Google Cloud Discovery Engine V1 Client - Class SearchRequest (1.11.1)

Reference documentation and code samples for the Google Cloud Discovery Engine V1 Client class SearchRequest.

Request message for SearchService.Search method.

Generated from protobuf message google.cloud.discoveryengine.v1.SearchRequest

Constructor.

Required. The resource name of the Search serving config, such as projects/*/locations/global/collections/default_collection/engines/*/servingConfigs/default_serving_config , or projects/*/locations/global/collections/default_collection/dataStores/default_data_store/servingConfigs/default_serving_config .

This field is used to identify the serving configuration name, set of models used to make the search.

Required. The resource name of the Search serving config, such as projects/*/locations/global/collections/default_collection/engines/*/servingConfigs/default_serving_config , or projects/*/locations/global/collections/default_collection/dataStores/default_data_store/servingConfigs/default_serving_config .

This field is used to identify the serving configuration name, set of models used to make the search.

The branch resource name, such as projects/*/locations/global/collections/default_collection/dataStores/default_data_store/branches/0 .

Use default_branch as the branch ID or leave this field empty, to search documents under the default branch.

The branch resource name, such as projects/*/locations/global/collections/default_collection/dataStores/default_data_store/branches/0 .

Use default_branch as the branch ID or leave this field empty, to search documents under the default branch.

Raw search query.

Raw search query.

Optional. The categories associated with a category page. Must be set for category navigation queries to achieve good search quality. The format should be the same as PageInfo.page_category .

This field is the equivalent of the query for browse (navigation) queries. It's used by the browse model when the query is empty. If the field is empty, it will not be used by the browse model. If the field contains more than one element, only the first element will be used. To represent full path of a category, use '>' character to separate different hierarchies. If '>' is part of the category name, replace it with other character(s). For example, Graphics Cards > RTX>4090 > Founders Edition where "RTX > 4090" represents one level, can be rewritten as `Graphics Cards > RTX_4090

Founders Edition`

Optional. The categories associated with a category page. Must be set for category navigation queries to achieve good search quality. The format should be the same as PageInfo.page_category .

This field is the equivalent of the query for browse (navigation) queries. It's used by the browse model when the query is empty. If the field is empty, it will not be used by the browse model. If the field contains more than one element, only the first element will be used. To represent full path of a category, use '>' character to separate different hierarchies. If '>' is part of the category name, replace it with other character(s). For example, Graphics Cards > RTX>4090 > Founders Edition where "RTX > 4090" represents one level, can be rewritten as `Graphics Cards > RTX_4090

Founders Edition`

Raw image query.

Raw image query.

Maximum number of Document s to return. The maximum allowed value depends on the data type. Values above the maximum value are coerced to the maximum value.

• Websites with basic indexing: Default 10 , Maximum 25 .
• Websites with advanced indexing: Default 25 , Maximum 50 .
• Other: Default 50 , Maximum 100 . If this field is negative, an INVALID_ARGUMENT is returned.

Maximum number of Document s to return. The maximum allowed value depends on the data type. Values above the maximum value are coerced to the maximum value.

• Websites with basic indexing: Default 10 , Maximum 25 .
• Websites with advanced indexing: Default 25 , Maximum 50 .
• Other: Default 50 , Maximum 100 . If this field is negative, an INVALID_ARGUMENT is returned.

A page token received from a previous SearchService.Search call. Provide this to retrieve the subsequent page.

When paginating, all other parameters provided to SearchService.Search must match the call that provided the page token. Otherwise, an INVALID_ARGUMENT error is returned.

A page token received from a previous SearchService.Search call. Provide this to retrieve the subsequent page.

When paginating, all other parameters provided to SearchService.Search must match the call that provided the page token. Otherwise, an INVALID_ARGUMENT error is returned.

A 0-indexed integer that specifies the current offset (that is, starting result location, amongst the Document s deemed by the API as relevant) in search results. This field is only considered if page_token is unset.

If this field is negative, an INVALID_ARGUMENT is returned. A large offset may be capped to a reasonable threshold.

A 0-indexed integer that specifies the current offset (that is, starting result location, amongst the Document s deemed by the API as relevant) in search results. This field is only considered if page_token is unset.

