AI summarized from verified sources
Gemini File Search becomes multimodal for RAG
Build RAG over images+text with page-cited answers.
SOURCE CHECK
1 sources
Sources
Key Points
- 1Multimodal retrieval across images and text
- 2Filter queries with custom metadata
- 3Return page-level citations for PDFs
Google expanded Gemini API File Search to support multimodal retrieval across images and text. It also added custom metadata filters and page-level citations for PDFs. This makes it easier to build verifiable RAG systems over messy real-world corpora like diagrams and screenshots.
Key point
File Search now handles multimodal data, making it easier to search documents that include images. Page-level citations also help users trace the basis for answers.
Impact
AI systems built on internal docs or manuals can show their sources more clearly. It also helps reduce misses in mixed text-and-image documents.
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