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[ARTICLE · art-78322] src=haystack.deepset.ai ↗ pub= topic=artificial-intelligence verified=true sentiment=· neutral

Conversational RAG Agent using InMemoryChatMessageStore

A new tutorial demonstrates building a conversational RAG agent using InMemoryChatMessageStore, InMemoryBM25Retriever, OpenAIChatGenerator, ChatMessageRetriever, and ChatMessageWriter components. The tutorial first constructs a simple conversational pipeline with an LLM, then extends it into a multi-turn RAG agent for document interactions.

read1 min views1 publishedJul 29, 2026

Agent

ChatPromptBuilder

InMemoryBM25Retriever

OpenAIChatGenerator

InMemoryChatMessageStore

ChatMessageRetriever

ChatMessageWriter

In this tutorial, you’ll first build a simple conversational pipeline using chat components and an LLM. You’ll then extend this setup into a conversational RAG pipeline using the Agent component, capable of handling multi-turn interactions over documents.

source & further reading
haystack.deepset.ai — original article Human-in-the-Loop with Haystack Agents Haystack: Open-Source AI Framework for Production Ready Agents, RAG Creating Your First QA Pipeline with Retrieval-Augmentation
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