Mathias a56a4db963 feat(brain_answer): Qwen3-Reranker cross-encoder filter (opt-in) ...

Adds an opt-in cross-encoder rerank step between BM25 retrieval and LLM
synthesis. With BRAIN_RERANKER_URL set, brain_answer retrieves BM25
top-20, scores each excerpt against the query via Qwen3-Reranker on
Ollama, drops the "no" answers, and forwards up to 5 surviving sources
to the LLM. Unset, behaviour is unchanged (BM25 top-10 → LLM).

The reranker is a *filter*, not a re-ranker: Qwen3-Reranker emits a
binary yes/no token under its native chat template, and ties within the
"yes" set are broken by BM25 rank — what got retrieved first stays
ahead.

New package ingestion/internal/reranker:
- Client with URL, Model, HTTP fields.
- New(url, model) returns nil on empty url so callers can treat
  "feature disabled" as a single nil check.
- Score(ctx, query, docs) issues one /api/generate call per doc using
  the Qwen3-Reranker yes/no chat template (verbatim, because the model
  was trained on this exact wording). Parses the first non-think token.

Wiring:
- mcp.Server gains a WithReranker fluent setter to keep NewServer
  signature stable.
- brain_answer's BM25 limit jumps to 20 only when a reranker is wired,
  to give the filter something to do.
- cmd/server/main.go reads BRAIN_RERANKER_URL (+ optional
  BRAIN_RERANKER_MODEL, default dengcao/Qwen3-Reranker-0.6B:F16).

Tests cover: nil-on-empty-url, ordered yes/no scoring, request shape
(model, prompt contents, yes/no template), ambiguous response → 0,
empty doc slice, upstream-error propagation, plus an end-to-end
brain_answer integration that proves only the relevant note reaches the
LLM when noise.md is rejected.

Closes hyperguild#7.

2026-05-18 22:55:46 +02:00

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