update_current_span

opik.opik_context.update_current_span(name: str | None = None, input: Dict[str, Any] | None = None, output: Dict[str, Any] | None = None, metadata: Dict[str, Any] | None = None, tags: List[str] | None = None, usage: Dict[str, Any] | OpikUsage | None = None, feedback_scores: List[FeedbackScoreDict] | None = None, model: str | None = None, provider: LLMProvider | str | None = None, total_cost: float | None = None) → None

Update the current span with the provided parameters. This method is usually called within a tracked function.

Parameters:

  • name – The name of the span.

  • input – The input data of the span.

  • output – The output data of the span.

  • metadata – The metadata of the span.

  • tags – The tags of the span.

  • usage – Usage data for the span. In order for input, output and total tokens to be visible in the UI, the usage must contain OpenAI-formatted keys (they can be passed additionaly to original usage on the top level of the dict): prompt_tokens, completion_tokens and total_tokens. If OpenAI-formatted keys were not found, Opik will try to calculate them automatically if the usage format is recognized (you can see which provider’s formats are recognized in opik.LLMProvider enum), but it is not guaranteed.

  • feedback_scores – The feedback scores of the span.

  • model – The name of LLM (in this case type parameter should be == llm)

  • provider – The provider of LLM. You can find providers officially supported by Opik for cost tracking in opik.LLMProvider enum. If your provider is not here, please open an issue in our github - https://github.com/comet-ml/opik. If your provider not in the list, you can still specify it but the cost tracking will not be available

  • total_cost – The cost of the span in USD. This value takes priority over the cost calculated by Opik from the usage.