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‎docs/apis/syntex/rest-applymodel-method.md

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---
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title: Batch apply model
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ms.author: chucked
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author: chuckedmonson
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manager: pamgreen
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ms.reviewer: ssquires
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audience: admin
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ms.topic: reference
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ms.prod: microsoft-365-enterprise
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search.appverid:
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ms.collection: m365initiative-syntex
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ms.localizationpriority: high
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description: Use REST API to apply a document understanding model to one or more libraries.
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---
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# Batch Apply model
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Applies (or syncs) a trained document understanding model to one or more libraries (see [example](rest-applymodel-method.md#examples)).
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## HTTP request
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```HTTP
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POST /_api/machinelearning/publications HTTP/1.1
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```
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## URI parameters
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None
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## Request headers
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| Header | Value |
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|--------|-------|
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|Accept|application/json;odata=verbose|
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|Content-Type|application/json;odata=verbose;charset=utf-8|
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|x-requestdigest|The appropriate digest for current site.|
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## Request body
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| Name | Required | Type | Description |
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|--------|-------|--------|------------|
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|__metadata|yes|string|Set the object meta on the SPO. Always use the value: {"type": "Microsoft.Office.Server.ContentCenter.SPMachineLearningPublicationsEntityData"}.|
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|Publications|yes|MachineLearningPublicationEntityData[]|The collection of MachineLearningPublicationEntityData each of which specifies the model and target document library.|
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### MachineLearningPublicationEntityData
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| Name | Required | Type | Description |
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|--------|-------|--------|------------|
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|ModelUniqueId|yes|string|The unique ID of the model file.|
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|TargetSiteUrl|yes|string|The full URL of the target library site.|
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|TargetWebServerRelativeUrl|yes|string|The server relative URL of the web for the target library.|
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|TargetLibraryServerRelativeUrl|yes|string|The server relative URL of the target library.|
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|ViewOption|no|string|Specifies whether to set new model view as the library default.|
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## Response
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| Name | Type | Description|
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|--------|-------|------------|
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|201 Created||This is a customized API to support applying a model to multi document libraries. In the case of partial success, 201 created could still be returned and the caller needs to inspect the response body to understand if the model has been successfully applied to a document library.|
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## Response Body
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| Name | Type | Description|
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|--------|-------|------------|
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|TotalSuccesses|int|The total number of a model being successfully applied to a document library.|
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|TotalFailures|int|The total number of a model failing to be applied to a document library.|
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|Details|MachineLearningPublicationResult[]|The collection of MachineLearningPublicationResult each of which specifies the detailed result of applying the model to the document library.|
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### MachineLearningPublicationResult
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| Name | Type | Description|
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|--------|-------|------------|
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|StatusCode|int|The HTTP status code.|
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|ErrorMessage|string|The error message which tells what's wrong when apply the model to the document library.|
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|Publication|MachineLearningPublicationEntityData|It specifies the model info and the target document library.|
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### MachineLearningPublicationEntityData
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| Name | Type | Description |
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|--------|--------|------------|
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|ModelUniqueId|string|The unique ID of the model file.|
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|TargetSiteUrl|string|The full URL of the target library site.|
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|TargetWebServerRelativeUrl|string|The server relative URL of the web for the target library.|
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|TargetLibraryServerRelativeUrl|string|The server relative URL of the target library.|
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## Examples
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### Apply a model to the contracts document library in the repository site
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In this sample, the ID of the Contoso Contract document understanding model is `7645e69d-21fb-4a24-a17a-9bdfa7cb63dc`.
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#### Sample request
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```HTTP
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{
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"__metadata": {
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"type": "Microsoft.Office.Server.ContentCenter.SPMachineLearningPublicationsEntityData"
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},
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"Publications": {
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"results": [
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{
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"ModelUniqueId": "7645e69d-21fb-4a24-a17a-9bdfa7cb63dc",
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"TargetSiteUrl": "https://contoso.sharepoint.com/sites/repository/",
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"TargetWebServerRelativeUrl": "/sites/repository",
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"TargetLibraryServerRelativeUrl": "/sites/repository/contracts",
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"ViewOption": "NewViewAsDefault"
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}
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]
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}
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}
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```
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#### Sample response
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In the response, TotalFailures and TotalSuccesses refers to the number of failures and successes of the model being applies to the specified libraries.
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**Status code:** 201
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```JSON
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{
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"Details": [
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{
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"ErrorMessage": null,
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"Publication": {
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"ModelUniqueId": "7645e69d-21fb-4a24-a17a-9bdfa7cb63dc",
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"TargetSiteUrl": "https://contoso.sharepoint.com/sites/repository/",
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"TargetWebServerRelativeUrl": "/sites/repository",
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"TargetLibraryServerRelativeUrl": "/sites/repository/contracts",
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"ViewOption": "NewViewAsDefault"
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},
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"StatusCode": 201
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}
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],
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"TotalFailures": 0,
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"TotalSuccesses": 1
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}
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```
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## See also
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[Syntex document understanding model REST API](syntex-model-rest-api.md)

