Answer multi-channel support queries with OpenAI RAG and Supabase

Quick overview Answers customer questions on Email, Live Chat, WhatsApp, Slack and Discord from your own documentation, retrieved through a Supabase vector store. Ungrounded answers, negative sentiment and explicit handover requests escalate to a human with a Zendesk ticket. Every conversation is categorised, logged and reported weekly. How it works A message arrives on Email, Live Chat, WhatsApp, Slack or Discord and is normalised into one schema, with an explicit branch per channel. Five guards run before a single model call is paid for: auto-replies and bounces, empty bodies, duplicate deliveries, oversized messages, and an explicit request for a human matched in six languages. Live chat

Help me set up the n8n workflow "Answer multi-channel support queries with OpenAI RAG and Supabase" (https://n8n.io/workflows/11807). It uses: Send Email, Google Sheets, Postgres, Slack, Discord, Zendesk, Supabase, WhatsApp Business Cloud, Code, AI Agent, Basic LLM Chain, Embeddings OpenAI, OpenAI Chat Model, Recursive Character Text Splitter, Supabase Vector Store, Default Data Loader, Postgres Chat Memory. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.