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Copy file name to clipboardexpand all lines: docs/dyn/retail_v2.projects.locations.catalogs.placements.html
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"pageSize": 42, # 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.
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"pageToken": "A String", # This field is not used; leave it unset.
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"params": { # 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.
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"params": { # 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 a 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.
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"a_key": "",
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},
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"userEvent": { # UserEvent captures all metadata information Retail API needs to know about how end users interact with customers' website. # 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 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 UserEvent.visitor_id to a random unique ID and leave UserInfo.user_id unset.
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],
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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},
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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},
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],
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"filter": "A String", # The filter syntax consists of an expression language for constructing a predicate from one or more fields of the products being filtered. Filter expression is case-sensitive. See more details at this [user guide](https://cloud.google.com/retail/docs/filter-and-order#filter). If this field is unrecognizable, an INVALID_ARGUMENT is returned.
Copy file name to clipboardexpand all lines: docs/dyn/retail_v2.projects.locations.catalogs.servingConfigs.html
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},
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"pageSize": 42, # 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.
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"pageToken": "A String", # This field is not used; leave it unset.
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"params": { # 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.
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"params": { # 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 a 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.
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"a_key": "",
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},
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"userEvent": { # UserEvent captures all metadata information Retail API needs to know about how end users interact with customers' website. # 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 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 UserEvent.visitor_id to a random unique ID and leave UserInfo.user_id unset.
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],
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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},
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"filter": "A String", # The filter syntax consists of an expression language for constructing a predicate from one or more fields of the products being filtered. Filter expression is case-sensitive. See more details at this [user guide](https://cloud.google.com/retail/docs/filter-and-order#filter). If this field is unrecognizable, an INVALID_ARGUMENT is returned.
Copy file name to clipboardexpand all lines: docs/dyn/retail_v2alpha.projects.locations.catalogs.controls.html
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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},
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"name": "A String", # Immutable. Fully qualified name `projects/*/locations/global/catalogs/*/controls/*`
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"rule": { # A rule is a condition-action pair * A condition defines when a rule is to be triggered. * An action specifies what occurs on that trigger. Currently rules only work for controls with SOLUTION_TYPE_SEARCH. # A rule control - a condition-action pair. Enacts a set action when the condition is triggered. For example: Boost "gShoe" when query full matches "Running Shoes".
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"name": "A String", # Immutable. Fully qualified name `projects/*/locations/global/catalogs/*/controls/*`
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"rule": { # A rule is a condition-action pair * A condition defines when a rule is to be triggered. * An action specifies what occurs on that trigger. Currently rules only work for controls with SOLUTION_TYPE_SEARCH. # A rule control - a condition-action pair. Enacts a set action when the condition is triggered. For example: Boost "gShoe" when query full matches "Running Shoes".
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"name": "A String", # Immutable. Fully qualified name `projects/*/locations/global/catalogs/*/controls/*`
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"rule": { # A rule is a condition-action pair * A condition defines when a rule is to be triggered. * An action specifies what occurs on that trigger. Currently rules only work for controls with SOLUTION_TYPE_SEARCH. # A rule control - a condition-action pair. Enacts a set action when the condition is triggered. For example: Boost "gShoe" when query full matches "Running Shoes".
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"name": "A String", # Immutable. Fully qualified name `projects/*/locations/global/catalogs/*/controls/*`
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"rule": { # A rule is a condition-action pair * A condition defines when a rule is to be triggered. * An action specifies what occurs on that trigger. Currently rules only work for controls with SOLUTION_TYPE_SEARCH. # A rule control - a condition-action pair. Enacts a set action when the condition is triggered. For example: Boost "gShoe" when query full matches "Running Shoes".
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"name": "A String", # Immutable. Fully qualified name `projects/*/locations/global/catalogs/*/controls/*`
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"rule": { # A rule is a condition-action pair * A condition defines when a rule is to be triggered. * An action specifies what occurs on that trigger. Currently rules only work for controls with SOLUTION_TYPE_SEARCH. # A rule control - a condition-action pair. Enacts a set action when the condition is triggered. For example: Boost "gShoe" when query full matches "Running Shoes".
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"returnMinMax": True or False, # Returns the min and max value for each numerical facet intervals. Ignored for textual facets.
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},
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 20. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"limit": 42, # Maximum of facet values that should be returned for this facet. If unspecified, defaults to 50. The maximum allowed value is 300. Values above 300 will be coerced to 300. If this field is negative, an INVALID_ARGUMENT is returned.
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"name": "A String", # Immutable. Fully qualified name `projects/*/locations/global/catalogs/*/controls/*`
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"rule": { # A rule is a condition-action pair * A condition defines when a rule is to be triggered. * An action specifies what occurs on that trigger. Currently rules only work for controls with SOLUTION_TYPE_SEARCH. # A rule control - a condition-action pair. Enacts a set action when the condition is triggered. For example: Boost "gShoe" when query full matches "Running Shoes".
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