isaaccs•10mo ago

python sdk: observations n same trace

Hey, I try to have one trace for all my endpoints without succeed example of my code

def call_llm(trace: StatefulTraceClient = None):
    span = trace.span(
        CreateSpan(
            name="name",
            input={some_values},
        )
    ) if trace else None
    handler = span.get_langchain_handler() if span else create_langfuse_callback()

    ## llm call
    output = await model.apredict(prompt, callbacks=[handler] if handler else None)
    if span:
        span.update(
            UpdateSpan(
                output={
                    "response": output
                }
            )
        )

def endpoint_1():
    langfuse = Langfuse(langfuse_key, langfuse_secret, langfuse_url, release=os.getenv("DD_VERSION", "local"))
    # create trace_id for future reference
    span = tracer.current_root_span()
    trace_id = span.trace_id if span else None
    # create the Trace
    trace = langfuse.trace(CreateTrace(trace_id=trace_id))


    call_llm = await llm_call(
        trace=trace
    )

def call_llm(trace: StatefulTraceClient = None):
    span = trace.span(
        CreateSpan(
            name="name",
            input={some_values},
        )
    ) if trace else None
    handler = span.get_langchain_handler() if span else create_langfuse_callback()

    ## llm call
    output = await model.apredict(prompt, callbacks=[handler] if handler else None)
    if span:
        span.update(
            UpdateSpan(
                output={
                    "response": output
                }
            )
        )

def endpoint_1():
    langfuse = Langfuse(langfuse_key, langfuse_secret, langfuse_url, release=os.getenv("DD_VERSION", "local"))
    # create trace_id for future reference
    span = tracer.current_root_span()
    trace_id = span.trace_id if span else None
    # create the Trace
    trace = langfuse.trace(CreateTrace(trace_id=trace_id))


    call_llm = await llm_call(
        trace=trace
    )

9 Replies

Marc•10mo ago

Hi @isaaccs, is this stable across all of your endpoints? span = tracer.current_root_span()

isaaccs•10mo ago

yes i also try with harcoded trace_id

Marc•10mo ago

found it, try langfuse.trace(CreateTrace(id=trace_id)), trace_id does not exist on the Pydantic object

Marc•10mo ago

See all parameters here: https://langfuse.com/docs/sdk/python#traces-1

Python SDK - Langfuse

Fully async and typed Python SDK. Uses Pydantic objects for data verification.

isaaccs•10mo ago

oh yes thank you

Marc•10mo ago

🤗 Happy that it works for you @Max currently improving the python interfces, with v2 this will be much simpler (without having to change much though)

isaaccs•10mo ago

perfect

isaaccs•10mo ago

last question let suppose my code is like that

def endpoint_1():
    langfuse = Langfuse(langfuse_key, langfuse_secret, langfuse_url, release=os.getenv("DD_VERSION", "local"))
    # create trace_id for future reference
    span = tracer.current_root_span()
    trace_id = span.trace_id if span else None
    # create the Trace
    trace = langfuse.trace(CreateTrace(id=trace_id))


    call_llm = await llm_call(
        trace=trace
    )
    call_llm = await llm_call(
        trace=trace
    )
    call_llm = await llm_call(
        trace=trace
    )

def endpoint_1():
    langfuse = Langfuse(langfuse_key, langfuse_secret, langfuse_url, release=os.getenv("DD_VERSION", "local"))
    # create trace_id for future reference
    span = tracer.current_root_span()
    trace_id = span.trace_id if span else None
    # create the Trace
    trace = langfuse.trace(CreateTrace(id=trace_id))


    call_llm = await llm_call(
        trace=trace
    )
    call_llm = await llm_call(
        trace=trace
    )
    call_llm = await llm_call(
        trace=trace
    )

how can i get something like this

Marc•10mo ago

depends, you can either use the sdk clients, each call returns the object which can create child objects

trace = langfuse.trace()
span = trace.span()
generation = span.generation()

trace = langfuse.trace()
span = trace.span()
generation = span.generation()

alternatively, you can nest with ids youself

trace_id = "no1"
span_id = "no2"
langfuse.trace(CreateTrace(id=trace_id))
langfuse.span(InitialSpan(trace_id=trace_id, id=span_id))

nested_generation = langfuse.generation(InitialGeneration(trace_id=trace_id, parent_observation_id=span_id))

trace_id = "no1"
span_id = "no2"
langfuse.trace(CreateTrace(id=trace_id))
langfuse.span(InitialSpan(trace_id=trace_id, id=span_id))

nested_generation = langfuse.generation(InitialGeneration(trace_id=trace_id, parent_observation_id=span_id))

instead of creating your own ids, you can also let the sdk generate ids

span = langfuse.span(InitialSpan(trace_id=trace_id))
nested_generation = langfuse.generation(InitialGeneration(trace_id=trace_id, id=span_id, parent_observation_id=span.id))

span = langfuse.span(InitialSpan(trace_id=trace_id))
nested_generation = langfuse.generation(InitialGeneration(trace_id=trace_id, id=span_id, parent_observation_id=span.id))

hope this helps