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Expose LLM usage in workflows (#21766)

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Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>
This commit is contained in:
Davide Delbianco
2025-07-08 15:18:00 +02:00
committed by GitHub
parent f925869f61
commit 816210d744
32 changed files with 201 additions and 81 deletions
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26
api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py
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@@ -213,11 +213,12 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
if model:
node_metadata["ls_model_name"] = model
usage = json.loads(node_execution.outputs).get("usage", {}) if node_execution.outputs else {}
if usage:
node_metadata["total_tokens"] = usage.get("total_tokens", 0)
node_metadata["prompt_tokens"] = usage.get("prompt_tokens", 0)
node_metadata["completion_tokens"] = usage.get("completion_tokens", 0)
outputs = json.loads(node_execution.outputs).get("usage", {})
usage_data = process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {})
if usage_data:
node_metadata["total_tokens"] = usage_data.get("total_tokens", 0)
node_metadata["prompt_tokens"] = usage_data.get("prompt_tokens", 0)
node_metadata["completion_tokens"] = usage_data.get("completion_tokens", 0)
elif node_execution.node_type == "dataset_retrieval":
span_kind = OpenInferenceSpanKindValues.RETRIEVER.value
elif node_execution.node_type == "tool":
@@ -246,14 +247,19 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
if model:
node_span.set_attribute(SpanAttributes.LLM_MODEL_NAME, model)
usage = json.loads(node_execution.outputs).get("usage", {}) if node_execution.outputs else {}
if usage:
node_span.set_attribute(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, usage.get("total_tokens", 0))
outputs = json.loads(node_execution.outputs).get("usage", {})
usage_data = (
process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {})
)
if usage_data:
node_span.set_attribute(
SpanAttributes.LLM_TOKEN_COUNT_PROMPT, usage.get("prompt_tokens", 0)
SpanAttributes.LLM_TOKEN_COUNT_TOTAL, usage_data.get("total_tokens", 0)
)
node_span.set_attribute(
SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, usage.get("completion_tokens", 0)
SpanAttributes.LLM_TOKEN_COUNT_PROMPT, usage_data.get("prompt_tokens", 0)
)
node_span.set_attribute(
SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, usage_data.get("completion_tokens", 0)
)
finally:
node_span.end(end_time=datetime_to_nanos(finished_at))