Extract personal data with self-hosted LLM Mistral NeMo

This workflow shows how to use a self-hosted Large Language Model (LLM) with n8n's LangChain integration to extract personal information from user input. This is particularly useful for enterprise environments where data privacy is crucial, as it allows sensitive information to be processed locally. 📖 For a detailed explanation and more insights on using open-source LLMs with n8n, take a look at our comprehensive guide on open-source LLMs. 🔑 Key Features Local LLM Connect Ollama to run Mistral NeMo LLM locally Provide a foundation for compliant data processing, keeping sensitive information on-premises Data extraction Convert unstructured text to a consistent JSON format Adjust the JSON sc

Help me set up the n8n workflow "Extract personal data with self-hosted LLM Mistral NeMo" (https://n8n.io/workflows/2766). It uses: Basic LLM Chain, Ollama Chat Model, Auto-fixing Output Parser, Structured Output Parser. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.