Скачать или смотреть Google’s new Gemini File Search Tool could be the biggest step forward in (RAG)

Google’s new Gemini File Search Tool could be the biggest step forward in Retrieval Augmented Generation (RAG) since the concept was coined. This update to the Gemini API essentially makes “grounded AI” — AI that actually knows your own data — accessible to anyone, not just big engineering teams with cloud budgets and patience to burn.

LLMs like Gemini, ChatGPT, and Claude are powerful, but blind to your private data — your notes, contracts, and internal reports. Traditionally, solving that meant building a RAG pipeline: chunking data, embedding text into vectors, setting up vector databases, and maintaining retrieval logic. That’s been a complex, expensive engineering slog.

The *Gemini File Search Tool (GFST)* collapses all of that into a single, fully managed process. You upload a file, it’s automatically chunked, embedded, indexed, and made searchable using semantic search. Ask a question later, and Gemini quietly runs a real-time retrieval loop: generating a semantic query, matching it against your indexed data, and producing a grounded answer — with citations — all managed through the Gemini API.

For developers, the difference is night and day. What used to take an entire RAG stack now takes three API calls:

1. Create a file store.
2. Upload and index your file.
3. Query Gemini with your question and point it to the store.

That’s it. The entire offline indexing and online retrieval process is automated.

The pricing is just as disruptive:

Storing files: free.
Query embeddings: free.
You only pay a small fee for the one-time file indexing and standard Gemini usage for context in answers.

This means even small teams can build AI tools that actually understand internal data — proposals, support tickets, or product documentation — in minutes.

In short, Google’s File Search Tool is RAG without the pain. It makes grounded, verifiable AI something you can build on a lunch break — and that changes the game.

Learn more or explore AI projects like this at www.imbila.ai http://www.imbila.ai/services