RAG:From Retrieval to Answers: LCEL Chains, Conversation Memory, and Comparing Four Vector Stores…
中文摘要
本文讲解如何利用 LCEL 链、对话记忆及对比四种向量数据库，将 RAG 从检索片段提升至生成完整答案。
English Summary
This guide explains how to evolve RAG from simple retrieval to answer generation using LCEL chains, conversation memory, and a comparison of four vector stores.
Original Excerpt
Part 3 got a working ChromaDB store returning ranked chunks for a query. Ranked chunks aren’t an answer though. This part covers turning… Continue reading on Medium »