This workflow follows the Chainllm → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "TtoDcjgthgA4NTkU",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "AI Voice Chat using Webhook, Memory Manager, OpenAI, Google Gemini & ElevenLabs",
"tags": [
{
"id": "mqOrNvCDgQLzPA2x",
"name": "Workflows",
"createdAt": "2024-08-07T14:18:53.614Z",
"updatedAt": "2024-08-07T14:18:53.614Z"
}
],
"nodes": [
{
"id": "86cbf150-df4f-42f7-b7b3-e03c32e6f23c",
"name": "Get Chat",
"type": "@n8n/n8n-nodes-langchain.memoryManager",
"position": [
1700,
-400
],
"parameters": {
"options": {}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "a9153a24-e902-4f29-9b83-447317ce3119",
"name": "Insert Chat",
"type": "@n8n/n8n-nodes-langchain.memoryManager",
"position": [
2540,
-400
],
"parameters": {
"mode": "insert",
"messages": {
"messageValues": [
{
"type": "user",
"message": "={{ $('OpenAI - Speech to Text').item.json[\"text\"] }}"
},
{
"type": "ai",
"message": "={{ $json.text }}"
}
]
}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "f5c272d4-248b-45a5-87b5-eb659a865d05",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1664,
-491
],
"parameters": {
"color": 6,
"width": 486.4746124819703,
"height": 238.4911357933579,
"content": "## Get Context"
},
"typeVersion": 1
},
{
"id": "32ad17ca-0045-487d-9387-71c2e73629d4",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
2510,
-489
],
"parameters": {
"color": 6,
"width": 321.2536584847704,
"height": 231.05945912581728,
"content": "## Save Context"
},
"typeVersion": 1
},
{
"id": "17ae4f1a-6192-4c52-8157-3cb47b37e0fb",
"name": "Aggregate",
"type": "n8n-nodes-base.aggregate",
"position": [
2020,
-400
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData",
"destinationFieldName": "context"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "00b3081e-fbcd-489b-b45a-4e847c346594",
"name": "Window Buffer Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
2080,
-100
],
"parameters": {
"sessionKey": "test-0dacb3b5-4bcd-47dd-8456-dcfd8c258204",
"sessionIdType": "customKey"
},
"typeVersion": 1.2
},
{
"id": "55ca2790-e905-414a-a9f6-7d88a9e5807d",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
2220,
-100
],
"parameters": {
"options": {},
"modelName": "models/gemini-1.5-flash"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "e8b3433f-b205-404c-9f05-504556d6b6dd",
"name": "Respond to Webhook",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
3560,
-400
],
"parameters": {
"options": {},
"respondWith": "binary"
},
"typeVersion": 1.1
},
{
"id": "de296743-5ac7-454b-bf3a-d020cc024511",
"name": "ElevenLabs - Generate Audio",
"type": "n8n-nodes-base.httpRequest",
"position": [
3240,
-400
],
"parameters": {
"url": "=https://api.elevenlabs.io/v1/text-to-speech/{{voice id}}",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "text",
"value": "={{ $('Basic LLM Chain').item.json.text }}"
}
]
},
"genericAuthType": "httpCustomAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpCustomAuth": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "214e15f2-8a16-4598-b4ac-9fc2ec6545e6",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
3040,
-560
],
"parameters": {
"width": 468.73250812192407,
"height": 843.7602354099661,
"content": "* ### For the Text-to-Speech part, we'll use ElevenLabs.io, which is free and offers a variety of voices to choose from. However, you can also use the OpenAI `\"Generate audio\"` node instead.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n* ### Since there is no pre-built node for `\"ElevenLabs\"` in n8n, we'll connect to it through its API using the \"HTTP Request\" node.\n\n## Prerequisites:\n* ### `\"ElevenLabs API Key\"` (you can obtain it from their website).\n* ### `\"Voice ID\"` (you can also get it from ElevenLabs' \"Voice Library\").\n## Setup\n* ### In the URL parameter, replace \"{{voice id}}\" at the end of the URL with the Voice ID you obtained from ElevenLabs.io.\n* ### To set up your API Key, add custom authentication and include the following `JSON` with your acual ElevenLabs API Key:\n```json\n{\n \"headers\": {\n \"xi-api-key\": \"put-your-API-Key-here\"\n }\n}\n```"
},
"typeVersion": 1
},
{
"id": "94ad934c-4a13-47b1-83a5-76fab43b3a47",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
1663,
-598
],
"parameters": {
"color": 6,
"width": 487.4293487597613,
"height": 91.01435855269375,
"content": "### The \"Get Chat,\" \"Insert Chat,\" and \"Window Buffer Memory\" nodes will help the LLM model maintain context throughout the conversation."
