> ## Documentation Index > Fetch the complete documentation index at: https://arize-ax.mintlify.site/docs/llms.txt > Use this file to discover all available pages before exploring further. # Data import mutations > Control file and table import jobs, integration keys and BYOB connectors. Arguments, return types and a validated example for each of the 24 mutations. Control file and table import jobs, integration keys and BYOB connectors. For task-oriented walkthroughs of these operations, see the [Data import guide](/docs/ax/graphql-reference/guides/data-import). Every mutation below is sent as a `POST` to `https://app.arize.com/graphql` with an `x-api-key` header; see [Forming calls](/docs/ax/graphql-reference/overview/how-to-use-graphql/forming-calls). ## Mutations in this page * [`createFileImportJob`](#createfileimportjob): Create a job that will import model inferences from a blob store * [`updateFileImportJob`](#updatefileimportjob): Update an existing job that has been imported from a blob store * [`startFileImportJob`](#startfileimportjob): Start an existing job that has been imported from a blob store * [`pauseFileImportJob`](#pausefileimportjob): Pause an existing job that has been imported from a blob store * [`deleteFileImportJob`](#deletefileimportjob): Delete an existing job that has been imported from a blob store * [`resetFileStatus`](#resetfilestatus): Reset the status of a file * [`createTableImportJob`](#createtableimportjob): Create a job that will import model inferences from a table * [`updateTableImportJob`](#updatetableimportjob): Update an existing job that has been imported from a table * [`updateTableIngestionParameters`](#updatetableingestionparameters): Update an existing job that has been imported from a table * [`startTableImportJob`](#starttableimportjob): Start an existing job that has been imported from a table * [`pauseTableImportJob`](#pausetableimportjob): Pause an existing job that has been imported from a table * [`deleteTableImportJob`](#deletetableimportjob): Delete an existing job that has been imported from a table * [`createTriggeredOngoingTableImportJob`](#createtriggeredongoingtableimportjob): Create a job that will import model inferences from a table * [`createTriggeredOngoingTableRun`](#createtriggeredongoingtablerun): Schedule a job run that will import model inferences from a table * [`createIntegrationKey`](#createintegrationkey): Create integration key. * [`patchIntegrationKey`](#patchintegrationkey): Patch integration key. * [`testIntegrationKey`](#testintegrationkey): Test integration key. * [`deleteIntegrationKey`](#deleteintegrationkey): Delete integration key. * [`validateByobConnector`](#validatebyobconnector): Validate a byob connector * [`createByobConnector`](#createbyobconnector): Create a byob connector * [`updateByobConnector`](#updatebyobconnector): Update a byob connector * [`deleteByobConnector`](#deletebyobconnector): Delete a byob connector * [`updateByobSyncedDatasource`](#updatebyobsynceddatasource): Update a byob synced datasource * [`deleteByobDatasource`](#deletebyobdatasource): Delete a byob datasource ## Reference ### createFileImportJob Create a job that will import model inferences from a blob store `createFileImportJob(input: CreateFileImportJobInput!): CreateFileImportJobPayload` #### Arguments The space id for the space under which the model should be ingested Additional information required to locate an Azure container. Required when running with an Azure service principal or managed identity. The Azure Active Directory Tenant ID associated with the Storage Account. The Azure Storage Account name. The model identifier or name under which the model will be stored. The type of model. This determines how the model will be analyzed One of: `numeric`, `score_categorical`, `ranking`, `object_detection`, `generative_llm`, `multi_class`. The environment for which the inferences are being ingested One of: `production`, `validation`, `training`, `tracing`. A name for the ingestion batch. Only required if the environment is validation The model version. This will tag all the inferences as being for a specific version string. The cloud storage solution where the files reside One of: `S3`, `GCS`, `Azure`. The bucket where the files are stored. Arize must have access to this bucket The path to the files. Ex. cc\_model The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions The name of the predictionId column in the file The name of the predictionGroupId column in the file. Required if the model is type ranking A prefix capture group used to match feature columns A list of column names specifying features The name of the timestamp column in the file The name of the prediction label column in the file. Supported on model of type score\_categorical The name of the prediction score column in the file. Supported on models of type numeric and score\_categorical The name of the prediction scores column in the file. Supported on multi\_class models The name of the actual label column in the file. Supported on model of type score\_categorical The name of the actual score column in the file. Supported on models of type numeric and score\_categorical The name of the actual scores column in the file. Supported on multi\_class models The name of the threshold scores column in the file. Supported on multi\_class models The name of the relevance label column in the file. Required if the model is type ranking The name of the relevance score column in the file. Required