report for Document Classification Model.

datasetSummaries List<Property Map>: Summary of count of samples used during model training.
labelMetricsReports List<Property Map>: List of metrics entries per label.
modelType String: The type of the Document model.
overallMetricsReports List<Property Map>: Overall Metrics report for Document Classification Model.

GetModelsModelCollectionItemMetricDatasetSummary

TestSampleCount int: Number of samples used for testing the model.
TrainingSampleCount int: Number of samples used for training the model.
ValidationSampleCount int: Number of samples used for validating the model.

TestSampleCount int: Number of samples used for testing the model.
TrainingSampleCount int: Number of samples used for training the model.
ValidationSampleCount int: Number of samples used for validating the model.

testSampleCount Integer: Number of samples used for testing the model.
trainingSampleCount Integer: Number of samples used for training the model.
validationSampleCount Integer: Number of samples used for validating the model.

testSampleCount number: Number of samples used for testing the model.
trainingSampleCount number: Number of samples used for training the model.
validationSampleCount number: Number of samples used for validating the model.

test_sample_count int: Number of samples used for testing the model.
training_sample_count int: Number of samples used for training the model.
validation_sample_count int: Number of samples used for validating the model.

testSampleCount Number: Number of samples used for testing the model.
trainingSampleCount Number: Number of samples used for training the model.
validationSampleCount Number: Number of samples used for validating the model.

GetModelsModelCollectionItemMetricLabelMetricsReport

ConfidenceEntries List<GetModelsModelCollectionItemMetricLabelMetricsReportConfidenceEntry>: List of document classification confidence report.
DocumentCount int: Total test documents in the label.
Label string: Label name
MeanAveragePrecision double: Mean average precision under different thresholds

ConfidenceEntries []GetModelsModelCollectionItemMetricLabelMetricsReportConfidenceEntry: List of document classification confidence report.
DocumentCount int: Total test documents in the label.
Label string: Label name
MeanAveragePrecision float64: Mean average precision under different thresholds

confidenceEntries List<GetModelsModelCollectionItemMetricLabelMetricsReportConfidenceEntry>: List of document classification confidence report.
documentCount Integer: Total test documents in the label.
label String: Label name
meanAveragePrecision Double: Mean average precision under different thresholds

confidenceEntries GetModelsModelCollectionItemMetricLabelMetricsReportConfidenceEntry[]: List of document classification confidence report.
documentCount number: Total test documents in the label.
label string: Label name
meanAveragePrecision number: Mean average precision under different thresholds

confidence_entries Sequence[GetModelsModelCollectionItemMetricLabelMetricsReportConfidenceEntry]: List of document classification confidence report.
document_count int: Total test documents in the label.
label str: Label name
mean_average_precision float: Mean average precision under different thresholds

confidenceEntries List<Property Map>: List of document classification confidence report.
documentCount Number: Total test documents in the label.
label String: Label name
meanAveragePrecision Number: Mean average precision under different thresholds

GetModelsModelCollectionItemMetricLabelMetricsReportConfidenceEntry

Accuracy double: accuracy under the threshold
F1score double: f1Score under the threshold
Precision double: Precision under the threshold
Recall double: Recall under the threshold
Threshold double: Threshold used to calculate precision and recall.

Accuracy float64: accuracy under the threshold
F1score float64: f1Score under the threshold
Precision float64: Precision under the threshold
Recall float64: Recall under the threshold
Threshold float64: Threshold used to calculate precision and recall.

accuracy Double: accuracy under the threshold
f1score Double: f1Score under the threshold
precision Double: Precision under the threshold
recall Double: Recall under the threshold
threshold Double: Threshold used to calculate precision and recall.

accuracy number: accuracy under the threshold
f1score number: f1Score under the threshold
precision number: Precision under the threshold
recall number: Recall under the threshold
threshold number: Threshold used to calculate precision and recall.

accuracy float: accuracy under the threshold
f1score float: f1Score under the threshold
precision float: Precision under the threshold
recall float: Recall under the threshold
threshold float: Threshold used to calculate precision and recall.

accuracy Number: accuracy under the threshold
f1score Number: f1Score under the threshold
precision Number: Precision under the threshold
recall Number: Recall under the threshold
threshold Number: Threshold used to calculate precision and recall.

