mirror of
https://github.com/snapotter-hq/SnapOtter.git
synced 2026-08-03 07:46:42 +02:00
SnapOtterandGitHub
d10d0f544f
A release-readiness QA pass over the whole product. The commits split into defects a user would hit and gates that were reporting green while measuring nothing. ## Fixes that change behaviour Rate limiting was bypassable on every install: TRUST_PROXY defaulted to true, so request.ip came from a client-set header and a forged X-Forwarded-For got past the login limiter. The default is now a private-network trust list. A transient Postgres outage stranded in-flight jobs, leaving finished output on disk with no row pointing at it. A reconciler now resolves those rows and adopts the bytes rather than dropping the work. A Redis connection that moved to a new address wedged every read-blocked consumer, so completions stopped signalling while health still answered 200. Socket timeouts plus subscriber pings recover it. Installing more than one AI bundle left the shared venv multi-versioned and silently broke three tools. The installer now reconciles distributions to one version each. Converting an image to JXL at quality 1 through 4 returned a 500, because libjxl 0.7 rejects the distance those values compute. The quality is floored at what the encoder honours. A missing ffmpeg was also reported to the user as a corrupt upload; it now says the engine is unavailable. RAW uploads reached an unpatched LibRaw on arm64, so it is built from source at 0.22.2, and the release scan was split so it can fail on an unfixed critical instead of hiding it behind ignore-unfixed. ## Gates that could not fail Two mutation lanes ran zero mutants because Stryker crawled the gitignored docs build; coverage discarded its whole report on any failing test; the lint gate skipped root tests, scripts, and two workspaces; and several generated matrices counted a host missing ffmpeg as a passing tool. Each now measures what it claims. Full evidence and the outstanding release items are tracked locally and are not part of this branch.
102 lines
4.3 KiB
Python
102 lines
4.3 KiB
Python
"""Gate runtime model downloads behind an explicit opt-in.
|
|
|
|
Models normally arrive through user-initiated feature bundle installs
|
|
(install_feature.py), and the resolvers in the AI scripts always prefer those
|
|
bundled files. If a model is missing, the runtime fails closed instead of
|
|
fetching mutable content. Operators may explicitly opt into public model
|
|
fallback downloads with SNAPOTTER_ALLOW_MODEL_DOWNLOAD=1.
|
|
"""
|
|
import os
|
|
|
|
|
|
def downloads_allowed():
|
|
"""Return True only when runtime downloads are explicitly enabled.
|
|
|
|
Unknown values remain fail-closed to avoid enabling network access through
|
|
a typo or an inherited environment setting.
|
|
"""
|
|
return os.environ.get("SNAPOTTER_ALLOW_MODEL_DOWNLOAD", "0").lower() in ("1", "true")
|
|
|
|
|
|
def ensure_download_allowed(what):
|
|
"""Raise a clear, actionable error when runtime downloads are disabled."""
|
|
if downloads_allowed():
|
|
return
|
|
raise RuntimeError(
|
|
f"{what} is missing and automatic downloads are disabled. Reinstall "
|
|
"the feature bundle from Settings, or explicitly set "
|
|
"SNAPOTTER_ALLOW_MODEL_DOWNLOAD=1 to permit runtime downloads."
|
|
)
|
|
|
|
|
|
def link_bundled_weight(link_path, target_path):
|
|
"""Best-effort: make link_path resolve to an installed bundle file.
|
|
|
|
gfpgan and codeformer-pip hardcode weight paths relative to the process
|
|
cwd, while the feature bundles install those weights under MODELS_PATH.
|
|
Symlinking the expected path to the bundled file lets the libraries find
|
|
the weight without downloading. Returns True when link_path exists
|
|
afterwards (already present, or successfully linked).
|
|
"""
|
|
if os.path.exists(link_path):
|
|
return True
|
|
if not os.path.exists(target_path):
|
|
return False
|
|
try:
|
|
parent = os.path.dirname(link_path)
|
|
if parent:
|
|
os.makedirs(parent, exist_ok=True)
|
|
os.symlink(target_path, link_path)
|
|
except OSError:
|
|
return os.path.exists(link_path)
|
|
return True
|
|
|
|
|
|
GFPGAN_HELPER_WEIGHTS = ("detection_Resnet50_Final.pth", "parsing_parsenet.pth")
|
|
|
|
|
|
def prepare_gfpgan_helper_weights(models_base):
|
|
"""Resolve GFPGAN's cwd-relative facexlib helper weights offline.
|
|
|
|
gfpgan 1.3.x hardcodes FaceRestoreHelper(model_rootpath="gfpgan/weights"),
|
|
a path relative to the process cwd, and facexlib downloads any file
|
|
missing from it (GitHub release URLs). The feature bundles install those
|
|
weights under <models>/gfpgan/facelib, so link them into the expected
|
|
location; when a weight cannot be resolved locally, strict offline mode
|
|
errors instead of downloading.
|
|
"""
|
|
for fname in GFPGAN_HELPER_WEIGHTS:
|
|
link = os.path.join("gfpgan", "weights", fname)
|
|
target = os.path.join(models_base, "gfpgan", "facelib", fname)
|
|
if not link_bundled_weight(link, target):
|
|
ensure_download_allowed(f"GFPGAN helper weight {fname}")
|
|
|
|
|
|
def prepare_codeformer_weights(models_base):
|
|
"""Resolve codeformer-pip's cwd-relative weights offline.
|
|
|
|
codeformer-pip 0.0.4 downloads four weights into a cwd-relative
|
|
CodeFormer/weights/ tree at import time of codeformer.app -- unconditionally,
|
|
even though this app calls inference_app with background_enhance=False and so
|
|
never uses the RealESRGAN background upsampler (RealESRGAN_x2plus.pth). All
|
|
four ship in the upscale-enhance bundle and are linked here from models_base
|
|
so the import never triggers a download; strict offline mode then works.
|
|
"""
|
|
expected = {
|
|
os.path.join("CodeFormer", "weights", "CodeFormer", "codeformer.pth"): os.path.join(
|
|
models_base, "codeformer", "codeformer.pth"
|
|
),
|
|
os.path.join("CodeFormer", "weights", "facelib", "detection_Resnet50_Final.pth"): os.path.join(
|
|
models_base, "gfpgan", "facelib", "detection_Resnet50_Final.pth"
|
|
),
|
|
os.path.join("CodeFormer", "weights", "facelib", "parsing_parsenet.pth"): os.path.join(
|
|
models_base, "gfpgan", "facelib", "parsing_parsenet.pth"
|
|
),
|
|
os.path.join("CodeFormer", "weights", "realesrgan", "RealESRGAN_x2plus.pth"): os.path.join(
|
|
models_base, "realesrgan", "RealESRGAN_x2plus.pth"
|
|
),
|
|
}
|
|
for link, target in expected.items():
|
|
if not link_bundled_weight(link, target):
|
|
ensure_download_allowed(f"CodeFormer weight {os.path.basename(link)}")
|