Extract personal data with a self-hosted LLM Mistral NeMo
Ready-to-use n8n workflow template for ai. This automation connects various tools with 13 nodes. Import directly into your n8n instance and customize for your needs.
Workflow JSON
{"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": "", "name": "[Your ollamaApi]"}}, "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 Import This Workflow
- 1Copy the workflow JSON above using the Copy Workflow JSON button.
- 2Open your n8n instance and go to Workflows.
- 3Click Import from JSON and paste the copied workflow.
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