GitHub user xuang7 added a comment to the discussion: Ambient "operator recommender" — predictive next-operator suggestions on the canvas
The idea sounds very good! This would significantly improve the usability of workflow building, and the plan discussed above seems like a solid way to get there incrementally. As discussed, version 1 can return hardcoded recommendations, so the `/recommend` endpoint does not need to call an LLM yet. This allows you to wire up and demo the full loop with zero API cost: the frontend listens for the "operator added" event, calls the endpoint, and renders the ghost suggestions. The `agent-service` should still run locally, since that is where the new endpoint should live, but for version 1, the default configuration should be sufficient because no LLM call is involved. For version 2, which connects to a real LLM, you could follow the suggestions earlier in this thread: reuse the same gateway that the chatbot already uses, and start with a smaller, cheaper model. That part can come later after we get more input from the community. GitHub link: https://github.com/apache/texera/discussions/5240#discussioncomment-17578163 ---- This is an automatically sent email for [email protected]. To unsubscribe, please send an email to: [email protected]