If this field is negative, an INVALID_ARGUMENT is returned. A large offset may be capped to a reasonable threshold.

The maximum number of results to return for OneBox.

This applies to each OneBox type individually. Default number is 10.

The maximum number of results to return for OneBox.

This applies to each OneBox type individually. Default number is 10.

Specifications that define the specific DataStore s to be searched, along with configurations for those data stores. This is only considered for Engine s with multiple data stores. For engines with a single data store, the specs directly under SearchRequest should be used.

Specifications that define the specific DataStore s to be searched, along with configurations for those data stores. This is only considered for Engine s with multiple data stores. For engines with a single data store, the specs directly under SearchRequest should be used.

The filter syntax consists of an expression language for constructing a predicate from one or more fields of the documents being filtered. Filter expression is case-sensitive.

If this field is unrecognizable, an INVALID_ARGUMENT is returned. Filtering in Vertex AI Search is done by mapping the LHS filter key to a key property defined in the Vertex AI Search backend -- this mapping is defined by the customer in their schema. For example a media customer might have a field 'name' in their schema. In this case the filter would look like this: filter --> name:'ANY("king kong")' For more information about filtering including syntax and filter operators, see Filter

The filter syntax consists of an expression language for constructing a predicate from one or more fields of the documents being filtered. Filter expression is case-sensitive.

If this field is unrecognizable, an INVALID_ARGUMENT is returned. Filtering in Vertex AI Search is done by mapping the LHS filter key to a key property defined in the Vertex AI Search backend -- this mapping is defined by the customer in their schema. For example a media customer might have a field 'name' in their schema. In this case the filter would look like this: filter --> name:'ANY("king kong")' For more information about filtering including syntax and filter operators, see Filter

The default filter that is applied when a user performs a search without checking any filters on the search page.

The filter applied to every search request when quality improvement such as query expansion is needed. In the case a query does not have a sufficient amount of results this filter will be used to determine whether or not to enable the query expansion flow. The original filter will still be used for the query expanded search. This field is strongly recommended to achieve high search quality. For more information about filter syntax, see SearchRequest.filter .

The default filter that is applied when a user performs a search without checking any filters on the search page.

The filter applied to every search request when quality improvement such as query expansion is needed. In the case a query does not have a sufficient amount of results this filter will be used to determine whether or not to enable the query expansion flow. The original filter will still be used for the query expanded search. This field is strongly recommended to achieve high search quality. For more information about filter syntax, see SearchRequest.filter .

The order in which documents are returned. Documents can be ordered by a field in an Document object.

Leave it unset if ordered by relevance. order_by expression is case-sensitive. For more information on ordering the website search results, see Order web search results . For more information on ordering the healthcare search results, see Order healthcare search results . If this field is unrecognizable, an INVALID_ARGUMENT is returned.

The order in which documents are returned. Documents can be ordered by a field in an Document object.

Leave it unset if ordered by relevance. order_by expression is case-sensitive. For more information on ordering the website search results, see Order web search results . For more information on ordering the healthcare search results, see Order healthcare search results . If this field is unrecognizable, an INVALID_ARGUMENT is returned.

Information about the end user.

Highly recommended for analytics and personalization. UserInfo.user_agent is used to deduce device_type for analytics.

Information about the end user.

Highly recommended for analytics and personalization. UserInfo.user_agent is used to deduce device_type for analytics.

The BCP-47 language code, such as "en-US" or "sr-Latn". For more information, see Standard fields . This field helps to better interpret the query. If a value isn't specified, the query language code is automatically detected, which may not be accurate.

The BCP-47 language code, such as "en-US" or "sr-Latn". For more information, see Standard fields . This field helps to better interpret the query. If a value isn't specified, the query language code is automatically detected, which may not be accurate.

Facet specifications for faceted search. If empty, no facets are returned.

A maximum of 100 values are allowed. Otherwise, an INVALID_ARGUMENT error is returned.

Facet specifications for faceted search. If empty, no facets are returned.

A maximum of 100 values are allowed. Otherwise, an INVALID_ARGUMENT error is returned.

Boost specification to boost certain documents.

