search_engine_id in previous versions of the retriever.The project_id and data_store_id parameters can be provided explicitly in the retriever's constructor or through the environment variables - PROJECT_ID and DATA_STORE_ID.You can also configure a number of optional parameters, including:max_documents - The maximum number of documents used to provide extractive segments or extractive answersget_extractive_answers - By default, the retriever is configured to return extractive segments.Set this field to True to return extractive answers. This is used only when engine_data_type set to 0 (unstructured)max_extractive_answer_count - The maximum number of extractive answers returned in each search result.At most 5 answers will be returned. This is used only when engine_data_type set to 0 (unstructured).max_extractive_segment_count - The maximum number of extractive segments returned in each search result.Currently one segment will be returned. This is used only when engine_data_type set to 0 (unstructured).filter - The filter expression for the search results based on the metadata associated with the documents in the data store.query_expansion_condition - Specification to determine under which conditions query expansion should occur.0 - Unspecified query expansion condition. In this case, server behavior defaults to disabled.1 - Disabled query expansion. Only the exact search query is used, even if SearchResponse.total_size is zero.2 - Automatic query expansion built by the Search API.engine_data_type - Defines the Vertex AI Search data type0 - Unstructured data1 - Structured dataMigration guide for GoogleCloudEnterpriseSearchRetriever‚ÄãIn previous versions, this retriever was called GoogleCloudEnterpriseSearchRetriever. Some backwards-incompatible changes had to be made to the retriever after the General Availability launch due to changes in the product behavior.To update to the new retriever, make the following changes:Change the import from: from
Vertex AI Search (formerly known as Enterprise Search on Generative AI App Builder) is a part of the Vertex AI machine learning platform offered by Google Cloud.
Vertex AI Search (formerly known as Enterprise Search on Generative AI App Builder) is a part of the Vertex AI machine learning platform offered by Google Cloud. ->: search_engine_id in previous versions of the retriever.The project_id and data_store_id parameters can be provided explicitly in the retriever's constructor or through the environment variables - PROJECT_ID and DATA_STORE_ID.You can also configure a number of optional parameters, including:max_documents - The maximum number of documents used to provide extractive segments or extractive answersget_extractive_answers - By default, the retriever is configured to return extractive segments.Set this field to True to return extractive answers. This is used only when engine_data_type set to 0 (unstructured)max_extractive_answer_count - The maximum number of extractive answers returned in each search result.At most 5 answers will be returned. This is used only when engine_data_type set to 0 (unstructured).max_extractive_segment_count - The maximum number of extractive segments returned in each search result.Currently one segment will be returned. This is used only when engine_data_type set to 0 (unstructured).filter - The filter expression for the search results based on the metadata associated with the documents in the data store.query_expansion_condition - Specification to determine under which conditions query expansion should occur.0 - Unspecified query expansion condition. In this case, server behavior defaults to disabled.1 - Disabled query expansion. Only the exact search query is used, even if SearchResponse.total_size is zero.2 - Automatic query expansion built by the Search API.engine_data_type - Defines the Vertex AI Search data type0 - Unstructured data1 - Structured dataMigration guide for GoogleCloudEnterpriseSearchRetriever‚ÄãIn previous versions, this retriever was called GoogleCloudEnterpriseSearchRetriever. Some backwards-incompatible changes had to be made to the retriever after the General Availability launch due to changes in the product behavior.To update to the new retriever, make the following changes:Change the import from: from