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LLM Observability with Self-Hosted Langfuse and vLLM - PyImageSearch

PyImageSearch·Vikram Singh·3 days ago
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Table of Contents LLM Observability with Self-Hosted Langfuse and vLLM Introduction to LLM Observability with Langfuse How Langfuse Fits into an LLM Observability Stack Langfuse Architecture for LLM Observability Why Understanding LLM Observability Architecture Matters Setting Up a Self-Hosted Langfuse and vLLM Stack Baseline LLM Application (Before Observability) Adding LLM Observability with the Langfuse @observe Decorator Running and Verifying a Self-Hosted Langfuse Observability Stack Summary In this lesson, you will finally demystify what Large Language Model (LLM) observability actually is. It is not just logs or print statements. It is a full, end-to-end view of how your AI system behaves in real-world conditions. You will learn why modern LLM apps need more than “it works on my machine,” and how traces, token usage, latency, and model interactions become powerful tools for debugging and optimization.…

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