--- title: SimilaritySolutionVersion - Global description: The SimilaritySolutionVersion API is a scriptable object used in Predictive Intelligence stores.Gets solution object properties and version number.Gets training completion status.Gets the version number of a solution object.Gets the input data for a prediction. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/api-reference/server-api-reference/SimilaritySolutionVersionAPI.html release: australia product: Server API Reference classification: server-api-reference topic_type: concept last_updated: "2026-03-12" reading_time_minutes: 7 breadcrumb: [Server API reference, API reference, API implementation and reference] --- # SimilaritySolutionVersion- Global The SimilaritySolutionVersion API is a scriptable object used in Predictive Intelligence stores. This API requires the Predictive Intelligence plugin \(com.glide.platform\_ml\) and is provided within the `sn_ml` namespace. This API is used is used for working with solution versions based on [SimilaritySolution API](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionAPI.md) objects in the [SimilaritySolution store](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionStoreAPI.md). The system creates a solution version each time you train a solution definition. Most versions are created during scheduled solution training. Methods in this API are accessible using the following SimilaritySolution methods: - [getActiveVersion\(\)](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionAPI.md) - [getAllVersions\(\)](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionAPI.md) - [getLatestVersion\(\)](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionAPI.md) - [getVersion\(\)](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionAPI.md) **Parent Topic:**[Server API reference](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/api-server.md) ## SimilaritySolutionVersion - getProperties\(\) Gets solution object properties and version number. |Name|Type|Description| |----|----|-----------| |None| | |
Type Description
Object Contents of the Dataset and [SimilaritySolution](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionAPI.md) version details. Results vary by object property setup.``` { "domainName": "String", "isActive": "String", "label": "String", "lookupDatasetProperties": {Object}, "name": "String", "predictedFieldName": "String", "processingLanguage": "String", "scope": "String", "stopwords": [Array], "testDatasetProperties": {Object}, "trainingFrequency": "String", "updateFrequency": "String", "versionNumber": "String" } ```
<Object>.domainName Domain name associated with this dataset. See [Domain separation and Predictive Intelligence](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/intelligent-experiences/domain-separation-predictive-intelligence.md).Type: String
<Object>.isActive Flag that indicates whether this version is active.Valid values: - true: Version is active. - false: Version is not active. Data type: String
<Object>.label Identifies the prediction task. ``` { "label": "my first prediction" } ``` Data type: String.
<Object>.lookupDatasetProperties Details of the [DatasetDefinition\(\)](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/DatasetDefinitionAPI.md) object used as the lookup set. ``` { "encodedQuery": "String", "fieldDetails": [Array], "fieldNames": [Array], "tableName": "String" } ``` Data type: Object.
<Object>.lookupDatasetProperties.tableName Name of the table for the dataset. For example, `"tableName" : "Incident"`. Data type: String.
<Object>.lookupDatasetProperties.fieldNames List of field names from the specified table as strings. For example, `"fieldNames" : ["short_description", "priority"]`. Data type: Array.
<Object>.lookupDatasetProperties.fieldNames.fieldDetails List of JavaScript objects that specify field properties. ``` [ { "name": "String", "type": "String" } ] ``` Data type: Array.
<Object>.lookupDatasetProperties.fieldNames.fieldDetails.<object>.name Name of the field defining the type of information to restrict this dataset to. Data type: String.
<Object>.lookupDatasetProperties.fieldDetails.<object>.type Machine-learning field type. Data type: String.
<Object>.lookupDatasetProperties.fieldDetails.encodedQuery Encoded query string in the standard platform format. See [Encoded query strings](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/platform-user-interface/c_EncodedQueryStrings.md).Data type: String.
<Object>.name System-assigned name. Data type: String.
<Object>.predictedFieldName Identifies a field to be trained for predictability. Data type: String.
<Object>.processingLanguage Processing language in two-letter ISO 639-1 language code format. Data type: String.
<Object>.scope Object scope. Currently the only valid value is `global`.Data type: String
<Object>.stopwords Optional. Preset list of strings that the system automatically generates based on the **language** property setting. For details, see [Create a custom stopwords list](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/intelligent-experiences/create-custom-stopwords-list.md). Data type: Array.
<Object>.testDatasetProperties Details of the [DatasetDefinition\(\)](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/DatasetDefinitionAPI.md) object used to retrieve similarities between results searched in this model and results found in the **lookupDataset**. ``` { "encodedQuery": "String", "fieldDetails": [Array], "fieldNames": [Array], "tableName": "String" } ``` Data type: Object.
