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update dependencies
This commit is contained in:
Sebastian Thiel
@@ -452,7 +452,6 @@
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],
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"parameters": {
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"name": {
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"description": "Required. Full resource name of the format: `{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}` The id of the recommendation engine placement. This id is used to identify the set of models that will be used to make the prediction. We currently support three placements with the following IDs by default: * `shopping_cart`: Predicts items frequently bought together with one or more catalog items in the same shopping session. Commonly displayed after `add-to-cart` events, on product detail pages, or on the shopping cart page. * `home_page`: Predicts the next product that a user will most likely engage with or purchase based on the shopping or viewing history of the specified `userId` or `visitorId`. For example - Recommendations for you. * `product_detail`: Predicts the next product that a user will most likely engage with or purchase. The prediction is based on the shopping or viewing history of the specified `userId` or `visitorId` and its relevance to a specified `CatalogItem`. Typically used on product detail pages. For example - More items like this. * `recently_viewed_default`: Returns up to 75 items recently viewed by the specified `userId` or `visitorId`, most recent ones first. Returns nothing if neither of them has viewed any items yet. For example - Recently viewed. The full list of available placements can be seen at https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard",
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"location": "path",
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"pattern": "^projects/[^/]+/locations/[^/]+/catalogs/[^/]+/eventStores/[^/]+/placements/[^/]+$",
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"required": true,
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@@ -842,7 +841,7 @@
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}
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}
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},
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"revision": "20220224",
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"revision": "20230105",
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"rootUrl": "https://recommendationengine.googleapis.com/",
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"schemas": {
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"GoogleApiHttpBody": {
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@@ -1429,7 +1428,7 @@
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"type": "object"
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},
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"GoogleCloudRecommendationengineV1beta1PredictRequest": {
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"description": "Request message for Predict method.",
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"description": "Request message for Predict method. Full resource name of the format: `{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}` The id of the recommendation engine placement. This id is used to identify the set of models that will be used to make the prediction. We currently support three placements with the following IDs by default: // * `shopping_cart`: Predicts items frequently bought together with one or more catalog items in the same shopping session. Commonly displayed after `add-to-cart` event, on product detail pages, or on the shopping cart page. * `home_page`: Predicts the next product that a user will most likely engage with or purchase based on the shopping or viewing history of the specified `userId` or `visitorId`. For example - Recommendations for you. * `product_detail`: Predicts the next product that a user will most likely engage with or purchase. The prediction is based on the shopping or viewing history of the specified `userId` or `visitorId` and its relevance to a specified `CatalogItem`. Typically used on product detail pages. For example - More items like this. * `recently_viewed_default`: Returns up to 75 items recently viewed by the specified `userId` or `visitorId`, most recent ones first. Returns nothing if neither of them has viewed any items yet. For example - Recently viewed. The full list of available placements can be seen at https://console.cloud.google.com/recommendation/catalogs/default_catalog/placements",
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"id": "GoogleCloudRecommendationengineV1beta1PredictRequest",
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"properties": {
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"dryRun": {
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@@ -1465,7 +1464,7 @@
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},
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"userEvent": {
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"$ref": "GoogleCloudRecommendationengineV1beta1UserEvent",
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"description": "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."
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"description": "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 UserInfo.visitor_id or 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 UserInfo.visitor_id to a random unique ID and leave UserInfo.user_id unset."
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}
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},
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"type": "object"
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@@ -1945,11 +1944,11 @@
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"type": "string"
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},
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"userId": {
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"description": "Optional. Unique identifier for logged-in user with a length limit of 128 bytes. Required only for logged-in users.",
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"description": "Optional. Unique identifier for logged-in user with a length limit of 128 bytes. Required only for logged-in users. Don't set for anonymous users. Don't set the field to the same fixed ID for different users. This mixes the event history of those users together, which results in degraded model quality.",
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"type": "string"
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},
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"visitorId": {
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"description": "Required. A unique identifier for tracking visitors with a length limit of 128 bytes. For example, this could be implemented with an HTTP cookie, which should be able to uniquely identify a visitor on a single device. This unique identifier should not change if the visitor logs in or out of the website. Maximum length 128 bytes. Cannot be empty.",
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"description": "Required. A unique identifier for tracking visitors with a length limit of 128 bytes. For example, this could be implemented with an HTTP cookie, which should be able to uniquely identify a visitor on a single device. This unique identifier should not change if the visitor logs in or out of the website. Maximum length 128 bytes. Cannot be empty. Don't set the field to the same fixed ID for different users. This mixes the event history of those users together, which results in degraded model quality.",
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"type": "string"
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}
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},
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@@ -2009,7 +2008,7 @@
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"type": "object"
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},
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"GoogleProtobufEmpty": {
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"description": "A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`.",
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"description": "A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }",
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"id": "GoogleProtobufEmpty",
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"properties": {},
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"type": "object"
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