Vertex AI Search (VAIS) is a fully-managed platform, powered by large language models, that lets you build AI-enabled search and recommendation experiences for your public or private websites or mobile applications
VAIS can handle a diverse set of data sources including structured, unstructured, and website data, as well as data from third-party applications such as Jira, Salesforce, and Confluence.
VAIS also has built-in integration with LLMs which enables you to provide answers to complex questions, grounded in your data
This folder contains a series of notebooks to demonstrate how different functionalities within Vertex AI Search can be used
We aim to keep these notebooks broader than a single API call and smaller than a fully fledged application.
The notebooks are expected to serve as building blocks which can be combined to achieve higher levels goals (e.g. ingest unstructured docuemnts with metadata and generate accurate answers based on that)
We will try to use REST APIs which will hopefully make the codes easier to understand without a need to read through documentations of different object types. For production use, many customer prefer Client libraries. Please consult the official documentation for alternative ways of achieving the same goals.
- Ingestion of Unstructured Documents with Metadata in Vertex AI Search
- Parsing and Chunking in Vertex AI Search: Featuring BYO Capabilities
- Defining custom attributes based on URL patterns in Vertex AI Search Website Datastores
- Query-Level Boosting, Filtering, and Facets for Vertex AI Search Website Datastores
- Inline Ingestion of Documents into Vertex AI Search