mxbai-rerank-base-v2 ships a Sigmoid activation and evaluates it in bf16, so
every strongly-relevant candidate rounds to exactly 1.0. Ties then leave the
order to the stable sort, which preserves the incoming hybrid ranking: on 100
t2_finqa retrieval cases the reranker scored MAP 0.661 against 0.659 with no
reranker at all, and 0.742 once the scores separate.
Ask the model for logits and apply the sigmoid here, where it runs in float64.
Scores stay 0-1, matching the cohere, vllm and zeroentropy rerankers.
Also drop the remaining pyright references; the project type-checks with ty.
Add tests for the MCP tools' degradation contracts, malformed WebDAV
multistatus bodies, dry-run poller sweeps including the circuit-open and
discover-failure paths, FS source scheme and symlink handling, docling-serve
zip parsing, and the remaining embedding and reranker helpers. Parametrize
_strip_etag.
Drop the misplaced pragma on the analyze handler, which sat on the return and
left the except uncovered. Add one on the FS symlink OSError guard, which
resolve(strict=False) absorbs for every real link.
reranking.multimodal (vllm provider only) attaches picture bytes to
synthetic picture chunks before rerank; VLLMReranker sends them as
content-parts documents (base64 data URI + description text) in the
same /v1/rerank request as plain text documents.
