Gemini API File Search expands to support multimodal RAG with image and text processing
By
Ivan Solovyev
Reliable enough to start your morning with. Toast it again tomorrow.
Summary
Google has expanded the Gemini API's File Search tool to support multimodal data (text and images) in retrieval-augmented generation (RAG) systems. The update, powered by the Gemini Embedding 2 model, allows developers to build RAG applications that natively process both text and visual data together. New features include custom metadata support and page citations for improved grounding and transparency. The tool is designed for both prototyping and production-scale applications.
Key quotes
· 5 pulledYou can now build retrieval-augmented generation (RAG) systems with multimodal data and custom metadata.
Whether you are prototyping a weekend project or scaling a production application for thousands of users, your RAG systems can now natively process and better organize your text and visual data.
Give your apps a photographic memory
File Search now processes images and text together.
Powered by the Gemini Embedding 2 model, the tool understands native image data
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