GetModelsModelCollectionItemMetricOverallMetricsReport

ConfidenceEntries List<GetModelsModelCollectionItemMetricOverallMetricsReportConfidenceEntry>: List of document classification confidence report.
DocumentCount int: Total test documents in the label.
MeanAveragePrecision double: Mean average precision under different thresholds

ConfidenceEntries []GetModelsModelCollectionItemMetricOverallMetricsReportConfidenceEntry: List of document classification confidence report.
DocumentCount int: Total test documents in the label.
MeanAveragePrecision float64: Mean average precision under different thresholds

confidenceEntries List<GetModelsModelCollectionItemMetricOverallMetricsReportConfidenceEntry>: List of document classification confidence report.
documentCount Integer: Total test documents in the label.
meanAveragePrecision Double: Mean average precision under different thresholds

confidenceEntries GetModelsModelCollectionItemMetricOverallMetricsReportConfidenceEntry[]: List of document classification confidence report.
documentCount number: Total test documents in the label.
meanAveragePrecision number: Mean average precision under different thresholds

confidence_entries Sequence[GetModelsModelCollectionItemMetricOverallMetricsReportConfidenceEntry]: List of document classification confidence report.
document_count int: Total test documents in the label.
mean_average_precision float: Mean average precision under different thresholds

confidenceEntries List<Property Map>: List of document classification confidence report.
documentCount Number: Total test documents in the label.
meanAveragePrecision Number: Mean average precision under different thresholds

GetModelsModelCollectionItemMetricOverallMetricsReportConfidenceEntry

Accuracy double: accuracy under the threshold
F1score double: f1Score under the threshold
Precision double: Precision under the threshold
Recall double: Recall under the threshold
Threshold double: Threshold used to calculate precision and recall.

Accuracy float64: accuracy under the threshold
F1score float64: f1Score under the threshold
Precision float64: Precision under the threshold
Recall float64: Recall under the threshold
Threshold float64: Threshold used to calculate precision and recall.

accuracy Double: accuracy under the threshold
f1score Double: f1Score under the threshold
precision Double: Precision under the threshold
recall Double: Recall under the threshold
threshold Double: Threshold used to calculate precision and recall.

accuracy number: accuracy under the threshold
f1score number: f1Score under the threshold
precision number: Precision under the threshold
recall number: Recall under the threshold
threshold number: Threshold used to calculate precision and recall.

accuracy float: accuracy under the threshold
f1score float: f1Score under the threshold
precision float: Precision under the threshold
recall float: Recall under the threshold
threshold float: Threshold used to calculate precision and recall.

accuracy Number: accuracy under the threshold
f1score Number: f1Score under the threshold
precision Number: Precision under the threshold
recall Number: Recall under the threshold
threshold Number: Threshold used to calculate precision and recall.

GetModelsModelCollectionItemModelSubType

ModelSubType string

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

ModelType string

The type of the Document model.

ModelSubType string

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

ModelType string

The type of the Document model.

modelSubType String

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

modelType String

The type of the Document model.

modelSubType string

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

modelType string

The type of the Document model.

model_sub_type str

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

model_type str

The type of the Document model.

modelSubType String

The model sub type for PRE_TRAINED_KEY_VALUE_EXTRACTION The allowed values are:

RECEIPT
INVOICE
PASSPORT
DRIVER_LICENSE
HEALTH_INSURANCE_ID

modelType String

The type of the Document model.

GetModelsModelCollectionItemTestingDataset

Bucket string: The name of the Object Storage bucket that contains the input data file.
DatasetId string: OCID of the Data Labeling dataset.
DatasetType string: The dataset type, based on where it is stored.
Namespace string: The namespace name of the Object Storage bucket that contains the input data file.
Object string: The object name of the input data file.

Bucket string: The name of the Object Storage bucket that contains the input data file.
DatasetId string: OCID of the Data Labeling dataset.
DatasetType string: The dataset type, based on where it is stored.
Namespace string: The namespace name of the Object Storage bucket that contains the input data file.
Object string: The object name of the input data file.

bucket String: The name of the Object Storage bucket that contains the input data file.
datasetId String: OCID of the Data Labeling dataset.
datasetType String: The dataset type, based on where it is stored.
namespace String: The namespace name of the Object Storage bucket that contains the input data file.
object String: The object name of the input data file.

bucket string: The name of the Object Storage bucket that contains the input data file.
datasetId string: OCID of the Data Labeling dataset.
datasetType string: The dataset type, based on where it is stored.
namespace string: The namespace name of the Object Storage bucket that contains the input data file.
object string: The object name of the input data file.

bucket str: The name of the Object Storage bucket that contains the input data file.
dataset_id str: OCID of the Data Labeling dataset.
dataset_type str: The dataset type, based on where it is stored.
namespace str: The namespace name of the Object Storage bucket that contains the input data file.
object str: The object name of the input data file.

bucket String: The name of the Object Storage bucket that contains the input data file.
datasetId String: OCID of the Data Labeling dataset.
datasetType String: The dataset type, based on where it is stored.
namespace String: The namespace name of the Object Storage bucket that contains the input data file.
object String: The object name of the input data file.

