Gemini API File Search adds multimodal retrieval and page-level citations
Google says Gemini API File Search now supports images plus text, metadata filtering, and page citations to ground RAG responses.
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- Source count
- 1
- Primary sources
- 1
- QA status
- pass
Plain English
What this means in simple words
You can ask questions about a folder of PDFs and images, and File Search can pull the right pages and show where the answer came from.
What happened
On May 5, 2026, Google updated the Gemini API File Search tool with multimodal retrieval, custom metadata filtering, and page-level citations for RAG.
Why it matters
Multimodal retrieval and citations make it easier to build assistants that can show evidence, reduce wrong references, and search images alongside documents.
Key points
- File Search can retrieve relevant images and text in one query flow.
- Custom metadata filters help narrow retrieval to the right subset of files.
- Page-level citations show the specific page that supported a response.
What to watch
Watch how well the citations hold up at scale, and whether SDKs and third-party RAG tooling adopt the new File Search features quickly.
Key terms
- Retrieval-augmented generation (RAG)
- A pattern where a model retrieves relevant sources first, then answers using that retrieved context.
- Page-level citations
- References that point to the exact page or location in a source that supports an answer.
Sources
Source dates are original publication dates. The posted date above is when The AI Tea published this explanation.
- Gemini API File Search is now multimodal: build efficient, verifiable RAG Google · Product announcement · Original source May 5, 2026 · Source age 2 days Primary