release: 0.14.1

CHANGELOG.md

@@ -1,6 +1,8 @@
 # Changelog
 
 ## [Unreleased]
+
+## [0.14.1] - 2026-10-21
 ### Fixed
 - **TabICL compiled new graphs inside requests** (#47): call shapes warmup didn't cover -- tables of ~20k+ rows (differently strided inputs), 1,024+-row regression predicts, and variants that overlapping calls on one worker produce -- each compiled 1-7 graphs inside the request that hit them, 5-25 s on an A100 and ~4x that on prod's A40s, holding the device so other models' calls waited too. On prod, a 5,000 x 500 TabICL fit compiled 3 graphs on every call (25.8 s, `timings_ms` from 0.14.0). Once every backend in a process has warmed up (`serve/factory.finish_warmup`: after all devices of an in-process engine, or a worker process's one), a call no compiled graph fits now runs eagerly instead (`torch.compiler.set_stance("eager_on_recompile")`, process-wide, only where compiled blocks were installed). On an A100: a first 20,000 x 100 fit 12.5 s -> 3.0 s, a first 1,000-row regression predict 1.8 s -> 0.14 s; eager costs ~30% on those families once a compile would have been paid (20,000 x 100 2.3 s compiled vs 2.9 s eager). `TABCTX_COMPILE_AFTER_WARMUP=1` restores compiling them.
 ### Added

README.md

@@ -504,8 +504,8 @@ spillover, multi-replica routing and multi-GPU replicas with a worker
 process per GPU have all shipped and been validated on real GPUs (see
 [CHANGELOG.md](CHANGELOG.md)); 0.14.0 infers the task from the labels,
 accepts missing values, and reports where each request's time went
-(`timings_ms`). Vector's 4x A40 prod node serves 0.13.0 until it is
-updated. Open roadmap items are
+(`timings_ms`); 0.14.1 stops TabICL compiling graphs inside requests
+(#47). Vector's 4x A40 prod node serves 0.14.0 until it is updated. Open roadmap items are
 tracked as GitHub issues labelled `roadmap`. **Read
 [ROADMAP.md](ROADMAP.md) before starting new work** -- it ranks what's
 next and why.

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "tabctx"
-version = "0.14.0"
+version = "0.14.1"
 description = "Serving engine for tabular foundation models (TabICL, TabPFN): fit a table once, keep its encoded context on the GPU, and serve fast repeat predictions to many tenants, with memory-aware admission and multi-GPU placement."
 readme = "README.md"
 license = "Apache-2.0"