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fixed CheckTrainingStatus to match python and js (#43)
* update the thresholdl for quickflow auto train
* new dataset
* update test
* test(quick_flow): tolerance on exhaustive recall instead of bit-exact 1.0
n_probes==n_lists exhaustive search should recover the ground truth, but
JSON->float32 rounding of query vectors differs slightly across SDKs and can
flip a few tie-broken neighbors at the top_k boundary. Assert recall within
0.01 of 1.0 rather than exact equality so the check is portable.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* renamed CheckTrainingStatus
---------
Co-authored-by: “Truman <“trumanngny@yahoo.com”>
Co-authored-by: ahellegit <ah.secured@gmail.com>
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
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