‎docs/apis/syntex/rest-batchdelete-method.md

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---
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title: BatchDelete
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ms.author: chucked
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author: chuckedmonson
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manager: pamgreen
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ms.reviewer: ssquires
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audience: admin
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ms.topic: reference
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ms.prod: microsoft-365-enterprise
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search.appverid:
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ms.collection: m365initiative-syntex
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ms.localizationpriority: high
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description: Use REST API to remove an applied document understanding model from one or more libraries.
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---
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# BatchDelete
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Removes an applied document understanding model from one or more libraries. Note that a model must be removed from all libraries before it can be deleted (see [example](rest-batchdelete-method.md#examples)).
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## HTTP request
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```HTTP
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POST /_api/machinelearning/publications/batchdelete HTTP/1.1
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```
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## URI parameters
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None
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## Request headers
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| Header | Value |
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|--------|-------|
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|Accept|application/json;odata=verbose|
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|Content-Type|application/json;odata=verbose;charset=utf-8|
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|x-requestdigest|The appropriate digest for current site.|
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## Request body
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| Name | Required | Type | Description |
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|--------|-------|--------|------------|
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|Publications|yes|MachineLearningPublicationEntityData[]|The collection of MachineLearningPublicationEntityData each of which specifies the model and target document library.|
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### MachineLearningPublicationEntityData
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| Name | Required | Type | Description |
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|--------|-------|--------|------------|
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|ModelUniqueId|yes|string|The unique ID of the model file.|
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|TargetSiteUrl|yes|string|The full URL of the target library site.|
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|TargetWebServerRelativeUrl|yes|string|The server relative URL of the web for the target library.|
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|TargetLibraryServerRelativeUrl|yes|string|The server relative URL of the target library.|
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## Response
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| Name | Type | Description|
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|--------|-------|------------|
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|200 OK||This is a customized API to support removing a model from multi document libraries. In the case of partial success, 200 OK could still be returned and the caller needs to inspect the response body to understand if the model has been successfully removed from a document library.|
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## Response Body
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| Name | Type | Description|
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|--------|-------|------------|
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|TotalSuccesses|int|The total number of a model being successfully removed from a document library.|
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|TotalFailures|int|The total number of a model failing to be removed from a document library.|
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|Details|MachineLearningPublicationResult[]|The collection of MachineLearningPublicationResult each of which specifies the detailed result of removing the model from a document library.|
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### MachineLearningPublicationResult
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| Name | Type | Description|
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|--------|-------|------------|
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|StatusCode|int|The HTTP status code.|
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|ErrorMessage|string|The error message which tells what's wrong when apply the model to the document library.|
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|Publication|MachineLearningPublicationEntityData|It specifies the model info and the target document library.|
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### MachineLearningPublicationEntityData
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| Name | Type | Description |
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|--------|--------|------------|
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|ModelUniqueId|string|The unique ID of the model file.|
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|TargetSiteUrl|string|The full URL of the target library site.|
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|TargetWebServerRelativeUrl|string|The server relative URL of the web for the target library.|
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|TargetLibraryServerRelativeUrl|string|The server relative URL of the target library.|
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## Examples
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### Remove a model from the contracts document library in the repository site
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In this sample, the ID of the Contoso Contract document understanding model is `7645e69d-21fb-4a24-a17a-9bdfa7cb63dc`.
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#### Sample request
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```HTTP
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{
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"publications": [
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{
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"ModelUniqueId": "7645e69d-21fb-4a24-a17a-9bdfa7cb63dc",
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"TargetSiteUrl": "https://constco.sharepoint-df.com/sites/docsite",
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"TargetWebServerRelativeUrl": "/sites/docsite ",
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"TargetLibraryServerRelativeUrl": "/sites/dcocsite/joedcos"
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}
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]
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}
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```
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#### Sample response
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In the response, TotalFailures and TotalSuccesses refer to the number of failures and successes of the model being removed from the specified libraries.
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**Status code:** 200
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```JSON
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{
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"Details": [
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{
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"ErrorMessage": null,
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"Publication": {
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"ModelUniqueId": "7645e69d-21fb-4a24-a17a-9bdfa7cb63dc",
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"TargetSiteUrl": "https://contoso.sharepoint.com/sites/repository/",
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"TargetWebServerRelativeUrl": "/sites/repository",
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"TargetLibraryServerRelativeUrl": "/sites/repository/contracts",
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"ViewOption": "NewViewAsDefault"
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},
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"StatusCode": 200
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}
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],
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"TotalFailures": 0,
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"TotalSuccesses": 1
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}
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```
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## See also
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[Syntex document understanding model REST API](syntex-model-rest-api.md)

