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 →
{
"name": "\ud83e\udd16RAG Agent Demo",
"nodes": [
{
"parameters": {
"options": {}
},
"id": "5dd304ff-944e-414f-8c77-861b059257cf",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
700,
320
]
},
{
"parameters": {
"options": {}
},
"id": "ee93bb9b-bcd9-4592-85aa-9c92d6b520ec",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
720,
500
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"contextWindowLength": 10
},
"id": "99c27507-a63a-461a-9535-826c0b48edc8",
"name": "Postgres Chat Memory",
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.1,
"position": [
840,
500
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"id": "ee350ee7-d27c-44e9-8c53-8bc7d43baa34",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
1200,
640
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"tableName": {
"__rl": true,
"value": "documents",
"mode": "list",
"cachedResultName": "documents"
},
"options": {
"queryName": "match_documents"
}
},
"id": "0b0c6f8a-6825-4dbf-8d1e-e5532712d4a5",
"name": "Supabase Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
"typeVersion": 1,
"position": [
940,
640
],
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"id": "9e1937bd-647a-4299-b2c9-eb3e2934092d",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"typeVersion": 1.1,
"position": [
820,
660
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"name": "project_data",
"description": "Retrieve information about the projects"
},
"id": "42dc9598-884a-4097-91b3-1e8070297b85",
"name": "Vector Store Tool",
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
980,
500
]
},
{
"parameters": {
"options": {
"systemMessage": "You are a helpful assistant. You will use the vector database to retrieve relevant information and respond to the user's query."
}
},
"id": "86d099c2-1f3b-479e-a56f-93612a20a07e",
"name": "RAG Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
880,
320
]
}
],
"connections": {
"When chat message received": {
"main": [
[
{
"node": "RAG Agent",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "RAG Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Postgres Chat Memory": {
"ai_memory": [
[
{
"node": "RAG Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Vector Store Tool",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Supabase Vector Store": {
"ai_vectorStore": [
[
{
"node": "Vector Store Tool",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Supabase Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Vector Store Tool": {
"ai_tool": [
[
{
"node": "RAG Agent",
"type": "ai_tool",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "daac2bf0-0865-48b3-b400-fe8b4a807ede",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "cQNSLNw1kntyShdn",
"tags": []
}
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.
openAiApipostgressupabaseApi
About this workflow
🤖RAG Agent Demo. Uses chatTrigger, lmChatOpenAi, memoryPostgresChat, vectorStoreSupabase. Chat trigger; 8 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →