unsloth/studio/install_llama_prebuilt.py
Daniel Han cad8c6ad05
Add AMD ROCm/HIP support across installer and hardware detection (#4720)
* Add ROCm detection to install.sh and expand shell tests

Add AMD ROCm GPU detection to get_torch_index_url() in install.sh.
When nvidia-smi is not found, probe for ROCm via amd-smi, /opt/rocm
version file, hipconfig, dpkg-query, and rpm.

Includes validation guard for malformed _rocm_tag, Debian epoch prefix
stripping, ROCm 7.2+ cap to rocm7.1 index, bitsandbytes AMD install,
and status messaging. Shell tests expanded to 23 cases.

Co-authored-by: Daniel Han <danielhanchen@gmail.com>

* Add ROCm torch reinstall support to install_python_stack.py

Add _detect_rocm_version() and _ensure_rocm_torch() to detect when a
Linux host has ROCm but the venv received CPU-only torch, and reinstall
with the correct ROCm wheels. Covers ROCm 6.0 through 7.1 with a
30-second timeout on the torch GPU probe subprocess.

Co-authored-by: Daniel Han <danielhanchen@gmail.com>

* Add ROCm support to llama.cpp prebuilt installer

Add has_rocm field to HostInfo, extend detect_host() to probe for ROCm
via hipcc/amd-smi/rocm-smi/ROCM_PATH, and route ROCm hosts to upstream
prebuilts (Linux ROCm 7.2 prebuilt with source fallback, Windows HIP
prebuilt with CPU fallback). Add linux-rocm and windows-hip install
kinds to runtime_patterns_for_choice().

Co-authored-by: Daniel Han <danielhanchen@gmail.com>

* Add IS_ROCM hardware flag and fix AMD error message

Add IS_ROCM flag to hardware.py detect_hardware() (set when
torch.version.hip is present, DeviceType stays CUDA). Export IS_ROCM
from __init__.py. Add "rocm" key to get_package_versions().

Replace "We do not support AMD" error in tokenizer_utils.py with a
helpful message pointing to ROCm installation docs.

Co-authored-by: Daniel Han <danielhanchen@gmail.com>

* Add comprehensive ROCm support test suite (68 tests)

Add tests/studio/install/test_rocm_support.py covering all ROCm code
paths across install_llama_prebuilt.py, install_python_stack.py,
hardware.py, tokenizer_utils.py, and install.sh. All tests use mocks
and run without AMD hardware.

Covers: asset selection (11), runtime patterns (5), HostInfo (4),
ROCm version detection (9), torch reinstall (9), index mapping (8),
hardware flag (8), tokenizer message (2), install.sh structure (10),
and live regression (1).

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* Harden ROCm support: probe error handling, version cap, validation

Address review findings from 8 independent reviewers:

- Wrap _ensure_rocm_torch() torch probe in try/except for
  TimeoutExpired and OSError so a hung or broken torch import does not
  crash the installer (8/8 reviewers flagged this)
- Add torch>=2.4,<2.11.0 version cap to the ROCm reinstall path to
  prevent installing unsupported torch 2.11.0 from the rocm7.1 index
- Use with-statement for file reads in _detect_rocm_version() to avoid
  resource leaks
- Handle ROCM_PATH="" correctly (use `or "/opt/rocm"` instead of
  default parameter to avoid relative path resolution)
- Strengthen shell validation guard from rocm[0-9] to rocm[1-9] to
  reject rocm0.x tags that would produce nonexistent PyTorch index URLs
- Switch shell version cap from blocklist to allowlist (rocm6.*|rocm7.0*
  |rocm7.1* pass through, everything else caps to rocm7.1) so future
  ROCm 10+ does not fall through to a nonexistent index
- Add sorted() to _ROCM_TORCH_INDEX lookup for defensive ordering
- Fix test_probe_timeout_handled: replace zero-assertion test with
  proper assertions verifying reinstall proceeds after timeout

* Clean up rocm_paths list construction in detect_host()

Filter None from the ROCM_PATH env var lookup at list construction time
instead of relying on the inline `if p` guard in the any() call.

