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[Misc] Remove experimental dep from tracing.py (#12007)

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Signed-off-by: Adrian Cole <adrian.cole@elastic.co>
This commit is contained in:
Adrian Cole
2025-01-21 11:51:55 -08:00
committed by GitHub
parent 18fd4a8331
commit 347eeebe3b
3 changed files with 66 additions and 60 deletions
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60
tests/tracing/test_tracing.py
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@@ -100,32 +100,32 @@ def test_traces(trace_service):
attributes = decode_attributes(
request.resource_spans[0].scope_spans[0].spans[0].attributes)
assert attributes.get(SpanAttributes.LLM_RESPONSE_MODEL) == model
assert attributes.get(SpanAttributes.GEN_AI_RESPONSE_MODEL) == model
assert attributes.get(
SpanAttributes.LLM_REQUEST_ID) == outputs[0].request_id
SpanAttributes.GEN_AI_REQUEST_ID) == outputs[0].request_id
assert attributes.get(SpanAttributes.GEN_AI_REQUEST_TEMPERATURE
) == sampling_params.temperature
assert attributes.get(
SpanAttributes.LLM_REQUEST_TEMPERATURE) == sampling_params.temperature
SpanAttributes.GEN_AI_REQUEST_TOP_P) == sampling_params.top_p
assert attributes.get(
SpanAttributes.LLM_REQUEST_TOP_P) == sampling_params.top_p
assert attributes.get(
SpanAttributes.LLM_REQUEST_MAX_TOKENS) == sampling_params.max_tokens
assert attributes.get(SpanAttributes.LLM_REQUEST_N) == sampling_params.n
assert attributes.get(SpanAttributes.LLM_USAGE_PROMPT_TOKENS) == len(
SpanAttributes.GEN_AI_REQUEST_MAX_TOKENS) == sampling_params.max_tokens
assert attributes.get(SpanAttributes.GEN_AI_REQUEST_N) == sampling_params.n
assert attributes.get(SpanAttributes.GEN_AI_USAGE_PROMPT_TOKENS) == len(
outputs[0].prompt_token_ids)
completion_tokens = sum(len(o.token_ids) for o in outputs[0].outputs)
assert attributes.get(
SpanAttributes.LLM_USAGE_COMPLETION_TOKENS) == completion_tokens
SpanAttributes.GEN_AI_USAGE_COMPLETION_TOKENS) == completion_tokens
metrics = outputs[0].metrics
assert attributes.get(
SpanAttributes.LLM_LATENCY_TIME_IN_QUEUE) == metrics.time_in_queue
SpanAttributes.GEN_AI_LATENCY_TIME_IN_QUEUE) == metrics.time_in_queue
ttft = metrics.first_token_time - metrics.arrival_time
assert attributes.get(
SpanAttributes.LLM_LATENCY_TIME_TO_FIRST_TOKEN) == ttft
SpanAttributes.GEN_AI_LATENCY_TIME_TO_FIRST_TOKEN) == ttft
e2e_time = metrics.finished_time - metrics.arrival_time
assert attributes.get(SpanAttributes.LLM_LATENCY_E2E) == e2e_time
assert attributes.get(SpanAttributes.GEN_AI_LATENCY_E2E) == e2e_time
assert metrics.scheduler_time > 0
assert attributes.get(
SpanAttributes.LLM_LATENCY_TIME_IN_SCHEDULER) == metrics.scheduler_time
assert attributes.get(SpanAttributes.GEN_AI_LATENCY_TIME_IN_SCHEDULER
) == metrics.scheduler_time
# Model forward and model execute should be none, since detailed traces is
# not enabled.
assert metrics.model_forward_time is None
@@ -166,37 +166,37 @@ def test_traces_with_detailed_steps(trace_service):
attributes = decode_attributes(
request.resource_spans[0].scope_spans[0].spans[0].attributes)
assert attributes.get(SpanAttributes.LLM_RESPONSE_MODEL) == model
assert attributes.get(SpanAttributes.GEN_AI_RESPONSE_MODEL) == model
assert attributes.get(
SpanAttributes.LLM_REQUEST_ID) == outputs[0].request_id
SpanAttributes.GEN_AI_REQUEST_ID) == outputs[0].request_id
assert attributes.get(SpanAttributes.GEN_AI_REQUEST_TEMPERATURE
) == sampling_params.temperature
assert attributes.get(
SpanAttributes.LLM_REQUEST_TEMPERATURE) == sampling_params.temperature
SpanAttributes.GEN_AI_REQUEST_TOP_P) == sampling_params.top_p
assert attributes.get(
SpanAttributes.LLM_REQUEST_TOP_P) == sampling_params.top_p
assert attributes.get(
SpanAttributes.LLM_REQUEST_MAX_TOKENS) == sampling_params.max_tokens
assert attributes.get(SpanAttributes.LLM_REQUEST_N) == sampling_params.n
assert attributes.get(SpanAttributes.LLM_USAGE_PROMPT_TOKENS) == len(
SpanAttributes.GEN_AI_REQUEST_MAX_TOKENS) == sampling_params.max_tokens
assert attributes.get(SpanAttributes.GEN_AI_REQUEST_N) == sampling_params.n
assert attributes.get(SpanAttributes.GEN_AI_USAGE_PROMPT_TOKENS) == len(
outputs[0].prompt_token_ids)
completion_tokens = sum(len(o.token_ids) for o in outputs[0].outputs)
assert attributes.get(
SpanAttributes.LLM_USAGE_COMPLETION_TOKENS) == completion_tokens
SpanAttributes.GEN_AI_USAGE_COMPLETION_TOKENS) == completion_tokens
metrics = outputs[0].metrics
assert attributes.get(
SpanAttributes.LLM_LATENCY_TIME_IN_QUEUE) == metrics.time_in_queue
SpanAttributes.GEN_AI_LATENCY_TIME_IN_QUEUE) == metrics.time_in_queue
ttft = metrics.first_token_time - metrics.arrival_time
assert attributes.get(
SpanAttributes.LLM_LATENCY_TIME_TO_FIRST_TOKEN) == ttft
SpanAttributes.GEN_AI_LATENCY_TIME_TO_FIRST_TOKEN) == ttft
e2e_time = metrics.finished_time - metrics.arrival_time
assert attributes.get(SpanAttributes.LLM_LATENCY_E2E) == e2e_time
assert attributes.get(SpanAttributes.GEN_AI_LATENCY_E2E) == e2e_time
assert metrics.scheduler_time > 0
assert attributes.get(
SpanAttributes.LLM_LATENCY_TIME_IN_SCHEDULER) == metrics.scheduler_time
assert attributes.get(SpanAttributes.GEN_AI_LATENCY_TIME_IN_SCHEDULER
) == metrics.scheduler_time
assert metrics.model_forward_time > 0
assert attributes.get(
SpanAttributes.LLM_LATENCY_TIME_IN_MODEL_FORWARD) == pytest.approx(
SpanAttributes.GEN_AI_LATENCY_TIME_IN_MODEL_FORWARD) == pytest.approx(
metrics.model_forward_time / 1000)
assert metrics.model_execute_time > 0
assert attributes.get(SpanAttributes.LLM_LATENCY_TIME_IN_MODEL_EXECUTE
assert attributes.get(SpanAttributes.GEN_AI_LATENCY_TIME_IN_MODEL_EXECUTE
) == metrics.model_execute_time
assert metrics.model_forward_time < 1000 * metrics.model_execute_time