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7c80b79bb0
Addresses the review on #51714: the trace/span layer was declared but unwired — tel_spans was never written, call rows had no timestamp, and nothing set parent lineage, so the store was metrics-only and couldn't reconstruct a trace. Wire the span layer (keeping the praised star-schema shape): - New SpanEvent (span_id/trace_id/run_id/parent_span_id/name/kind/start_ns/end_ns) mapped into tel_spans via the emitter's _TABLE_COLUMNS. - The plugin mints a root span per run and, on each model/tool call, emits a SpanEvent (timing + parent = the run's root) keyed by the SAME span_id as the detail row, so tel_model_calls / tel_tool_calls JOIN to their span. - Call hooks fire on completion, so end_ns = now and start_ns is reconstructed from the measured latency/duration. The run's root span is emitted at finalize with the true run start/end. Result: tel_spans is a connected, single-trace_id, run -> calls tree a desktop waterfall (or any reader) can render directly, ordered by start_ns. Existing metrics rows (tel_runs/model_calls/tool_calls) are unchanged. OTLP: spans now flow to the exporter with their trace/parent/timing attributes. The exporter still emits one OTel span per event rather than reconstructing OTel SpanContexts into a connected trace tree; that projection is left for a follow-up and the module docstring now says so plainly instead of over-claiming. Adds test_spans_trace.py (connected-tree + detail-row JOIN) over the real dispatch path. Accurate (pre-hook) start times, real OTLP SpanContexts, and subagent cross-run lineage remain follow-ups. |
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| .. | ||
| browser | ||
| context_engine | ||
| cron_providers | ||
| dashboard_auth | ||
| disk-cleanup | ||
| google_meet | ||
| hermes-achievements | ||
| image_gen | ||
| kanban | ||
| memory | ||
| model-providers | ||
| observability | ||
| platforms | ||
| security-guidance | ||
| spotify | ||
| teams_pipeline | ||
| telemetry | ||
| video_gen | ||
| web | ||
| __init__.py | ||
| plugin_utils.py | ||