* Require actual AMD GPU presence before selecting ROCm paths

All 8 reviewers across 2 cycles independently flagged that ROCm
detection used toolkit/filesystem hints (hipcc, /opt/rocm, rocm-core)
as a proxy for GPU presence, which would misroute CPU-only or NVIDIA
hosts that happen to have ROCm tools installed.

Now all 3 detection points (install.sh, install_python_stack.py,
install_llama_prebuilt.py) probe for an actual AMD GPU before
entering the ROCm path:

- install.sh: check rocminfo for gfx* GPU names, or amd-smi list
  for device rows, before version detection
- install_python_stack.py: new _has_rocm_gpu() function probes
  rocminfo and amd-smi list before _ensure_rocm_torch() proceeds
- install_llama_prebuilt.py: detect_host() probes rocminfo/amd-smi
  list instead of just checking tool existence or directory paths

Also:
- Shell test mock amd-smi now handles "list" subcommand
- Python tests updated to mock _has_rocm_gpu where needed
- Added test_no_gpu_with_rocm_tools_skips to verify the new guard
- Test index lookups now use sorted() to match production code

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* Harden hipconfig version parsing and torch probe compatibility

- Add parts[1].isdigit() check in hipconfig version parsing to handle
  versions like "6.3-HIP" where the minor component has non-numeric
  suffix (strip "-" prefix before int() conversion)
- Use getattr() in torch probe subprocess to safely handle old or
  custom torch builds that may lack torch.version.hip/cuda attributes

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* Strengthen AMD GPU detection and add NVIDIA precedence guard

- Change amd-smi list detection from any-non-empty-output to requiring
  "gpu" marker in output, matching the shell-side NR>1 check. Prevents
  false positives from header-only amd-smi list output.
- Add nvidia-smi check at the top of _ensure_rocm_torch() so mixed
  AMD+NVIDIA hosts preserve NVIDIA precedence (matching install.sh and
  install_llama_prebuilt.py behavior).
- Apply the same amd-smi marker fix to install_llama_prebuilt.py
  detect_host() for consistency.

* Add Windows-specific ROCm/HIP detection in detect_host()

The previous detect_host() ROCm check used rocminfo and amd-smi list
which are Linux-only tools. On Windows, has_rocm would always be False,
making the Windows HIP prebuilt path at line 1794 unreachable.

Now detect_host() uses platform-specific detection:
- Linux: rocminfo (check for gfx GPU names) or amd-smi list
- Windows: hipinfo.exe, amd-smi, or amdhip64.dll on PATH

This allows Windows AMD users to get the HIP prebuilt binary instead
of silently falling through to the CPU prebuilt.

* Add AMD ROCm gaps: Mamba/SSM source builds, GPU monitoring, Windows messaging, RDNA expansion

- worker.py: Add HIP detection to causal-conv1d/mamba-ssm probe, check
  for hipcc before ROCm source builds, improve status messages and error
  reporting, add timeout and uv support for the source build fallback
- amd.py: New AMD GPU monitoring module via amd-smi metric --json,
  mirroring nvidia.py structure (utilization, temperature, power, VRAM)
- hardware.py: Branch to amd.py when IS_ROCM is True for GPU utilization,
  visible GPU queries, and physical GPU count
- install_python_stack.py: Detect AMD GPUs on Windows and warn that
  ROCm-enabled PyTorch must be installed manually
- kernels/utils.py: Expand is_rdna() to cover RDNA2 (gfx1030-1032),
  RDNA3 (gfx1102-1103), RDNA3.5 (gfx1150-1152) alongside existing entries
- tests: Add 32 new tests covering all changes (95/95 pass)

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* Harden ROCm detection, fix VRAM heuristic, and expand RDNA2 coverage

