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fix(ai): address missing attributes and propagate agent name in AI integrations #5727

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7d39c1b
fix(ai): resolve injection and propagation issues in AI tests
harryautomazione Mar 20, 2026
7597505
fix(ai): remove duplicate push_agent_name in async wrapper
harryautomazione Mar 20, 2026
c37daad
fix(ai): move push_agent_name inside try/finally core block in langgraph
harryautomazione Mar 20, 2026
62a0647
fix(pydantic_ai): remove redundant fallback branch in response logic
harryautomazione Mar 20, 2026
76b8a6b
fix(pydantic_ai): clean up unused import and redundant locals() check
harryautomazione Mar 20, 2026
e8a9c76
fix(pydantic_ai): remove unused imports in ai_client.py
harryautomazione Mar 20, 2026
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37 changes: 37 additions & 0 deletions sentry_sdk/ai/utils.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -747,3 +747,40 @@ def set_conversation_id(conversation_id: str) -> None:
"""
scope = sentry_sdk.get_current_scope()
scope.set_conversation_id(conversation_id)


import contextvars

_gen_ai_agent_stack: "contextvars.ContextVar[Optional[list[Optional[str]]]]" = (
contextvars.ContextVar("gen_ai_agent_stack", default=None)
)


def push_agent_name(agent_name: "Optional[str]") -> None:
"""Push an agent name onto the stack."""
stack = _gen_ai_agent_stack.get()
if stack is None:
stack = []
else:
stack = stack.copy()
stack.append(agent_name)
_gen_ai_agent_stack.set(stack)


def pop_agent_name() -> "Optional[str]":
"""Pop an agent name from the stack and return it."""
stack = _gen_ai_agent_stack.get()
if stack:
stack = stack.copy()
agent_name = stack.pop()
_gen_ai_agent_stack.set(stack)
return agent_name
return None


def get_current_agent_name() -> "Optional[str]":
"""Get the current agent name (top of stack) without removing it."""
stack = _gen_ai_agent_stack.get()
if stack:
return stack[-1]
return None
1 change: 1 addition & 0 deletions sentry_sdk/integrations/langchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -650,6 +650,7 @@ def on_tool_start(

span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "execute_tool")
span.set_data(SPANDATA.GEN_AI_TOOL_NAME, tool_name)
span.set_data(SPANDATA.GEN_AI_TOOL_TYPE, "function")

tool_description = serialized.get("description")
if tool_description is not None:
Expand Down
122 changes: 65 additions & 57 deletions sentry_sdk/integrations/langgraph.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,8 @@
set_data_normalized,
normalize_message_roles,
truncate_and_annotate_messages,
push_agent_name,
pop_agent_name,
)
from sentry_sdk.consts import OP, SPANDATA
from sentry_sdk.integrations import DidNotEnable, Integration
Expand Down Expand Up @@ -168,36 +170,39 @@ def new_invoke(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
if graph_name:
span.set_data(SPANDATA.GEN_AI_PIPELINE_NAME, graph_name)
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, graph_name)

span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")

# 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,
push_agent_name(graph_name)

try:
span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")

# 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
)

result = f(self, *args, **kwargs)

_set_response_attributes(span, input_messages, result, integration)

return result
if messages_data is not None:
set_data_normalized(
span,
SPANDATA.GEN_AI_REQUEST_MESSAGES,
messages_data,
unpack=False,
)

result = f(self, *args, **kwargs)
_set_response_attributes(span, input_messages, result, integration)
return result
finally:
if graph_name:
pop_agent_name()

return new_invoke

Expand All @@ -222,35 +227,38 @@ async def new_ainvoke(self: "Any", *args: "Any", **kwargs: "Any") -> "Any":
if graph_name:
span.set_data(SPANDATA.GEN_AI_PIPELINE_NAME, graph_name)
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, graph_name)

span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")

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,
push_agent_name(graph_name)

try:
span.set_data(SPANDATA.GEN_AI_OPERATION_NAME, "invoke_agent")

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
)

result = await f(self, *args, **kwargs)

_set_response_attributes(span, input_messages, result, integration)

return result
if messages_data is not None:
set_data_normalized(
span,
SPANDATA.GEN_AI_REQUEST_MESSAGES,
messages_data,
unpack=False,
)

result = await f(self, *args, **kwargs)
_set_response_attributes(span, input_messages, result, integration)
return result
finally:
if graph_name:
pop_agent_name()

return new_ainvoke

Expand Down
5 changes: 5 additions & 0 deletions sentry_sdk/integrations/openai.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@
normalize_message_roles,
truncate_and_annotate_messages,
truncate_and_annotate_embedding_inputs,
get_current_agent_name,
)
from sentry_sdk.ai._openai_completions_api import (
_is_system_instruction as _is_system_instruction_completions,
Expand Down Expand Up @@ -226,6 +227,10 @@ def _commmon_set_input_data(
# Input attributes: Common
set_data_normalized(span, SPANDATA.GEN_AI_SYSTEM, "openai")

agent_name = get_current_agent_name()
if agent_name:
span.set_data(SPANDATA.GEN_AI_AGENT_NAME, agent_name)

