Effortless Personal Data Extraction with Self-Hosted Mistral NeMo LLM

This workflow leverages the power of a self-hosted Mistral NeMo Large Language Model, integrated through Ollama, to intelligently extract specific personal data from incoming chat messages. Designed for robust data handling, it employs Langchain nodes to create a seamless pipeline. The process begins by triggering on a chat message, which is then fed into a basic LLM chain. To ensure accuracy and adherence to a defined structure, the output is processed through a structured output parser with a custom JSON schema. For any parsing errors, an auto-fixing output parser is employed to re-evaluate and correct the response, guaranteeing reliable and structured data extraction, all while keeping your sensitive information within your own infrastructure.