Create a webhook-ready conversational assistant with Google Gemini and session memory
Needs changesWhat this workflow does
This AI workflow has 5 nodes and runs when an HTTP POST request hits its webhook URL. Along the way it connects Google Gemini Chat Model.
How it runs
Trigger: When an HTTP POST request hits its webhook URL.
- AI Agent: runs an AI agent, with model: Google Gemini Chat Model; memory: Simple Memory
- Respond to Webhook: sends the response back to the webhook caller
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent (v1.8): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent (v1.8) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (5)
- AI Agent
@n8n/n8n-nodes-langchain.agent - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Webhook
n8n-nodes-base.webhook - Respond to Webhook
n8n-nodes-base.respondToWebhook - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow
From the author
Universal AI Assistant - Webhook-Ready Conversational AI Transform any platform into an intelligent conversational experience with this plug-and-play n8n workflow. This AI assistant can be seamlessly integrated into websites, mobile apps, or any system that…