# Input attributes: Optional
kwargs_keys_to_attributes = {
"model": SPANDATA.GEN_AI_REQUEST_MODEL,
Expand Down
76 changes: 2 additions & 74 deletions sentry_sdk/integrations/pydantic_ai/spans/ai_client.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -20,9 +20,8 @@
get_is_streaming,
)
from .utils import (
_serialize_binary_content_item,
_serialize_image_url_item,
_set_usage_data,
_format_messages,
)

from typing import TYPE_CHECKING
Expand All @@ -35,24 +34,16 @@
try:
from pydantic_ai.messages import (
BaseToolCallPart,
BaseToolReturnPart,
SystemPromptPart,
UserPromptPart,
TextPart,
ThinkingPart,
BinaryContent,
ImageUrl,
)
except ImportError:
# Fallback if these classes are not available
BaseToolCallPart = None
BaseToolReturnPart = None
SystemPromptPart = None
UserPromptPart = None
TextPart = None
ThinkingPart = None
BinaryContent = None
ImageUrl = None


def _transform_system_instructions(
Expand Down Expand Up @@ -116,70 +107,7 @@ def _set_input_messages(span: "sentry_sdk.tracing.Span", messages: "Any") -> Non
)

try:
formatted_messages = []

for msg in messages:
if hasattr(msg, "parts"):
for part in msg.parts:
role = "user"
# Use isinstance checks with proper base classes
if SystemPromptPart and isinstance(part, SystemPromptPart):
continue
elif (
(TextPart and isinstance(part, TextPart))
or (ThinkingPart and isinstance(part, ThinkingPart))
or (BaseToolCallPart and isinstance(part, BaseToolCallPart))
):
role = "assistant"
elif BaseToolReturnPart and isinstance(part, BaseToolReturnPart):
role = "tool"

content: "List[Dict[str, Any] | str]" = []
tool_calls = None
tool_call_id = None

# Handle ToolCallPart (assistant requesting tool use)
if BaseToolCallPart and isinstance(part, BaseToolCallPart):
tool_call_data = {}
if hasattr(part, "tool_name"):
tool_call_data["name"] = part.tool_name
if hasattr(part, "args"):
tool_call_data["arguments"] = safe_serialize(part.args)
if tool_call_data:
tool_calls = [tool_call_data]
# Handle ToolReturnPart (tool result)
elif BaseToolReturnPart and isinstance(part, BaseToolReturnPart):
if hasattr(part, "tool_name"):
tool_call_id = part.tool_name
if hasattr(part, "content"):
content.append({"type": "text", "text": str(part.content)})
# Handle regular content
elif hasattr(part, "content"):
if isinstance(part.content, str):
content.append({"type": "text", "text": part.content})
elif isinstance(part.content, list):
for item in part.content:
if isinstance(item, str):
content.append({"type": "text", "text": item})
elif ImageUrl and isinstance(item, ImageUrl):
content.append(_serialize_image_url_item(item))
elif BinaryContent and isinstance(item, BinaryContent):
content.append(_serialize_binary_content_item(item))
else:
content.append(safe_serialize(item))
else:
content.append({"type": "text", "text": str(part.content)})
# Add message if we have content or tool calls
if content or tool_calls:
message: "Dict[str, Any]" = {"role": role}
if content:
message["content"] = content
if tool_calls:
message["tool_calls"] = tool_calls
if tool_call_id:
message["tool_call_id"] = tool_call_id
formatted_messages.append(message)

formatted_messages = _format_messages(messages)
if formatted_messages:
normalized_messages = normalize_message_roles(formatted_messages)
scope = sentry_sdk.get_current_scope()
Expand Down
28 changes: 24 additions & 4 deletions sentry_sdk/integrations/pydantic_ai/spans/invoke_agent.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@
_serialize_binary_content_item,
_serialize_image_url_item,
_set_usage_data,
_format_messages,
)

from typing import TYPE_CHECKING
Expand Down Expand Up @@ -142,10 +143,29 @@ def update_invoke_agent_span(span: "sentry_sdk.tracing.Span", result: "Any") ->
output = getattr(result, "output", None)

# Set response text if prompts are enabled
if _should_send_prompts() and output:
set_data_normalized(
span, SPANDATA.GEN_AI_RESPONSE_TEXT, str(output), unpack=False
)
if _should_send_prompts():
messages = None
if hasattr(result, "new_messages") and callable(result.new_messages):
try:
messages = result.new_messages()
except Exception:
pass
elif hasattr(result, "all_messages") and callable(result.all_messages):
try:
messages = result.all_messages()
except Exception:
pass

formatted_messages = _format_messages(messages) if messages else []

if formatted_messages:
set_data_normalized(
span, SPANDATA.GEN_AI_RESPONSE_TEXT, formatted_messages, unpack=False
)
elif output:
set_data_normalized(
span, SPANDATA.GEN_AI_RESPONSE_TEXT, str(output), unpack=False
)

# Set token usage data if available
if hasattr(result, "usage") and callable(result.usage):
Expand Down
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