Dispatch EAGLE radix bigram builder to tai-kernel

The pure-Python convert_to_bigram_key list comprehension runs on every
cache_finished_req / cache_unfinished_req of every EAGLE radix variant
(radix_cache, hiradix_cache, swa_radix_cache), with token-list lengths
that scale with prompt + output.  Scheduler profiles consistently flag it
as the largest mem_cache-side CPU hotspot.

This commit wires sglang.srt.mem_cache.utils.convert_to_bigram_key to
tai_kernel.radix.convert_to_bigram_key when the extension is importable,
falling back to the pure-Python implementation otherwise.  The tai-kernel
path uses a pybind11 module that calls the CPython C API directly
(PyTuple_New + PyTuple_SET_ITEM with ref-stealing) rather than rebuilding
the list comprehension's bytecode-level tuple allocations.  Measured 1.4x
at n=131k and up to 2.5x for n=1k on g0034 Python 3.11; allocator-bound
at large n because CPython's 2-tuple freelist already amortises the
construction.  The int64-packing follow-up that bypasses tuple allocation
entirely is parked as a separate work item.

Runtime safety:
- The dispatcher catches any first-call JIT compile / runtime failure,
  logs once, and falls through to the pure-Python path for the rest of
  the process — JIT failures must degrade rather than crash a serving
  loop.
- SGLANG_DISABLE_TAI_BIGRAM forces the Python path for bisecting.

Constraint: Output must be a real Python List[Tuple[int, int]] because
downstream radix dicts use the tuples as hashable keys.

Rejected: Pre-allocated tuple slab pool | CPython's per-interpreter 2-tuple
freelist already serves this case, and we cannot recycle tuples that
become radix-tree keys without changing the consumer.

Rejected: int64-packed keys this round | requires changes to RadixKey,
get_child_key_fn, key_match_fn, and EAGLE bigram detection; deserves its
own plan.

Confidence: high

Scope-risk: low

Directive: Keep _python_convert_to_bigram_key reachable; if the tai-kernel
path is ever removed, the EAGLE radix cache must continue to work
unchanged.

Tested: tai-kernel side validated on the cluster
(``python benchmark/radix/benchmark_convert_to_bigram_key.py --check``
prints byte-exact correctness then 1.4-2.5x speedup across sizes
128..131072 on g0034).  The new
``test/registered/unit/mem_cache/test_convert_to_bigram_key.py``
exercises both dispatch paths via SGLANG_DISABLE_TAI_BIGRAM patching.

Not-tested: End-to-end EAGLE serving accuracy + scheduler-time delta on
a real workload.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/sglang/srt/environ.py

@@ -215,6 +215,7 @@ class Envs:
     SGLANG_CP_SHARED_KV_MLA_PREFETCH_MIN_PREFIX_PAGES = EnvInt(-1)
     SGLANG_CP_DRAFT_SHARED_KV = EnvBool(False)
     SGLANG_CP_DRAFT_SHARED_KV_DEBUG = EnvBool(False)
+    SGLANG_DISABLE_TAI_BIGRAM = EnvBool(False)
     SGLANG_TEST_REQUEST_TIME_STATS = EnvBool(False)
     SGLANG_DISABLE_TP_MEMORY_INBALANCE_CHECK = EnvBool(False)
     SGLANG_SIMULATE_ACC_LEN = EnvFloat(-1)