AI-powered WhatsApp chatbot with Venom Bot & Google Gemini (no official API)

by ObisDev ✓ · 3,423 views · created 2025-07-07 · Support Chatbot, AI Chatbot

What this workflow does

This AI workflow has 13 nodes and runs when an HTTP POST request hits its webhook URL. Along the way it connects Google Docs and Google Gemini Chat Model. It also calls srv892192.hstgr.cloud and 0.0.0.0:3000 over HTTP.

How it runs

Trigger: When an HTTP POST request hits its webhook URL.

1. Process Message (Code): runs custom JavaScript code
2. Get Knowledge Base (Google Docs): get
3. Check for Errors (If): checks a condition and branches into true / false
4. Extract Knowledge (Code): runs custom JavaScript code
5. Send Error Response (HTTP Request): calls srv892192.hstgr.cloud
6. AI Agent: runs an AI agent, with model: Google Gemini Chat Model; memory: Simple Memory
7. Error Webhook Response (Respond to Webhook): sends the response back to the webhook caller
8. Format Response (Code): runs custom JavaScript code
9. Send to WhatsApp (HTTP Request): calls 0.0.0.0:3000 (POST)
10. Webhook Response (Respond to Webhook): sends the response back to the webhook caller

Services it uses

Google DocsGoogle Gemini Chat Model

HTTP calls to: srv892192.hstgr.cloud, 0.0.0.0:3000

Before you upgrade to n8n 3.0

Nodes used (9)

• Coden8n-nodes-base.code
• Google Docsn8n-nodes-base.googleDocs
• HTTP Requestn8n-nodes-base.httpRequest
• Respond to Webhookn8n-nodes-base.respondToWebhook
• Ifn8n-nodes-base.if
• AI Agent@n8n/n8n-nodes-langchain.agent
• Google Gemini Chat Model@n8n/n8n-nodes-langchain.lmChatGoogleGemini
• Webhookn8n-nodes-base.webhook
• Simple Memory@n8n/n8n-nodes-langchain.memoryBufferWindow

From the author

Get Started Creator: @obisdev This workflow powers a fully automated WhatsApp chatbot using a self-hosted Venom Bot instead of the official WhatsApp Business API. It integrates Google Gemini AI to generate intelligent, conversational responses and optionally…

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