- Windows ROCm detection: validate actual GPU presence via hipinfo/amd-smi
  output markers instead of just checking tool existence on PATH
- _ensure_rocm_torch: validate nvidia-smi actually reports a GPU before
  giving NVIDIA precedence (fixes AMD-only hosts with stale NVIDIA tools)
- amd.py _parse_numeric: handle dict-shaped metric objects from newer
  amd-smi versions ({"value": 10, "unit": "W"}) and strip MiB/GiB units
- amd.py VRAM heuristic: raise threshold from 100k to 10M to correctly
  handle MI300X (192 GB = 196608 MB) and other high-VRAM GPUs
- amd.py visible GPU: use AMD-reported GPU IDs instead of enumerate index
  so non-dense sets like CUDA_VISIBLE_DEVICES=1,3 report correctly
- install.sh: add ROCm <6.0 minimum version guard (no PyTorch wheels
  exist for older versions); fix rocm7.1* glob to not match rocm7.10+
- is_rdna: add gfx1033-1036 for RDNA2 mobile GPUs (RX 6600M etc.)
- worker.py: increase ROCm source build timeout from 600s to 1800s;
  fix success log message for ROCm source builds
- Tests: update mocks for _has_usable_nvidia_gpu, add RDNA2 target asserts

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* Add HIP_VISIBLE_DEVICES support, unit-aware VRAM parsing, Windows GPU validation

- hardware.py: check HIP_VISIBLE_DEVICES and ROCR_VISIBLE_DEVICES on ROCm
  before falling back to CUDA_VISIBLE_DEVICES, so multi-GPU AMD setups with
  HIP-specific env vars report the correct visible device set
- amd.py: add _parse_memory_mb() that reads "unit" from dict-shaped amd-smi
  JSON (e.g. {"value": 192, "unit": "GiB"}) and converts to MB correctly;
  fixes MI300X VRAM misreported as 0.19 GB instead of 192 GB
- install_python_stack.py: Windows AMD warning now validates actual GPU
  presence via hipinfo/amd-smi output markers before printing
- install_llama_prebuilt.py: restore amdhip64.dll fallback for Windows HIP
  detection after tool-based checks, so Windows HIP installs without CLI
  tools on PATH are still detected
- hardware.py: fix IS_ROCM comment to accurately describe its role

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* Fix HIP_VISIBLE_DEVICES empty-string handling in GPU visibility spec

Use explicit None checks instead of Python `or` operator when reading
HIP_VISIBLE_DEVICES / ROCR_VISIBLE_DEVICES, so that an empty string
("") is correctly honored as "no visible GPUs" rather than silently
falling through to CUDA_VISIBLE_DEVICES on mixed ROCm+CUDA systems.

* Fix IS_ROCM test assertion for multi-line formatting

* Cap torchvision/torchaudio versions, remove amdhip64.dll fallback, fix visible GPU count

- Cap torchvision<0.26.0 and torchaudio<2.11.0 alongside torch<2.11.0 in
  both install.sh and install_python_stack.py to prevent resolver from
  selecting incompatible companion packages from ROCm wheel index
- Remove amdhip64.dll fallback in Windows ROCm detection (DLL presence
  without hipinfo/amd-smi is not proof of GPU existence)
- Fix get_visible_gpu_count() to use _get_parent_visible_gpu_spec() which
  respects HIP_VISIBLE_DEVICES/ROCR_VISIBLE_DEVICES on ROCm hosts

* Attribute is_rdna() RDNA2/3/3.5/4 expansion to PR #4428

The is_rdna() expansion to cover RDNA2 (gfx1030-1036), RDNA3
(gfx1100-1103), RDNA3.5 (gfx1150-1152), and RDNA4 (gfx1200-1201)
architectures is based on the original work from PR #4428.

Co-authored-by: GoldenGrapeGentleman <yueyuan@amd.com>
Co-authored-by: billishyahao <bill.he@amd.com>

* Support AMD Radeon for studio (#4770)

Co-authored-by: Iswarya Alex <iswarya.alex@amd.com>

* Remove ROCm test files from main PR

Move test_rocm_support.py and shell test additions to a separate PR
to keep the main ROCm support PR focused on implementation changes.

