Koodihommia

I've been working on an OTel sink recently. To be more specific, it concerns receiving telemetry data from LLM interactions. Fortunately, there is a spec for all of this called GenAI Semantic Conventions . That is what I based my work on, so I can make assumptions about key attributes to highlight in the sink's UI, which is actually a CLI in my case. I dogfooded my handrolled sink using Pydantic AI (my favorite LLM framework), and all good, it follows the spec well. Key attributes flow in as specified. Pydantic AI also includes some of its own attributes, but that is expected. However, pick something like Claude Code, (via anthropic agent sdk), the reality is a bit different. It does not follow the spec at all. It has its own custom attribute layout . Same direction, different flavor with LangChain. The Python source has zero opentelemetry imports anywhere. None. The ls_* namespace ( ls_provider , ls_model_name , ls_temperature ) is its own thing, with LangSmith as the on...