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feat(ai): Add python-genai integration
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‎pyproject.toml‎

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@@ -118,6 +118,10 @@ ignore_missing_imports = true
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module = "langgraph.*"
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ignore_missing_imports = true
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[[tool.mypy.overrides]]
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module = "google.genai.*"
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ignore_missing_imports = true
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[[tool.mypy.overrides]]
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module = "executing.*"
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ignore_missing_imports = true

‎scripts/populate_tox/config.py‎

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@@ -143,6 +143,13 @@
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"package": "gql[all]",
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"num_versions": 2,
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},
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"google_genai": {
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"package": "google-genai",
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"deps": {
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"*": ["pytest-asyncio"],
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},
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"python": ">=3.8",
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},
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"graphene": {
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"package": "graphene",
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"deps": {

‎sentry_sdk/integrations/__init__.py‎

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@@ -91,6 +91,7 @@ def iter_default_integrations(with_auto_enabling_integrations):
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"sentry_sdk.integrations.flask.FlaskIntegration",
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"sentry_sdk.integrations.gql.GQLIntegration",
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"sentry_sdk.integrations.graphene.GrapheneIntegration",
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"sentry_sdk.integrations.google_genai.GoogleGenAIIntegration",
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"sentry_sdk.integrations.httpx.HttpxIntegration",
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"sentry_sdk.integrations.huey.HueyIntegration",
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"sentry_sdk.integrations.huggingface_hub.HuggingfaceHubIntegration",
@@ -140,6 +141,7 @@ def iter_default_integrations(with_auto_enabling_integrations):
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"flask": (1, 1, 4),
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"gql": (3, 4, 1),
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"graphene": (3, 3),
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"google_genai": (1, 0, 0), # google-genai
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"grpc": (1, 32, 0), # grpcio
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"httpx": (0, 16, 0),
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"huggingface_hub": (0, 24, 7),

