Which RAG design patterns are you actually using for internal chatbots? And where do you find solid templates?
Building an internal chatbot in n8n and trying to figure out which RAG architecture makes the most sense before I get too deep into it.
There seem to be a few patterns floating around, basic single-agent RAG, multi-agent setups with a router, hierarchical agents, corrective RAG, self-RAG, and I’m not sure which ones people are actually running in production vs. which ones just look good in blog posts.
A few things I’m trying to work out:
Which RAG pattern are you using for your internal chatbot, and what made you pick it over the others?
If you’re running multiple agents, how are you handling the system prompts for each one? Did you write them from scratch or find a solid starting point somewhere?
Is there a resource, repo, or collection that has different RAG design patterns mapped out with template system messages included? Not looking for generic prompt libraries, more specifically RAG agent roles like retriever, reranker, answer synthesizer, query planner, etc.
For context, the bot needs to handle internal docs, some structured data, and the occasional multi-step question that probably needs more than one retrieval pass.
Any patterns, repos, or hard-won lessons would be genuinely useful.