if the model is type ranking The name of the model version column in the file The name of the validation batch id. Required if the model is type validation A prefix capture group used to match tag column A list of column names specifying tags A regex like capture group that should be used to match shap column The name of the rank column in the file. Required if the model is type ranking The names of fields to be excluded from data ingestion The embedding fields that will be ingested The embedding feature name The name of the vector column The name of the raw data column The name of the link to data column The columns which contain the prompt used in a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the response from a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative\_llm The name of the column which contains the prompt template The name of the column which contains the prompt template version The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative\_llm The name of the column which contains the llm name The name of the column which contains a map of llm params to values The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative\_llm The name of the column which contains the total number of tokens used in the llm call The name of the column which contains the number of prompt tokens in the llm call The name of the column which contains the number of response tokens in the llm call The name of the column which contains the response latency in ms of the llm call The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The name of the file to perform a dry run on (ex. test-file.avro). If a file name is not selected, the dry run will be performed on the first file If true, the import job will be attempted but no changes will be written. The fileResult field may be requested to check the validation status. Default is false #### Returns Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. Scalar fields: `filePath`, `validationStatus`. Object fields (select subfields): `error`. Scalar fields: `filePath`. Object fields (select subfields): `columnMetadata`, `rows`, `errorCode`. Scalar fields: `id`, `jobId`, `bucketName`, `createdAt`, `modelName`, `modelId`, `jobUuid`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `blobStore`, `prefix`, `totalFilesSuccessCount`, `totalFilesFailedCount`, `totalFilesPendingCount`, `jobStatus`. Object fields (select subfields): `schema`, `files`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation CreateFileImportJob($input: CreateFileImportJobInput!) { createFileImportJob(input: $input) { space { id name } validationResult { filePath } filePreview { filePath } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "spaceId": "", "modelName": "", "modelType": "numeric", "modelEnvironmentName": "production", "blobStore": "S3", "bucketName": "", "prefix": "", "schema": {} } } ``` ### updateFileImportJob Update an existing job that has been imported from a blob store `updateFileImportJob(input: UpdateFileImportJobInput!): UpdateFileImportJobPayload` #### Arguments The ID of an import job to delete The status of the imported job One of: `ONGOING_INACTIVE`, `ONGOING_DELETED`. The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions The name of the predictionId column in the file The name of the predictionGroupId column in the file. Required if the model is type ranking A prefix capture group used to match feature columns A list of column names specifying features The name of the timestamp column in the file The name of the prediction label column in the file. Supported on model of type score\_categorical The name of the prediction score column in the file. Supported on models of type numeric and score\_categorical The name of the prediction scores column in the file. Supported on multi\_class models The name of the actual label column in the file. Supported on model of type score\_categorical The name of the actual score column in the file. Supported on models of type numeric and score\_categorical The name of the actual scores column in the file. Supported on multi\_class models The name of the threshold scores column in the file. Supported on multi\_class models The name of the relevance label column in the file. Required if the model is type ranking The name of the relevance score column in the file. Required if the model is type ranking The name of the model version column in the file The name of the validation batch id. Required if the model is type validation A prefix capture group used to match tag column A list of column names specifying tags A regex like capture group that should be used to match shap column The name of the rank column in the file. Required if the model is type ranking The names of fields to be excluded from data ingestion The embedding fields that will be ingested The embedding feature name The name of the vector column The name of the raw data column The name of the link to data column The columns which contain the prompt used in a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the response from a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative\_llm The name of the column which contains the prompt template The name of the column which contains the prompt template version The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative\_llm The name of the column which contains the llm name The name of the column which contains a map of llm params to values The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative\_llm The name of the