* Fix installer and hardware detection issues for PR #4720

- Fix empty _tri_arg passed to uv pip install in Radeon path (causes
  "Empty field is not allowed for PEP508" error)
- Fix Radeon fallback: use ROCm index instead of CPU-only when
  repo.radeon.com is unreachable (TORCH_INDEX_URL already has ROCm)
- Use $TORCH_CONSTRAINT in fallback paths instead of hardcoded strings
- Fix _pick_radeon_wheel: relax suffix to match manylinux_2_28_x86_64
  wheels (AMD Radeon repo does not use bare linux_x86_64 platform tag)
- Fix IS_ROCM export: use __getattr__ so callers always see the live
  value after detect_hardware() runs
- Fix apply_gpu_ids: set HIP_VISIBLE_DEVICES and ROCR_VISIBLE_DEVICES
  on ROCm so _get_parent_visible_gpu_spec picks up narrowed GPU set
- Fix _parse_memory_mb: distinguish GB (1000 MB) from GiB (1024 MiB)
- Add amd-smi version as a fallback in _detect_rocm_version
- Fix trailing whitespace and missing newline at EOF in install.sh

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Fix GPU detection false positives and add missing health groups

- Fix _has_rocm_gpu() false positive: require "GPU: <number>" data rows
  from amd-smi list, not just header containing "gpu"
- Apply same fix in detect_host() in install_llama_prebuilt.py
- Add runtime_payload_health_groups for linux-rocm and windows-hip so
  partial/corrupt ROCm/HIP prebuilt installs are properly detected
- Add bitsandbytes install to Radeon fallback paths (was only in the
  success path, skipped when repo.radeon.com was unreachable)
- Keep DEVICE/CHAT_ONLY as direct imports in __init__.py (matching main)
  and only use __getattr__ for IS_ROCM

* Fix _ensure_rocm_torch and Windows AMD warning false positives

- _ensure_rocm_torch: only skip when HIP is already present, not for
  CUDA builds (which are unusable on AMD-only hosts). Fixes the case
  where a venv has a stale CUDA wheel and the repair step is skipped.
- Windows AMD warning: use GPU data row check (same as Linux fix) to
  avoid false positives from amd-smi list header-only output.

* Fix amd-smi GPU detection for GPU[N] output format

Older amd-smi versions output "GPU[0] : Card series: ..." instead of
"GPU: 0". The regex now matches both "GPU: <digit>" and "GPU[<digit>"
formats to detect actual GPU data rows.

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* Harden AMD GPU detection against false positives

- install.sh: replace weak amd-smi list check (awk 'NR>1 && NF') with
  strict pattern matching GPU data rows (/^GPU[[:space:]]*[:\[]/)
- All files: reject rocminfo gfx000 (CPU HSA agent) by requiring
  gfx[1-9] instead of gfx[0-9] in the rocminfo GPU probe
- Fixes false positives on hosts with ROCm tools but no AMD GPU

* Remove duplicate comment from pre-commit merge

* Refactor: deduplicate AMD detection, consolidate bitsandbytes, clean up imports

- Extract _has_amd_rocm_gpu() shell function to avoid duplicating the
  rocminfo/amd-smi GPU detection logic in get_torch_index_url and
  the Radeon auto-detect block
- Consolidate bitsandbytes install into a single case block after torch
  install (was duplicated 4 times across Radeon success/fallback paths)
- Move math and re imports to top of amd.py (were inline in functions)
- Add _smi_query() helper in hardware.py to centralize IS_ROCM backend
  selection for get_gpu_utilization and get_visible_gpu_utilization

Addresses Gemini code review suggestions.

* Fix VRAM parsing for string values and GB/GiB consistency

- Extract unit from string-valued VRAM fields (e.g. "192 GiB") so
  _parse_memory_mb correctly applies the unit multiplier instead of
  treating the value as bare MB
- Treat GB and GiB identically (both as binary x1024) since GPU tools
  including amd-smi use binary units even when labeling them "GB"
- Fixes incorrect VRAM reporting on MI300-class cards (was showing
  ~0.19 GB instead of 192 GB for string-valued outputs)

* Add --no-cache to uv for ROCm HIP source builds

Avoid stale cache artifacts from partial HIP source builds when
uv is used for causal-conv1d/mamba-ssm compilation on ROCm.
The pip path already uses --no-cache-dir; this adds the uv equivalent
(--no-cache) only when is_hip is True.

* Fix critical: initialize _amd_gpu_radeon before case block

_amd_gpu_radeon was only set inside the */rocm*) case arm, so on
NVIDIA/CPU/macOS paths where TORCH_INDEX_URL does not contain "rocm",
the variable was unbound. With set -u (nounset) enabled, this crashes
the installer for every non-AMD user.

Move initialization to before the case block so it is always defined.