GetModelsModelCollectionItemTrainingDataset

Bucket string: The name of the Object Storage bucket that contains the input data file.
DatasetId string: OCID of the Data Labeling dataset.
DatasetType string: The dataset type, based on where it is stored.
Namespace string: The namespace name of the Object Storage bucket that contains the input data file.
Object string: The object name of the input data file.

Bucket string: The name of the Object Storage bucket that contains the input data file.
DatasetId string: OCID of the Data Labeling dataset.
DatasetType string: The dataset type, based on where it is stored.
Namespace string: The namespace name of the Object Storage bucket that contains the input data file.
Object string: The object name of the input data file.

bucket String: The name of the Object Storage bucket that contains the input data file.
datasetId String: OCID of the Data Labeling dataset.
datasetType String: The dataset type, based on where it is stored.
namespace String: The namespace name of the Object Storage bucket that contains the input data file.
object String: The object name of the input data file.

bucket string: The name of the Object Storage bucket that contains the input data file.
datasetId string: OCID of the Data Labeling dataset.
datasetType string: The dataset type, based on where it is stored.
namespace string: The namespace name of the Object Storage bucket that contains the input data file.
object string: The object name of the input data file.

bucket str: The name of the Object Storage bucket that contains the input data file.
dataset_id str: OCID of the Data Labeling dataset.
dataset_type str: The dataset type, based on where it is stored.
namespace str: The namespace name of the Object Storage bucket that contains the input data file.
object str: The object name of the input data file.

bucket String: The name of the Object Storage bucket that contains the input data file.
datasetId String: OCID of the Data Labeling dataset.
datasetType String: The dataset type, based on where it is stored.
namespace String: The namespace name of the Object Storage bucket that contains the input data file.
object String: The object name of the input data file.

GetModelsModelCollectionItemValidationDataset

Bucket string: The name of the Object Storage bucket that contains the input data file.
DatasetId string: OCID of the Data Labeling dataset.
DatasetType string: The dataset type, based on where it is stored.
Namespace string: The namespace name of the Object Storage bucket that contains the input data file.
Object string: The object name of the input data file.

Bucket string: The name of the Object Storage bucket that contains the input data file.
DatasetId string: OCID of the Data Labeling dataset.
DatasetType string: The dataset type, based on where it is stored.
Namespace string: The namespace name of the Object Storage bucket that contains the input data file.
Object string: The object name of the input data file.

bucket String: The name of the Object Storage bucket that contains the input data file.
datasetId String: OCID of the Data Labeling dataset.
datasetType String: The dataset type, based on where it is stored.
namespace String: The namespace name of the Object Storage bucket that contains the input data file.
object String: The object name of the input data file.

bucket string: The name of the Object Storage bucket that contains the input data file.
datasetId string: OCID of the Data Labeling dataset.
datasetType string: The dataset type, based on where it is stored.
namespace string: The namespace name of the Object Storage bucket that contains the input data file.
object string: The object name of the input data file.

bucket str: The name of the Object Storage bucket that contains the input data file.
dataset_id str: OCID of the Data Labeling dataset.
dataset_type str: The dataset type, based on where it is stored.
namespace str: The namespace name of the Object Storage bucket that contains the input data file.
object str: The object name of the input data file.

bucket String: The name of the Object Storage bucket that contains the input data file.
datasetId String: OCID of the Data Labeling dataset.
datasetType String: The dataset type, based on where it is stored.
namespace String: The namespace name of the Object Storage bucket that contains the input data file.
object String: The object name of the input data file.

Package Details

Repository: oci pulumi/pulumi-oci
License: Apache-2.0
Notes: This Pulumi package is based on the oci Terraform Provider.

Oracle Cloud Infrastructure v3.9.0 published on Wednesday, Sep 24, 2025 by Pulumi

pulumi/pulumi-oci

oci.AiDocument.getModels

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Example Usage

Using getModels

getModels Result

Supporting Types

GetModelsFilter

GetModelsModelCollection

GetModelsModelCollectionItem

GetModelsModelCollectionItemComponentModel

GetModelsModelCollectionItemLock

GetModelsModelCollectionItemMetric

GetModelsModelCollectionItemMetricDatasetSummary

GetModelsModelCollectionItemMetricLabelMetricsReport

GetModelsModelCollectionItemMetricLabelMetricsReportConfidenceEntry

GetModelsModelCollectionItemMetricOverallMetricsReport

GetModelsModelCollectionItemMetricOverallMetricsReportConfidenceEntry

GetModelsModelCollectionItemModelSubType

GetModelsModelCollectionItemTestingDataset

GetModelsModelCollectionItemTrainingDataset

GetModelsModelCollectionItemValidationDataset

Package Details

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