feat(langgraph): Usage attributes on invocation spans

[alexander-alderman-webb]

Description

Add prompt, response, and total token counts to LangGraph invocation spans.

Issues

Contributes to #5170

Reminders

• Please add tests to validate your changes, and lint your code using tox -e linters.
• Add GH Issue ID & Linear ID (if applicable)
• PR title should use conventional commit style (feat:, fix:, ref:, meta:)
• For external contributors: CONTRIBUTING.md, Sentry SDK development docs, Discord community

[codecov]

Codecov Report

❌ Patch coverage is 92.30769% with 2 lines in your changes missing coverage. Please review.
✅ Project coverage is 84.22%. Comparing base (1b7085d) to head (4f3fab3).
⚠️ Report is 6 commits behind head on master.
✅ All tests successful. No failed tests found.

Files with missing lines	Patch %	Lines
sentry_sdk/integrations/langgraph.py	92.30%	1 Missing and 1 partial ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #5211      +/-   ##
==========================================
+ Coverage   84.17%   84.22%   +0.04%     
==========================================
  Files         181      181              
  Lines       18443    18486      +43     
  Branches     3283     3295      +12     
==========================================
+ Hits        15524    15569      +45     
+ Misses       1904     1899       -5     
- Partials     1015     1018       +3     

Files with missing lines	Coverage Δ
sentry_sdk/integrations/langgraph.py	76.27% <92.30%> (-0.81%)	⬇️

... and 5 files with indirect coverage changes

[cursor]

Bug: Usage data miscounted when PII collection disabled

When should_send_default_pii() is false or include_prompts is false, input_messages remains None. This causes _get_new_messages in _set_response_attributes to return all output messages instead of just the new ones. Since LangGraph state accumulates messages, usage data will include tokens from all messages in the response rather than only the new messages added during this invocation. The input messages need to be parsed unconditionally (at least for _get_new_messages) to correctly calculate usage data regardless of PII settings.

sentry_sdk/integrations/langgraph.py#L184-L204

sentry-python/sentry_sdk/integrations/langgraph.py

Lines 184 to 204 in 4f3fab3

	# Store input messages to later compare with output
	input_messages = None
	if (
	len(args) > 0
	and should_send_default_pii()
	and integration.include_prompts
	):
	input_messages = _parse_langgraph_messages(args[0])
	if input_messages:
	normalized_input_messages = normalize_message_roles(input_messages)
	scope = sentry_sdk.get_current_scope()
	messages_data = truncate_and_annotate_messages(
	normalized_input_messages, span, scope
	)
	if messages_data is not None:
	set_data_normalized(
	span,
	SPANDATA.GEN_AI_REQUEST_MESSAGES,
	messages_data,
	unpack=False,
	)

sentry_sdk/integrations/langgraph.py#L240-L260

sentry-python/sentry_sdk/integrations/langgraph.py

Lines 240 to 260 in 4f3fab3

	input_messages = None
	if (
	len(args) > 0
	and should_send_default_pii()
	and integration.include_prompts
	):
	input_messages = _parse_langgraph_messages(args[0])
	if input_messages:
	normalized_input_messages = normalize_message_roles(input_messages)
	scope = sentry_sdk.get_current_scope()
	messages_data = truncate_and_annotate_messages(
	normalized_input_messages, span, scope
	)
	if messages_data is not None:
	set_data_normalized(
	span,
	SPANDATA.GEN_AI_REQUEST_MESSAGES,
	messages_data,
	unpack=False,
	)

 

---

Bug: Usage data miscounted when PII collection disabled

When should_send_default_pii() is false or include_prompts is false, input_messages remains None. This causes _get_new_messages in _set_response_attributes to return all output messages instead of just the new ones. Since LangGraph state accumulates messages, usage data will include tokens from all messages in the response rather than only the new messages added during this invocation. The input messages need to be parsed unconditionally (at least for _get_new_messages) to correctly calculate usage data regardless of PII settings.

sentry_sdk/integrations/langgraph.py#L184-L204

sentry-python/sentry_sdk/integrations/langgraph.py

Lines 184 to 204 in 4f3fab3

	# Store input messages to later compare with output
	input_messages = None
	if (
	len(args) > 0
	and should_send_default_pii()
	and integration.include_prompts
	):
	input_messages = _parse_langgraph_messages(args[0])
	if input_messages:
	normalized_input_messages = normalize_message_roles(input_messages)
	scope = sentry_sdk.get_current_scope()
	messages_data = truncate_and_annotate_messages(
	normalized_input_messages, span, scope
	)
	if messages_data is not None:
	set_data_normalized(
	span,
	SPANDATA.GEN_AI_REQUEST_MESSAGES,
	messages_data,
	unpack=False,
	)

sentry_sdk/integrations/langgraph.py#L240-L260

sentry-python/sentry_sdk/integrations/langgraph.py

Lines 240 to 260 in 4f3fab3

	input_messages = None
	if (
	len(args) > 0
	and should_send_default_pii()
	and integration.include_prompts
	):
	input_messages = _parse_langgraph_messages(args[0])
	if input_messages:
	normalized_input_messages = normalize_message_roles(input_messages)
	scope = sentry_sdk.get_current_scope()
	messages_data = truncate_and_annotate_messages(
	normalized_input_messages, span, scope
	)
	if messages_data is not None:
	set_data_normalized(
	span,
	SPANDATA.GEN_AI_REQUEST_MESSAGES,
	messages_data,
	unpack=False,
	)

 

---

[alexander-alderman-webb]

This is okay, input messages do not have token info attached to them.

usage data will include tokens from all messages in the response rather than only the new messages added during this invocation.