‎docs/apis/syntex/rest-createclassificationrequest.md

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---
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title: Create file classification request
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ms.author: chucked
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author: chuckedmonson
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manager: pamgreen
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ms.reviewer: ssquires
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audience: admin
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ms.topic: reference
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ms.prod: microsoft-365-enterprise
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search.appverid:
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ms.collection: m365initiative-syntex
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ms.localizationpriority: high
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description: Use REST API to create a request to classify one or more files using a trained document understanding model.
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---
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# Create file classification request
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Creates a request to classify one or more files using the applied document understanding model. (For more information, see [example](rest-createclassificationrequest.md#examples).)
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The REST service of SharePoint Online (and SharePoint 2016 and later on-premises) supports the combining of multiple requests. Requests are combined into a single call to the service by using the OData $batch query option. This method can be used to enqueue classification work items for hundreds of documents at one time.
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## HTTP request
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```http
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POST /_api/machinelearning/workItems HTTP/1.1
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```
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## URI Parameters
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None
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## Request headers
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| Header | Value |
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|--------|-------|
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|Accept|application/json;odata=verbose|
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|Content-Type|application/json;odata=verbose;charset=utf-8|
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|x-requestdigest|The appropriate digest for current site|
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## Request body
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|Name |Type |Description |
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|--------|-------|------------|
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|_metadata|string |Set the object meta on the SPO. Always use the value: {"type": "Microsoft.Office.Server.ContentCenter.SPMachineLearningWorkItemEntityData"}. |
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|TargetSiteId|guid|The ID of the site where the file to classify is located. This can be omitted when TargetSiteUrl has a value. |
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|TargetSiteUrl|string|The full URL of the site where the file to classify is located. This can be omitted when TargeSiteId has a value.|
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|TargetWebId|guid|The ID of the web where the file to classify is located. This can be omitted when TargetWebServerRelativeUrl has a value. |
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|TargetWebServerRelativeUrl|string|The server relative URL of the web where the file to classify is located. This can be omitted when TargetWebId has a value. |
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|TargetUniqueId|guid|The ID of the folder to classify. This can be omitted when TargetServerRelativeUrl has a value. |
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|TargetServerRelativeUrl|string|The server relative URL of the file to classify is located. This can be omitted when TargetUniqueId has a value.|
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## Responses
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| Name | Type | Description|
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|--------|-------|------------|
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|201 Created| |The response is customized. In there is failure, it could still return 201 Created. The caller should further check the response body to determine the exact result.|
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## Examples
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### Enqueue a request to classify a file of ID "e6cff8b7-c90c-4564-b5b8-033449090932"
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#### Sample request
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```JSON
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{
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"__metadata": {
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"type": "Microsoft.Office.Server.ContentCenter.SPMachineLearningWorkItemEntityData"
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},
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"TargetSiteId": "f686e63b-aba7-48e5-97c7-68c4c1df292f",
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"TargetWebId": "66d6b64d-6f88-4dd9-b3db-47e6f00c53e8",
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"TargetUniqueId": "e6cff8b7-c90c-4564-b5b8-033449090932"
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}
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```
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#### Sample response
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**Status code:** 201
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```JSON
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{
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"ErrorMessage": null,
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"StatusCode": 201
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}
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```
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```JSON
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{
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"ErrorMessage": null,
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"StatusCode": 201
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}
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```
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## See also
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[Syntex document understanding model REST API](syntex-model-rest-api.md)

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