‎sentry_sdk/integrations/google_genai/__init__.py‎

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@@ -0,0 +1,290 @@
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from functools import wraps
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from typing import (
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Any,
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AsyncIterator,
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Callable,
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Iterator,
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List,
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)
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import sentry_sdk
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from sentry_sdk.integrations import DidNotEnable, Integration
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from sentry_sdk.consts import OP, SPANDATA
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try:
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from google import genai
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from google.genai.models import Models, AsyncModels
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except ImportError:
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raise DidNotEnable("google-genai not installed")
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from .consts import IDENTIFIER, ORIGIN, GEN_AI_SYSTEM
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from .utils import (
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set_span_data_for_request,
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set_span_data_for_response,
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capture_exception,
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)
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from .streaming import (
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set_span_data_for_streaming_response,
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accumulate_streaming_response,
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prepare_generate_content_args,
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)
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class GoogleGenAIIntegration(Integration):
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identifier = IDENTIFIER
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origin = ORIGIN
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def __init__(self, include_prompts=True):
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# type: (GoogleGenAIIntegration, bool) -> None
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self.include_prompts = include_prompts
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@staticmethod
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def setup_once():
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# type: () -> None
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# Patch sync methods
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Models.generate_content = _wrap_generate_content(Models.generate_content)
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Models.generate_content_stream = _wrap_generate_content_stream(
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Models.generate_content_stream
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)
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# Patch async methods
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AsyncModels.generate_content = _wrap_async_generate_content(
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AsyncModels.generate_content
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)
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AsyncModels.generate_content_stream = _wrap_async_generate_content_stream(
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AsyncModels.generate_content_stream
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)
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def _wrap_generate_content_stream(f):
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# type: (Callable[..., Any]) -> Callable[..., Any]
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@wraps(f)
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def new_generate_content_stream(self, *args, **kwargs):
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# type: (Any, Any, Any) -> Any
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integration = sentry_sdk.get_client().get_integration(GoogleGenAIIntegration)
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if integration is None:
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return f(self, *args, **kwargs)
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_model, contents, model_name = prepare_generate_content_args(args, kwargs)
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span = sentry_sdk.start_span(
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op=OP.GEN_AI_INVOKE_AGENT,
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name="invoke_agent",
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origin=ORIGIN,
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)
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span.set_data(SPANDATA.GEN_AI_AGENT_NAME, model_name)
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span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")
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set_span_data_for_request(span, integration, model_name, contents, kwargs)
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span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, True)
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chat_span = sentry_sdk.start_span(
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op=OP.GEN_AI_CHAT,
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name=f"chat {model_name}",
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origin=ORIGIN,
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)
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chat_span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "chat")
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chat_span.set_data(SPANDATA.GEN_AI_SYSTEM, GEN_AI_SYSTEM)
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chat_span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model_name)
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set_span_data_for_request(chat_span, integration, model_name, contents, kwargs)
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chat_span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, True)
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try:
94+
stream = f(self, *args, **kwargs)
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# Create wrapper iterator to accumulate responses
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def new_iterator():
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# type: () -> Iterator[Any]
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chunks = [] # type: List[Any]
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try:
101+
for chunk in stream:
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chunks.append(chunk)
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yield chunk
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except Exception as exc:
105+
capture_exception(exc)
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raise
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finally:
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# Accumulate all chunks and set final response data on spans
109+
if chunks:
110+
accumulated_response = accumulate_streaming_response(chunks)
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set_span_data_for_streaming_response(
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chat_span, integration, accumulated_response
113+
)
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set_span_data_for_streaming_response(
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span, integration, accumulated_response
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)
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chat_span.finish()
118+
span.finish()
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return new_iterator()
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122+
except Exception as exc:
123+
capture_exception(exc)
124+
chat_span.finish()
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span.finish()
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raise
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return new_generate_content_stream
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def _wrap_async_generate_content_stream(f):
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# type: (Callable[..., Any]) -> Callable[..., Any]
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@wraps(f)
