Ashfaqbs opened a new issue, #1065: URL: https://github.com/apache/flink-agents/issues/1065
### Search before asking - [x] I searched in the [issues](https://github.com/apache/flink-agents/issues) and found nothing similar. ### Description #858 tracks embedding models not consistently *reporting* token usage metrics, and chat models already have a working token-accounting path that lands in the metrics layer. That's visibility. There's no enforcement layer on top of it. What problem does it solve: a Flink Agents job is a long-running streaming application, not a one-shot script. A misbehaving action (a bad prompt loop, an unexpectedly chatty tool-call cycle, a runaway retry) can burn LLM spend continuously for as long as the job stays up, with the only signal being a metrics dashboard someone has to be watching. There's currently no built-in way to say "stop calling this model for this agent/action once N tokens (or $ cost) have been spent in a window" the way, for example, Flink itself lets you bound resource usage with slot/memory limits. What I have in mind: a budget guardrail configured per agent (or per action/chat-model-setup), expressed as a token or cost ceiling over a sliding or fixed window, enforced on the same durable, metered chat/embedding path the token-accounting and #1062's MODEL_ROUTER work already run through — so it's a policy layered on infrastructure that already exists, not a new call path. When the ceiling is hit, the configured behavior could range from a raised error (fail the action, let normal error-handling strategy take over, same as a routing/judge failure already does in #1062) to a soft warning event for observability-only setups. This is a runtime safety feature, distinct from #1062's routing/fallback-among-candidates concern — routing decides *which* model answers a call; this decides *whether* the call is still allowed to happen given spend so far. ### Are you willing to submit a PR? - [ ] I'm willing to submit a PR! -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
