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ref(anthropic): Revert input truncation #6113

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ref(anthropic): Revert input truncation #6113

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8ff1b2c
ref(anthropic): Revert input truncation
alexander-alderman-webb Apr 21, 2026
68278d3
remove truncation test
alexander-alderman-webb Apr 21, 2026
154033e
Merge branch 'webb/remove-litellm-truncation' into webb/remove-anthro…
alexander-alderman-webb Apr 21, 2026
978e74f
Merge branch 'webb/remove-litellm-truncation' into webb/remove-anthro…
alexander-alderman-webb Apr 21, 2026
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13 changes: 5 additions & 8 deletions sentry_sdk/integrations/anthropic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,6 @@
GEN_AI_ALLOWED_MESSAGE_ROLES,
set_data_normalized,
normalize_message_roles,
truncate_and_annotate_messages,
get_start_span_function,
)
from sentry_sdk.consts import OP, SPANDATA
Expand Down Expand Up @@ -394,14 +393,12 @@ def _set_common_input_data(
normalized_messages.append(message)

role_normalized_messages = normalize_message_roles(normalized_messages)
scope = sentry_sdk.get_current_scope()
messages_data = truncate_and_annotate_messages(
role_normalized_messages, span, scope
set_data_normalized(
span,
SPANDATA.GEN_AI_REQUEST_MESSAGES,
role_normalized_messages,
unpack=False,
)
if messages_data is not None:
set_data_normalized(
span, SPANDATA.GEN_AI_REQUEST_MESSAGES, messages_data, unpack=False
)

if max_tokens is not None and _is_given(max_tokens):
span.set_data(SPANDATA.GEN_AI_REQUEST_MAX_TOKENS, max_tokens)
Expand Down
99 changes: 0 additions & 99 deletions tests/integrations/anthropic/test_anthropic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2478,105 +2478,6 @@ def mock_messages_create(*args, **kwargs):
assert stored_messages[0]["role"] == expected_role


def test_anthropic_message_truncation(sentry_init, capture_items):
"""Test that large messages are truncated properly in Anthropic integration."""
sentry_init(
integrations=[AnthropicIntegration(include_prompts=True)],
traces_sample_rate=1.0,
send_default_pii=True,
)
items = capture_items("transaction", "span")

client = Anthropic(api_key="z")
client.messages._post = mock.Mock(return_value=EXAMPLE_MESSAGE)

large_content = (
"This is a very long message that will exceed our size limits. " * 1000
)
messages = [
{"role": "user", "content": "small message 1"},
{"role": "assistant", "content": large_content},
{"role": "user", "content": large_content},
{"role": "assistant", "content": "small message 4"},
{"role": "user", "content": "small message 5"},
]

with start_transaction():
client.messages.create(max_tokens=1024, messages=messages, model="model")

spans = [item.payload for item in items if item.type == "span"]
chat_spans = [
span for span in spans if span["attributes"].get("sentry.op") == OP.GEN_AI_CHAT
]
assert len(chat_spans) > 0

chat_span = chat_spans[0]
assert chat_span["attributes"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
assert chat_span["attributes"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
assert SPANDATA.GEN_AI_REQUEST_MESSAGES in chat_span["attributes"]

messages_data = chat_span["attributes"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
assert isinstance(messages_data, str)

parsed_messages = json.loads(messages_data)
assert isinstance(parsed_messages, list)
assert len(parsed_messages) == 1
assert "small message 5" in str(parsed_messages[0])

tx = next(item.payload for item in items if item.type == "transaction")
assert tx["_meta"]["spans"]["0"]["data"]["gen_ai.request.messages"][""]["len"] == 5


@pytest.mark.asyncio
async def test_anthropic_message_truncation_async(sentry_init, capture_items):
"""Test that large messages are truncated properly in Anthropic integration."""
sentry_init(
integrations=[AnthropicIntegration(include_prompts=True)],
traces_sample_rate=1.0,
send_default_pii=True,
)
items = capture_items("transaction", "span")

client = AsyncAnthropic(api_key="z")
client.messages._post = mock.AsyncMock(return_value=EXAMPLE_MESSAGE)

large_content = (
"This is a very long message that will exceed our size limits. " * 1000
)
messages = [
{"role": "user", "content": "small message 1"},
{"role": "assistant", "content": large_content},
{"role": "user", "content": large_content},
{"role": "assistant", "content": "small message 4"},
{"role": "user", "content": "small message 5"},
]

with start_transaction():
await client.messages.create(max_tokens=1024, messages=messages, model="model")

spans = [item.payload for item in items if item.type == "span"]
chat_spans = [
span for span in spans if span["attributes"].get("sentry.op") == OP.GEN_AI_CHAT
]
assert len(chat_spans) > 0

chat_span = chat_spans[0]
assert chat_span["attributes"][SPANDATA.GEN_AI_SYSTEM] == "anthropic"
assert chat_span["attributes"][SPANDATA.GEN_AI_OPERATION_NAME] == "chat"
assert SPANDATA.GEN_AI_REQUEST_MESSAGES in chat_span["attributes"]

messages_data = chat_span["attributes"][SPANDATA.GEN_AI_REQUEST_MESSAGES]
assert isinstance(messages_data, str)

parsed_messages = json.loads(messages_data)
assert isinstance(parsed_messages, list)
assert len(parsed_messages) == 1
assert "small message 5" in str(parsed_messages[0])

tx = next(item.payload for item in items if item.type == "transaction")
assert tx["_meta"]["spans"]["0"]["data"]["gen_ai.request.messages"][""]["len"] == 5


@pytest.mark.parametrize(
"send_default_pii, include_prompts",
[
Expand Down
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