Last updated
Last updated
The blog post provides a practical guide for developers on implementing Arize Phoenix to enhance observability in Large Language Models (LLMs). It details steps such as installing necessary libraries, setting up tracing with Phoenix, and integrating it with LlamaIndex and OpenAI API for real-time monitoring and evaluation of LLM applications. Developers can learn how to effectively trace LLM operations, evaluate performance metrics, and visualize data to optimize model accuracy and efficiency. The tutorial offers hands-on instructions, making it valuable for those looking to improve LLM deployment and maintenance.