LLM Learning Hub

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Logging

Logging records request prompts, generated outputs, latency, errors, and model versions for debugging, auditing, safety review, and post-hoc analysis of LLM behaviour.

What is Logging?

Logging records request prompts, generated outputs, latency, errors, and model versions for debugging, auditing, safety review, and post-hoc analysis of LLM behaviour.

Logging records request prompts, generated outputs, latency, errors, and model versions for debugging, auditing, safety review, and post-hoc analysis of LLM behaviour.

Where is it used?

Langfuse, Helicone, and Phoenix log LLM I/O for production apps; vLLM and TGI expose structured logs; OpenAI Dashboard logs API calls for billing and abuse review.

How to build it

Integrate `langfuse` SDK by wrapping the OpenAI client with `langfuse.openai.OpenAI()`, and inspect traced prompts, responses, token counts, and latency in the Langfuse dashboard.