Introducing Google’s File Search Tool

Large Language Models are limited by their training data, a problem addressed by Retrieval-Augmented Generation (RAG), which grounds models in specific, private data. Building a robust RAG pipeline is a complex engineering task involving data chunking, embedding, and vector storage. Google's new File Search tool aims to simplify this by providing an integrated abstraction layer over a complete RAG pipeline directly within the Gemini API. The tool automatically handles data ingestion, embedding, and retrieval, and includes features like built-in citations to enhance verifiability. A Python code example demonstrates how to upload a document and query it using the File Search tool.