A walkthrough of building RAG systems using the Gemini API's file search tool, a fully managed solution that abstracts away vector DB setup, chunking, and retrieval complexity. Covers ingestion of documents, agentic RAG (where the model iteratively refines search queries), metadata filtering, citation grounding, and structured outputs. Also introduces three new Gemini API data features: direct Google Cloud Storage bucket integration, signed URL support for third-party cloud storage, and service tier controls for balancing cost vs. request priority.
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