This tutorial demonstrates how to build an end-to-end observability and evaluation pipeline using Langfuse, an open-source platform for LLM engineering. It covers tracing function calls, managing prompts, attaching evaluation scores, and running dataset experiments. The process can be configured to use either a real OpenAI API key or a deterministic mock LLM, allowing users to explore Langfuse features without incurring costs for paid model access. AI
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IMPACT Provides a practical guide for developers to enhance LLM application development and deployment.
RANK_REASON Tutorial on using an open-source LLM engineering platform.