* Fix Windows AMD: route has_rocm hosts to HIP prebuilt path

resolve_release_asset_choice was selecting windows-cpu for all Windows
x86_64 hosts including those with has_rocm=True. Windows AMD users
should fall through to resolve_upstream_asset_choice which tries the
HIP prebuilt first. Add "not host.has_rocm" guard to the published
windows-cpu selection.

* Harden ROCm detection, Radeon wheel fallback, and HIP visibility

Addresses review findings from parallel reviewers on PR #4720:

- install.sh: add _has_usable_nvidia_gpu() helper requiring nvidia-smi -L
  to actually list a GPU before treating the host as NVIDIA. Fixes the
  stale-nvidia-smi-on-PATH regression where AMD-only hosts fell into the
  CUDA branch.
- install.sh: fix hipconfig awk blocks to propagate a non-zero exit code
  when the output is not a recognisable version string, so the ||-chain
  continues to dpkg-query / rpm instead of terminating early.
- install.sh: fail-closed on Radeon wheel fallback. When torch,
  torchvision or torchaudio is missing from the Radeon repo for the
  active Python tag, fall back to the standard ROCm index instead of
  silently mixing Radeon wheels with PyPI defaults. Quote all wheel
  arguments individually so wheel filenames cannot be word-split or
  glob-expanded.
- install_llama_prebuilt.py: detect_host() now requires nvidia-smi -L to
  list a GPU before setting has_physical_nvidia. Routes AMD ROCm hosts
  with a broken leftover nvidia-smi to the ROCm path instead of
  misclassifying them as NVIDIA.
- install_llama_prebuilt.py: scan upstream assets for any rocm-<version>
  prebuilt instead of hard-coding rocm-7.2, so ROCm 6.x / 7.0 / 7.1 / 7.3+
  users pick up a matching upstream prebuilt when one exists.
- install_llama_prebuilt.py: validate_server() adds --n-gpu-layers 1 for
  linux-rocm and windows-hip hosts, so new HIP prebuilts are preflighted
  on the GPU path instead of passing validation on CPU only.
- install_llama_prebuilt.py: restore the published windows-cpu fallback
  for AMD Windows hosts without a HIP prebuilt so hash-approved bundles
  are still preferred over the raw upstream CPU asset.
- install_python_stack.py: drop the /opt/rocm / hipcc gate in
  _ensure_rocm_torch() and rely on _has_rocm_gpu(). Runtime-only ROCm
  installs (package-managed minimal installs, Radeon software) that ship
  amd-smi / rocminfo without hipcc can now repair a CPU-only venv via
  "unsloth studio update". Adds an explicit IS_WINDOWS / IS_MACOS guard.
- studio/backend/utils/hardware/amd.py: honour HIP_VISIBLE_DEVICES /
  ROCR_VISIBLE_DEVICES / CUDA_VISIBLE_DEVICES in
  get_primary_gpu_utilization(). A process restricted to GPU 2 now
  reports metrics for GPU 2 instead of physical GPU 0. Tighten the plain
  bytes unit detection to an explicit allowlist.
- studio/backend/utils/hardware/hardware.py: route
  get_backend_visible_gpu_info()'s backend_cuda_visible_devices field
  through a helper that reads HIP_VISIBLE_DEVICES on ROCm. Drop the
  unconditional "(rocm=False)" suffix in apply_gpu_ids() logs.

* Fix round 2 regressions: ROCm validate_server and Windows HIP routing

Follow-up to 810b833b addressing review findings on the first round of
hardening commits:

