Google Expands Gemini API File Search to Multimodal RAG

Overview

Google has announced an expansion of the Gemini API File Search tool to support multimodal retrieval-augmented generation (RAG). The update enables developers to build search systems that work across text, images, audio, and video files.

Key Features

Multimodal file retrieval: Search across diverse file types including images, audio clips, and video content.

Verifiable responses: Search results include source attribution so applications can surface grounding evidence for AI-generated answers.

Token efficiency: Rather than loading entire documents into the context window, File Search retrieves only relevant chunks, reducing costs and latency.

Developer Impact

The update lowers the barrier for building enterprise RAG applications that go beyond text. Developers working on document intelligence, media libraries, or knowledge management systems can now incorporate images and audio into their Gemini-powered search pipelines. Google frames this as part of a broader push to make the Gemini API a platform for production-grade AI applications with measurable quality and reliability.