Templates / Decide multi‑agent vs simple workflows using Azure OpenAI GPT‑4o‑mini

Decide multi‑agent vs simple workflows using Azure OpenAI GPT‑4o‑mini

Ready for 3.0

by Rahul Joshi ✓ · 188 views · created 2026-03-02 · Engineering, AI Chatbot

Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.

Nodes used (5)

AI AgentAzure OpenAI Chat Model

What it does

📘 Description This workflow acts as an AI Multi-Agent Architecture Advisor for n8n. It receives a problem statement via webhook, uses Azure OpenAI (gpt-4o-mini) to decide whether the problem needs a multi-agent design or a simple workflow, then returns a styled HTML report showing the decision, recommended agents (if any), and the suggested step flow. ⚙️ Step-by-Step Flow - Receive Problem Description via POST (Webhook) - Accepts a POST payload containing a description field. - Extract Request Body (Code) - Strips the wrapper and outputs only the body JSON to simplify downstream prompts. - Multi-Agent Architecture Decision Agent (AI Agent) - Analyzes the problem description and outputs one of: - Decision: Multi-Agent Required + agent definitions + workflow steps - Decision: Not Required + minimal simplified workflow nodes - Parse Decision, Agents & Steps (Code) - Extracts three structured fields from the AI output: decision - agents (name, purpose, node, reason) - workflowflow (ordered steps) - Build HTML Architecture Report (Code) - Renders a clean card-based HTML dashboard: - Decision badge (multi vs simple) - Agent cards (if present) - Workflow flow chips (steps) - Return HTML Report to Caller (Respond to Webhook) - Returns the HTML report directly as the webhook response. - 🧩 Prerequisites - • Azure OpenAI credential with an active gpt-4o-mini deployment - • n8n webhook endpoint exposed to the caller (or via tunnel) - 💡 Key Benefits ✔ Fast “multi-agent vs simple” decisioning ✔ Outputs an actionable architecture, not generic advice ✔ HTML report is ready to embed in internal tools (Base44/UI) ✔ Structured parsing makes it easy to store or extend later 👥 Perfect For - Automation agencies doing solution design calls - Teams standardizing how they choose agent-based workflows - Internal tooling that needs instant architecture recommendations

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