Replaces the per-item Add loop in the HTTP handler with one call to
Index.BatchAdd, which acquires the write-lock once and pushes the
whole batch through coder/hnsw's variadic Graph.Add. Pre-validation
stays in the handler so per-item error messages keep their item-index
precision.
Microbench (internal/vectord/batch_bench_test.go) at d=768 cosine:
N=16 SingleAdd 283µs/op → BatchAdd 170µs/op 1.66×
N=128 SingleAdd 7.9ms/op → BatchAdd 7.5ms/op 1.05×
N=1024 SingleAdd 87.5ms/op → BatchAdd 83.4ms/op 1.05×
Win is biggest at staffing-driver batch sizes (N=16) where
per-call lock + validation overhead is a meaningful fraction. At
larger N the inner HNSW neighborhood search per insert dominates,
which is the load-bearing finding for Option B (sharded indexes):
the throughput ceiling lives inside the library, not at the lock,
so sharding to N parallel Graphs is the only path to true
concurrent-Add throughput.
g1, g1p, g2 smokes all PASS post-change.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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