openapi: 3.1.0 info: title: Amazon Neptune Neptune Analytics ?Action=AddTagsToResource ?Action=AddTagsToResource ML API description: Neptune Analytics is a memory-optimized graph database engine for analytics, providing optimized graph analytic algorithms, low-latency queries, and vector search capabilities within graph traversals. This API provides management operations for Neptune Analytics graph resources including creating, managing, and querying graph databases optimized for analytical workloads. version: '2023-11-29' contact: name: Amazon Web Services url: https://docs.aws.amazon.com/neptune-analytics/latest/userguide/what-is-neptune-analytics.html license: name: Apache 2.0 url: https://www.apache.org/licenses/LICENSE-2.0 servers: - url: https://neptune-graph.{region}.amazonaws.com description: Neptune Analytics control plane regional endpoint variables: region: default: us-east-1 description: AWS region security: - aws_sigv4: [] tags: - name: ML description: Machine learning operations paths: /ml/dataprocessing: post: operationId: startMLDataProcessingJob summary: Amazon Neptune Start an ML Data Processing Job description: Creates a new Neptune ML data processing job that prepares graph data for model training using Amazon SageMaker. tags: - ML requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/StartMLDataProcessingJobInput' responses: '200': description: Data processing job started successfully. content: application/json: schema: type: object properties: id: type: string examples: startMLDataProcessingJob200Example: summary: Default startMLDataProcessingJob 200 response x-microcks-default: true value: id: neptune-cluster-abc123 x-microcks-operation: delay: 0 dispatcher: FALLBACK get: operationId: listMLDataProcessingJobs summary: Amazon Neptune List ML Data Processing Jobs description: Returns a list of active Neptune ML data processing job IDs. tags: - ML parameters: - name: maxItems in: query description: Maximum number of items to return (default 10, max 1024). schema: type: integer default: 10 maximum: 1024 - name: neptuneIamRoleArn in: query description: The ARN of the IAM role for Neptune access. schema: type: string responses: '200': description: Data processing job list retrieved successfully. content: application/json: schema: type: object properties: ids: type: array items: type: string examples: listMLDataProcessingJobs200Example: summary: Default listMLDataProcessingJobs 200 response x-microcks-default: true value: ids: - example-value x-microcks-operation: delay: 0 dispatcher: FALLBACK /ml/dataprocessing/{jobId}: get: operationId: getMLDataProcessingJobStatus summary: Amazon Neptune Get ML Data Processing Job Status description: Returns the status of a Neptune ML data processing job. tags: - ML parameters: - name: jobId in: path required: true description: The unique identifier of the data processing job. schema: type: string - name: neptuneIamRoleArn in: query description: The ARN of the IAM role for Neptune access. schema: type: string responses: '200': description: Job status retrieved successfully. content: application/json: schema: $ref: '#/components/schemas/MLJobStatusOutput' examples: getMLDataProcessingJobStatus200Example: summary: Default getMLDataProcessingJobStatus 200 response x-microcks-default: true value: status: available id: neptune-cluster-abc123 processingJob: name: my-neptune-cluster arn: arn:aws:neptune:us-east-1:123456789012:db:neptune-cluster-1 status: available outputLocation: example-value x-microcks-operation: delay: 0 dispatcher: FALLBACK delete: operationId: cancelMLDataProcessingJob summary: Amazon Neptune Cancel an ML Data Processing Job description: Cancels a running Neptune ML data processing job. tags: - ML parameters: - name: jobId in: path required: true description: The unique identifier of the data processing job. schema: type: string - name: clean in: query description: Whether to delete all S3 artifacts when cancelling. schema: type: boolean default: false - name: neptuneIamRoleArn in: query description: The ARN of the IAM role for Neptune access. schema: type: string responses: '200': description: Job cancelled successfully. x-microcks-operation: delay: 0 dispatcher: FALLBACK /ml/modeltraining: post: operationId: startMLModelTrainingJob summary: Amazon Neptune Start an ML Model Training Job description: Creates a new Neptune ML model training job using Amazon SageMaker. tags: - ML requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/StartMLModelTrainingJobInput' responses: '200': description: Model training job started successfully. content: application/json: schema: type: object properties: id: type: string examples: startMLModelTrainingJob200Example: summary: Default startMLModelTrainingJob 200 response x-microcks-default: true value: id: neptune-cluster-abc123 x-microcks-operation: delay: 0 dispatcher: FALLBACK get: operationId: listMLModelTrainingJobs summary: Amazon Neptune List ML Model Training Jobs description: Returns a list of active Neptune ML model training job IDs. tags: - ML parameters: - name: maxItems in: query schema: type: integer default: 10 maximum: 1024 - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Model training job list retrieved successfully. content: application/json: schema: type: object properties: ids: type: array items: type: string examples: listMLModelTrainingJobs200Example: summary: Default listMLModelTrainingJobs 