},
"typeVersion": 1
},
{
"id": "0a96f48d-0d8b-4240-9eab-a681bfd4c8b5",
"name": "Limit",
"type": "n8n-nodes-base.limit",
"position": [
2900,
-400
],
"parameters": {},
"typeVersion": 1
},
{
"id": "9a5d4ddb-6403-4758-858e-9fbe10c421a9",
"name": "Basic LLM Chain",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
2200,
-400
],
"parameters": {
"text": "={{ $('OpenAI - Speech to Text').item.json[\"text\"] }}",
"messages": {
"messageValues": [
{
"type": "AIMessagePromptTemplate",
"message": "=To maintain context and fully understand the user's question, always review the previous conversation between you and him before providing an answer.\nThis is the previous conversation:\n{{ $('Aggregate').item.json[\"context\"].map(m => `\nHuman: ${m.human || 'undefined'}\nAI Assistant: ${m.ai || 'undefined'}\n`).join('') }}"
}
]
},
"promptType": "define"
},
"typeVersion": 1.4
},
{
"id": "f2f99895-9678-41b8-ad28-db40e1e23dc0",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
1320,
-400
],
"parameters": {
"path": "voice_message",
"options": {},
"httpMethod": "POST",
"responseMode": "responseNode"
},
"typeVersion": 2
},
{
"id": "d9a5fb04-4c02-4da4-b690-7b0ecd0ae052",
"name": "OpenAI - Speech to Text",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
1500,
-400
],
"parameters": {
"options": {},
"resource": "audio",
"operation": "transcribe",
"binaryPropertyName": "voice_message"
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
}
],
"active": true,
"settings": {
"callerPolicy": "workflowsFromSameOwner",
"executionOrder": "v1",
"saveManualExecutions": true
},
"versionId": "fe5792ca-03d7-4cdd-96db-20f4cd479c7e",
"connections": {
"Limit": {
"main": [
[
{
"node": "ElevenLabs - Generate Audio",
"type": "main",
"index": 0
}
]
]
},
"Webhook": {
"main": [
[
{
"node": "OpenAI - Speech to Text",
"type": "main",
"index": 0
}
]
]
},
"Get Chat": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Basic LLM Chain",
"type": "main",
"index": 0
}
]
]
},
"Insert Chat": {
"main": [
[
{
"node": "Limit",
"type": "main",
"index": 0
}
]
]
},
"Basic LLM Chain": {
"main": [
[
{
"node": "Insert Chat",
"type": "main",
"index": 0
}
]
]
},
"Window Buffer Memory": {
"ai_memory": [
[
{
"node": "Insert Chat",
"type": "ai_memory",
"index": 0
},
{
"node": "Get Chat",
"type": "ai_memory",
"index": 0
}
]
]
},
"OpenAI - Speech to Text": {
"main": [
[
{
"node": "Get Chat",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Basic LLM Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"ElevenLabs - Generate Audio": {
"main": [
[
{
"node": "Respond to Webhook",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googlePalmApihttpCustomAuthopenAiApi
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How this works
This workflow delivers seamless AI-powered voice conversations, allowing users to interact naturally via voice inputs that are transcribed, processed with contextual memory, and responded to in synthesised speech. It's designed for developers building chatbots or virtual assistants who need persistent conversation history without managing complex backends. The key step involves the memory buffer window, which maintains dialogue context across interactions, integrating OpenAI for transcription and ElevenLabs for lifelike voice generation to ensure responses feel intuitive and responsive.
Use this when creating real-time voice interfaces for customer support or personal assistants, especially with webhook-driven apps like web forms or telephony systems. Avoid it for non-conversational tasks or when low-latency isn't critical, as the 15-node chain adds slight overhead. Common variations include swapping Google Gemini for other LLMs or adding sentiment analysis nodes for more nuanced replies.
About this workflow
AI Voice Chat using Webhook, Memory Manager, OpenAI, Google Gemini & ElevenLabs. Uses memoryManager, stickyNote, memoryBufferWindow, lmChatGoogleGemini. Webhook trigger; 15 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
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