AI voice chat using webhook, Memory Manager, OpenAI, Google Gemini & ElevenLabs
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
Nodes used (10)
- Chat Memory Manager
@n8n/n8n-nodes-langchain.memoryManager - Aggregate
n8n-nodes-base.aggregate - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Respond to Webhook
n8n-nodes-base.respondToWebhook - HTTP Request
n8n-nodes-base.httpRequest - Limit
n8n-nodes-base.limit - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Webhook
n8n-nodes-base.webhook - OpenAI
@n8n/n8n-nodes-langchain.openAi
What it does
Who is this for? This workflow is designed for businesses or developers looking to integrate voice-based chat applications with dynamic responses and conversational memory. What problem does this solve? It automates AI-powered voice conversations, maintaining context between sessions and converting speech-to-text and text-to-speech. What this workflow does: The workflow receives audio input, transcribes it using OpenAI, and processes the conversation using Google Gemini Chat Model (you can use OpenAI Chat Model). Responses are converted back to speech using ElevenLabs. Prerequisites: You'll need API keys for: OpenAI (you can obtain it from OpenAI website) ElevenLabs (you can obtain it from their website) Google Gemini (You can obtain it from Google AI Studio) Setup: Configure you API keys Ensure that the value (voicemessage) in the "Path" parameter in the Webhook node is used as the name of the parameter that will contain the voice message you are sending via the HTTP Post request.