200 response x-microcks-default: true value: ids: - example-value x-microcks-operation: delay: 0 dispatcher: FALLBACK /ml/modeltraining/{jobId}: get: operationId: getMLModelTrainingJobStatus summary: Amazon Neptune Get ML Model Training Job Status description: Returns the status of a Neptune ML model training job. tags: - ML parameters: - name: jobId in: path required: true schema: type: string - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Job status retrieved successfully. content: application/json: schema: $ref: '#/components/schemas/MLJobStatusOutput' examples: getMLModelTrainingJobStatus200Example: summary: Default getMLModelTrainingJobStatus 200 response x-microcks-default: true value: status: available id: neptune-cluster-abc123 processingJob: name: my-neptune-cluster arn: arn:aws:neptune:us-east-1:123456789012:db:neptune-cluster-1 status: available outputLocation: example-value x-microcks-operation: delay: 0 dispatcher: FALLBACK delete: operationId: cancelMLModelTrainingJob summary: Amazon Neptune Cancel an ML Model Training Job description: Cancels a running Neptune ML model training job. tags: - ML parameters: - name: jobId in: path required: true schema: type: string - name: clean in: query schema: type: boolean default: false - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Job cancelled successfully. x-microcks-operation: delay: 0 dispatcher: FALLBACK /ml/modeltransform: post: operationId: startMLModelTransformJob summary: Amazon Neptune Start an ML Model Transform Job description: Creates a new Neptune ML model transform job that generates model artifacts for inference. tags: - ML requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/StartMLModelTransformJobInput' responses: '200': description: Model transform job started successfully. content: application/json: schema: type: object properties: id: type: string examples: startMLModelTransformJob200Example: summary: Default startMLModelTransformJob 200 response x-microcks-default: true value: id: neptune-cluster-abc123 x-microcks-operation: delay: 0 dispatcher: FALLBACK get: operationId: listMLModelTransformJobs summary: Amazon Neptune List ML Model Transform Jobs description: Returns a list of active Neptune ML model transform job IDs. tags: - ML parameters: - name: maxItems in: query schema: type: integer default: 10 maximum: 1024 - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Model transform job list retrieved successfully. x-microcks-operation: delay: 0 dispatcher: FALLBACK /ml/modeltransform/{jobId}: get: operationId: getMLModelTransformJobStatus summary: Amazon Neptune Get ML Model Transform Job Status description: Returns the status of a Neptune ML model transform job. tags: - ML parameters: - name: jobId in: path required: true schema: type: string - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Job status retrieved successfully. content: application/json: schema: $ref: '#/components/schemas/MLJobStatusOutput' examples: getMLModelTransformJobStatus200Example: summary: Default getMLModelTransformJobStatus 200 response x-microcks-default: true value: status: available id: neptune-cluster-abc123 processingJob: name: my-neptune-cluster arn: arn:aws:neptune:us-east-1:123456789012:db:neptune-cluster-1 status: available outputLocation: example-value x-microcks-operation: delay: 0 dispatcher: FALLBACK delete: operationId: cancelMLModelTransformJob summary: Amazon Neptune Cancel an ML Model Transform Job description: Cancels a running Neptune ML model transform job. tags: - ML parameters: - name: jobId in: path required: true schema: type: string - name: clean in: query schema: type: boolean default: false - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Job cancelled successfully. x-microcks-operation: delay: 0 dispatcher: FALLBACK /ml/endpoints: post: operationId: createMLEndpoint summary: Amazon Neptune Create an ML Inference Endpoint description: Creates a new Neptune ML inference endpoint backed by Amazon SageMaker. tags: - ML requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CreateMLEndpointInput' responses: '200': description: Inference endpoint created successfully. content: application/json: schema: type: object properties: id: type: string examples: createMLEndpoint200Example: summary: Default createMLEndpoint 200 response x-microcks-default: true value: id: neptune-cluster-abc123 x-microcks-operation: delay: 0 dispatcher: FALLBACK get: operationId: listMLEndpoints summary: Amazon Neptune List ML Inference Endpoints description: Returns a list of active Neptune ML inference endpoint IDs. tags: - ML parameters: - name: maxItems in: query schema: type: integer default: 10 maximum: 1024 - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Endpoint list retrieved successfully. x-microcks-operation: delay: 0 dispatcher: FALLBACK /ml/endpoints/{endpointId}: get: operationId: getMLEndpointStatus summary: Amazon Neptune Get ML Inference Endpoint Status description: Returns the status of a Neptune ML inference endpoint. tags: - ML parameters: - name: endpointId in: path required: true schema: type: string - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Endpoint status retrieved successfully. content: application/json: schema: $ref: '#/components/schemas/MLEndpointStatusOutput' examples: getMLEndpointStatus200Example: summary: Default getMLEndpointStatus 200 response x-microcks-default: true value: status: