Evaluate RAG Response Groundedness with OpenAI

This workflow automates the evaluation of Retrieval-Augmented Generation (RAG) response accuracy by computing the 'document groundedness' metric. It uses an OpenAI LLM to analyze whether the generated response contains information exclusively from provided retrieved documents, flagging potential hallucinations or deviations. Adapted from Google Vertex AI's pointwise groundedness template, it processes inputs like user questions, agent responses, and context documents to output a precise score.