Fix: Pins numpy to an older, non X86_V2 requringing version + updates the migration docs to warn people

docs/migration-v3.md

@@ -341,7 +341,10 @@ citing that these instructions have been present in over 99.7% of CPUs since 200
 
 NumPy is a dependency of the document classifier (via scikit-learn), so any CPU that
 predates SSE4.2 support will crash with `SIGILL` (illegal instruction) when the classifier
-is loaded or trained, regardless of whether AI features are enabled.
+is loaded or trained, regardless of whether AI features are enabled. NumPy is also pulled in
+transitively by `ocrmypdf`'s default page-finalization step (via the `fpdf2` package), which
+runs during normal OCR/archive generation - so affected hardware can crash during ordinary
+document consumption as well, not only during classifier training.
 
 This differs from NumPy's optional SIMD dispatch (e.g. AVX2, AVX512), which is detected and
 selected safely at runtime - the `x86-64-v2` requirement above is a hard floor baked into the
@@ -365,28 +368,64 @@ If this prints nothing, your CPU is affected.
 
 The Celery worker (and potentially the web server) repeatedly crashes and restarts with a
 `SIGILL` error, typically visible in `dmesg`/`journalctl` as a `trap invalid opcode` inside
-`_multiarray_umath...so`. Because the classifier is trained on a periodic schedule
-(hourly, by default), affected instances see intermittent, hard-to-reproduce document
-consumption failures whenever that scheduled task runs and takes down the worker process
-mid-task.
+`_multiarray_umath...so`. This can surface either as an intermittent crash when the
+classifier's periodic training task runs (hourly, by default), or as a `RuntimeError: NumPy
+was built with baseline optimizations... but your machine doesn't support` raised from
+`documents.parsers.ParseError` during OCR of a document being consumed, since `ocrmypdf`
+imports NumPy indirectly through `fpdf2` while finalizing pages.
 
-### Action Required (for affected hardware only)
+### Current mitigation: NumPy is pinned below 2.4
 
-There is no way to make the classifier itself work on such CPUs - it requires an unofficial
-NumPy build with `cpu-baseline=none`, which is not something we can ship. The practical
-path forward is to stop the classifier from ever loading or training, which avoids
-importing NumPy at all:
+Because so much affected hardware is still in active use, Paperless-ngx pins NumPy to
+`<2.4` (currently resolving to the 2.3.x series) rather than requiring affected users to
+work around the problem themselves. This is a **temporary accommodation, not a permanent
+fix** - we don't control NumPy's wheel baseline, and this pin holds back a transitive
+dependency indefinitely.
+
+**Check whether your hardware will keep being supported.** Use the SSE4.2 check under
+[Affected hardware](#affected-hardware) above. If your CPU has SSE4.2, this issue never
+applies to you, now or later - the pin doesn't change anything for you. If your CPU lacks
+SSE4.2, the pin is the only reason Paperless-ngx works for you today, and that protection is
+not indefinite - see below.
+
+**This pin has an expiration date.** NumPy 2.3.x is only
+[supported upstream until 2027-06-08](https://endoflife.date/numpy) under the
+[SPEC 0](https://scientific-python.org/specs/spec-0000/) policy (roughly 24 months from its
+June 2025 release). After that date, 2.3.x stops receiving security fixes, and we will need
+to either drop the pin (reintroducing this crash on affected hardware) or find another way
+forward. If your CPU lacks SSE4.2, plan around that date rather than assuming indefinite
+support - watch the
+[paperless-ngx release notes](https://github.com/paperless-ngx/paperless-ngx/releases) as
+it approaches, since we'll announce there if/when the pin is lifted.
+
+If you build your own image or otherwise manage dependencies independently of our lockfile,
+make sure your own NumPy pin matches (`numpy<2.4`) - nothing stops your build tooling from
+picking up 2.4+ on its own.
+
+### If you're stuck on NumPy 2.4+ (custom builds, or after the pin is eventually dropped)
+
+There is no way to make NumPy 2.4+ itself work on affected CPUs on the official images - it
+requires an unofficial build with `cpu-baseline=none`, which is not something we can ship.
+
+Setting
 
 ```bash
 PAPERLESS_TRAIN_TASK_CRON=disable
 ```
 
-This disables the periodic classifier training task (see
-[`PAPERLESS_TRAIN_TASK_CRON`](configuration.md#PAPERLESS_TRAIN_TASK_CRON)). Automatic
-matching based on the classifier (suggested correspondents, document types, tags, and
-storage paths from trained rules) will no longer be available, but rule-based matching is
-unaffected, and document consumption itself will no longer be at risk of crashing the
-worker.
+disables the periodic classifier training task (see
+[`PAPERLESS_TRAIN_TASK_CRON`](configuration.md#PAPERLESS_TRAIN_TASK_CRON)) and stops the
+classifier itself from ever loading or training. Automatic matching based on the classifier
+(suggested correspondents, document types, tags, and storage paths from trained rules) will
+no longer be available, but rule-based matching is unaffected.
+
+**This setting alone does not fully resolve the issue**, because `ocrmypdf` also imports
+NumPy indirectly (via `fpdf2`) as part of its normal page-finalization step, independent of
+the classifier. On affected hardware, OCR of documents can therefore still crash the worker
+even with the classifier disabled. Advanced users may be able to work around this by building
+a custom image that installs an alternate NumPy build compiled without the `x86-64-v2`
+baseline (e.g. from source with `-Dcpu-baseline=none`), but this is unsupported and not
+something the project can provide guidance for.
 
 ## Database Migrations
 

pyproject.toml

@@ -149,6 +149,12 @@ typing = [
 
 [tool.uv]
 required-version = ">=0.9.0"
+# TEMPORARY: numpy>=2.4 raises the manylinux x86_64 wheel's CPU baseline to
+# x86-64-v2 (SSE4.2+), which crashes on older/embedded CPUs. Pinning below
+# 2.4 keeps that hardware working. numpy 2.3.x is supported upstream until
+# 2027-06-08 (https://endoflife.date/numpy); revisit this pin before then.
+# See docs/migration-v3.md#minimum-cpu-requirements-numpy-baseline
+constraint-dependencies = [ "numpy<2.4" ]
 environments = [
   "sys_platform == 'darwin'",
   "sys_platform == 'linux'",