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fix(anthropic): Close span on GeneratorExit #5643

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fix(anthropic): Close span on GeneratorExit #5643

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9eff33e
fix(anthropic): Close span on GeneratorExit
alexander-alderman-webb Mar 12, 2026
5e3cb5f
revert conftest
alexander-alderman-webb Mar 12, 2026
804db65
Merge branch 'webb/anthropic/only-raw-message-stream-events' into web…
alexander-alderman-webb Mar 12, 2026
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170 changes: 86 additions & 84 deletions sentry_sdk/integrations/anthropic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -364,52 +364,53 @@ def _wrap_synchronous_message_iterator(
usage = _RecordedUsage()
content_blocks: "list[str]" = []

for event in iterator:
if not isinstance(
event,
try:
for event in iterator:
if not isinstance(
event,
(
MessageStartEvent,
MessageDeltaEvent,
MessageStopEvent,
ContentBlockStartEvent,
ContentBlockDeltaEvent,
ContentBlockStopEvent,
),
):
yield event
continue

(
MessageStartEvent,
MessageDeltaEvent,
MessageStopEvent,
ContentBlockStartEvent,
ContentBlockDeltaEvent,
ContentBlockStopEvent,
),
):
model,
usage,
content_blocks,
) = _collect_ai_data(
event,
model,
usage,
content_blocks,
)
yield event
continue

(
model,
usage,
content_blocks,
) = _collect_ai_data(
event,
model,
usage,
content_blocks,
finally:
# Anthropic's input_tokens excludes cached/cache_write tokens.
# Normalize to total input tokens for correct cost calculations.
total_input = (
usage.input_tokens
+ (usage.cache_read_input_tokens or 0)
+ (usage.cache_write_input_tokens or 0)
)
yield event

# Anthropic's input_tokens excludes cached/cache_write tokens.
# Normalize to total input tokens for correct cost calculations.
total_input = (
usage.input_tokens
+ (usage.cache_read_input_tokens or 0)
+ (usage.cache_write_input_tokens or 0)
)

_set_output_data(
span=span,
integration=integration,
model=model,
input_tokens=total_input,
output_tokens=usage.output_tokens,
cache_read_input_tokens=usage.cache_read_input_tokens,
cache_write_input_tokens=usage.cache_write_input_tokens,
content_blocks=[{"text": "".join(content_blocks), "type": "text"}],
finish_span=True,
)
_set_output_data(
span=span,
integration=integration,
model=model,
input_tokens=total_input,
output_tokens=usage.output_tokens,
cache_read_input_tokens=usage.cache_read_input_tokens,
cache_write_input_tokens=usage.cache_write_input_tokens,
content_blocks=[{"text": "".join(content_blocks), "type": "text"}],
finish_span=True,
)


async def _wrap_asynchronous_message_iterator(
Expand All @@ -425,52 +426,53 @@ async def _wrap_asynchronous_message_iterator(
usage = _RecordedUsage()
content_blocks: "list[str]" = []

async for event in iterator:
if not isinstance(
event,
try:
async for event in iterator:
if not isinstance(
event,
(
MessageStartEvent,
MessageDeltaEvent,
MessageStopEvent,
ContentBlockStartEvent,
ContentBlockDeltaEvent,
ContentBlockStopEvent,
),
):
yield event
continue

(
MessageStartEvent,
MessageDeltaEvent,
MessageStopEvent,
ContentBlockStartEvent,
ContentBlockDeltaEvent,
ContentBlockStopEvent,
),
):
model,
usage,
content_blocks,
) = _collect_ai_data(
event,
model,
usage,
content_blocks,
)
yield event
continue

(
model,
usage,
content_blocks,
) = _collect_ai_data(
event,
model,
usage,
content_blocks,
finally:
# Anthropic's input_tokens excludes cached/cache_write tokens.
# Normalize to total input tokens for correct cost calculations.
total_input = (
usage.input_tokens
+ (usage.cache_read_input_tokens or 0)
+ (usage.cache_write_input_tokens or 0)
)
yield event

# Anthropic's input_tokens excludes cached/cache_write tokens.
# Normalize to total input tokens for correct cost calculations.
total_input = (
usage.input_tokens
+ (usage.cache_read_input_tokens or 0)
+ (usage.cache_write_input_tokens or 0)
)

_set_output_data(
span=span,
integration=integration,
model=model,
input_tokens=total_input,
output_tokens=usage.output_tokens,
cache_read_input_tokens=usage.cache_read_input_tokens,
cache_write_input_tokens=usage.cache_write_input_tokens,
content_blocks=[{"text": "".join(content_blocks), "type": "text"}],
finish_span=True,
)
_set_output_data(
span=span,
integration=integration,
model=model,
input_tokens=total_input,
output_tokens=usage.output_tokens,
cache_read_input_tokens=usage.cache_read_input_tokens,
cache_write_input_tokens=usage.cache_write_input_tokens,
content_blocks=[{"text": "".join(content_blocks), "type": "text"}],
finish_span=True,
)


def _set_output_data(
Expand Down
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