GPU eval (hybrid+rerank, RERANK_URL=http://10.10.1.65:8082):
MRR=0.672 Recall@5=0.638 nDCG@5=0.621 (35 queries, 1 transient
500, otherwise clean)
Quality identical to the CPU rerank run as expected — only latency
changed (single rerank call dropped from ~23s to ~0.7-1.5s on the
Tesla P4). Per-query report at eval/results/with_rerank_gpu.md.
CLI parser fix: `--retrievers dense+rerank,hybrid+rerank` now
correctly wires the dense+rerank variant. Previously only literal
"rerank" (without prefix) matched the dense+rerank branch, so
combined-retriever runs silently dropped dense+rerank.
(Note: the eval's RerankedRetriever does 50 individual Chroma `get`
calls per query to fetch chunk text by (source, source_key); this
adds ~15s per query of pure SQLite lookup overhead. Not a production
concern — docs_mcp/server.py's _rerank_pool reranks docs already in
the dense pool, no extra Chroma round-trips. Worth tightening the
eval-side impl on a later pass.)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
