About this recipe
A recipe for Extract Personal Data With Self Hosted Llm Mistral Nemo
Recipe Template
{
"id": "HMoUOg8J7RzEcslH",
"meta": {
"instanceId": "3f91626b10fcfa8a3d3ab8655534ff3e94151838fd2709ecd2dcb14afb3d061a",
"templateCredsSetupCompleted": true
},
"name": "Extract personal data with a self-hosted LLM Mistral NeMo",
"tags": [],
"nodes": [
{
"id": "7e67ae65-88aa-4e48-aa63-2d3a4208cf4b",
"name": "When chat message received",
"type": "@n8n\/n8n-nodes-langchain.chatTrigger",
"position": [
-500,
20
],
"webhookId": "3a7b0ea1-47f3-4a94-8ff2-f5e1f3d9dc32",
"parameters": {
"options": []
},
"typeVersion": 1.1
},
{
"id": "e064921c-69e6-4cfe-a86e-4e3aa3a5314a",
"name": "Ollama Chat Model",
"type": "@n8n\/n8n-nodes-langchain.lmChatOllama",
"position": [
-280,
420
],
"parameters": {
"model": "mistral-nemo:latest",
"options": {
"useMLock": true,
"keepAlive": "2h",
"temperature": 0.1
}
},
"credentials": {
"ollamaApi": {
"id": "vgKP7LGys9TXZ0KK",
"name": "Ollama account"
}
},
"typeVersion": 1
},
{
"id": "fe1379da-a12e-4051-af91-9d67a7c9a76b",
"name": "Auto-fixing Output Parser",
"type": "@n8n\/n8n-nodes-langchain.outputParserAutofixing",
"position": [
-200,
220
],
"parameters": {
"options": {
"prompt": "Instructions:\n--------------\n{instructions}\n--------------\nCompletion:\n--------------\n{completion}\n--------------\n\nAbove, the Completion did not satisfy the constraints given in the Instructions.\nError:\n--------------\n{error}\n--------------\n\nPlease try again. Please only respond with an answer that satisfies the constraints laid out in the Instructions:"
}
},
"typeVersion": 1
},
{
"id": "b6633b00-6ebb-43ca-8e5c-664a53548c17",
"name": "Structured Output Parser",
"type": "@n8n\/n8n-nodes-langchain.outputParserStructured",
"position": [
60,
400
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"Name of the user\"\n },\n \"surname\": {\n \"type\": \"string\",\n \"description\": \"Surname of the user\"\n },\n \"commtype\": {\n \"type\": \"string\",\n \"enum\": [\"email\", \"phone\", \"other\"],\n \"description\": \"Method of communication\"\n },\n \"contacts\": {\n \"type\": \"string\",\n \"description\": \"Contact details. ONLY IF PROVIDED\"\n },\n \"timestamp\": {\n \"type\": \"string\",\n \"format\": \"date-time\",\n \"description\": \"When the communication occurred\"\n },\n \"subject\": {\n \"type\": \"string\",\n \"description\": \"Brief description of the communication topic\"\n }\n },\n \"required\": [\"name\", \"commtype\"]\n}"
},
"typeVersion": 1.2
},
{
"id": "23681a6c-cf62-48cb-86ee-08d5ce39bc0a",
"name": "Basic LLM Chain",
"type": "@n8n\/n8n-nodes-langchain.chainLlm",
"onError": "continueErrorOutput",
"position": [
-240,
20
],
"parameters": {
"messages": {
"messageValues": [
{
"message": "=Please analyse the incoming user request. Extract information according to the JSON schema. Today is: \"{{ $now.toISO() }}\""
}
]
},
"hasOutputParser": true
},
"typeVersion": 1.5
},
{
"id": "8f4d1b4b-58c0-41ec-9636-ac555e440821",
"name": "On Error",
"type": "n8n-nodes-base.noOp",
"position": [
200,
140
],
"parameters": [],
"typeVersion": 1
},
{
"id": "f4d77736-4470-48b4-8f61-149e09b70e3e",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
-160
],
"parameters": {
"color": 2,
"width": 960,
"height": 500,
"content": "## Update data source\nWhen you change the data source, remember to update the `Prompt Source (User Message)` setting in the **Basic LLM Chain node**."
