Block 1 - OpenAI Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
Intelligent AI Assistant with RAG & Voice for WhatsApp – Built with GPT 4o & Supabase About this workflow and its creator Hi! I’m Amanda, a creator of intelligent automations using n8n and Ma...
@n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.converttofile, n8n-nodes-base.set, n8n-nodes-base.if, n8n-nodes-base.wait, n8n-nodes-base.redis, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.openai
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Amanda Benks.
Original n8n.io sourceHi! I’m Amanda, a creator of intelligent automations using n8n and Make. I’ve been building AI-powered workflows for over 2 years, always focused on usability and innovation. This one here is very special to me – a truly advanced AI assistant that reads, listens, interprets and responds like a real human 🤖✨
This ready-to-use workflow acts as a powerful AI personal assistant capable of understanding messages via voice, text, documents, or even images. It supports full multi-channel operation (WhatsApp via Evolution API, Instagram, Facebook, and more), and includes advanced RAG capabilities using Supabase + GPT-4o. It’s designed to be highly extensible, with memory, prompt update tools, and knowledge base management.
n8n Hosting
This workflow requires n8n self-hosted (or n8n Cloud with custom credentials + community nodes enabled).
Create required databases
Use the provided SQL queries inside the setar_supabase_tabelas_vectoriais, criar_cerebro, and criar_rag_controle nodes to initialize:
documents table for RAGcerebro table for promptmemoria_chat for session memoryrag_controle for summaries and indexingCredentials needed
Webhook Set the webhook path to receive messages from your Evolution or WhatsApp API provider.
Configure ‘Set’ node
In the config node, adjust:
adminNumero: your personal WhatsApp or admin numberevolutionApiKey: your private API keyutilizacaoApenasViaAdmin: toggle if this should only respond to admin numbersTool connections Ensure the supporting workflows are also imported and connected for:
❤️ Buy workflows: https://iloveflows.com
☁️ Use n8n Cloud with my partner link: https://n8n.partnerlinks.io/amanda
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 76 workflow blocks. Download the JSON for the full node graph.
| Workflow | AI personal assistant with GPT-4o, RAG & voice for WhatsApp using Supabase |
|---|---|
| Complexity | advanced |
| Nodes | 76 |
| Categories | Personal Productivity, AI Chatbot |
| Author | Amanda Benks |
| Published | 08 May 2025 |
Use the JSON export at /data/workflows/3947/3947.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Intelligent AI Assistant with RAG & Voice for WhatsApp – Built with GPT 4o & Supabase About this workflow and its creator Hi! I’m Amanda, a creator of intelligent automations using n8n and Ma...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Personal Productivity, AI Chatbot use case.