Discovery Engine V1BETA API - Class Google::Cloud::DiscoveryEngine::V1beta::SearchRequest::ContentSearchSpec::SummarySpec (v0.15.0)

Reference documentation and code samples for the Discovery Engine V1BETA API class Google::Cloud::DiscoveryEngine::V1beta::SearchRequest::ContentSearchSpec::SummarySpec.

A specification for configuring a summary returned in a search response.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#ignore_adversarial_query

def ignore_adversarial_query() -> ::Boolean
Returns
  • (::Boolean) — Specifies whether to filter out adversarial queries. The default value is false.

    Google employs search-query classification to detect adversarial queries. No summary is returned if the search query is classified as an adversarial query. For example, a user might ask a question regarding negative comments about the company or submit a query designed to generate unsafe, policy-violating output. If this field is set to true, we skip generating summaries for adversarial queries and return fallback messages instead.

#ignore_adversarial_query=

def ignore_adversarial_query=(value) -> ::Boolean
Parameter
  • value (::Boolean) — Specifies whether to filter out adversarial queries. The default value is false.

    Google employs search-query classification to detect adversarial queries. No summary is returned if the search query is classified as an adversarial query. For example, a user might ask a question regarding negative comments about the company or submit a query designed to generate unsafe, policy-violating output. If this field is set to true, we skip generating summaries for adversarial queries and return fallback messages instead.

Returns
  • (::Boolean) — Specifies whether to filter out adversarial queries. The default value is false.

    Google employs search-query classification to detect adversarial queries. No summary is returned if the search query is classified as an adversarial query. For example, a user might ask a question regarding negative comments about the company or submit a query designed to generate unsafe, policy-violating output. If this field is set to true, we skip generating summaries for adversarial queries and return fallback messages instead.

#ignore_low_relevant_content

def ignore_low_relevant_content() -> ::Boolean
Returns
  • (::Boolean) — Specifies whether to filter out queries that have low relevance. The default value is false.

    If this field is set to false, all search results are used regardless of relevance to generate answers. If set to true, only queries with high relevance search results will generate answers.

#ignore_low_relevant_content=

def ignore_low_relevant_content=(value) -> ::Boolean
Parameter
  • value (::Boolean) — Specifies whether to filter out queries that have low relevance. The default value is false.

    If this field is set to false, all search results are used regardless of relevance to generate answers. If set to true, only queries with high relevance search results will generate answers.

Returns
  • (::Boolean) — Specifies whether to filter out queries that have low relevance. The default value is false.

    If this field is set to false, all search results are used regardless of relevance to generate answers. If set to true, only queries with high relevance search results will generate answers.

#ignore_non_summary_seeking_query

def ignore_non_summary_seeking_query() -> ::Boolean
Returns
  • (::Boolean) — Specifies whether to filter out queries that are not summary-seeking. The default value is false.

    Google employs search-query classification to detect summary-seeking queries. No summary is returned if the search query is classified as a non-summary seeking query. For example, why is the sky blue and Who is the best soccer player in the world? are summary-seeking queries, but SFO airport and world cup 2026 are not. They are most likely navigational queries. If this field is set to true, we skip generating summaries for non-summary seeking queries and return fallback messages instead.

#ignore_non_summary_seeking_query=

def ignore_non_summary_seeking_query=(value) -> ::Boolean
Parameter
  • value (::Boolean) — Specifies whether to filter out queries that are not summary-seeking. The default value is false.

    Google employs search-query classification to detect summary-seeking queries. No summary is returned if the search query is classified as a non-summary seeking query. For example, why is the sky blue and Who is the best soccer player in the world? are summary-seeking queries, but SFO airport and world cup 2026 are not. They are most likely navigational queries. If this field is set to true, we skip generating summaries for non-summary seeking queries and return fallback messages instead.

Returns
  • (::Boolean) — Specifies whether to filter out queries that are not summary-seeking. The default value is false.

    Google employs search-query classification to detect summary-seeking queries. No summary is returned if the search query is classified as a non-summary seeking query. For example, why is the sky blue and Who is the best soccer player in the world? are summary-seeking queries, but SFO airport and world cup 2026 are not. They are most likely navigational queries. If this field is set to true, we skip generating summaries for non-summary seeking queries and return fallback messages instead.

#include_citations

def include_citations() -> ::Boolean
Returns
  • (::Boolean) — Specifies whether to include citations in the summary. The default value is false.

    When this field is set to true, summaries include in-line citation numbers.

    Example summary including citations:

    BigQuery is Google Cloud's fully managed and completely serverless enterprise data warehouse [1]. BigQuery supports all data types, works across clouds, and has built-in machine learning and business intelligence, all within a unified platform [2, 3].