column which contains the total number of tokens used in the llm call The name of the column which contains the number of prompt tokens in the llm call The name of the column which contains the number of response tokens in the llm call The name of the column which contains the response latency in ms of the llm call The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores #### Returns The updated import job Scalar fields: `id`, `jobId`, `bucketName`, `createdAt`, `modelName`, `modelId`, `jobUuid`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `blobStore`, `prefix`, `totalFilesSuccessCount`, `totalFilesFailedCount`, `totalFilesPendingCount`, `jobStatus`. Object fields (select subfields): `schema`, `files`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation UpdateFileImportJob($input: UpdateFileImportJobInput!) { updateFileImportJob(input: $input) { fileImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "", "schema": {} } } ``` ### startFileImportJob Start an existing job that has been imported from a blob store `startFileImportJob(input: StartFileImportJobInput!): StartFileImportJobPayload` #### Arguments The ID of an import job to start #### Returns The import job which has been started Scalar fields: `id`, `jobId`, `bucketName`, `createdAt`, `modelName`, `modelId`, `jobUuid`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `blobStore`, `prefix`, `totalFilesSuccessCount`, `totalFilesFailedCount`, `totalFilesPendingCount`, `jobStatus`. Object fields (select subfields): `schema`, `files`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation StartFileImportJob($input: StartFileImportJobInput!) { startFileImportJob(input: $input) { fileImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "" } } ``` ### pauseFileImportJob Pause an existing job that has been imported from a blob store `pauseFileImportJob(input: PauseFileImportJobInput!): PauseFileImportJobPayload` #### Arguments The ID of an import job to pause #### Returns The paused import job Scalar fields: `id`, `jobId`, `bucketName`, `createdAt`, `modelName`, `modelId`, `jobUuid`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `blobStore`, `prefix`, `totalFilesSuccessCount`, `totalFilesFailedCount`, `totalFilesPendingCount`, `jobStatus`. Object fields (select subfields): `schema`, `files`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation PauseFileImportJob($input: PauseFileImportJobInput!) { pauseFileImportJob(input: $input) { fileImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "" } } ``` ### deleteFileImportJob Delete an existing job that has been imported from a blob store `deleteFileImportJob(input: DeleteFileImportJobInput!): DeleteFileImportJobPayload` #### Arguments The ID of an import job to delete #### Returns The deleted import job Scalar fields: `id`, `jobId`, `bucketName`, `createdAt`, `modelName`, `modelId`, `jobUuid`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `blobStore`, `prefix`, `totalFilesSuccessCount`, `totalFilesFailedCount`, `totalFilesPendingCount`, `jobStatus`. Object fields (select subfields): `schema`, `files`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation DeleteFileImportJob($input: DeleteFileImportJobInput!) { deleteFileImportJob(input: $input) { fileImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "" } } ``` ### resetFileStatus Reset the status of a file `resetFileStatus(input: ResetFileStatusInput!): ResetFileStatusPayload` #### Arguments The id of the job to reset the status of The id of the file to reset the status of #### Returns The updated import job Scalar fields: `id`, `jobId`, `bucketName`, `createdAt`, `modelName`, `modelId`, `jobUuid`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `blobStore`, `prefix`, `totalFilesSuccessCount`, `totalFilesFailedCount`, `totalFilesPendingCount`, `jobStatus`. Object fields (select subfields): `schema`, `files`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation ResetFileStatus($input: ResetFileStatusInput!) { resetFileStatus(input: $input) { job { id } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "", "fileId": "" } } ``` ### createTableImportJob Create a job that will import model inferences from a table `createTableImportJob(input: CreateTableImportJobInput!): CreateTableImportJobPayload` #### Arguments The space id for the space under which the model should be ingested The model identifier or name under which the model will be stored. The type of model. This determines how the model will be analyzed One of: `numeric`, `score_categorical`, `ranking`, `object_detection`, `generative_llm`, `multi_class`. The environment for which the inferences are being ingested One of: `production`, `validation`, `training`, `tracing`. A name for the ingestion batch. Only required if the environment is validation The model version. This will tag all the inferences as being for a specific version string. The table solution where the inferences reside One of: `BigQuery`, `Snowflake`, `Databricks`. The unique string used to differentiate a Google Cloud project The dataset where the tables are stored. Arize must have access to this dataset The path to the table The account identifier assigned to the Snowflake account. The schema which the target Table belongs to. Together, a database and schema comprise a namespace in Snowflake. The database which the schema of the target Table belongs to. The table which to import data from. The base URL of the workspace ex. databricks-hostname-example.databricks.com The URL fragment that corresponds to