unsloth/docker/fetch_llama_prebuilt.py
2026-07-19 15:32:20 +00:00

228 lines
9.9 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-Present the Unsloth team. See /studio/LICENSE.AGPL-3.0
"""Bake a pinned llama.cpp prebuilt into the Docker image, deterministically.
Why not studio/install_llama_prebuilt.py: that resolver selects a bundle for
the CURRENT host (nvidia-smi, /proc/driver/nvidia, installed CUDA runtime),
which is exactly what an image build must not do -- a B200 build host, a
GPU-less CI runner and a laptop must all produce byte-identical layers. This
script instead pins release + asset by build target only:
amd64 -> app-<tag>-linux-x64-cuda12-portable.tar.gz (sm_70..sm_120)
arm64 -> app-<tag>-linux-arm64-cuda13-portable.tar.gz (sm_90..sm_121)
The portable bundles carry their own CUDA runtime libs and dynamically load
the CUDA backend at runtime, so the same binaries also run CPU-only.
Every download is sha256-verified against the release's own
llama-prebuilt-sha256.json. The converter (convert_hf_to_gguf.py) and its
gguf-py library are hydrated from the SAME release's source tarball so the
tensor mappings match the binaries -- the layout unsloth_zoo's
check_llama_cpp() expects: binaries, converter and gguf-py/ at the install
dir root.
The tag may be the literal "latest" (or empty), in which case the newest
published release of RELEASE_REPO is resolved at build time by following the
/releases/latest redirect (no API token, no API rate limit). Pass a concrete
tag for a reproducible build.
Usage (in the Dockerfile):
python fetch_llama_prebuilt.py <tag|latest> <targetarch> <install_dir>
"""
import hashlib
import json
import os
import shutil
import subprocess
import sys
import tarfile
import tempfile
import urllib.request
RELEASE_REPO = "unslothai/llama.cpp"
def resolve_latest_tag(repo: str) -> str:
# Follow the /releases/latest redirect: no API token or rate limit.
url = f"https://github.com/{repo}/releases/latest"
request = urllib.request.Request(url, headers = {"User-Agent": "unsloth-docker-build"})
with urllib.request.urlopen(request, timeout = 60) as response:
final_url = response.geturl()
marker = "/releases/tag/"
if marker not in final_url:
raise SystemExit(
f"FAIL: could not resolve latest release of {repo} (landed on {final_url})"
)
return final_url.rsplit(marker, 1)[1].strip("/")
def fetch(url: str, dest: str) -> None:
request = urllib.request.Request(url, headers = {"User-Agent": "unsloth-docker-build"})
with urllib.request.urlopen(request, timeout = 600) as response, open(dest, "wb") as f:
shutil.copyfileobj(response, f, length = 1 << 20)
def sha256_file(path: str) -> str:
digest = hashlib.sha256()
with open(path, "rb") as f:
for chunk in iter(lambda: f.read(1 << 20), b""):
digest.update(chunk)
return digest.hexdigest()
def fetch_verified(base_url: str, name: str, sums: dict, work: str) -> str:
path = os.path.join(work, name)
fetch(f"{base_url}/{name}", path)
expected = sums.get(name, {}).get("sha256")
if not expected:
raise SystemExit(f"FAIL: {name} not listed in llama-prebuilt-sha256.json")
actual = sha256_file(path)
if actual != expected:
raise SystemExit(f"FAIL: sha256 mismatch for {name}: expected {expected}, got {actual}")
print(f"verified {name} sha256={actual[:16]}...")
return path
def extracted_root(extract_dir: str) -> str:
children = os.listdir(extract_dir)
if len(children) == 1 and os.path.isdir(os.path.join(extract_dir, children[0])):
return os.path.join(extract_dir, children[0])
return extract_dir
def main() -> None:
tag, target_arch, install_dir = sys.argv[1], sys.argv[2] or "amd64", sys.argv[3]
if tag in ("", "latest"):
tag = resolve_latest_tag(RELEASE_REPO)
print(f"resolved latest {RELEASE_REPO} release: {tag}")
base_url = f"https://github.com/{RELEASE_REPO}/releases/download/{tag}"
assets = {
"amd64": f"app-{tag}-linux-x64-cuda12-portable.tar.gz",
"arm64": f"app-{tag}-linux-arm64-cuda13-portable.tar.gz",
}
if target_arch not in assets:
raise SystemExit(f"FAIL: unsupported TARGETARCH={target_arch}")
bundle_name = assets[target_arch]
source_name = f"llama.cpp-source-{tag}.tar.gz"
with tempfile.TemporaryDirectory() as work:
sha_path = os.path.join(work, "llama-prebuilt-sha256.json")
fetch(f"{base_url}/llama-prebuilt-sha256.json", sha_path)
sums = json.load(open(sha_path))["artifacts"]