    The citation numbers refer to the returned search results and are 1-indexed. For example, [1] means that the sentence is attributed to the first search result. [2, 3] means that the sentence is attributed to both the second and third search results.

#include_citations=

def include_citations=(value) -> ::Boolean
Parameter
  • value (::Boolean) — Specifies whether to include citations in the summary. The default value is false.

    When this field is set to true, summaries include in-line citation numbers.

    Example summary including citations:

    BigQuery is Google Cloud's fully managed and completely serverless enterprise data warehouse [1]. BigQuery supports all data types, works across clouds, and has built-in machine learning and business intelligence, all within a unified platform [2, 3].

    The citation numbers refer to the returned search results and are 1-indexed. For example, [1] means that the sentence is attributed to the first search result. [2, 3] means that the sentence is attributed to both the second and third search results.

Returns
  • (::Boolean) — Specifies whether to include citations in the summary. The default value is false.

    When this field is set to true, summaries include in-line citation numbers.

    Example summary including citations:

    BigQuery is Google Cloud's fully managed and completely serverless enterprise data warehouse [1]. BigQuery supports all data types, works across clouds, and has built-in machine learning and business intelligence, all within a unified platform [2, 3].

    The citation numbers refer to the returned search results and are 1-indexed. For example, [1] means that the sentence is attributed to the first search result. [2, 3] means that the sentence is attributed to both the second and third search results.

#language_code

def language_code() -> ::String
Returns
  • (::String) — Language code for Summary. Use language tags defined by BCP47. Note: This is an experimental feature.

#language_code=

def language_code=(value) -> ::String
Parameter
  • value (::String) — Language code for Summary. Use language tags defined by BCP47. Note: This is an experimental feature.
Returns
  • (::String) — Language code for Summary. Use language tags defined by BCP47. Note: This is an experimental feature.

#model_prompt_spec

def model_prompt_spec() -> ::Google::Cloud::DiscoveryEngine::V1beta::SearchRequest::ContentSearchSpec::SummarySpec::ModelPromptSpec
Returns

#model_prompt_spec=

def model_prompt_spec=(value) -> ::Google::Cloud::DiscoveryEngine::V1beta::SearchRequest::ContentSearchSpec::SummarySpec::ModelPromptSpec
Parameter
Returns

#model_spec

def model_spec() -> ::Google::Cloud::DiscoveryEngine::V1beta::SearchRequest::ContentSearchSpec::SummarySpec::ModelSpec
Returns

#model_spec=

def model_spec=(value) -> ::Google::Cloud::DiscoveryEngine::V1beta::SearchRequest::ContentSearchSpec::SummarySpec::ModelSpec
Parameter
Returns

#summary_result_count

def summary_result_count() -> ::Integer
Returns
  • (::Integer) — The number of top results to generate the summary from. If the number of results returned is less than summaryResultCount, the summary is generated from all of the results.

    At most 10 results for documents mode, or 50 for chunks mode, can be used to generate a summary. The chunks mode is used when SearchRequest.ContentSearchSpec.search_result_mode is set to CHUNKS.

#summary_result_count=

def summary_result_count=(value) -> ::Integer
Parameter
  • value (::Integer) — The number of top results to generate the summary from. If the number of results returned is less than summaryResultCount, the summary is generated from all of the results.

    At most 10 results for documents mode, or 50 for chunks mode, can be used to generate a summary. The chunks mode is used when SearchRequest.ContentSearchSpec.search_result_mode is set to CHUNKS.

Returns
  • (::Integer) — The number of top results to generate the summary from. If the number of results returned is less than summaryResultCount, the summary is generated from all of the results.

    At most 10 results for documents mode, or 50 for chunks mode, can be used to generate a summary. The chunks mode is used when SearchRequest.ContentSearchSpec.search_result_mode is set to CHUNKS.

#use_semantic_chunks

def use_semantic_chunks() -> ::Boolean
Returns
  • (::Boolean) — If true, answer will be generated from most relevant chunks from top search results. This feature will improve summary quality. Note that with this feature enabled, not all top search results will be referenced and included in the reference list, so the citation source index only points to the search results listed in the reference list.

#use_semantic_chunks=

def use_semantic_chunks=(value) -> ::Boolean
Parameter
  • value (::Boolean) — If true, answer will be generated from most relevant chunks from top search results. This feature will improve summary quality. Note that with this feature enabled, not all top search results will be referenced and included in the reference list, so the citation source index only points to the search results listed in the reference list.
Returns
  • (::Boolean) — If true, answer will be generated from most relevant chunks from top search results. This feature will improve summary quality. Note that with this feature enabled, not all top search results will be referenced and included in the reference list, so the citation source index only points to the search results listed in the reference list.