All URIs are relative to http://localhost
| Method | HTTP request | Description |
|---|---|---|
| predict | POST /api/predict | Provide Recommendations AI functionality. |
| predictV2 | POST /api/recommendation | Provide Recommendations AI functionality. |
open class func predict(xGroupbyCustomerId: String, recommendationsRequest: RecommendationsRequest, completion: @escaping (_ data: PredictResults?, _ error: Error?) -> Void)Provide Recommendations AI functionality.
Perform a recommendation request against the GroupBy Retail Recommendations API.
// The following code samples are still beta. For any issue, please report via http://github.com/OpenAPITools/openapi-generator/issues/new
import GroupByRetailClient
let xGroupbyCustomerId = "xGroupbyCustomerId_example" // String | Custom HTTP header which may contain tenant name. Used to define a client by its name.
let recommendationsRequest = RecommendationsRequest(collection: "collection_example", visitorId: "visitorId_example", limit: "limit_example", pageSize: "pageSize_example", eventType: "eventType_example", loginId: "loginId_example", productID: ["productID_example"], fields: ["fields_example"], filters: [Filter(field: "field_example", value: "value_example", exclude: false, derivedFromProduct: false)], rawFilter: "rawFilter_example", placement: "placement_example", name: "name_example", strictFiltering: false) // RecommendationsRequest | Request that should be populated to configure a recommendations API call made by the client.
// Provide Recommendations AI functionality.
RecommendationsAPIAPI.predict(xGroupbyCustomerId: xGroupbyCustomerId, recommendationsRequest: recommendationsRequest) { (response, error) in
guard error == nil else {
print(error)
return
}
if (response) {
dump(response)
}
}| Name | Type | Description | Notes |
|---|---|---|---|
| xGroupbyCustomerId | String | Custom HTTP header which may contain tenant name. Used to define a client by its name. | |
| recommendationsRequest | RecommendationsRequest | Request that should be populated to configure a recommendations API call made by the client. |
- Content-Type: application/json
- Accept: application/json
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open class func predictV2(xGroupbyCustomerId: String, recommendationsRequest: RecommendationsRequest, completion: @escaping (_ data: PredictResults?, _ error: Error?) -> Void)Provide Recommendations AI functionality.
Perform a recommendation request against the GroupBy Retail Recommendations API.
// The following code samples are still beta. For any issue, please report via http://github.com/OpenAPITools/openapi-generator/issues/new
import GroupByRetailClient
let xGroupbyCustomerId = "xGroupbyCustomerId_example" // String | Custom HTTP header which may contain tenant name. Used to define a client by its name.
let recommendationsRequest = RecommendationsRequest(collection: "collection_example", visitorId: "visitorId_example", limit: "limit_example", pageSize: "pageSize_example", eventType: "eventType_example", loginId: "loginId_example", productID: ["productID_example"], fields: ["fields_example"], filters: [Filter(field: "field_example", value: "value_example", exclude: false, derivedFromProduct: false)], rawFilter: "rawFilter_example", placement: "placement_example", name: "name_example", strictFiltering: false) // RecommendationsRequest | Request that should be populated to configure a recommendations API call made by the client.
// Provide Recommendations AI functionality.
RecommendationsAPIAPI.predictV2(xGroupbyCustomerId: xGroupbyCustomerId, recommendationsRequest: recommendationsRequest) { (response, error) in
guard error == nil else {
print(error)
return
}
if (response) {
dump(response)
}
}| Name | Type | Description | Notes |
|---|---|---|---|
| xGroupbyCustomerId | String | Custom HTTP header which may contain tenant name. Used to define a client by its name. | |
| recommendationsRequest | RecommendationsRequest | Request that should be populated to configure a recommendations API call made by the client. |
- Content-Type: application/json
- Accept: application/json
[Back to top] [Back to API list] [Back to Model list] [Back to README]