Log Levels

from langfuse import observe, get_client   @observe() def my_function():  langfuse = get_client()    # ... processing logic ...  # Update the current span with a warning level  langfuse.update_current_span(  level="WARNING",  status_message="This is a warning"  )

from langfuse import get_client   langfuse = get_client()   # Using context managers (recommended) with langfuse.start_as_current_span(name="my-operation") as span:  # Set level and status message on creation  with span.start_as_current_span(  name="potentially-risky-operation",  level="WARNING",  status_message="Operation may fail"  ) as risky_span:  # ... do work ...    # Or update level and status message later  risky_span.update(  level="ERROR",  status_message="Operation failed with unexpected input"  )   # You can also update the currently active span without a direct reference with langfuse.start_as_current_span(name="another-operation"):  # ... some processing ...  langfuse.update_current_span(  level="DEBUG",  status_message="Processing intermediate results"  )

langfuse = get_client()   with langfuse.start_as_current_generation(  name="llm-call",  model="gpt-4o",  level="DEFAULT" # Default level ) as generation:  # ... make LLM call ...    if error_detected:  generation.update(  level="ERROR",  status_message="Model returned malformed output"  )

import { startActiveObservation, startObservation } from "@langfuse/tracing";   await startActiveObservation("context-manager", async (span) => {  span.update({  input: { query: "What is the capital of France?" },  });    updateActiveObservation({  level: "WARNING",  statusMessage: "This is a warning",  }); });

import { observe, updateActiveObservation } from "@langfuse/tracing";   // An existing function async function fetchData(source: string) {  updateActiveObservation({  level: "WARNING",  statusMessage: "This is a warning",  });    // ... logic to fetch data  return { data: `some data from ${source}` }; }   // Wrap the function to trace it const tracedFetchData = observe(fetchData, {  name: "observe-wrapper", });   const result = await tracedFetchData("API");

import { startObservation } from "@langfuse/tracing";   const span = startObservation("manual-observation", {  input: { query: "What is the capital of France?" }, });   span.update({  level: "WARNING",  statusMessage: "This is a warning", });   span.update({ output: "Paris" }).end();