the resource, either a Compute Cluster or SQL Warehouse ex. /sql/1.0/warehouses/example The port of the resource ex. 443 Personal access token (for a service principal) ex. dapi12392103129093021. Required if 'azureResourceId' is needed & not provided. The Azure Resource Manager ID for the Azure Databricks workspace. Required only if not doing token-based authentication. If using Unity Catalog, this is the catalog name. If not, this will be hive\_metastore A logical collection of tables The name of the table or view The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions The name of the predictionId column in the file The name of the predictionGroupId column in the file. Required if the model is type ranking A prefix capture group used to match feature columns A list of column names specifying features The name of the timestamp column in the file The name of the prediction label column in the file. Supported on model of type score\_categorical The name of the prediction score column in the file. Supported on models of type numeric and score\_categorical The name of the prediction scores column in the file. Supported on multi\_class models The name of the actual label column in the file. Supported on model of type score\_categorical The name of the actual score column in the file. Supported on models of type numeric and score\_categorical The name of the actual scores column in the file. Supported on multi\_class models The name of the threshold scores column in the file. Supported on multi\_class models The name of the relevance label column in the file. Required if the model is type ranking The name of the relevance score column in the file. Required if the model is type ranking The name of the model version column in the file The name of the validation batch id. Required if the model is type validation A prefix capture group used to match tag column A list of column names specifying tags A regex like capture group that should be used to match shap column The name of the rank column in the file. Required if the model is type ranking The names of fields to be excluded from data ingestion The embedding fields that will be ingested The embedding feature name The name of the vector column The name of the raw data column The name of the link to data column The columns which contain the prompt used in a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the response from a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative\_llm The name of the column which contains the prompt template The name of the column which contains the prompt template version The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative\_llm The name of the column which contains the llm name The name of the column which contains a map of llm params to values The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative\_llm The name of the column which contains the total number of tokens used in the llm call The name of the column which contains the number of prompt tokens in the llm call The name of the column which contains the number of response tokens in the llm call The name of the column which contains the response latency in ms of the llm call The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The name of the change timestamp column in the file. If true, the import job will be attempted but no changes will be written. The fileResult field may be requested to check the validation status. Default is false #### Returns Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. Scalar fields: `jobId`, `tableQueryId`, `queryId`, `validationStatus`. Object fields (select subfields): `error`. Scalar fields: `id`, `jobId`, `jobStatus`, `tableStore`, `projectId`, `dataset`, `createdAt`, `modelName`, `modelId`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `table`, `totalQueriesSuccessCount`, `totalQueriesFailedCount`, `totalQueriesPendingCount`. Object fields (select subfields): `schema`, `tableIngestionParameters`, `queries`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation CreateTableImportJob($input: CreateTableImportJobInput!) { createTableImportJob(input: $input) { space { id name } validationResult { jobId } tableImportJob { id } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "spaceId": "", "modelName": "", "modelType": "numeric", "modelEnvironmentName": "production", "tableStore": "BigQuery", "schema": { "predictionId": "" } } } ``` ### updateTableImportJob Update an existing job that has been imported from a table `updateTableImportJob(input: UpdateTableImportJobInput!): UpdateTableImportJobPayload` #### Arguments The ID of an import job to delete The status of the imported job One of: `ONGOING_INACTIVE`, `ONGOING_DELETED`. The model version set as a constant The schema describes a mapping from your column names to model dimensions The name of the predictionId column in the file The name of the predictionGroupId column in the file. Required if the model is type ranking A prefix capture group used to match feature columns A list of column names specifying features The name of the timestamp column in the file The name of the prediction label column in the file. Supported on model of type score\_categorical The name of the prediction score column in the file. Supported on models of type numeric and score\_categorical The name of the prediction scores column in the file. Supported on multi\_class models The name of the actual label column in the file. Supported on model of type score\_categorical The name of the actual score