Lee-W commented on code in PR #72786:
URL: https://github.com/apache/airflow/pull/72786#discussion_r4034576665
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providers/common/ai/src/airflow/providers/common/ai/toolsets/managed_agent.py:
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@@ -232,9 +273,17 @@ async def call_tool(
ctx: RunContext[Any],
tool: ToolsetTool[Any],
) -> Any:
- ref = self.agent_ref
+ ref = _safe_agent_ref(self)
log.info("Consulting managed agent %s on %s", ref.get("name"),
ref.get("platform"))
result = await self.invoke(tool_args["prompt"])
+ # Emitted here, not in FailoverManagedAgentToolset.invoke(), so a lone
+ # toolset gets it too -- it is the only per-tool signal a bare toolset
+ # has, and it is the ratio that turns managed_agent.failover from a raw
+ # count into a rate (failovers / invocations for the same tool).
+ Stats.incr(
Review Comment:
moved `managed_agent.invoked` increments before `invoke()` runs.
The docs stop short of calling `served`/`invoked` a success rate, though.
* `served` only exists for a group and only counts returns from
`FailoverManagedAgentToolset.invoke()`
* `invoked` counts the `call_tool()` path, so a direct `invoke(prompt)` is
outside both.
The Metrics section says so, and `invoked` is documented as the denominator
for `managed_agent.failover` alone.
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