How to implement LLM guardrails for RAG applications

Learn how to use the contextual grounding checks that come with the guardrails functionality in watsonx Flows Engine. With watsonx Flows Engine, you can build AI applications for several use cases, including retrieval augmented generation (RAG) applications. These checks are designed to detect hallucinations in responses, especially in RAG applications, where the model pulls data from various sources to craft its answers. Guardrails can help you identify responses that are factually incorrect or irrelevant to a user’s query, helping to maintain the reliability of AI-driven applications.

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https://developer.ibm.com/tutorials/a...

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