Depending on the data type used in Vertex AI Search (structured or unstructured) the page_content field is populated as follows:Structured data source: either an extractive segment or an extractive answer that matches a query. The metadata field is populated with metadata (if any) of the document from which the segments or answers were extracted.Unstructured data source: a string json containing all the fields returned from the structured data source. The metadata field is populated with metadata (if any) of the documentOnly for Unstructured data sources:‚ÄãAn extractive answer is verbatim text that is returned with each search result. It is extracted directly from the original document. Extractive answers are typically displayed near the top of web pages to provide an end user with a brief answer that is contextually relevant to their query. Extractive answers are available for website and unstructured search.An extractive segment is verbatim text that is returned with each search result. An extractive segment is usually more verbose than an extractive answer. Extractive segments can be displayed as an answer to a query, and can be used to perform post-processing tasks and as input for large language models to generate answers or new text. Extractive segments are available for unstructured search.For more information about extractive segments and extractive answers refer to product documentation.NOTE: Extractive segments require the Enterprise edition features to be enabled.When creating an instance of the retriever you can specify a number of parameters that control which data store to access and how a natural language query is processed, including configurations for extractive answers and segments.The mandatory parameters are:‚Äãproject_id - Your Google Cloud Project ID.location_id - The location of the data store.global (default)useudata_store_id - The ID of the data store you want to use.Note: This was called search_engine_id in previous versions of the
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. ->: Depending on the data type used in Vertex AI Search (structured or unstructured) the page_content field is populated as follows:Structured data source: either an extractive segment or an extractive answer that matches a query. The metadata field is populated with metadata (if any) of the document from which the segments or answers were extracted.Unstructured data source: a string json containing all the fields returned from the structured data source. The metadata field is populated with metadata (if any) of the documentOnly for Unstructured data sources:‚ÄãAn extractive answer is verbatim text that is returned with each search result. It is extracted directly from the original document. Extractive answers are typically displayed near the top of web pages to provide an end user with a brief answer that is contextually relevant to their query. Extractive answers are available for website and unstructured search.An extractive segment is verbatim text that is returned with each search result. An extractive segment is usually more verbose than an extractive answer. Extractive segments can be displayed as an answer to a query, and can be used to perform post-processing tasks and as input for large language models to generate answers or new text. Extractive segments are available for unstructured search.For more information about extractive segments and extractive answers refer to product documentation.NOTE: Extractive segments require the Enterprise edition features to be enabled.When creating an instance of the retriever you can specify a number of parameters that control which data store to access and how a natural language query is processed, including configurations for extractive answers and segments.The mandatory parameters are:‚Äãproject_id - Your Google Cloud Project ID.location_id - The location of the data store.global (default)useudata_store_id - The ID of the data store you want to use.Note: This was called search_engine_id in previous versions of the