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We're rolling out AlphaEvolve widely to solve Google Cloud customers' hardest problems. Expanding Managed Agents in Gemini API: background tasks, remote MCP and more The latest AI news we announced in June 2026 Ask an AI expert: What exactly is the full stack? Interactions API: our primary interface for Gemini models and agents DiffusionGemma: 4x faster text generation See what 3 builders are making with Gemma 4 Bringing the latest Gemini models to Apple developers Gemma 4 QAT models: Optimizing model compression for mobile and laptop efficiency Kaggle is making AI benchmark creation effortless Introducing Gemma 4 12B: a unified, encoder-free multimodal model How we used Gemini to build Google I/O 2026 Take our I/O 2026 quiz, vibe coded in Google AI Studio. Here's what developers can do with the latest Google Play updates. Building the agentic future: Developer highlights from I/O 2026 I/O 2026 Introducing Managed Agents in the Gemini API Bring any idea to life: Google AI Studio at I/O 2026 Accelerating Gemma 4: faster inference with multi-token prediction drafters The latest AI news we announced in April 2026 Reduce friction and latency for long-running jobs with Webhooks in Gemini API Join the new AI Agents Vibe Coding Course from Google and Kaggle Deep Research Max: a step change for autonomous research agents Start vibe coding in AI Studio with your Google AI subscription. Prepay for the Gemini API to get more control over your spend Introducing Learn Mode: your personal coding tutor in Google Colab Gemma 4: Byte for byte, the most capable open models New ways to balance cost and reliability in the Gemini API The latest AI news we announced in March 2026 Improve coding agents’ performance with Gemini API Docs MCP and Agent Skills. Build with Veo 3.1 Lite, our most cost-effective video generation model
Gemini API File Search is now multimodal: build efficient, verifiable RAG
Ivan Solovyev · 2026-05-06 · via Developer tools

We’re introducing three major updates to the Gemini API File Search tool: multimodal support, custom metadata and page-level citations. These features help developers bring structure to unstructured data for efficient, verifiable RAG.

Kriti Dwivedi

Software Engineer

Gemini API File Search

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Today, we are expanding the Gemini API’s File Search tool. You can now build retrieval-augmented generation (RAG) systems with multimodal data and custom metadata. We’re also introducing page citations to improve grounding and transparency.

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, providing your agents contextual awareness.

Think of a creative agency trying to dig up a specific visual asset. Instead of relying on keywords or filenames, your app can search an entire archive for an image matching a specific emotional tone or visual style described in a natural language brief.

See how developers are already using it:

Filter the noise with custom metadata

Dumping files into a database is easy. Finding the right one at scale is the real challenge. Custom metadata allows you to attach key-value labels to your unstructured data — things like department: Legal or status: Final.

By applying metadata filters at query time, your application can scope requests to the data slice required. This significantly reduces noise from irrelevant documents, increasing both the speed and accuracy of your RAG workflows.

Show your work with page citations

When your application pulls an answer from a massive PDF, users need to verify exactly where that answer came from.

File Search now ties the model’s response directly to the original source. It captures the page number for every piece of indexed information. This level of granularity allows you to point users directly to the right spot, which helps build trust and makes your tool immediately useful for rigorous fact-checking.

Get started with File Search

We want to make it as easy as possible to store and retrieve the data that makes your ideas work. The File Search tool handles the heavy infrastructure so you can focus on building the product.

Uploading files and searching across them is simple:

Explore more code snippets in our developer guide and Gemini API documentation to learn how to build with File Search.

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