134+
async def new_async_generate_content_stream(self, *args, **kwargs):
135+
# type: (Any, Any, Any) -> Any
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integration = sentry_sdk.get_client().get_integration(GoogleGenAIIntegration)
137+
if integration is None:
138+
return await f(self, *args, **kwargs)
139+
140+
_model, contents, model_name = prepare_generate_content_args(args, kwargs)
141+
142+
span = sentry_sdk.start_span(
143+
op=OP.GEN_AI_INVOKE_AGENT,
144+
name="invoke_agent",
145+
origin=ORIGIN,
146+
)
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span.set_data(SPANDATA.GEN_AI_AGENT_NAME, model_name)
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span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")
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set_span_data_for_request(span, integration, model_name, contents, kwargs)
150+
span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, True)
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chat_span = sentry_sdk.start_span(
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op=OP.GEN_AI_CHAT,
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name=f"chat {model_name}",
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origin=ORIGIN,
156+
)
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chat_span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "chat")
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chat_span.set_data(SPANDATA.GEN_AI_SYSTEM, GEN_AI_SYSTEM)
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chat_span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model_name)
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set_span_data_for_request(chat_span, integration, model_name, contents, kwargs)
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chat_span.set_data(SPANDATA.GEN_AI_RESPONSE_STREAMING, True)
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try:
164+
stream = await f(self, *args, **kwargs)
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166+
# Create wrapper async iterator to accumulate responses
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async def new_async_iterator():
168+
# type: () -> AsyncIterator[Any]
169+
chunks = [] # type: List[Any]
170+
try:
171+
async for chunk in stream:
172+
chunks.append(chunk)
173+
yield chunk
174+
except Exception as exc:
175+
capture_exception(exc)
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raise
177+
finally:
178+
# Accumulate all chunks and set final response data on spans
179+
if chunks:
180+
accumulated_response = accumulate_streaming_response(chunks)
181+
set_span_data_for_streaming_response(
182+
chat_span, integration, accumulated_response
183+
)
184+
set_span_data_for_streaming_response(
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span, integration, accumulated_response
186+
)
187+
chat_span.finish()
188+
span.finish()
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190+
return new_async_iterator()
191+
192+
except Exception as exc:
193+
capture_exception(exc)
194+
chat_span.finish()
195+
span.finish()
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raise
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198+
return new_async_generate_content_stream
199+
200+
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def _wrap_generate_content(f):
202+
# type: (Callable[..., Any]) -> Callable[..., Any]
203+
@wraps(f)
204+
def new_generate_content(self, *args, **kwargs):
205+
# type: (Any, Any, Any) -> Any
206+
integration = sentry_sdk.get_client().get_integration(GoogleGenAIIntegration)
207+
if integration is None:
208+
return f(self, *args, **kwargs)
209+
210+
model, contents, model_name = prepare_generate_content_args(args, kwargs)
211+
212+
with sentry_sdk.start_span(
213+
op=OP.GEN_AI_INVOKE_AGENT,
214+
name="invoke_agent",
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origin=ORIGIN,
216+
) as span:
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span.set_data(SPANDATA.GEN_AI_AGENT_NAME, model_name)
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span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")
219+
set_span_data_for_request(span, integration, model_name, contents, kwargs)
220+
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try:
222+
with sentry_sdk.start_span(
223+
op=OP.GEN_AI_CHAT,
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name=f"chat {model_name}",
225+
origin=ORIGIN,
226+
) as chat_span:
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chat_span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "chat")
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chat_span.set_data(SPANDATA.GEN_AI_SYSTEM, GEN_AI_SYSTEM)
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chat_span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model_name)
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set_span_data_for_request(
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chat_span, integration, model_name, contents, kwargs
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)
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response = f(self, *args, **kwargs)
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set_span_data_for_response(chat_span, integration, response)
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set_span_data_for_response(span, integration, response)
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return response
240+
except Exception as exc:
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capture_exception(exc)
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raise
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return new_generate_content
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def _wrap_async_generate_content(f):
248+
# type: (Callable[..., Any]) -> Callable[..., Any]
249+
@wraps(f)
250+
async def new_async_generate_content(self, *args, **kwargs):
251+
# type: (Any, Any, Any) -> Any
252+
integration = sentry_sdk.get_client().get_integration(GoogleGenAIIntegration)
253+
if integration is None:
254+
return await f(self, *args, **kwargs)
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256+
model, contents, model_name = prepare_generate_content_args(args, kwargs)
257+
258+
with sentry_sdk.start_span(
259+
op=OP.GEN_AI_INVOKE_AGENT,
260+
name="invoke_agent",
261+
origin=ORIGIN,
262+
) as span:
263+
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, model_name)
264+
span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")
265+
set_span_data_for_request(span, integration, model_name, contents, kwargs)
266+
267+
try:
268+
with sentry_sdk.start_span(
269+
op=OP.GEN_AI_CHAT,
270+
name=f"chat {model_name}",
271+
origin=ORIGIN,
272+
) as chat_span:
273+
chat_span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "chat")
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chat_span.set_data(SPANDATA.GEN_AI_SYSTEM, GEN_AI_SYSTEM)
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chat_span.set_data(SPANDATA.GEN_AI_REQUEST_MODEL, model_name)
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set_span_data_for_request(
277+
chat_span, integration, model_name, contents, kwargs
278+
)
279+
280+
response = await f(self, *args, **kwargs)
281+
282+
set_span_data_for_response(chat_span, integration, response)
283+
set_span_data_for_response(span, integration, response)
284+
285+
return response
286+
except Exception as exc:
287+
capture_exception(exc)
288+
raise
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290+
return new_async_generate_content

‎sentry_sdk/integrations/google_genai/consts.py‎

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GEN_AI_SYSTEM = "gcp.gemini"
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# Mapping of tool attributes to their descriptions
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# These are all tools that are available in the Google GenAI API
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TOOL_ATTRIBUTES_MAP = {
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"google_search_retrieval": "Google Search retrieval tool",
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"google_search": "Google Search tool",
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"retrieval": "Retrieval tool",
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"enterprise_web_search": "Enterprise web search tool",
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"google_maps": "Google Maps tool",
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"code_execution": "Code execution tool",
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"computer_use": "Computer use tool",
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}
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IDENTIFIER = "google_genai"
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ORIGIN = f"auto.ai.{IDENTIFIER}"

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