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. |
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| __init__.py | ||
| prompts.py | ||
| score.py | ||