<Object>.testDatasetProperties.tableName Name of the table for the dataset. For example, `"tableName" : "Incident"`. Data type: String.
<Object>.testDatasetProperties.fieldNames List of field names from the specified table as strings. For example, `"fieldNames" : ["short_description", "priority"]`. Data type: Array.
<Object>.testDatasetProperties.fieldNames.fieldDetails List of JavaScript objects that specify field properties. ``` [ { "name": "String", "type": "String" } ] ``` Data type: Array.
<Object>.testDatasetProperties.fieldNames.fieldDetails.<object>.name Name of the field defining the type of information to restrict this dataset to. Data type: String.
<Object>.testDatasetProperties.fieldDetails.<object>.type Machine-learning field type. Data type: String.
<Object>.testDatasetProperties.fieldDetails.encodedQuery Encoded query string in the standard platform format. Data type: String.
<Object>.trainingFrequency The frequency to retrain the model. Possible values: - every\_30\_days - every\_60\_days - every\_90\_days - every\_120\_days - every\_180\_days - run\_once Default: run\_once Data type: String.
<Object>.updateFrequency The frequency at which the model for the solution definition must be rebuilt. Possible values: - do\_not\_update - every\_1\_day - every\_1\_hour - every\_6\_hours - every\_12\_hours - every\_1\_minute - every\_15\_minutes - every\_30\_minutes Default: do\_not\_update Datatype: String
<Object>.versionNumber Version number of the SimilaritySolution object.Data type: String.
The following example gets properties of the active object version in the store. ``` // Get properties var mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution'); gs.print(JSON.stringify(JSON.parse(mlSolution.getActiveVersion().getProperties()), null, 2)); ``` Output: ``` *** Script: { "domainName": "global", "isActive": "true", "label": "similarity", "lookupDatasetProperties": { "encodedQuery": "", "fieldNames": [ "short_description" ], "tableName": "incident" }, "name": "ml_x_snc_global_global_similarity", "processingLanguage": "en", "stopwords": [ "Default English Stopwords" ], "testDatasetProperties": { "fieldNames": [ "short_description" ], "tableName": "incident" }, "versionNumber": "3" } ``` ## SimilaritySolutionVersion - getStatus\(Boolean includeDetails\) Gets training completion status.
Name Type Description
includeDetails Boolean Flag that indicates whether to return status **details**.Valid values: - true: Return additional details. - false: Don't return additional details. Default: False
Type Description
Object JavaScript object containing training status information for a [SimilaritySolution](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/SimilaritySolutionAPI.md) object.``` { "state": "String", "percentComplete": "Number as a String", "hasJobEnded": "Boolean value as a String", "details": {Object} } ```
<Object>.state Training completion state. If the training job reaches a terminal state, the job does not leave that state. If the state is terminal, the **hasJobEnded** property is set to `true`.Possible values: - `fetching_files_for_training` - `preparing_data` - `retry` - `solution_cancelled` \(terminal\) - `solution_complete`\(terminal\) - `solution_error` \(terminal\) - `solution_incomplete` - `training_request_received` - `training_request_timed_out` \(terminal\) - `training_solution` - `uploading_solution` - `waiting_for_training` Data type: String
<Object>.hasJobEnded Flag that indicates whether training is complete.Valid values: - true: Training is complete. - false: Training is incomplete. Data type: Boolean value as a String
<Object>.percentComplete Training percent complete. If the completion percentage is less than 100, the job might be in a terminal state. For example, if training times out.Data type: Number as a String Range: 0 thru 100
<Object>.details Object containing a list of additional training details.Data type: Object
The following example shows a successful result with training complete. ``` // Get status var mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution'); gs.print(JSON.stringify(JSON.parse(mlSolution.getActiveVersion().getStatus(true), null, 2))); ``` Output: ``` { "state":"solution_complete", "percentComplete":"100", "hasJobEnded":"true", "details":{"stepLabel":"Solution Complete"} // This information is only returned if getStatus(true); } ``` The following example shows an unsuccessful result with training complete. ``` // Get status var solutionName = 'ml_x_snc_global_global_similarity_solution'; var mlSolution = sn_ml.SimilaritySolutionStore.get(solutionName); var trainingStatus = JSON.parse(mlSolution.getLatestVersion().getStatus()); gs.print(JSON.stringify(JSON.parse(trainingStatus), null, 2)); ``` Output: ``` { "state":"solution_error", "percentComplete":"100", "hasJobEnded":"true" } ``` ## SimilaritySolutionVersion - getVersionNumber\(\) Gets the version number of a solution object. |Name|Type|Description| |----|----|-----------| |None| | | |Type|Description| |----|-----------| |String|Version number.| The following example shows how to get a version number. ``` // Get version number var mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution'); gs.print("Version number: "+JSON.stringify(JSON.parse(mlSolution.getActiveVersion().getVersionNumber()), null, 2)); ``` Output: ``` Version number: 1 ``` ## SimilaritySolutionVersion - predict\(Object input, Object options\) Gets the input data for a prediction.
