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feat(openai-agents): Set system instruction attribute #5355

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feat(openai-agents): Set system instruction attribute
alexander-alderman-webb Jan 21, 2026
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add const
alexander-alderman-webb Jan 21, 2026
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alexander-alderman-webb Jan 22, 2026
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alexander-alderman-webb Jan 22, 2026
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4 changes: 4 additions & 0 deletions sentry_sdk/_types.py
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Original file line number Diff line number Diff line change
Expand Up @@ -359,3 +359,7 @@ class SDKInfo(TypedDict):
)

HttpStatusCodeRange = Union[int, Container[int]]

class TextPart(TypedDict):
type: Literal["text"]
content: str
6 changes: 6 additions & 0 deletions sentry_sdk/consts.py
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Expand Up @@ -542,6 +542,12 @@ class SPANDATA:
Example: 2048
"""

GEN_AI_SYSTEM_INSTRUCTIONS = "gen_ai.system_instructions"
"""
The system instructions passed to the model.
Example: [{"type": "text", "text": "You are a helpful assistant."},{"type": "text", "text": "Be concise and clear."}]
"""

GEN_AI_REQUEST_MESSAGES = "gen_ai.request.messages"
"""
The messages passed to the model. The "content" can be a string or an array of objects.
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23 changes: 17 additions & 6 deletions sentry_sdk/integrations/openai_agents/spans/invoke_agent.py
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Expand Up @@ -18,6 +18,17 @@
import agents
from typing import Any, Optional

from sentry_sdk._types import TextPart


def _transform_system_instruction(system_instructions: "str") -> "list[TextPart]":
return [
{
"type": "text",
"content": system_instructions,
}
]
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System instruction format uses wrong key name

Medium Severity

The _transform_system_instruction function and TextPart TypedDict use "content" as the dictionary key, but the OpenTelemetry semantic conventions and the rest of the codebase use "text". The docstring example for GEN_AI_SYSTEM_INSTRUCTIONS shows {"type": "text", "text": "..."}, and existing code in utils.py, anthropic.py, and langchain.py all use the "text" key. This inconsistency means the telemetry data won't conform to the OTel structure as intended by the PR.

Additional Locations (1)

Fix in Cursor Fix in Web

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@alexander-alderman-webb alexander-alderman-webb Jan 22, 2026

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um check the link in the PR description.



def invoke_agent_span(
context: "agents.RunContextWrapper", agent: "agents.Agent", kwargs: "dict[str, Any]"
Expand All @@ -35,16 +46,16 @@ def invoke_agent_span(
if should_send_default_pii():
messages = []
if agent.instructions:
message = (
system_instruction = (
agent.instructions
if isinstance(agent.instructions, str)
else safe_serialize(agent.instructions)
)
messages.append(
{
"content": [{"text": message, "type": "text"}],
"role": "system",
}
set_data_normalized(
span,
SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS,
_transform_system_instruction(system_instruction),
unpack=False,
)

original_input = kwargs.get("original_input")
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44 changes: 27 additions & 17 deletions tests/integrations/openai_agents/test_openai_agents.py
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Expand Up @@ -151,8 +151,12 @@ def test_agent_custom_model():


@pytest.mark.asyncio
@pytest.mark.parametrize(
"send_default_pii",
(True, False),
)
async def test_agent_invocation_span(
sentry_init, capture_events, test_agent, mock_model_response
sentry_init, capture_events, test_agent, mock_model_response, send_default_pii
):
"""
Test that the integration creates spans for agent invocations.
Expand All @@ -167,7 +171,7 @@ async def test_agent_invocation_span(
sentry_init(
integrations=[OpenAIAgentsIntegration()],
traces_sample_rate=1.0,
send_default_pii=True,
send_default_pii=send_default_pii,
)

events = capture_events()
Expand All @@ -187,21 +191,27 @@ async def test_agent_invocation_span(
assert transaction["contexts"]["trace"]["origin"] == "auto.ai.openai_agents"

assert invoke_agent_span["description"] == "invoke_agent test_agent"
assert invoke_agent_span["data"]["gen_ai.request.messages"] == safe_serialize(
[
{
"content": [
{"text": "You are a helpful test assistant.", "type": "text"}
],
"role": "system",
},
{"content": [{"text": "Test input", "type": "text"}], "role": "user"},
]
)
assert (
invoke_agent_span["data"]["gen_ai.response.text"]
== "Hello, how can I help you?"
)

if send_default_pii:
assert invoke_agent_span["data"][
SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS
] == safe_serialize(
[{"type": "text", "content": "You are a helpful test assistant."}]
)
assert invoke_agent_span["data"]["gen_ai.request.messages"] == safe_serialize(
[
{"content": [{"text": "Test input", "type": "text"}], "role": "user"},
]
)
assert (
invoke_agent_span["data"]["gen_ai.response.text"]
== "Hello, how can I help you?"
)
else:
assert SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS not in invoke_agent_span["data"]
assert "gen_ai.request.messages" not in invoke_agent_span["data"]
assert "gen_ai.response.text" not in invoke_agent_span["data"]

assert invoke_agent_span["data"]["gen_ai.operation.name"] == "invoke_agent"
assert invoke_agent_span["data"]["gen_ai.system"] == "openai"
assert invoke_agent_span["data"]["gen_ai.agent.name"] == "test_agent"
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