As part of your Retrieval Augmented Generation (RAG) experience in Agent Search, you can generate grounded answers to prompts based on the following grounding sources:
- Google Search: Use Grounding with Google Search if you want to connect the model with world knowledge, a wide range of topics, or up-to-date information on the internet. Grounding with Google Search supports dynamic retrieval that gives you the option to generate Grounded Results with Google Search only when necessary. Therefore, the dynamic retrieval configuration evaluates whether a prompt requires knowledge about recent events and enables Grounding with Google Search. For more information, see Dynamic retrieval.
- Inline text: Use grounding with inline text to ground the answer in pieces of text called fact text that are provided in the request. A fact text is a user-provided statement that is considered to be factual for a given request. The model doesn't check the authenticity of the fact text.
- Agent Search data stores: Use grounding with Agent Search if you want to connect the model to your enterprise documents from Agent Search data stores.
This page describes how to generate grounded answers based on these grounding sources using the following approaches:
Single-turn answer generation