- install_llama_prebuilt.py validate_server: gate --n-gpu-layers on the
  resolved install_kind instead of host.has_rocm. AMD Windows hosts
  without a HIP prebuilt fall back to windows-cpu and must not be
  validated with GPU layers; thread install_kind through from the
  caller.
- install_llama_prebuilt.py resolve_release_asset_choice: reinstate the
  "not has_rocm" guard on the published windows-cpu bundle so AMD
  Windows hosts reach resolve_upstream_asset_choice() where the new
  HIP prebuilt path lives. Prefer a published windows-hip bundle first
  when one exists, fall through to upstream HIP + upstream CPU
  otherwise.
- install_llama_prebuilt.py detect_host: also set has_physical_nvidia
  when the secondary --query-gpu block confirms a working NVIDIA GPU,
  so older nvidia-smi versions without -L support do not silently skip
  the Linux diagnostics that key off has_physical_nvidia.
- install_llama_prebuilt.py: drop redundant "import re as _re" /
  "import re as _re_rocm" local aliases in favour of the existing
  top-level "import re".
- install_python_stack.py _ensure_rocm_torch: run the AMD
  bitsandbytes install unconditionally after the HIP-torch probe so
  "unsloth studio update" on venvs that already have ROCm torch still
  gains the AMD bitsandbytes build.
- install.sh: add a non-x86_64 early-exit to get_torch_index_url() so
  aarch64 / arm64 Linux hosts do not hit the ROCm wheel index
  (PyTorch only publishes ROCm wheels for linux_x86_64).
- install.sh: add bitsandbytes install to the migrated-environment
  branch so upgrades pick it up for ROCm hosts instead of only the
  fresh-install path.
- install.sh: in the Radeon wheel path, pass version constraints +
  --no-index --find-links to uv instead of explicit wheel URLs so a
  version-compatible torch / torchvision / torchaudio triple is
  resolved, rather than picking the highest-version wheel for each
  package independently.
- studio/backend/utils/hardware/amd.py _first_visible_amd_gpu_id: fall
  through to lower-priority visibility env vars when the first entry
  is malformed (leading comma, all-whitespace first token) instead of
  silently returning GPU 0.

* Fix round 3 findings: x86_64 guard, ROCm version clip, Radeon deps

Address issues surfaced by the round 3 reviewers on top of 8636fa63:

- install_python_stack.py _ensure_rocm_torch: add the same `x86_64`
  guard that install.sh already has. Linux aarch64 / arm64 ROCm hosts
  must skip the repair path entirely; PyTorch only publishes ROCm
  wheels for linux_x86_64, and without this guard
  `unsloth studio update` aborts with a missing-wheel error on non
  x86_64 hosts.
- install_llama_prebuilt.py resolve_upstream_asset_choice: add a
  best-effort _detect_host_rocm_version() helper (reading
  /opt/rocm/.info/version, amd-smi version, hipconfig --version) and
  filter rocm_candidates to entries whose major.minor is <= host
  version. Falls back to the newest candidate only when no compatible
  one exists, so a ROCm 6.4 host downloads rocm-6.4 instead of being
  handed the numerically newest rocm-7.2 bundle (which fails preflight
  and forces a source build).
- install.sh: remove the round 2 --no-index switch from the Radeon
  wheel branch. --no-index forced uv to ignore PyPI entirely, which
  broke transitive dependency resolution (filelock, sympy, networkx,
  jinja2, fsspec, setuptools, typing-extensions, ...) on a fresh venv.
  Restore the round 1 explicit wheel URL invocation but add a
  torch / torchvision / torchaudio version-pair sanity check so a
  mismatched trio (e.g. torch 2.9.1 + torchvision 0.23.0 + torchaudio
  2.9.0) falls back to the standard ROCm index instead of installing a
  broken combination.
- install_python_stack.py _ensure_rocm_torch: restructure the
  "tag is None" path so it no longer short-circuits the bitsandbytes
  install. On a ROCm runtime older than anything in
  _ROCM_TORCH_INDEX, print the "no wheel" warning but still run the
  AMD bitsandbytes install.
- studio/backend/core/training/worker.py: restore the pre-PR
  "no timeout" behaviour for non-HIP causal-conv1d / mamba-ssm source
  builds. The round 2 "timeout = 1800 if is_hip else 300" cap aborts
  slow non-HIP builds (Linux aarch64, unsupported torch/CUDA combos)
  after 5 minutes; omit timeout for the non-HIP branch so the cap
  only applies to ROCm source builds.

