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

Description

📘 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) workflow_flow[] (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. An n8n automation workflow template by Rahul Joshi.

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Categories

• Automation
• AI

Tags

• n8n
• workflow
• code
• ai-agent
• azure-openai-chat-model

Capabilities

• 3 nodes
• 1 views

Information