available id: neptune-cluster-abc123 endpoint: name: my-neptune-cluster arn: arn:aws:neptune:us-east-1:123456789012:db:neptune-cluster-1 status: available endpointConfig: {} x-microcks-operation: delay: 0 dispatcher: FALLBACK delete: operationId: deleteMLEndpoint summary: Amazon Neptune Delete an ML Inference Endpoint description: Deletes a Neptune ML inference endpoint. tags: - ML parameters: - name: endpointId in: path required: true schema: type: string - name: clean in: query schema: type: boolean default: false - name: neptuneIamRoleArn in: query schema: type: string responses: '200': description: Endpoint deleted successfully. x-microcks-operation: delay: 0 dispatcher: FALLBACK components: schemas: MLJobStatusOutput: type: object properties: status: type: string id: type: string processingJob: type: object properties: name: type: string arn: type: string status: type: string outputLocation: type: string StartMLModelTrainingJobInput: type: object required: - dataProcessingJobId - trainModelS3Location properties: id: type: string dataProcessingJobId: type: string description: Job ID of the completed data processing job. trainModelS3Location: type: string description: S3 location for model artifacts. previousModelTrainingJobId: type: string sagemakerIamRoleArn: type: string neptuneIamRoleArn: type: string modelName: type: string description: The model type to use. enum: - rgcn - transe - distmult - rotate - custom baseProcessingInstanceType: type: string trainingInstanceType: type: string default: ml.p3.2xlarge trainingInstanceVolumeSizeInGB: type: integer trainingTimeOutInSeconds: type: integer default: 86400 maxHPONumberOfTrainingJobs: type: integer default: 2 maxHPOParallelTrainingJobs: type: integer default: 2 subnets: type: array items: type: string securityGroupIds: type: array items: type: string volumeEncryptionKMSKey: type: string s3OutputEncryptionKMSKey: type: string enableInterContainerTrafficEncryption: type: boolean default: true enableManagedSpotTraining: type: boolean default: false customModelTrainingParameters: type: object properties: sourceS3DirectoryPath: type: string trainingEntryPointScript: type: string transformEntryPointScript: type: string MLEndpointStatusOutput: type: object properties: status: type: string id: type: string endpoint: type: object properties: name: type: string arn: type: string status: type: string endpointConfig: type: object StartMLModelTransformJobInput: type: object required: - modelTransformOutputS3Location properties: id: type: string dataProcessingJobId: type: string mlModelTrainingJobId: type: string trainingJobName: type: string modelTransformOutputS3Location: type: string description: S3 location for transform output. sagemakerIamRoleArn: type: string neptuneIamRoleArn: type: string baseProcessingInstanceType: type: string baseProcessingInstanceVolumeSizeInGB: type: integer subnets: type: array items: type: string securityGroupIds: type: array items: type: string volumeEncryptionKMSKey: type: string s3OutputEncryptionKMSKey: type: string enableInterContainerTrafficEncryption: type: boolean default: true customModelTransformParameters: type: object properties: sourceS3DirectoryPath: type: string transformEntryPointScript: type: string CreateMLEndpointInput: type: object properties: id: type: string description: Unique identifier for the endpoint. mlModelTrainingJobId: type: string description: Job ID from a completed training job. mlModelTransformJobId: type: string description: Job ID from a completed transform job. update: type: boolean description: Whether this is an update request. default: false neptuneIamRoleArn: type: string modelName: type: string enum: - rgcn - kge - transe - distmult - rotate instanceType: type: string default: ml.m5.xlarge instanceCount: type: integer default: 1 volumeEncryptionKMSKey: type: string StartMLDataProcessingJobInput: type: object required: - inputDataS3Location - processedDataS3Location properties: id: type: string description: Unique identifier for the job (auto-generated if omitted). inputDataS3Location: type: string description: S3 URI for input data. processedDataS3Location: type: string description: S3 URI for output results. previousDataProcessingJobId: type: string description: Job ID of a previous job for incremental processing. sagemakerIamRoleArn: type: string description: IAM role ARN for SageMaker execution. neptuneIamRoleArn: type: string description: IAM role ARN for Neptune access. processingInstanceType: type: string description: ML instance type (default auto-selected ml.r5 type). processingInstanceVolumeSizeInGB: type: integer description: Disk volume size in GB (default 0 = auto-selected). processingTimeOutInSeconds: type: integer description: Timeout in seconds (default 86400). modelType: type: string description: Model type selection. enum: - heterogeneous - kge configFileName: type: string description: Data specification file name. default: training-data-configuration.json subnets: type: array items: type: string description: Subnet IDs in Neptune VPC. securityGroupIds: type: array items: type: string description: VPC security group IDs. volumeEncryptionKMSKey: type: string s3OutputEncryptionKMSKey: type: string enableInterContainerTrafficEncryption: type: boolean default: true securitySchemes: aws_sigv4: type: apiKey name: Authorization in: header description: AWS Signature Version 4 authentication