feat: musicgen + embeddings/rerank surfaces (ADR-0021, ADR-0022)

- NEW musicgen leaf package: blocking Generate over ACE-Step's async job
  queue (release_task -> poll query_result -> fetch file, all via
  /upstream); tolerant envelope parsing, double-encoded result handled
- NEW embeddings leaf package: EmbedModel + RerankModel as separate mints
  (two server instances on the host, llama.cpp #20085); InstructedQuery
  helper for Qwen3-style query/document asymmetry
- provider/llamaswap: /v1/embeddings + /v1/rerank clients with strict
  validation (index-ordered vectors, count mismatch and out-of-range
  index are hard errors; rerank sorted descending, minimal parser)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

docs/adr/0022-embeddings-rerank-interface.md

@@ -0,0 +1,41 @@
+# ADR-0022: embeddings + rerank interface
+
+Status: Accepted (2026-07-12)
+
+## Context
+
+majordomo had no embedding or reranking surface at all. The llama-swap host
+now runs two persistent CPU-only llama-server members (Qwen3-Embedding-0.6B
+via `/v1/embeddings`, bge-reranker-v2-m3 via `/v1/rerank`), and mort wants a
+reranking stage in memory retrieval with embedding-backed retrieval as a
+later step.
+
+## Decision
+
+- New `embeddings` leaf package with TWO half-surfaces, split like audio's
+  Speech/Transcription: `EmbedModel`/`EmbedProvider` and
+  `RerankModel`/`RerankProvider`. They are separate mints because on the
+  reference host they are two DIFFERENT server instances — llama-server with
+  `--embeddings` and `--rerank` together returns all-zero embeddings
+  (llama.cpp #20085) — and because rerankers are cross-encoders, not
+  embedders.
+- `EmbedResult.Vectors [][]float32` in input order (provider must order by
+  the response's `index`, never trust wire order). No `dimensions` param:
+  llama-server doesn't implement it; Matryoshka truncation is caller-side.
+- `InstructedQuery(task, query)` helper encodes the instruction-aware
+  asymmetry (queries wrapped, documents bare) so call sites can't silently
+  degrade retrieval by forgetting the prefix.
+- `RerankResult` sorted by descending score; parser reads ONLY
+  `results[].index` and `results[].relevance_score` because llama-server
+  documents the shape as subject to change. Scores are model-specific —
+  comparable within one response only.
+
+## Consequences
+
+- Callers get vectors/scores with strict validation (count mismatch, index
+  out of range, empty vector are hard errors — a silently missing vector is
+  a retrieval bug factory).
+- llama-server's rerank scoring has open correctness issues for some models
+  (llama.cpp #16407); consumers must validate against a fixture before
+  trusting scores in production (mort gates its memory-rerank convar on
+  exactly that).