Name Type Description
input Object [GlideRecord](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/c_GlideRecordAPI.md) or array of JSON objects containing field names and values as key-value pairs.
options Object Optional values for filtering prediction results.``` { "apply_threshold": Boolean, "top_n": Number } ```
options.apply\_threshold Boolean Flag that indicates whether to check the threshold value for the solution and apply it to the result set.Valid values: - true: Return results in which confidence is greater than threshold. - false: Return all results. Default: True
options.top\_n Number If provided, returns the top results, up to the specified number of predictions.
Type Description
Object JSON object containing the prediction results sorted by sys\_id or record\_number. ``` { : [Array] } ```
<Object>.<identifier> List of objects with details for each prediction result.Data type: Array of Objects ``` : [ { "confidence": Number, "predictedSysId": "String", "predictedValue": "String", "threshold": Number } ] ```
<Object>.<identifier>.<object>.confidence Value of the confidence associated with the prediction. For example, 53.84. Data type: Number
<Object>.<identifier>.<object>.predictedSysId The sys\_id of the predicted value. Results can be from any table on which information is being predicted. Data type: String
<Object>.<identifier>.<object>.predictedValue Value representing the prediction result. Data type: String
<Object>.<identifier>.<object>.threshold Value of the configured threshold associated with the prediction. Data type: Number
The following example shows how to display prediction results for a predict\(\) method that takes a GlideRecord by sys\_id for input and includes optional parameters to restrict to top three results and exclude the threshold value. ``` var mlSolution = sn_ml.SimilaritySolutionStore.get('ml_x_snc_global_similarity_solution'); // single GlideRecord input var input = new GlideRecord("incident"); input.get(""); // configure optional parameters var options = {}; options.top_n = 3; options.apply_threshold = false; var results = mlSolution.getVersion(1).predict(input, options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2)); ``` ``` { "": [ { "confidence": 62.10782320780268, "threshold": 20.36, "predictedValue": "Clone Issues", "predictedSysId": "" }, { "confidence": 6.945237375770391, "threshold": 16.63, "predictedValue": "Instance Administration", "predictedSysId": "" }, { "confidence": 5.321061076300759, "threshold": 23.7, "predictedValue": "Administration", "predictedSysId": "" } ] } ``` The following example shows how to display prediction results for a predict\(\) method that takes an array of field names as key-value pairs for input and includes optional parameters to restrict to top three results and exclude the threshold value. ``` var mlSolution = sn_ml.SimilaritySolutionStore.get("ml_x_snc_global_similarity_solution"); // key-value pairs input var input = [{"short_description":"my email is not working"}, {short_description:"need help with password"}]; // configure optional parameters var options = {}; options.top_n = 3; options.apply_threshold = false; var results = mlSolution.predict(input, options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2)); ``` ``` { "1": [ { "confidence": 37.5023032262591, "threshold": 10.72, "predictedValue": "Authentication", "predictedSysId": "" }, { "confidence": 24.439964862166583, "threshold": 23.7, "predictedValue": "Administration", "predictedSysId": "" }, { "confidence": 11.736320486031047, "threshold": 100, "predictedValue": "Security", "predictedSysId": "" } ], "2": [ { "confidence": 99, "threshold": 17.77, "predictedValue": "Email", "predictedSysId": "" }, { "confidence": 3.182137005157543, "threshold": 10.72, "predictedValue": "Authentication", "predictedSysId": "" }, { "confidence": 2.8773826570713514, "threshold": -1, "predictedValue": "Email (I/f)", "predictedSysId": "" } ] } ```