# Binaries: flat tarball, llama-quantize / llama-server / lib*.so at root.
bundle_path = fetch_verified(base_url, bundle_name, sums, work)
bundle_dir = os.path.join(work, "bundle")
os.makedirs(bundle_dir)
with tarfile.open(bundle_path) as tf:
tf.extractall(bundle_dir, filter = "tar")
os.makedirs(install_dir, exist_ok = True)
root = extracted_root(bundle_dir)
for entry in os.listdir(root):
target = os.path.join(install_dir, entry)
shutil.move(os.path.join(root, entry), target)
if os.path.isfile(target) and not entry.startswith("lib") and ".so" not in entry:
os.chmod(target, 0o755)
# Converter + gguf-py from the same-tag source tarball so tensor mappings
# match the binaries (mirrors unsloth_zoo's _hydrate_converter_sources).
source_path = fetch_verified(base_url, source_name, sums, work)
source_dir = os.path.join(work, "source")
os.makedirs(source_dir)
with tarfile.open(source_path) as tf:
tf.extractall(source_dir, filter = "tar")
src_root = extracted_root(source_dir)
converter = os.path.join(src_root, "convert_hf_to_gguf.py")
gguf_py = os.path.join(src_root, "gguf-py")
if not (os.path.isfile(converter) and os.path.isdir(gguf_py)):
raise SystemExit(f"FAIL: source tarball for {tag} is missing converter files")
for script in os.listdir(src_root):
if script.startswith("convert_") and script.endswith(".py"):
shutil.copy2(os.path.join(src_root, script), os.path.join(install_dir, script))
shutil.copytree(gguf_py, os.path.join(install_dir, "gguf-py"), dirs_exist_ok = True)
conversion = os.path.join(src_root, "conversion")
if os.path.isdir(conversion):
shutil.copytree(conversion, os.path.join(install_dir, "conversion"), dirs_exist_ok = True)
# Make the baked marker readable by Studio's freshness check. The tarball keys
# off upstream_tag/source_repo, but the reader wants tag/release_tag/
# published_repo (the install_llama_prebuilt.py schema). setdefault() leaves an
# already-populated tarball untouched; no timestamp, so layers stay identical.
marker_path = os.path.join(install_dir, "UNSLOTH_PREBUILT_INFO.json")
try:
with open(marker_path) as f:
marker = json.load(f)
except (OSError, ValueError):
marker = {}
marker.setdefault("tag", tag)
marker.setdefault("release_tag", tag)
marker.setdefault("published_repo", RELEASE_REPO)
with open(marker_path, "w") as f:
json.dump(marker, f, indent = 2)
f.write("\n")
print(f"marker augmented for freshness: tag={tag} published_repo={RELEASE_REPO}")
# Mirror the install into build/bin/ via hardlinks (zero extra bytes) so
# Studio's setup.sh treats it as a complete local build and skips its
# source-build fallback (which would compile CPU-only llama.cpp over the baked
# CUDA bundle). Hardlinks keep $ORIGIN rpath and avoid a cycle when setup.sh
# relinks the root quantizer to build/bin/llama-quantize.
build_bin = os.path.join(install_dir, "build", "bin")
os.makedirs(build_bin, exist_ok = True)
for entry in os.listdir(install_dir):
source = os.path.join(install_dir, entry)
if os.path.isfile(source) and not os.path.islink(source):
try:
os.link(source, os.path.join(build_bin, entry))
except OSError:
shutil.copy2(source, os.path.join(build_bin, entry))
elif os.path.islink(source):
# Mirror same-dir soname symlinks (libllama.so.0 -> ...); without them
# a binary relinked into build/bin fails $ORIGIN (loader wants soname).
target = os.readlink(source)
dest = os.path.join(build_bin, entry)
if "/" not in target and not os.path.lexists(dest):
os.symlink(target, dest)
# Sanity: the server must run on a GPU-less host (CUDA backend is a dlopen'd
# plugin). Check the quantizer from both roots: setup.sh relinks the root copy
# to build/bin, so build/bin must resolve standalone.
checks = (
# llama-quantize has no --version: healthy run prints usage (rc 0),
# loader failure rc 127.
(os.path.join(install_dir, "llama-server"), "version"),
(os.path.join(install_dir, "llama-quantize"), "usage"),
(os.path.join(build_bin, "llama-quantize"), "usage"),
)
for binary, expect in checks:
out = subprocess.run(
[binary, "--version"],
capture_output = True,
text = True,
timeout = 120,
)
banner = (out.stdout + out.stderr).strip()
print(
os.path.relpath(binary, install_dir),
"->",
banner.splitlines()[0] if banner else "(no output)",
)
if expect not in banner:
raise SystemExit(
f"FAIL: {binary} did not print '{expect}': rc={out.returncode}\n{banner[:400]}"
)
for required in (
"llama-quantize",
"convert_hf_to_gguf.py",
"gguf-py",
"UNSLOTH_PREBUILT_INFO.json",
):
if not os.path.exists(os.path.join(install_dir, required)):
raise SystemExit(f"FAIL: {required} missing from {install_dir}")
print(f"OK: llama.cpp {tag} ({bundle_name}) installed at {install_dir}")
if __name__ == "__main__":
main()