* Fix round 4 findings: apply_gpu_ids env inheritance, Radeon X.Y, bitsandbytes gate

Address remaining issues surfaced by the round 4 reviewers:

- studio/backend/utils/hardware/hardware.py apply_gpu_ids: mirror the
  selection into HIP_VISIBLE_DEVICES / ROCR_VISIBLE_DEVICES whenever
  the caller already had a ROCm visibility env var set, not only when
  IS_ROCM has already been set by detect_hardware(). Training and
  inference workers call apply_gpu_ids() before detect_hardware()
  runs, so the old guard would leave a forked ROCm worker with a
  stale HIP_VISIBLE_DEVICES mask that no longer matched the
  narrowed CUDA_VISIBLE_DEVICES selection.
- install.sh get_radeon_wheel_url: accept X.Y ROCm versions in
  addition to X.Y.Z. The `/opt/rocm/.info/version` file and some
  hipconfig versions report only two components, and the Radeon
  repository publishes both rocm-rel-X.Y.Z/ and rocm-rel-X.Y/
  directories, so treating X.Y as invalid caused Radeon hosts to fall
  back to the generic ROCm index even when a matching AMD wheel set
  existed.
- install_python_stack.py _ensure_rocm_torch: only install the AMD
  bitsandbytes build when the venv actually has a ROCm-compatible
  torch (either already present or just installed by this function).
  Previously the bitsandbytes install ran unconditionally, which
  could leave an AMD bitsandbytes layered on top of a CPU/CUDA torch
  on hosts where the ROCm runtime is older than any entry in
  _ROCM_TORCH_INDEX. Also add --force-reinstall so an existing
  CPU/CUDA bitsandbytes is replaced by the AMD build during upgrades.

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* Fix gemini findings: amd-smi metric envelope validation and dict-wrapped GPU id

Two medium-severity defensive fixes from the gemini-code-assist review on
the AMD monitoring backend:

1. _extract_gpu_metrics may return a dict where every value is None when
   amd-smi succeeds (zero exit) but the JSON envelope contains no usable
   fields (error response, unsupported card). The new _has_real_metrics
   helper lets get_primary_gpu_utilization surface available:False and
   lets get_visible_gpu_utilization skip ghost device rows so the UI
   does not render placeholder cards with empty numbers.

2. Newer amd-smi versions wrap scalar fields as {"value": 0, "unit":
   "none"}, including the per-GPU id. The previous int(raw_id) call
   silently fell back to the enumeration index in that case, losing the
   real GPU id. Routing raw_id through the existing _parse_numeric
   helper handles bare ints, floats, strings, and the dict shape
   uniformly, with a debug log on parse failure.

* Fix gemini round 2 findings: explicit length guard on ROCm version file parser

Both _detect_rocm_version (install_python_stack.py) and
_detect_host_rocm_version (install_llama_prebuilt.py) read /opt/rocm/.info/version
or $ROCM_PATH/lib/rocm_version, split on "." and unconditionally accessed
parts[1]. The surrounding broad `except Exception: pass` already swallowed
the resulting IndexError, so a one-component file like "6\n" did fall
through to the next detection source -- but the control flow relied on
exception handling instead of an explicit check.

Add `if len(parts) >= 2:` guards in both helpers so the loop falls through
on its own without raising. Behaviour is unchanged for the common multi-
component case; the previously-silent IndexError path becomes an explicit
no-op.

* Fix gemini round 3: include has_rocm in validate_server fallback path

When validate_server is called without an explicit install_kind (older
call sites that have not been updated), the fallback was only enabling
--n-gpu-layers for NVIDIA and macOS arm64 hosts. AMD ROCm Linux hosts
fell through to the CPU validation path even though the prebuilt being
exercised was a HIP binary.

Add host.has_rocm to the fallback expression so the GPU offload flag is
applied consistently with the install_kind=='linux-rocm' / 'windows-hip'
branches above.

* Fix gemini round 4: remove risky bytes-vs-MB heuristic in _parse_memory_mb

The previous heuristic divided any bare number above 10_000_000 by
1024*1024 on the assumption that large unit-less values were bytes.
This misclassified small VRAM allocations: 5 MB of used VRAM reported
as 5_242_880 bytes without a unit would be taken at face value and
render as 5_242_880 MB (~5 TB) in the monitoring UI.

Modern amd-smi always provides explicit units (MiB/GiB dict form),
and legacy amd-smi returns bare numbers in MB -- the heuristic never
had a real workload to handle. Drop it and default to MB for bare
numeric input, keeping the existing unit-aware branches for dict /
string inputs unchanged.

