Current File : /opt/hc_python/lib/python3.12/site-packages/sentry_sdk/integrations//anthropic.py
from functools import wraps
from typing import TYPE_CHECKING
import sentry_sdk
from sentry_sdk.ai.monitoring import record_token_usage
from sentry_sdk.consts import OP, SPANDATA
from sentry_sdk.integrations import _check_minimum_version, DidNotEnable, Integration
from sentry_sdk.scope import should_send_default_pii
from sentry_sdk.utils import (
capture_internal_exceptions,
event_from_exception,
package_version,
)
try:
from anthropic.resources import AsyncMessages, Messages
if TYPE_CHECKING:
from anthropic.types import MessageStreamEvent
except ImportError:
raise DidNotEnable("Anthropic not installed")
if TYPE_CHECKING:
from typing import Any, AsyncIterator, Iterator
from sentry_sdk.tracing import Span
class AnthropicIntegration(Integration):
identifier = "anthropic"
origin = f"auto.ai.{identifier}"
def __init__(self, include_prompts=True):
# type: (AnthropicIntegration, bool) -> None
self.include_prompts = include_prompts
@staticmethod
def setup_once():
# type: () -> None
version = package_version("anthropic")
_check_minimum_version(AnthropicIntegration, version)
Messages.create = _wrap_message_create(Messages.create)
AsyncMessages.create = _wrap_message_create_async(AsyncMessages.create)
def _capture_exception(exc):
# type: (Any) -> None
event, hint = event_from_exception(
exc,
client_options=sentry_sdk.get_client().options,
mechanism={"type": "anthropic", "handled": False},
)
sentry_sdk.capture_event(event, hint=hint)
def _calculate_token_usage(result, span):
# type: (Messages, Span) -> None
input_tokens = 0
output_tokens = 0
if hasattr(result, "usage"):
usage = result.usage
if hasattr(usage, "input_tokens") and isinstance(usage.input_tokens, int):
input_tokens = usage.input_tokens
if hasattr(usage, "output_tokens") and isinstance(usage.output_tokens, int):
output_tokens = usage.output_tokens
total_tokens = input_tokens + output_tokens
record_token_usage(span, input_tokens, output_tokens, total_tokens)
def _get_responses(content):
# type: (list[Any]) -> list[dict[str, Any]]
"""
Get JSON of a Anthropic responses.
"""
responses = []
for item in content:
if hasattr(item, "text"):
responses.append(
{
"type": item.type,
"text": item.text,
}
)
return responses
def _collect_ai_data(event, input_tokens, output_tokens, content_blocks):
# type: (MessageStreamEvent, int, int, list[str]) -> tuple[int, int, list[str]]
"""
Count token usage and collect content blocks from the AI streaming response.
"""
with capture_internal_exceptions():
if hasattr(event, "type"):
if event.type == "message_start":
usage = event.message.usage
input_tokens += usage.input_tokens
output_tokens += usage.output_tokens
elif event.type == "content_block_start":
pass
elif event.type == "content_block_delta":
if hasattr(event.delta, "text"):
content_blocks.append(event.delta.text)
elif hasattr(event.delta, "partial_json"):
content_blocks.append(event.delta.partial_json)
elif event.type == "content_block_stop":
pass
elif event.type == "message_delta":
output_tokens += event.usage.output_tokens
return input_tokens, output_tokens, content_blocks
def _add_ai_data_to_span(
span, integration, input_tokens, output_tokens, content_blocks
):
# type: (Span, AnthropicIntegration, int, int, list[str]) -> None
"""
Add token usage and content blocks from the AI streaming response to the span.
