In this summary, we explore how IBM Granite and Ollama can be integrated with HCP Vault to handle sensitive data effectively. The method involves configuring vaults to mask or tokenize data before passing it to the LLMs, ensuring that personal identifiable information (PII) is protected. By Rosemary Wang.
The article covers how to:
- Configure Vault transform secrets engine
- Apply masking or tokenization to sensitive information
- Configure a local LLM model
- Add documents to a knowledge base for RAG
- Test the knowledge base
The rise in use of large language models (LLMs) for various tasks has brought up significant concerns regarding data privacy, especially concerning sensitive information like personal identifiable information (PII). This article explores a solution to mitigate these risks by integrating IBM Granite and Ollama with HCP Vault to anonymize RAG data effectively. Nice one!
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