Gemini RAG In Minutes: Your Guide To Building With The New File Search Tool

Description

Read the companion article: https://binaryverseai.com/gemini-rag-stacks-pricing-file-search-pricing/ Ship grounded answers without the plumbing. In this 16:10 walkthrough, we build a production-ready Gemini RAG workflow using Gemini File Search, then pressure test it against a DIY RAG pipeline. You will see how to create a file search store, upload and index documents, ask questions with citations, tune chunking, and filter by metadata. We also cover pricing so you can scale with confidence. What you will learn The core pieces of Gemini RAG, how managed RAG cuts setup from weeks to minutes File Search basics, chunking, embeddings, retrieval, citations Pricing model, free storage and query time embeddings, pay on indexing Practical tuning, chunk size and overlap, metadata filters, multi store strategy When to use File Search, when a custom RAG pipeline still wins Chapters 00:00 Weeks of heavy lifting 00:50 Plumbing is the perfect word 01:25 Gemini file search tool 02:10 Automated chunking 03:05 Built-in embeddings 03:50 Managed vector storage 04:45 Seamless retrieval 05:40 Storage is free 06:45 Pay for the value 07:30 Create a file search store 08:10 Upload and index a document 08:50 Ask questions and return citations 09:45 Chunking trade-offs 10:45 Metadata filters 11:45 Start simple with the managed service 12:40 Knowing the limits is crucial 13:40 Not a killer 14:35 The craft 15:20 Create a store. Upload one one document. 15:55 Ask three real questions Who is this for Engineers who want a fast path to Gemini RAG Teams replacing ad hoc search with grounded answers Builders comparing managed RAG to LangChain plus a vector database Key takeaways Gemini File Search makes Gemini RAG simple to run and easy to trust with citations Free storage and query time embeddings reduce ongoing cost Start managed, move to custom only when requirements demand it If this saved you time, like and subscribe. Comment with your use case and I will map an ingestion and evaluation plan you can ship this week. #GeminiRAG #GoogleGemini #RAG #AIEngineering #VectorSearch