"""
with capture_internal_exceptions():
if should_send_default_pii() and integration.include_prompts:
complete_message = "".join(content_blocks)
span.set_data(
SPANDATA.AI_RESPONSES,
[{"type": "text", "text": complete_message}],
)
total_tokens = input_tokens + output_tokens
record_token_usage(span, input_tokens, output_tokens, total_tokens)
span.set_data(SPANDATA.AI_STREAMING, True)
def _sentry_patched_create_common(f, *args, **kwargs):
# type: (Any, *Any, **Any) -> Any
integration = kwargs.pop("integration")
if integration is None:
return f(*args, **kwargs)
if "messages" not in kwargs:
return f(*args, **kwargs)
try:
iter(kwargs["messages"])
except TypeError:
return f(*args, **kwargs)
span = sentry_sdk.start_span(
op=OP.ANTHROPIC_MESSAGES_CREATE,
description="Anthropic messages create",
origin=AnthropicIntegration.origin,
)
span.__enter__()
result = yield f, args, kwargs
# add data to span and finish it
messages = list(kwargs["messages"])
model = kwargs.get("model")
with capture_internal_exceptions():
span.set_data(SPANDATA.AI_MODEL_ID, model)
span.set_data(SPANDATA.AI_STREAMING, False)
if should_send_default_pii() and integration.include_prompts:
span.set_data(SPANDATA.AI_INPUT_MESSAGES, messages)
if hasattr(result, "content"):
if should_send_default_pii() and integration.include_prompts:
span.set_data(SPANDATA.AI_RESPONSES, _get_responses(result.content))
_calculate_token_usage(result, span)
span.__exit__(None, None, None)
# Streaming response
elif hasattr(result, "_iterator"):
old_iterator = result._iterator
def new_iterator():
# type: () -> Iterator[MessageStreamEvent]
input_tokens = 0
output_tokens = 0
content_blocks = [] # type: list[str]
for event in old_iterator:
input_tokens, output_tokens, content_blocks = _collect_ai_data(
event, input_tokens, output_tokens, content_blocks
)
yield event
_add_ai_data_to_span(
span, integration, input_tokens, output_tokens, content_blocks
)
span.__exit__(None, None, None)
async def new_iterator_async():
# type: () -> AsyncIterator[MessageStreamEvent]
input_tokens = 0
output_tokens = 0
content_blocks = [] # type: list[str]
async for event in old_iterator:
input_tokens, output_tokens, content_blocks = _collect_ai_data(
event, input_tokens, output_tokens, content_blocks
)
yield event
_add_ai_data_to_span(
span, integration, input_tokens, output_tokens, content_blocks
)
span.__exit__(None, None, None)
if str(type(result._iterator)) == "<class 'async_generator'>":
result._iterator = new_iterator_async()
else:
result._iterator = new_iterator()
else:
span.set_data("unknown_response", True)
span.__exit__(None, None, None)
return result
def _wrap_message_create(f):
# type: (Any) -> Any
def _execute_sync(f, *args, **kwargs):
# type: (Any, *Any, **Any) -> Any
gen = _sentry_patched_create_common(f, *args, **kwargs)
try:
f, args, kwargs = next(gen)
except StopIteration as e:
return e.value
try:
try:
result = f(*args, **kwargs)
except Exception as exc:
_capture_exception(exc)
raise exc from None
return gen.send(result)
except StopIteration as e:
return e.value
@wraps(f)
def _sentry_patched_create_sync(*args, **kwargs):
# type: (*Any, **Any) -> Any
integration = sentry_sdk.get_client().get_integration(AnthropicIntegration)
kwargs["integration"] = integration
return _execute_sync(f, *args, **kwargs)
return _sentry_patched_create_sync
def _wrap_message_create_async(f):
# type: (Any) -> Any
async def _execute_async(f, *args, **kwargs):
# type: (Any, *Any, **Any) -> Any
gen = _sentry_patched_create_common(f, *args, **kwargs)
try:
f, args, kwargs = next(gen)
except StopIteration as e:
return await e.value
try:
try:
result = await f(*args, **kwargs)
except Exception as exc:
_capture_exception(exc)
raise exc from None
return gen.send(result)
except StopIteration as e:
return e.value
@wraps(f)
async def _sentry_patched_create_async(*args, **kwargs):
# type: (*Any, **Any) -> Any
integration = sentry_sdk.get_client().get_integration(AnthropicIntegration)
kwargs["integration"] = integration
return await _execute_async(f, *args, **kwargs)
return _sentry_patched_create_async