For more information on boosting, see Boosting

Boost specification to boost certain documents.

For more information on boosting, see Boosting

Additional search parameters.

For public website search only, supported values are:

• user_country_code : string. Default empty. If set to non-empty, results are restricted or boosted based on the location provided. For example, user_country_code: "au" For available codes see Country Codes
• search_type : double. Default empty. Enables non-webpage searching depending on the value. The only valid non-default value is 1, which enables image searching. For example, search_type: 1

Additional search parameters.

For public website search only, supported values are:

• user_country_code : string. Default empty. If set to non-empty, results are restricted or boosted based on the location provided. For example, user_country_code: "au" For available codes see Country Codes
• search_type : double. Default empty. Enables non-webpage searching depending on the value. The only valid non-default value is 1, which enables image searching. For example, search_type: 1

The query expansion specification that specifies the conditions under which query expansion occurs.

The query expansion specification that specifies the conditions under which query expansion occurs.

The spell correction specification that specifies the mode under which spell correction takes effect.

The spell correction specification that specifies the mode under which spell correction takes effect.

Optional. A unique identifier for tracking visitors. 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.

This field should NOT have a fixed value such as unknown_visitor . This should be the same identifier as UserEvent.user_pseudo_id and CompleteQueryRequest.user_pseudo_id The field must be a UTF-8 encoded string with a length limit of 128 characters. Otherwise, an INVALID_ARGUMENT error is returned.

Optional. A unique identifier for tracking visitors. 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.

This field should NOT have a fixed value such as unknown_visitor . This should be the same identifier as UserEvent.user_pseudo_id and CompleteQueryRequest.user_pseudo_id The field must be a UTF-8 encoded string with a length limit of 128 characters. Otherwise, an INVALID_ARGUMENT error is returned.

A specification for configuring the behavior of content search.

A specification for configuring the behavior of content search.

Optional. The ranking expression controls the customized ranking on retrieval documents. This overrides ServingConfig.ranking_expression .

The syntax and supported features depend on the ranking_expression_backend value. If ranking_expression_backend is not provided, it defaults to RANK_BY_EMBEDDING . If ranking_expression_backend is not provided or set to RANK_BY_EMBEDDING , it should be a single function or multiple functions that are joined by "+".

• ranking_expression = function, { " + ", function }; Supported functions:
• double * relevance_score
• double * dotProduct(embedding_field_path) Function variables:
• relevance_score : pre-defined keywords, used for measure relevance between query and document.
• embedding_field_path : the document embedding field used with query embedding vector.
• dotProduct : embedding function between embedding_field_path and query embedding vector. Example ranking expression: If document has an embedding field doc_embedding, the ranking expression could be 0.5 * relevance_score + 0.3 * dotProduct(doc_embedding) . If ranking_expression_backend is set to RANK_BY_FORMULA , the following expression types (and combinations of those chained using + or
  • operators) are supported:
• double
• signal
• log(signal)
• exp(signal)
• rr(signal, double > 0) -- reciprocal rank transformation with second argument being a denominator constant.
• is_nan(signal) -- returns 0 if signal is NaN, 1 otherwise.
• fill_nan(signal1, signal2 | double) -- if signal1 is NaN, returns signal2 | double, else returns signal1. Here are a few examples of ranking formulas that use the supported ranking expression types:
• 0.2 * semantic_similarity_score + 0.8 * log(keyword_similarity_score) -- mostly rank by the logarithm of keyword_similarity_score with slight semantic_smilarity_score adjustment.
• 0.2 * exp(fill_nan(semantic_similarity_score, 0)) + 0.3 * is_nan(keyword_similarity_score) -- rank by the exponent of semantic_similarity_score filling the value with 0 if it's NaN, also add constant 0.3 adjustment to the final score if semantic_similarity_score is NaN.
• 0.2 * rr(semantic_similarity_score, 16) + 0.8 * rr(keyword_similarity_score, 16) -- mostly rank by the reciprocal rank of keyword_similarity_score with slight adjustment of reciprocal rank of semantic_smilarity_score . The following signals are supported:
• semantic_similarity_score : semantic similarity adjustment that is calculated using the embeddings generated by a proprietary Google model. This score determines how semantically similar a search query is to a document.
• keyword_similarity_score : keyword match adjustment uses the Best Match 25 (BM25) ranking function. This score is calculated using a probabilistic model to estimate the probability that a document is relevant to a given query.
• relevance_score : semantic relevance adjustment that uses a proprietary Google model to determine the meaning and intent behind a user's query in context with the content in the documents.
• pctr_rank : predicted conversion rate adjustment as a rank use predicted Click-through rate (pCTR) to gauge the relevance and attractiveness of a search result from a user's perspective. A higher pCTR suggests that the result is more likely to satisfy the user's query and intent, making it a valuable signal for ranking.
• freshness_rank : freshness adjustment as a rank
• document_age : The time in hours elapsed since the document was last updated, a floating-point number (e.g., 0.25 means 15 minutes).
• topicality_rank : topicality adjustment as a rank. Uses proprietary Google model to determine the keyword-based overlap between the query and the document.
• base_rank : the default rank of the result

