Four fixes from automated code review:
1. score.py: pre-compute embeddings per content string to cut API
calls from O(P*T) to O(P+T). Was making 2*P*T HTTP round-trips
to Ollama embeddings per memory_extraction sample; now P+T.
Significant speed-up on cloud endpoints where each embed is a
network call.
2. metrics.py: bump VRAMPoller default interval from 100ms to 500ms.
nvidia-smi subprocess every 100ms was creating measurable jitter
on the timing numbers. 500ms still captures peak (inference VRAM
is steady-state during a request) with much less overhead.
3. orchestrator.py: use argparse.BooleanOptionalAction for
--continue-on-error so --no-continue-on-error actually disables
the default. The previous combination of store_true and
default=True made the flag a permanent True.
4. summarize.py: drop the buggy first attempt at the reasoning
filter (had operator-precedence issue with `or` and `and`).
Keep only the clean prefix-based filter that was already on
the next line shadowing it.
Igor Lins e Silva
67f6fc6974