},
"typeVersion": 1
},
{
"id": "5fd273c8-e61d-452b-8eac-8ac4b7fff6c2",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
340
],
"parameters": {
"color": 2,
"width": 440,
"height": 220,
"content": "## Configure local LLM\nOllama offers additional settings \nto optimize model performance\nor memory usage."
},
"typeVersion": 1
},
{
"id": "63cbf762-0134-48da-a6cd-0363e870decd",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
340
],
"parameters": {
"color": 2,
"width": 400,
"height": 220,
"content": "## Define JSON Schema"
},
"typeVersion": 1
},
{
"id": "9625294f-3cb4-4465-9dae-9976e0cf5053",
"name": "Extract JSON Output",
"type": "n8n-nodes-base.set",
"position": [
200,
-80
],
"parameters": {
"mode": "raw",
"options": [],
"jsonOutput": "={{ $json.output }}\n"
},
"typeVersion": 3.4
},
{
"id": "2c6fba3b-0ffe-4112-b904-823f52cc220b",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
200
],
"parameters": {
"width": 960,
"height": 120,
"content": "If the LLM response does not pass \nthe **Structured Output Parser** checks,\n**Auto-Fixer** will call the model again with a different \nprompt to correct the original response."
},
"typeVersion": 1
},
{
"id": "c73ba1ca-d727-4904-a5fd-01dd921a4738",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
460
],
"parameters": {
"height": 80,
"content": "The same LLM connects to both **Basic LLM Chain** and to the **Auto-fixing Output Parser**. \n"
},
"typeVersion": 1
},
{
"id": "193dd153-8511-4326-aaae-47b89d0cd049",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
200,
440
],
"parameters": {
"width": 200,
"height": 100,
"content": "When the LLM model responds, the output is checked in the **Structured Output Parser**"
},
"typeVersion": 1
}
],
"active": false,
"pinData": [],
"settings": {
"executionOrder": "v1"
},
"versionId": "9f3721a8-f340-43d5-89e7-3175c29c2f3a",
"connections": {
"Basic LLM Chain": {
"main": [
[
{
"node": "Extract JSON Output",
"type": "main",
"index": 0
}
],
[
{
"node": "On Error",
"type": "main",
"index": 0
}
]
]
},
"Ollama Chat Model": {
"ai_languageModel": [
[
{
"node": "Auto-fixing Output Parser",
"type": "ai_languageModel",
"index": 0
},
{
"node": "Basic LLM Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Auto-fixing Output Parser",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Auto-fixing Output Parser": {
"ai_outputParser": [
[
{
"node": "Basic LLM Chain",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Basic LLM Chain",
"type": "main",
"index": 0
}
]
]
}
}
}How to Use an n8n Template
1
Create a New Workflow
Click "New Workflow" in your n8n dashboard to get started.
2
Copy & Paste Template
First, copy this template:
Click here to copy the JSON
.
Then, in n8n, click the three dots (···) → "Import from file" and paste the JSON code.
3
Customize the Nodes
Go through each node in the workflow to update inputs like spreadsheet IDs, email addresses, or message content. Adjust field mappings to match your data.
4
Grant Access
For nodes that connect to external apps (like Google Sheets or Slack), you'll need to grant access. Connect your accounts using OAuth or an API key and save the credentials in the node.
5
Test It
Run the workflow by clicking "Execute Node" for each step or "Run Once" for the whole thing. Check the right sidebar to inspect data and debug any errors (they'll show up in red).
6
Activate Workflow
Once everything works as expected, click the "Activate" toggle to turn your workflow on. You're all set!