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.

ingestion/internal/mcp/tools_answer.go

@@ -6,9 +6,35 @@ import (
 	"fmt"
 	"strings"
 
+	"github.com/mathiasbq/hyperguild/ingestion/internal/reranker"
 	"github.com/mathiasbq/hyperguild/ingestion/internal/search"
 )
 
+// rerankResults scores each candidate's excerpt against the query and
+// returns up to top results whose score is positive, preserving the
+// caller's input order (BM25 rank) within the kept set. The reranker is
+// a filter: ties are broken by BM25, not by the reranker's binary score.
+func rerankResults(ctx context.Context, rr *reranker.Client, query string, results []search.Result, top int) ([]search.Result, error) {
+	docs := make([]string, len(results))
+	for i, r := range results {
+		docs[i] = r.Excerpt
+	}
+	scores, err := rr.Score(ctx, query, docs)
+	if err != nil {
+		return nil, err
+	}
+	kept := make([]search.Result, 0, top)
+	for i, r := range results {
+		if scores[i] > 0 {
+			kept = append(kept, r)
+		}
+		if len(kept) == top {
+			break
+		}
+	}
+	return kept, nil
+}
+
 const (
 	answerSystemPrompt = `You are a knowledge assistant. Answer the question using ONLY the provided sources.
 Cite source file paths inline when referencing specific content.
@@ -35,10 +61,22 @@ func (s *Server) brainAnswer(ctx context.Context, args json.RawMessage) (json.Ra
 		return nil, fmt.Errorf("query is required")
 	}
 
-	results, err := search.Query(s.brainDir, search.QueryOptions{Query: a.Query, Limit: 10})
+	// With reranker disabled: BM25 top-10 straight to the LLM.
+	// With reranker enabled: BM25 top-20 → cross-encoder filter → top-5.
+	bm25Limit := 10
+	if s.reranker != nil {
+		bm25Limit = 20
+	}
+	results, err := search.Query(s.brainDir, search.QueryOptions{Query: a.Query, Limit: bm25Limit})
 	if err != nil {
 		return nil, fmt.Errorf("search: %w", err)
 	}
+	if s.reranker != nil && len(results) > 0 {
+		results, err = rerankResults(ctx, s.reranker, a.Query, results, 5)
+		if err != nil {
+			return nil, fmt.Errorf("rerank: %w", err)
+		}
+	}
 	if len(results) == 0 {
 		return json.Marshal(map[string]any{
 			"answer":  "No relevant content found in brain.",