Optional. The ranking expression controls the customized ranking on retrieval documents. This overrides ServingConfig.ranking_expression .

The syntax and supported features depend on the ranking_expression_backend value. If ranking_expression_backend is not provided, it defaults to RANK_BY_EMBEDDING . If ranking_expression_backend is not provided or set to RANK_BY_EMBEDDING , it should be a single function or multiple functions that are joined by "+".

• ranking_expression = function, { " + ", function }; Supported functions:
• double * relevance_score
• double * dotProduct(embedding_field_path) Function variables:
• relevance_score : pre-defined keywords, used for measure relevance between query and document.
• embedding_field_path : the document embedding field used with query embedding vector.
• dotProduct : embedding function between embedding_field_path and query embedding vector. Example ranking expression: If document has an embedding field doc_embedding, the ranking expression could be 0.5 * relevance_score + 0.3 * dotProduct(doc_embedding) . If ranking_expression_backend is set to RANK_BY_FORMULA , the following expression types (and combinations of those chained using + or
  • operators) are supported:
• double
• signal
• log(signal)
• exp(signal)
• rr(signal, double > 0) -- reciprocal rank transformation with second argument being a denominator constant.
• is_nan(signal) -- returns 0 if signal is NaN, 1 otherwise.
• fill_nan(signal1, signal2 | double) -- if signal1 is NaN, returns signal2 | double, else returns signal1. Here are a few examples of ranking formulas that use the supported ranking expression types:
• 0.2 * semantic_similarity_score + 0.8 * log(keyword_similarity_score) -- mostly rank by the logarithm of keyword_similarity_score with slight semantic_smilarity_score adjustment.
• 0.2 * exp(fill_nan(semantic_similarity_score, 0)) + 0.3 * is_nan(keyword_similarity_score) -- rank by the exponent of semantic_similarity_score filling the value with 0 if it's NaN, also add constant 0.3 adjustment to the final score if semantic_similarity_score is NaN.
• 0.2 * rr(semantic_similarity_score, 16) + 0.8 * rr(keyword_similarity_score, 16) -- mostly rank by the reciprocal rank of keyword_similarity_score with slight adjustment of reciprocal rank of semantic_smilarity_score . The following signals are supported:
• semantic_similarity_score : semantic similarity adjustment that is calculated using the embeddings generated by a proprietary Google model. This score determines how semantically similar a search query is to a document.
• keyword_similarity_score : keyword match adjustment uses the Best Match 25 (BM25) ranking function. This score is calculated using a probabilistic model to estimate the probability that a document is relevant to a given query.
• relevance_score : semantic relevance adjustment that uses a proprietary Google model to determine the meaning and intent behind a user's query in context with the content in the documents.
• pctr_rank : predicted conversion rate adjustment as a rank use predicted Click-through rate (pCTR) to gauge the relevance and attractiveness of a search result from a user's perspective. A higher pCTR suggests that the result is more likely to satisfy the user's query and intent, making it a valuable signal for ranking.
• freshness_rank : freshness adjustment as a rank
• document_age : The time in hours elapsed since the document was last updated, a floating-point number (e.g., 0.25 means 15 minutes).
• topicality_rank : topicality adjustment as a rank. Uses proprietary Google model to determine the keyword-based overlap between the query and the document.
• base_rank : the default rank of the result

Optional. The backend to use for the ranking expression evaluation.

