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A Coding Guide to Instrumenting, Tracing, and Evaluating LLM Applications Using TruLens and OpenAI Models

The tutorial demonstrates how to build a transparent evaluation pipeline for Retrieval‑Augmented Generation (RAG) applications using TruLens and OpenAI models. It walks through installing dependencies, chunking documents, creating a Chroma vector store with OpenAI embeddings, and instrumenting retrieval, generation, and query functions. Custom feedback functions measure groundedness, answer relevance, and context relevance, while versioned runs compare a base prompt against a strict‑citation prompt. Results are visualized via a leaderboard and interactive dashboard, showcasing disciplined experimentation and reproducibility.