Mohsin This workflow corresponds to n8n.io template #4773 — we link there as the canonical source.
This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"id": "Mj1ghjtbl9gF3Zyv",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "RAG Pipeline and Chatbot",
"tags": [],
"nodes": [
{
"id": "f7f16cac-dda3-45df-8725-4b0febd05a41",
"name": "Google Drive Trigger",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
0,
0
],
"parameters": {},
"typeVersion": 1
},
{
"id": "ca68784d-cf16-4e34-a069-54af6724b036",
"name": "Google Drive",
"type": "n8n-nodes-base.googleDrive",
"position": [
220,
0
],
"parameters": {},
"typeVersion": 3
},
{
"id": "eb26965d-a53e-4a69-9cb3-a12aecb3c06c",
"name": "Embeddings Ollama",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"position": [
320,
200
],
"parameters": {},
"typeVersion": 1
},
{
"id": "517e0980-2cf6-43f6-9018-1debe566df18",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
440,
200
],
"parameters": {},
"typeVersion": 1
},
{
"id": "c51bf4a5-e644-46fd-8de5-61d169f55aa3",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
540,
420
],
"parameters": {},
"typeVersion": 1
},
{
"id": "e215d75e-6138-4c99-97cb-1456a2d96fc0",
"name": "Qdrant Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
440,
0
],
"parameters": {},
"typeVersion": 1.1
},
{
"id": "cf9e6861-3b99-44f2-89d2-15fde5120254",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1260,
0
],
"parameters": {},
"typeVersion": 1.9
},
{
"id": "de875567-e2f5-47e8-8145-0d6158a108b1",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
1040,
0
],
"parameters": {},
"typeVersion": 1.1
},
{
"id": "a043f2ce-fd95-4286-8dd1-e3d1c9fd9051",
"name": "Ollama Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOllama",
"position": [
1300,
220
],
"parameters": {},
"typeVersion": 1
},
{
"id": "58afa38b-0c7f-46d9-8d2e-a346ab2baf06",
"name": "Qdrant Vector Store1",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
1420,
240
],
"parameters": {},
"typeVersion": 1.1
},
{
"id": "c3151cb4-e066-40af-9eff-fe975fdffbb7",
"name": "Embeddings Ollama1",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"position": [
1420,
460
],
"parameters": {},
"typeVersion": 1
},
{
"id": "76717f0e-917a-492f-873e-9dae174ba04e",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
20,
-840
],
"parameters": {
"content": ""
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "28873c1d-0035-45ba-81a0-02a5b35482da",
"connections": {
"Google Drive": {
"main": [
[
{
"node": "Qdrant Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Embeddings Ollama": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Ollama Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings Ollama1": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store1",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Google Drive Trigger": {
"main": [
[
{
"node": "Google Drive",
"type": "main",
"index": 0
}
]
]
},
"Qdrant Vector Store1": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
}
}
}
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About this workflow
Overview This template allows users to set up an AI-powered chatbot that retrieves and processes knowledge from Google Drive documents using Retrieval-Augmented Generation (RAG). By leveraging Llama 3 for natural language responses and Qdrant vector storage for document…
Source: https://n8n.io/workflows/4773/ — original creator credit. Request a take-down →
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