column in the file. Supported on models of type numeric and score\_categorical The name of the actual scores column in the file. Supported on multi\_class models The name of the threshold scores column in the file. Supported on multi\_class models The name of the relevance label column in the file. Required if the model is type ranking The name of the relevance score column in the file. Required if the model is type ranking The name of the model version column in the file The name of the validation batch id. Required if the model is type validation A prefix capture group used to match tag column A list of column names specifying tags A regex like capture group that should be used to match shap column The name of the rank column in the file. Required if the model is type ranking The names of fields to be excluded from data ingestion The embedding fields that will be ingested The embedding feature name The name of the vector column The name of the raw data column The name of the link to data column The columns which contain the prompt used in a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the response from a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative\_llm The name of the column which contains the prompt template The name of the column which contains the prompt template version The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative\_llm The name of the column which contains the llm name The name of the column which contains a map of llm params to values The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative\_llm The name of the column which contains the total number of tokens used in the llm call The name of the column which contains the number of prompt tokens in the llm call The name of the column which contains the number of response tokens in the llm call The name of the column which contains the response latency in ms of the llm call The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The name of the change timestamp column in the file. Table ingestion parameters How often a user wants to query data in minutes How large of a query window to use in hours #### Returns The updated table import job Scalar fields: `id`, `jobId`, `jobStatus`, `tableStore`, `projectId`, `dataset`, `createdAt`, `modelName`, `modelId`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `table`, `totalQueriesSuccessCount`, `totalQueriesFailedCount`, `totalQueriesPendingCount`. Object fields (select subfields): `schema`, `tableIngestionParameters`, `queries`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation UpdateTableImportJob($input: UpdateTableImportJobInput!) { updateTableImportJob(input: $input) { tableImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "", "schema": { "predictionId": "" }, "tableIngestionParameters": {} } } ``` ### updateTableIngestionParameters Update an existing job that has been imported from a table `updateTableIngestionParameters(input: UpdateTableIngestionParametersInput!): UpdateTableIngestionParametersPayload` #### Arguments The import job id Table ingestion parameters How often a user wants to query data in minutes How large of a query window to use in hours #### Returns The updated table import job Scalar fields: `id`, `jobId`, `jobStatus`, `tableStore`, `projectId`, `dataset`, `createdAt`, `modelName`, `modelId`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `table`, `totalQueriesSuccessCount`, `totalQueriesFailedCount`, `totalQueriesPendingCount`. Object fields (select subfields): `schema`, `tableIngestionParameters`, `queries`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation UpdateTableIngestionParameters($input: UpdateTableIngestionParametersInput!) { updateTableIngestionParameters(input: $input) { tableImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "", "tableIngestionParameters": {} } } ``` ### startTableImportJob Start an existing job that has been imported from a table `startTableImportJob(input: StartTableImportJobInput!): StartTableImportJobPayload` #### Arguments The ID of an import job to start #### Returns The import job which has been started Scalar fields: `id`, `jobId`, `bucketName`, `createdAt`, `modelName`, `modelId`, `jobUuid`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `blobStore`, `prefix`, `totalFilesSuccessCount`, `totalFilesFailedCount`, `totalFilesPendingCount`, `jobStatus`. Object fields (select subfields): `schema`, `files`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation StartTableImportJob($input: StartTableImportJobInput!) { startTableImportJob(input: $input) { tableImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "" } } ``` ### pauseTableImportJob Pause an existing job that has been imported from a table `pauseTableImportJob(input: PauseTableImportJobInput!): PauseTableImportJobPayload` #### Arguments The ID of an import job to pause #### Returns The paused import job Scalar fields: `id`, `jobId`, `jobStatus`, `tableStore`, `projectId`, `dataset`, `createdAt`, `modelName`, `modelId`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `table`, `totalQueriesSuccessCount`, `totalQueriesFailedCount`, `totalQueriesPendingCount`. Object fields (select subfields): `schema`, `tableIngestionParameters`, `queries`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation PauseTableImportJob($input: PauseTableImportJobInput!) { pauseTableImportJob(input: $input) { tableImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "" } } ``` ### deleteTableImportJob Delete an existing job that has been imported from a table `deleteTableImportJob(input: DeleteTableImportJobInput!): DeleteTableImportJobPayload` #### Arguments The ID of a table import job to delete #### Returns The deleted table import job Scalar fields: `id`, `jobId`, `jobStatus`, `tableStore`, `projectId`, `dataset`, `createdAt`, `modelName`, `modelId`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `table`, `totalQueriesSuccessCount`, `totalQueriesFailedCount`, `totalQueriesPendingCount`. Object fields (select subfields): `schema`, `tableIngestionParameters`, `queries`. Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation DeleteTableImportJob($input: DeleteTableImportJobInput!) { deleteTableImportJob(input: $input) { tableImportJob { id } space { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "" } } ``` ### createTriggeredOngoingTableImportJob Create a job that will import model inferences from a table `createTriggeredOngoingTableImportJob(input: CreateTriggeredOngoingTableImportJobInput!): CreateTriggeredOngoingTableImportJobPayload` #### Arguments The space id for the space under which the model should be ingested The model identifier or name under which the model will be stored. The type of model. This determines how the model will be analyzed One of: `numeric`, `score_categorical`, `ranking`, `object_detection`, `generative_llm`, `multi_class`. The environment for which the inferences are being ingested One of: `production`, `validation`, `training`, `tracing`. A name for the ingestion batch. Only required if the environment is validation The model version. This will tag all the inferences as being for a specific version string. The table solution where the inferences reside One of: `BigQuery`, `Snowflake`, `Databricks`. The unique string used to differentiate a Google Cloud project The dataset where the tables are stored. Arize must have access to this dataset The path to the table The account identifier assigned to the Snowflake account. The schema which the target Table belongs to. Together, a database and schema comprise a namespace in Snowflake. The database which the schema of the target Table belongs to. The table which to import data from. The base URL of the workspace ex. databricks-hostname-example.databricks.com The URL fragment that corresponds to the resource, either a Compute Cluster or SQL Warehouse ex. /sql/1.0/warehouses/example The port of the resource ex. 443 Personal access token (for a service principal) ex. dapi12392103129093021. Required if 'azureResourceId' is needed & not provided. The Azure Resource Manager ID for the Azure Databricks workspace. Required only if not doing token-based authentication. If using Unity Catalog, this is the catalog name. If not, this will be hive\_metastore A logical collection of tables The name of the table or view The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions The name of the predictionId column in the file The name of the predictionGroupId column in the file. Required if the model is type ranking A prefix capture group used to match feature columns A list of column names specifying features The name of the timestamp column in the file The name of the prediction label column in the file. Supported on model of type score\_categorical The name of the prediction score column in the file. Supported on models of type numeric and score\_categorical The name of the prediction scores column in the file. Supported on multi\_class models The name of the actual label column in the file. Supported on model of type score\_categorical The name of the actual score column in the file. Supported on models of type numeric and score\_categorical The name of the actual scores column in the file. Supported on multi\_class models The name of the threshold scores column in the file. Supported on multi\_class models The name of the relevance label column in the file. Required if the model is type ranking The name of the relevance score column in the file. Required if the model is type ranking The name of the model version column in the file The name of the validation batch id. Required if the model is type validation A prefix capture group used to match tag column A list of column names specifying tags A regex like capture group that should be used to match shap column The name of the rank column in the file. Required if the model is type ranking The names of fields to be excluded from data ingestion The embedding fields that will be ingested The embedding feature name The name of the vector column The name of the raw data column The name of the link to data column The columns which contain the prompt used in a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the response from a generative LLM. Relevant if the model is generative\_llm The name of the vector column The name of the raw data column. Required if the prompt or response is specified The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative\_llm The name of the column which contains the prompt template The name of the column which contains the prompt template version The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative\_llm The name of the column which contains the llm name The name of the column which contains a map of llm params to values The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative\_llm The name of the column which contains the total number of tokens used in the llm call The name of the column which contains the number of prompt tokens in the llm call The name of the column which contains the number of response