If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. https://t.co/lmcVmii1EUAvi Chawla (@_avichawla):A Python decorator is all you need to trace LLM apps (open-source).Most LLM evals treat the app like an end-to-end black box.But LLM apps need component-level evals and tracing since the issue can be anywhere inside the box, like the retriever, tool call, or the LLM itself. https://t.co/UUZDbAvUe0 ...

A Python decorator is all you need to trace LLM apps (open-source).Most LLM evals treat the app like an end-to-end black box.But LLM apps need component-level evals and tracing since the issue can be anywhere inside the box, like the retriever, tool call, or the LLM itself.In DeepEval, you can do that with just 3 lines of code:- Trace individual LLM components (tools, retrievers, generators) with the "@ observe" decorator.- Attach different metrics to each part.- Get a visual breakdown of what’s working and ...