Optional. The backend to use for the ranking expression evaluation.

Whether to turn on safe search. This is only supported for website search.

Whether to turn on safe search. This is only supported for website search.

The user 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 for more details.

The user 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 for more details.

Optional. Config for natural language query understanding capabilities, such as extracting structured field filters from the query. Refer to this documentation for more information.

If naturalLanguageQueryUnderstandingSpec is not specified, no additional natural language query understanding will be done.

Optional. Config for natural language query understanding capabilities, such as extracting structured field filters from the query. Refer to this documentation for more information.

If naturalLanguageQueryUnderstandingSpec is not specified, no additional natural language query understanding will be done.

Search as you type configuration. Only supported for the IndustryVertical.MEDIA vertical.

Search as you type configuration. Only supported for the IndustryVertical.MEDIA vertical.

Optional. Config for display feature, like match highlighting on search results.

Optional. Config for display feature, like match highlighting on search results.

Optional. Crowding specifications for improving result diversity.

If multiple CrowdingSpecs are specified, crowding will be evaluated on each unique combination of the field values, and max_count will be the maximum value of max_count across all CrowdingSpecs. For example, if the first CrowdingSpec has field = "color" and max_count = 3, and the second CrowdingSpec has field = "size" and max_count = 2, then after 3 documents that share the same color AND size have been returned, subsequent ones should be removed or demoted.

Optional. Crowding specifications for improving result diversity.

If multiple CrowdingSpecs are specified, crowding will be evaluated on each unique combination of the field values, and max_count will be the maximum value of max_count across all CrowdingSpecs. For example, if the first CrowdingSpec has field = "color" and max_count = 3, and the second CrowdingSpec has field = "size" and max_count = 2, then after 3 documents that share the same color AND size have been returned, subsequent ones should be removed or demoted.

The session resource name. Optional.

Session allows users to do multi-turn /search API calls or coordination between /search API calls and /answer API calls. Example #1 (multi-turn /search API calls): Call /search API with the session ID generated in the first call. Here, the previous search query gets considered in query standing. I.e., if the first query is "How did Alphabet do in 2022?" and the current query is "How about 2023?", the current query will be interpreted as "How did Alphabet do in 2023?". Example #2 (coordination between /search API calls and /answer API calls): Call /answer API with the session ID generated in the first call. Here, the answer generation happens in the context of the search results from the first search call. Multi-turn Search feature is currently at private GA stage. Please use v1alpha or v1beta version instead before we launch this feature to public GA. Or ask for allowlisting through Google Support team.

The session resource name. Optional.

Session allows users to do multi-turn /search API calls or coordination between /search API calls and /answer API calls. Example #1 (multi-turn /search API calls): Call /search API with the session ID generated in the first call. Here, the previous search query gets considered in query standing. I.e., if the first query is "How did Alphabet do in 2022?" and the current query is "How about 2023?", the current query will be interpreted as "How did Alphabet do in 2023?". Example #2 (coordination between /search API calls and /answer API calls): Call /answer API with the session ID generated in the first call. Here, the answer generation happens in the context of the search results from the first search call. Multi-turn Search feature is currently at private GA stage. Please use v1alpha or v1beta version instead before we launch this feature to public GA. Or ask for allowlisting through Google Support team.

Session specification.

Can be used only when session is set.

Session specification.

Can be used only when session is set.

The global relevance threshold of the search results.

Defaults to Google defined threshold, leveraging a balance of precision and recall to deliver both highly accurate results and comprehensive coverage of relevant information. If more granular relevance filtering is required, use the relevance_filter_spec instead. This feature is not supported for healthcare search.

The global relevance threshold of the search results.

Defaults to Google defined threshold, leveraging a balance of precision and recall to deliver both highly accurate results and comprehensive coverage of relevant information. If more granular relevance filtering is required, use the relevance_filter_spec instead. This feature is not supported for healthcare search.

Optional. The specification for returning the relevance score.

Optional. The specification for returning the relevance score.