tokens in the llm call The name of the column which contains the response latency in ms of the llm call The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object\_detection The name of the column which contains the bounding box coordinates The name of the column which contains a map of bounding box categories The name of the column which contains a map of bounding box scores The name of the change timestamp column in the file. #### Returns Scalar fields: `id`, `name`, `description`, `uuid`, `createdAt`, `liveEnabled`, `isLLMOnlySpace`, `playgroundTracingModelId`, `evalTracingModelId`, `sandboxTracingModelId`, `mlModelsEnabled`, `private`, `gradientStartColor`, `gradientEndColor`, `hasDashboardsCreated`. Object fields (select subfields): `organization`, `models`, `monitors`, `dashboards`, `spaceUsers`, `byobConnectors`, `importJobs`, `tableJobs`, `sandboxJobs`, `signalInsightSummary`, `signalEnabledProjectSummary`, `signalIssues`, `agentIssues`, `automations`, `datasets`, `experiments`, `customMetrics`, `onlineTasks`, `prompts`, `tags`, `evaluators`, `annotationQueues`, `playgroundViews`, `annotationConfigs`, `traceFilters`, `llmIntegrations`, `defaultLlmIntegration`, `defaultAgentRuntime`, `gates`, `_access`. Scalar fields: `jobId`, `tableQueryId`, `queryId`, `validationStatus`. Object fields (select subfields): `error`. Scalar fields: `id`, `jobId`, `jobStatus`, `tableStore`, `projectId`, `dataset`, `createdAt`, `modelName`, `modelId`, `modelType`, `modelVersion`, `modelEnvironmentName`, `batchId`, `table`, `totalQueriesSuccessCount`, `totalQueriesFailedCount`, `totalQueriesPendingCount`. Object fields (select subfields): `schema`, `tableIngestionParameters`, `queries`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation CreateTriggeredOngoingTableImportJob($input: CreateTriggeredOngoingTableImportJobInput!) { createTriggeredOngoingTableImportJob(input: $input) { space { id name } validationResult { jobId } tableImportJob { id } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "spaceId": "", "modelName": "", "modelType": "numeric", "modelEnvironmentName": "production", "tableStore": "BigQuery", "schema": { "predictionId": "" } } } ``` ### createTriggeredOngoingTableRun Schedule a job run that will import model inferences from a table `createTriggeredOngoingTableRun(input: CreateTriggeredOngoingTableRunInput!): CreateTriggeredOngoingTableRunPayload` #### Arguments The job id to schedule a table ingestion run for The start time for the query The end time for the query #### Returns #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation CreateTriggeredOngoingTableRun($input: CreateTriggeredOngoingTableRunInput!) { createTriggeredOngoingTableRun(input: $input) { clientMutationId } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "jobId": "", "queryStart": "2026-01-01T00:00:00Z", "queryEnd": "2026-01-01T00:00:00Z" } } ``` ### createIntegrationKey `createIntegrationKey(input: CreateIntegrationKeyInput!): CreateIntegrationKeyPayload` #### Arguments The global relay id of the organization to create the integration key in. The name of an integration provider e.g. opsgeneie, pagerduty, slack One of: `opsgenie`, `pagerduty`, `slack`. The name of the integration, used to denote a target service or team e.x. ML Team Opsgenie. The integration's api key The priority/severity level when sending alerts to the given integration provider. One of: `opsgenieP1`, `opsgenieP2`, `opsgenieP3`, `opsgenieP4`, `opsgenieP5`, `pagerdutycritical`, `pagerdutyerror`, `pagerdutywarning`, `pagerdutyinfo`. #### Returns The created integration key. Scalar fields: `id`, `name`, `providerName`, `createdAt`, `alertSeverity`, `channelName`. Object fields (select subfields): `creator`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation CreateIntegrationKey($input: CreateIntegrationKeyInput!) { createIntegrationKey(input: $input) { integrationKey { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "accountOrganizationId": "", "providerName": "opsgenie", "serviceName": "", "apiKey": "" } } ``` ### patchIntegrationKey `patchIntegrationKey(input: PatchIntegrationKeyInput!): PatchIntegrationKeyPayload` #### Arguments The ID of the integration to patch Patch of the integration The name of the integration, used to denote a target service or team e.x. ML Team Opsgenie. The integration's api key The priority/severity level when sending alerts to the given integration provider. One of: `opsgenieP1`, `opsgenieP2`, `opsgenieP3`, `opsgenieP4`, `opsgenieP5`, `pagerdutycritical`, `pagerdutyerror`, `pagerdutywarning`, `pagerdutyinfo`. #### Returns The updated integration. Scalar fields: `id`, `name`, `providerName`, `createdAt`, `alertSeverity`, `channelName`. Object fields (select subfields): `creator`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation PatchIntegrationKey($input: PatchIntegrationKeyInput!) { patchIntegrationKey(input: $input) { integrationKey { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "integrationKeyId": "", "set": {} } } ``` ### testIntegrationKey `testIntegrationKey(input: TestIntegrationKeyInput!): TestIntegrationKeyPayload` #### Arguments The global relay id for the integration key to update #### Returns The http status code of the test integration endpoint response e.g. 201, 401, etc #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation TestIntegrationKey($input: TestIntegrationKeyInput!) { testIntegrationKey(input: $input) { statusCode } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "integrationKeyId": "" } } ``` ### deleteIntegrationKey `deleteIntegrationKey(input: DeleteIntegrationKeyInput!): DeleteIntegrationKeyPayload` #### Arguments The global relay id for the integration key to delete #### Returns The soft deleted integration key. Scalar fields: `id`, `name`, `providerName`, `createdAt`, `alertSeverity`, `channelName`. Object fields (select subfields): `creator`. #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation DeleteIntegrationKey($input: DeleteIntegrationKeyInput!) { deleteIntegrationKey(input: $input) { integrationKey { id name } } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "integrationKeyId": "" } } ``` ### validateByobConnector Validate a byob connector `validateByobConnector(input: ValidateByobConnectorInput!): ValidateByobConnectorPayload` #### Arguments The id of the space that the byob connector belongs to The object that identifies the byob connector The id of the space that the byob connector belongs to The cloud storage provider that the byob connector belongs to One of: `GCS`, `S3`, `AZURE`. The full path of the bucket that the byob connector belongs to The Azure tenant ID for Azure Blob Storage connectors #### Returns Whether the byob connector is valid The reason why the byob connector is valid One of: `UNKNOWN_INVALID_REASON`, `FAILED_BUCKET_OWNERSHIP_CHECK`, `FAILED_BUCKET_ACCESS`. The message that explains why the byob connector is valid #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation ValidateByobConnector($input: ValidateByobConnectorInput!) { validateByobConnector(input: $input) { isValid validationReason validationMessage } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "spaceId": "", "connectorIdentifier": { "spaceId": "", "cloudStorageProvider": "GCS", "bucketAndPath": "" } } } ``` ### createByobConnector Create a byob connector `createByobConnector(input: CreateByobConnectorInput!): CreateByobConnectorPayload` #### Arguments The id of the space that the byob connector belongs to The identifier of the byob connector The id of the space that the byob connector belongs to The cloud storage provider that the byob connector belongs to One of: `GCS`, `S3`, `AZURE`. The full path of the bucket that the byob connector belongs to The name of the byob connector The external model ids of the byob connector The table format for the connector (defaults to ICEBERG) One of: `ICEBERG`, `DELTA`. The Azure tenant ID for Azure Blob Storage connectors #### Returns The id of the created byob connector #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation CreateByobConnector($input: CreateByobConnectorInput!) { createByobConnector(input: $input) { id } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "spaceId": "", "connectorIdentifier": { "spaceId": "", "cloudStorageProvider": "GCS", "bucketAndPath": "" }, "name": "", "externalModelIds": [ "" ] } } ``` ### updateByobConnector Update a byob connector `updateByobConnector(input: UpdateByobConnectorInput!): UpdateByobConnectorPayload` #### Arguments The id of the byob connector The id of the space that the byob connector belongs to The name of the byob connector The external model ids of the byob connector #### Returns Whether the update was successful #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation UpdateByobConnector($input: UpdateByobConnectorInput!) { updateByobConnector(input: $input) { success } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "id": "", "spaceId": "", "name": "", "externalModelIds": [ "" ] } } ``` ### deleteByobConnector Delete a byob connector `deleteByobConnector(input: DeleteByobConnectorInput!): DeleteByobConnectorPayload` #### Arguments The id of the byob connector The id of the space that the byob connector belongs to #### Returns Whether the delete was successful #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation DeleteByobConnector($input: DeleteByobConnectorInput!) { deleteByobConnector(input: $input) { success } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "id": "", "spaceId": "" } } ``` ### updateByobSyncedDatasource Update a byob synced datasource `updateByobSyncedDatasource(input: UpdateByobSyncedDatasourceInput!): UpdateByobSyncedDatasourcePayload` #### Arguments The id of the byob synced datasource The id of the space The active status of the byob synced datasource One of: `active`, `paused`. The sync frequency minutes of the byob synced datasource #### Returns Whether the update was successful #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation UpdateByobSyncedDatasource($input: UpdateByobSyncedDatasourceInput!) { updateByobSyncedDatasource(input: $input) { success } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "id": "", "spaceId": "" } } ``` ### deleteByobDatasource Delete a byob datasource `deleteByobDatasource(input: DeleteByobDatasourceInput!): DeleteByobDatasourcePayload` #### Arguments The id of the byob datasource The id of the space that the byob datasource belongs to #### Returns Whether the delete was successful #### Example Only required input fields are shown. Replace `` and `` placeholders with real values; the [object graph](/docs/ax/graphql-reference/queries/object-graph) page shows how to look IDs up. ```graphql Mutation theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} mutation DeleteByobDatasource($input: DeleteByobDatasourceInput!) { deleteByobDatasource(input: $input) { success } } ``` ```json Variables theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}} { "input": { "id": "", "spaceId": "" } } ```