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Extract personal data with a self-hosted LLM Mistral NeMo

13 nodes · chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm

Engine
n8n
Nodes
13
Trigger
scheduled/triggered
Source file
1442_Noop_Stickynote_Automation_Triggered.json

Workflow flow

IntegrationsChatLmChatOllamaOutputParserAutofixingOutputParserStructuredChainLlm@n8n/n8n-nodes-langchain.chat@n8n/n8n-nodes-langchain.lmChatOllama@n8n/n8n-nodes-langchain.outputParserAutofixing@n8n/n8n-nodes-langchain.outputParserStructured@n8n/n8n-nodes-langchain.chainLlmNoOpSet
100%
TRIGGER

When chat message received

@n8n/n8n-nodes-langchain.chat

Ollama Chat Model

@n8n/n8n-nodes-langchain.lmChatOllama

Auto-fixing Output Parser

@n8n/n8n-nodes-langchain.outputParserAutofixing

Structured Output Parser

@n8n/n8n-nodes-langchain.outputParserStructured

Basic LLM Chain

@n8n/n8n-nodes-langchain.chainLlm

On Error

NoOp

Extract JSON Output

Set

7 steps · flows top to bottom, branches left to right

Browse by integration

chatlmChatOllamaoutputParserAutofixingoutputParserStructuredchainLlm
Browse all integrations →
Download n8n JSONDownload sanitized JSONDownload flow graph

Import into n8n

  1. Download the n8n JSON file (full or sanitized).
  2. In n8n: Workflows → Import from file.
  3. Open each node and reconnect credentials to your accounts.
  4. Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Extract personal data with a self-hosted LLM Mistral NeMo (13-node n8n automation, chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm) is free on OpenRuna — view the graph and export the JSON to import into n8n.

What this workflow does

Built in n8n, "Extract personal data with a self-hosted LLM Mistral NeMo" chains 13 nodes to move data between chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm. 13 nodes · chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm It starts from a scheduled/triggered trigger and routes data through every node in order. OpenRuna renders the node graph and offers the JSON export so you can import and adapt it in minutes. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Study how data moves from chat to lmChatOllama before building your own variant.
  • Share it with your team as a documented reference for scheduled/triggered automations in the chat stack.
  • Import "Extract personal data with a self-hosted LLM Mistral NeMo" into n8n, reconnect credentials for chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm, and run the same automation in your own workspace.
  • Use it as a starting template when wiring chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm — adjust node parameters to your accounts and record IDs.

Example output

Imported into n8n, "Extract personal data with a self-hosted LLM Mistral NeMo" exposes 13 configured nodes. Trigger type: scheduled/triggered. Integrations: chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm. Reconnect the chat credential first, then walk the remaining nodes top to bottom. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Ask Claude to turn the "Extract personal data with a self-hosted LLM Mistral NeMo" JSON into a plain-English runbook, node by node. It can flag where chat rate limits or missing retries might bite before you go live.

ChatGPT

Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "Extract personal data with a self-hosted LLM Mistral NeMo" — extract chat IDs and secrets into environment variables without changing the 13-node structure.

Frequently asked questions

How do I import "Extract personal data with a self-hosted LLM Mistral NeMo" into n8n?
Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "Extract personal data with a self-hosted LLM Mistral NeMo" use?
It uses: chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm. The flow diagram above shows how each service connects across the 13 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?
Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own chat and lmChatOllama credentials in n8n after import.
What trigger type does "Extract personal data with a self-hosted LLM Mistral NeMo" use?
Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "Extract personal data with a self-hosted LLM Mistral NeMo" free to use?
OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for chat, lmChatOllama, outputParserAutofixing, outputParserStructured, chainLlm.

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