Spaces:
Runtime error
Runtime error
fix: magic-byte asset validation and hub repair
Browse files- scripts/bootstrap_assets.py +67 -29
scripts/bootstrap_assets.py
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"""
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Runs before the seeder in the image CMD chain.
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"""
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@@ -13,36 +14,67 @@ from __future__ import annotations
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import os
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from pathlib import Path
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POINTER_MAGIC = b"version https://git-lfs"
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SCAN_DIRS = ("seed-assets", "weights")
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continue
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def main() -> None:
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if not
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print("[bootstrap] all
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return
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repo_id = os.environ.get("SPACE_ID") # injected by Spaces, e.g. "Minifigures/claimflow-api"
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if repo_id is None:
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raise SystemExit(
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f"[bootstrap] {len(
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f"cannot resolve: {[str(p) for p in pointers]}"
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)
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# The image pins offline mode for serving; this one bootstrap step needs the hub.
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@@ -50,11 +82,17 @@ def main() -> None:
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os.environ.pop("TRANSFORMERS_OFFLINE", None)
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from huggingface_hub import hf_hub_download
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for
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print(f"[bootstrap]
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resolved = hf_hub_download(
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if __name__ == "__main__":
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"""Verify runtime binary assets at container start; re-fetch any that are invalid.
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Hugging Face Space builds can deliver repo binaries in surprising states
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(git-LFS pointers, xet pointers, partial materialization) depending on storage
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class — outside our control and version-dependent. Instead of guessing storage
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formats, every asset the app needs is validated by its content magic; anything
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invalid is downloaded through the hub API, which resolves storage correctly.
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Local and compose runs have real files on disk, so this is a no-op.
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Runs before the seeder in the image CMD chain.
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"""
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import os
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from pathlib import Path
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from typing import Callable
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def _png(data: bytes) -> bool:
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return data.startswith(b"\x89PNG\r\n\x1a\n")
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def _dicom(data: bytes) -> bool:
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return len(data) >= 132 and data[128:132] == b"DICM"
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def _torch_zip(data: bytes) -> bool:
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return data.startswith(b"PK")
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def _safetensors(data: bytes) -> bool:
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# 8-byte little-endian header length followed by a JSON header.
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return len(data) > 8 and data[8:9] == b"{"
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REQUIRED: dict[str, Callable[[bytes], bool]] = {
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"seed-assets/clean_ct.png": _png,
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"seed-assets/clean_mri.png": _png,
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"seed-assets/clean_xray.png": _png,
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"seed-assets/tampered_xray.dcm": _dicom,
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"weights/modality_efficientnet_b0.pt": _torch_zip,
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"weights/authenticity_efficientnet_b0.pt": _torch_zip,
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"weights/all-MiniLM-L6-v2/model.safetensors": _safetensors,
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}
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def _invalid_assets() -> list[str]:
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bad: list[str] = []
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for rel, check in REQUIRED.items():
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path = Path(rel)
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if not path.is_file():
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print(f"[bootstrap] MISSING: {rel}", flush=True)
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bad.append(rel)
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continue
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with path.open("rb") as fh:
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head = fh.read(160)
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if not check(head):
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print(
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f"[bootstrap] INVALID: {rel} size={path.stat().st_size} "
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f"head={head[:24].hex()} text={head[:24]!r}",
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flush=True,
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)
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bad.append(rel)
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return bad
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def main() -> None:
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bad = _invalid_assets()
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if not bad:
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print("[bootstrap] all required assets valid; nothing to do", flush=True)
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return
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repo_id = os.environ.get("SPACE_ID") # injected by Spaces, e.g. "Minifigures/claimflow-api"
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if repo_id is None:
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raise SystemExit(
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f"[bootstrap] {len(bad)} invalid assets and SPACE_ID unset; cannot resolve: {bad}"
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)
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# The image pins offline mode for serving; this one bootstrap step needs the hub.
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os.environ.pop("TRANSFORMERS_OFFLINE", None)
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from huggingface_hub import hf_hub_download
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for rel in bad:
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print(f"[bootstrap] fetching from hub: {rel}", flush=True)
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resolved = hf_hub_download(
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repo_id=repo_id, repo_type="space", filename=rel, force_download=True
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)
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Path(rel).write_bytes(Path(resolved).read_bytes())
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still_bad = _invalid_assets()
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if still_bad:
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raise SystemExit(f"[bootstrap] assets still invalid after hub fetch: {still_bad}")
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print(f"[bootstrap] repaired {len(bad)} assets from the hub", flush=True)
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if __name__ == "__main__":
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