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prediction_service.predict.js
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prediction_service.predict.js
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// Copyright 2022 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
// ** This file is automatically generated by gapic-generator-typescript. **
// ** https://github.com/googleapis/gapic-generator-typescript **
// ** All changes to this file may be overwritten. **
'use strict';
function main(placement, userEvent) {
// [START retail_v2_generated_PredictionService_Predict_async]
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. Full resource name of the format:
* `{placement=projects/* /locations/global/catalogs/default_catalog/servingConfigs/*}`
* or
* `{placement=projects/* /locations/global/catalogs/default_catalog/placements/*}`.
* We recommend using the `servingConfigs` resource. `placements` is a legacy
* resource.
* The ID of the Recommendations AI serving config or placement.
* Before you can request predictions from your model, you must create at
* least one serving config or placement for it. For more information, see
* Managing serving configurations
* (https://cloud.google.com/retail/docs/manage-configs).
* The full list of available serving configs can be seen at
* https://console.cloud.google.com/ai/retail/catalogs/default_catalog/configs
*/
// const placement = 'abc123'
/**
* Required. Context about the user, what they are looking at and what action
* they took to trigger the predict request. Note that this user event detail
* won't be ingested to userEvent logs. Thus, a separate userEvent write
* request is required for event logging.
* Don't set
* UserEvent.visitor_id google.cloud.retail.v2.UserEvent.visitor_id or
* UserInfo.user_id google.cloud.retail.v2.UserInfo.user_id to the same
* fixed ID for different users. If you are trying to receive non-personalized
* recommendations (not recommended; this can negatively impact model
* performance), instead set
* UserEvent.visitor_id google.cloud.retail.v2.UserEvent.visitor_id to a
* random unique ID and leave
* UserInfo.user_id google.cloud.retail.v2.UserInfo.user_id unset.
*/
// const userEvent = {}
/**
* Maximum number of results to return. Set this property to the number of
* prediction results needed. If zero, the service will choose a reasonable
* default. The maximum allowed value is 100. Values above 100 will be coerced
* to 100.
*/
// const pageSize = 1234
/**
* This field is not used; leave it unset.
*/
// const pageToken = 'abc123'
/**
* Filter for restricting prediction results with a length limit of 5,000
* characters. Accepts values for tags and the `filterOutOfStockItems` flag.
* * Tag expressions. Restricts predictions to products that match all of the
* specified tags. Boolean operators `OR` and `NOT` are supported if the
* expression is enclosed in parentheses, and must be separated from the
* tag values by a space. `-"tagA"` is also supported and is equivalent to
* `NOT "tagA"`. Tag values must be double quoted UTF-8 encoded strings
* with a size limit of 1,000 characters.
* Note: "Recently viewed" models don't support tag filtering at the
* moment.
* * filterOutOfStockItems. Restricts predictions to products that do not
* have a
* stockState value of OUT_OF_STOCK.
* Examples:
* * tag=("Red" OR "Blue") tag="New-Arrival" tag=(NOT "promotional")
* * filterOutOfStockItems tag=(-"promotional")
* * filterOutOfStockItems
* If your filter blocks all prediction results, the API will return generic
* (unfiltered) popular products. If you only want results strictly matching
* the filters, set `strictFiltering` to True in `PredictRequest.params` to
* receive empty results instead.
* Note that the API will never return items with storageStatus of "EXPIRED"
* or "DELETED" regardless of filter choices.
* If `filterSyntaxV2` is set to true under the `params` field, then
* attribute-based expressions are expected instead of the above described
* tag-based syntax. Examples:
* * (colors: ANY("Red", "Blue")) AND NOT (categories: ANY("Phones"))
* * (availability: ANY("IN_STOCK")) AND
* (colors: ANY("Red") OR categories: ANY("Phones"))
*/
// const filter = 'abc123'
/**
* Use validate only mode for this prediction query. If set to true, a
* dummy model will be used that returns arbitrary products.
* Note that the validate only mode should only be used for testing the API,
* or if the model is not ready.
*/
// const validateOnly = true
/**
* Additional domain specific parameters for the predictions.
* Allowed values:
* * `returnProduct`: Boolean. If set to true, the associated product
* object will be returned in the `results.metadata` field in the
* prediction response.
* * `returnScore`: Boolean. If set to true, the prediction 'score'
* corresponding to each returned product will be set in the
* `results.metadata` field in the prediction response. The given
* 'score' indicates the probability of an product being clicked/purchased
* given the user's context and history.
* * `strictFiltering`: Boolean. True by default. If set to false, the service
* will return generic (unfiltered) popular products instead of empty if
* your filter blocks all prediction results.
* * `priceRerankLevel`: String. Default empty. If set to be non-empty, then
* it needs to be one of {'no-price-reranking', 'low-price-reranking',
* 'medium-price-reranking', 'high-price-reranking'}. This gives
* request-level control and adjusts prediction results based on product
* price.
* * `diversityLevel`: String. Default empty. If set to be non-empty, then
* it needs to be one of {'no-diversity', 'low-diversity',
* 'medium-diversity', 'high-diversity', 'auto-diversity'}. This gives
* request-level control and adjusts prediction results based on product
* category.
* * `filterSyntaxV2`: Boolean. False by default. If set to true, the `filter`
* field is interpreteted according to the new, attribute-based syntax.
*/
// const params = 1234
/**
* The labels applied to a resource must meet the following requirements:
* * Each resource can have multiple labels, up to a maximum of 64.
* * Each label must be a key-value pair.
* * Keys have a minimum length of 1 character and a maximum length of 63
* characters and cannot be empty. Values can be empty and have a maximum
* length of 63 characters.
* * Keys and values can contain only lowercase letters, numeric characters,
* underscores, and dashes. All characters must use UTF-8 encoding, and
* international characters are allowed.
* * The key portion of a label must be unique. However, you can use the same
* key with multiple resources.
* * Keys must start with a lowercase letter or international character.
* See Google Cloud
* Document (https://cloud.google.com/resource-manager/docs/creating-managing-labels#requirements)
* for more details.
*/
// const labels = 1234
// Imports the Retail library
const {PredictionServiceClient} = require('@google-cloud/retail').v2;
// Instantiates a client
const retailClient = new PredictionServiceClient();
async function callPredict() {
// Construct request
const request = {
placement,
userEvent,
};
// Run request
const response = await retailClient.predict(request);
console.log(response);
}
callPredict();
// [END retail_v2_generated_PredictionService_Predict_async]
}
process.on('unhandledRejection', err => {
console.error(err.message);
process.exitCode = 1;
});
main(...process.argv.slice(2));