fix(pydantic_ai): support pydantic-ai 2.0#538
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This makes Braintrust tracing work with pydantic-ai 2.0. Streamed agent events are traced again instead of failing because pydantic-ai changed that API. What users will see in Braintrust: stream-event spans continue to appear, completed direct streaming spans include the final model response, and errors during stream-event consumption are recorded on the span. Traces also include additional pydantic-ai 2.0 response details when pydantic-ai returns them, such as finish reason, provider URL/name, run id, and conversation id. This also removes an internal deprecation warning that could appear during normal setup_pydantic_ai() tracing.
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Andrew Kent (realark)
approved these changes
Jun 30, 2026
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| event = await self._iterator.__anext__() | ||
| self._wrapper._event_count += 1 | ||
| if hasattr(event, "output"): |
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FYI, my large language friend says this is the wrong attribute to check. Not sure if it's legit:
In _AgentStreamEventsIteratorProxy.__anext__, the code checks hasattr(event, "output"), but the final event (AgentRunResultEvent) exposes .result, not .output — confirmed in both pydantic-ai 1.x and 2.0 source. As a result:
- _final_result stays None, so the span logs no output
- _maybe_create_tool_spans_from_messages is never called
Verified empirically: final_result=None, output=None. This is pre-existing (carried over verbatim from the old wrapper, not a regression), but it sits in the rewritten code and contradicts the PR's goal. To fix, the check likely needs getattr(event, "result", None) and should shape event.result. Existing tests pass only because they assert event count / span presence, not the span's output.
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good catch llm! will fix.
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resolves #536
AI Summary:
This makes Braintrust tracing work with pydantic-ai 2.0. Streamed agent events are traced again instead of failing because pydantic-ai changed that API.
What users will see in Braintrust: stream-event spans continue to appear, completed direct streaming spans include the final model response, and errors during stream-event consumption are recorded on the span.
Traces also include additional pydantic-ai 2.0 response details when pydantic-ai returns them, such as finish reason, provider URL/name, run id, and conversation id. This also removes an internal deprecation warning that could appear during normal setup_pydantic_ai() tracing.