Skip to content

ref(langgraph): Stop setting tokens on Invoke Agent spans #7514

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
alexander-alderman-webb merged 2 commits into from
Sep 15, 2026
Merged

ref(langgraph): Stop setting tokens on Invoke Agent spans #7514

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
43cd4aa
ref(langgraph): Stop setting tokens on Invoke Agent spans
alexander-alderman-webb Sep 15, 2026
97575d3
merge
alexander-alderman-webb Sep 15, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
35 changes: 1 addition & 34 deletions sentry_sdk/integrations/langgraph.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@
)

if TYPE_CHECKING:
from sentry_sdk.traces import Span
pass

try:
from langgraph.errors import GraphBubbleUp
Expand Down Expand Up @@ -268,37 +268,6 @@ def _extract_tool_calls(messages: "Optional[List[Any]]") -> "Optional[List[Any]]
return tool_calls if tool_calls else None


def _set_usage_data(span: "Span", messages: "Any") -> None:
input_tokens = 0
output_tokens = 0
total_tokens = 0

for message in messages:
response_metadata = message.get("response_metadata")
if response_metadata is None:
continue

token_usage = response_metadata.get("token_usage")
if not token_usage:
continue

input_tokens += int(token_usage.get("prompt_tokens", 0))
output_tokens += int(token_usage.get("completion_tokens", 0))
total_tokens += int(token_usage.get("total_tokens", 0))

if input_tokens > 0:
span.set_attribute(SPANDATA.GEN_AI_USAGE_INPUT_TOKENS, input_tokens)

if output_tokens > 0:
span.set_attribute(SPANDATA.GEN_AI_USAGE_OUTPUT_TOKENS, output_tokens)

if total_tokens > 0:
span.set_attribute(
SPANDATA.GEN_AI_USAGE_TOTAL_TOKENS,
total_tokens,
)


def _set_response_attributes(
span: "Any",
input_messages: "Optional[List[Any]]",
Expand All @@ -311,8 +280,6 @@ def _set_response_attributes(
if new_messages is None:
return

_set_usage_data(span, new_messages)

if _should_record_outputs(integration):
llm_response_text = _extract_llm_response_text(new_messages)
if llm_response_text:
Expand Down
Loading
Loading