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## Pull Request --- ### 📄 Summary follow-up for #12027. Span-list trace-aggregate filtering ships in #12122. Adds `scalar` and `time_series` request types to `builder_ai_query`. The `trace.` prefix selects the aggregation domain: trace aggregates use a native CTE pipeline, while span aggregates delegate to the standard traces builder with the qualification gate applied. Trace-level filters qualify entire traces across both domains using the standard filter pipeline. Grouping, `HAVING`, ordering, and limits match the traces builder, including whole-window ranking for grouped time series and top-N limits for scalar queries. `count(trace.trace_id)` counts every AI trace, matching the trace list; token aggregates average over traces that have token data (standard `NULL` semantics, same as span-attribute aggregations elsewhere). Includes SQL golden tests, rewrite unit tests, and integration coverage for both domains, qualification, grouping, limits, bucketing, variables, and targeted `400` errors. #### Issues closed by this PR Fixes https://github.com/SigNoz/engineering-pod/issues/5602 Fixes https://github.com/SigNoz/engineering-pod/issues/5603 --- ### ✅ Change Type _Select all that apply_ - [x] ✨ Feature - [ ] 🐛 Bug fix - [ ] ♻️ Refactor - [ ] 🛠️ Infra / Tooling - [ ] 🧪 Test-only --- ### 🧪 Testing Strategy > How was this change validated? - Tests added/updated: ✅ - Manual verification: - Edge cases covered: --- ### ⚠️ Risk & Impact Assessment > What could break? How do we recover? - Blast radius: None - Potential regressions: - Rollback plan: --- ### 📋 Checklist - [x] Tests added or explicitly not required - [x] Manually tested - [ ] Breaking changes documented - [ ] Backward compatibility considered --- ## 👀 Notes for Reviewers Still in testing phase ---