v0.1.0: Apple Silicon support + variable-Ld training fix

Fixed

• Triton kernels no longer recompile or re-autotune per distinct Ld.
  Ld was declared tl.constexpr and (for the autotuned forwards) keyed
  the autotuner — but inside the kernels it only drives a runtime
  range(0, Ld, BLOCK_D) loop, so variable-length training was paying
  one Triton recompile + one autotune sweep per distinct doc length.
  Ld is now a runtime arg and is out of the autotune key across
  forward, soft, smooth, fp8, fused_head, matryoshka, and the
  three backward kernels. Measured 9.3× faster cold start on H100 (4
  distinct Ld values, fp16); steady-state per-call performance
  unchanged. Pinned by tests/test_compile_cache.py.

Added

• Apple Silicon (MPS) — fused simdgroup_matrix Metal kernel for forward
  MaxSim (late_interaction_kernels.metal.maxsim_inference_metal),
  JIT-compiled via torch.mps.compile_shader. Persistent threadgroups serve
  8 consecutive j values per launch, Q is register-resident across every
  (j, d-chunk) pair, and the cooperative D load stages each row through
  per-thread registers so the optional L2-normalize fold pays one threadgroup
  write per element instead of three. Forward-only; never materialises the
  [Nq · Nd · Lq · Ld] similarity tensor.
• MPS dispatch (late_interaction_kernels._mps) — torch.compile-fused
  reference (autograd-aware) for training calls, with the Metal kernel
  selected for inference when its envelope holds (fp16 / bf16, d ≤ 128,
  d % 8 == 0, Nq · Nd ≥ 64 ∧ Ld ≥ 192). Compile-time MSL errors and
  device-side faults fall back transparently to the compile path.
• patch_pylate() MPS routing — pylate.scores.colbert_scores /
  colbert_kd_scores now route MPS tensors through maxsim_mps. The
  maxsim Triton import is now lazy, so pylate_compat is importable on
  machines without Triton (e.g. macOS).
• Env overrides: LIK_FORCE_MPS_BACKEND={metal,compile,reference},
  LIK_DISABLE_COMPILE=1, LIK_MPS_METAL_MIN_BATCH, LIK_MPS_METAL_MIN_LD.
• benchmarks/bench_mps.py benches Metal / torch.compile / eager
  side-by-side and reports metal vs eager, metal vs compile, and
  compile vs eager ratios. Apple M4 fp16: 1.9–3.2× over eager
  (1.1–2.0× over torch.compile) on realistic inference shapes.
• benchmarks/bench_flash_maxsim.py is back in the runner script and the
  documentation; pinned to flash-maxsim==0.2.0 so the published numbers
  are reproducible.
• 87 new MPS tests across tests/test_mps.py, tests/test_mps_metal.py,
  and tests/test_pylate_compat_mps.py (parity, masks, autograd, dispatch
  fallbacks, env overrides, KD layout, PyLate routing).

Changed

• MaxSimScorer / _score() now raises an explicit ValueError when
  Q.device != D.device instead of silently dropping through to the eager
  reference and surfacing an opaque RuntimeError from torch.matmul —
  same contract retrieve() already enforced.
• docs/benchmarks.md Apple Silicon section rewritten with the Metal
  numbers, the dispatch heuristic, and the headline metal vs eager ratio.
• Minimum Python is now 3.10 (was 3.9). pyproject.toml bumps
  requires-python = ">=3.10", the Python classifiers, and
  tool.ruff.target-version = "py310". uv.lock regenerated; the CI matrix
  was already 3.10 / 3.11 / 3.12.

Removed

• All from __future__ import annotations lines across the package, tests,
  benchmarks, and examples (67 files). Annotations now use the native PEP 604
  / PEP 585 syntax (X | Y, list[X], dict[K, V]) that Python 3.10
  supports at runtime — no compatibility shim needed.

Fixed

• patch_pylate() previously gated on q.is_cuda and silently fell through
  to PyLate's reference implementation for MPS tensors. Replaced with a
  per-call _device_path(Q, D) → {"cuda", "mps", None} switch so Mac users
  get the same one-liner upgrade as CUDA users.
• benchmarks/results/ is now .gitignored; benchmark outputs are no
  longer tracked in version control.
• MPS torch.compile path no longer trips the inductor symbolic-shape
  bug. On torch 2.8 / nightly, MPS inductor fails to lower
  S.max(dim=-1) when the reduction axis is symbolic
  (cannot determine truth value of Relational: s12 <= 1024 from
  codegen_iteration_ranges_entry). Switched the compile call from
  dynamic=True to dynamic=False so PyTorch's dynamo cache transparently
  recompiles per (Nq, Nd, Lq, Ld) tuple instead — fine for typical
  inference where shapes are stable, and shape-varying workloads can fall
  back to the Metal kernel. Unblocks the 28 MPS tests that were skipped on
  this bug; 167 / 167 pass on macOS with no skips on the dispatch /
  metal / pylate_compat_mps suites.
• README.md header restored. The Python-3.10 bump (#24) accidentally
  stripped <div align="center">, the badge ![]() image syntax, and
  reformatted a handful of markdown tables — leaving the landing page
  un-centered with plain-text "badges" instead of the shields.io images.
  Restored from the pre-#24 revision and re-applied the
  python-3.10–3.12 shield change. No other content changes.