0.1.0

• Add Choice, Score, Noul, Request, Response and their answer types
  as frozen, validated dataclasses (decide/types.py).
• Add Client/AsyncClient with an ordered backend fallback chain,
  confidence gating via Gate, Client.from_env/AsyncClient.from_env
  environment-based configuration, and decide_batch with partial-failure
  reporting through AllBackendsFailed.
• Add six backends: typesafe (TypeSafe/Jev HTTP API), openrouter
  (OpenRouter Decisions endpoint), laya (local PyTorch), laya_mlx
  (local MLX, Apple Silicon), crossencoder (any sentence-transformers
  CrossEncoder, with generic and KaLM-Jev templates), and llm (JSON-prompted
  fallback over any OpenAI-compatible chat-completions server).
• Add a Jev/TypeSafe wire-compatible HTTP server (decide serve, the
  server extra) exposing POST /v1/systemone, GET /health and
  GET /v1/models over any configured backend chain.
• Add a command line interface: decide ask, decide backends, decide serve.

Known limitations

• LLM emulation (llm backend) probabilities are self-reported by the
  model, not measured or calibrated.
• CrossEncoder (crossencoder backend) outputs are normalized scores
  (softmax/sigmoid over raw logits), not calibrated probabilities.
• AsyncClient.decide_batch calls each backend's adecide concurrently
  per request; it does not use a backend's batch path.
• The mlx extra (laya_mlx backend) needs Python 3.11 or newer.