Reranker (e.g. BAAI/bge-reranker-v2-m3):
- new codai/api/rerank.py: /v1/rerank scores query↔document pairs with a native
  AutoModelForSequenceClassification cross-encoder (no new dep), cached +
  VRAM/thermal-managed via request_model like embeddings. Returns
  {index, relevance_score(sigmoid), document?} sorted desc, top_n honored.
- router: /v1/rerank added to _INFERENCE_PATHS so the front routes it by model
  capability (transformers → nvidia engine), like /v1/embeddings.
- app: include rerank_router.
- capabilities: add `reranking` + `ocr` fields; detect 'rerank'/'cross-encoder'
  names as reranking.

/v1/models discoverability:
- list_models() now appends enabled OCR engines (paddle/doctr/surya) as
  type='ocr' entries (a node subsystem invoked at /v1/ocr?engine=<id>), so
  clients can discover them.
- a reranker registered in models.json (embedding_models, capabilities
  ['reranking']) surfaces automatically via list_models, like bge-m3.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Mw2KQiswmD69T45fTfjKwW