Re: [D] Proposal: Databricks Unity AI Gateway model class for apache-airflow-providers-common-ai [airflow]

["richardchen874-sys (via GitHub)" <gi...@apache.org>]

GitHub user richardchen874-sys closed the discussion with a comment: Proposal: Databricks Unity AI Gateway model class for apache-airflow-providers-common-ai

The stream-timing focus is exactly the right first layer; without chunk gaps, stalls, and interruption data, usage and cost comparison comes too early.

I would log route choice, provider/model, tool-call support, latency, usage, and retry/fallback reason together. Agent failures are much easier to debug when the route decision is visible.

This is close to what I am experimenting with: official Chinese models behind an OpenAI-compatible multi-model layer, with an emphasis on predictable usage and routing behavior. For airflow, is the harder problem provider compatibility, routing quality, or keeping per-run cost predictable?

GitHub link: https://github.com/apache/airflow/discussions/67581#discussioncomment-17922113

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