The unrelated gemini suggestion to "default minor to 0" in the
amd-smi version awk parser was intentionally NOT applied: rocm7.0
and rocm7.1 ship different wheel sets, so silently substituting 0
for a missing minor could install the wrong wheels. The existing
reject-and-fall-through behaviour is safer.

* Fix gemini round 5: POSIX compliance and leading-comma visibility parsing

Three medium findings from gemini-code-assist addressed in this commit:

1. _pick_radeon_wheel used grep -o and sort -V, both GNU extensions
   that are not in POSIX and break on BSD/BusyBox coreutils. install.sh
   has a #!/bin/sh shebang so the whole pipeline was rewritten as a
   single awk script that extracts all href="..." hits on each line,
   filters to wheels matching the package prefix and python tag, and
   picks the newest version via zero-padded lexical comparison. No
   external sort or grep is needed.

2. _first_visible_amd_gpu_id in the AMD monitoring backend treated a
   leading comma (e.g. HIP_VISIBLE_DEVICES=",1") as "fall through to
   the next env var", which is surprising given the clear intent to
   narrow to device 1. Filter empty tokens after the split and return
   the first real one. An all-commas value ("," / ",,,") still falls
   through because no real tokens exist; the empty-string and "-1"
   explicit-zero cases are unchanged.

The unrelated amd-smi version awk parser suggestion was not applied
(see round 4 commit message for rationale: defaulting a missing minor
to 0 could silently install the wrong ROCm wheel set).

* Fix 20-reviewer.py findings: base drift, Radeon %2B, dpkg/rpm fallback, bnb, backend label

Consolidated fix batch from a 20-parallel reviewer.py run on the current
head. Each fix is drawn from a high-consensus finding and addresses a
real bug or feature gap, not a stylistic preference.

1. install.sh: bump `unsloth>=2026.4.2` -> `unsloth>=2026.4.4` at five
   call sites so this branch no longer regresses main's version floor
   (main bumped to 2026.4.4 in #4876). Without this, merging 4720 would
   silently downgrade the minimum version pin for fresh installs.

2. install.sh: URL-decode Radeon wheel names before extracting the
   torch / torchvision / torchaudio version strings. Real wheel URLs
   from repo.radeon.com are percent-encoded ("torch-2.10.0%2Brocm7.2.0...")
   so the previous `[+-]` terminator in the sed regex never matched,
   `_torch_ver` stayed empty, `_radeon_versions_match` stayed false,
   and every Radeon consumer install silently fell back to the generic
   ROCm index. Now decode %2B -> + first, then extract, then validate.

3. install.sh: the two AMD bitsandbytes install lines were running
   `uv pip install "bitsandbytes>=0.49.1"` without `--force-reinstall`,
   so upgrades where the venv already has a CPU/CUDA bitsandbytes
   satisfying the constraint would keep the stale non-AMD wheel. Add
   `--force-reinstall --no-cache-dir` to both call sites, matching the
   pattern already used in install_python_stack.py::_ensure_rocm_torch.

4. install_python_stack.py and install_llama_prebuilt.py: add
   `dpkg-query -W rocm-core` and `rpm -q rocm-core` fallbacks to the
   Python-side ROCm version detectors so they match the chain in
   install.sh::get_torch_index_url. Package-managed ROCm installs
   (Debian/Ubuntu/RHEL/Fedora distro packages) can expose GPUs via
   rocminfo/amd-smi but still lack /opt/rocm/.info/version, hipconfig,
   or amd-smi `version` output -- without these fallbacks, `unsloth
   studio update` on such hosts returned None and skipped the ROCm
   torch repair. Also strip the dpkg epoch prefix ("1:6.3.0-1") before
   parsing so epoch-annotated packages parse correctly.

5. hardware.py: add a `_backend_label(device)` helper that returns
   "rocm" when IS_ROCM is set and the device is DeviceType.CUDA, and
   use it for every `"backend": ...` emission in JSON responses served
   to the Studio frontend. Internally we still represent ROCm hosts as
   DeviceType.CUDA (ROCm torch reuses the whole torch.cuda.* API
   surface), but the user-facing API now correctly reports "rocm" on
   AMD boxes instead of labeling them as "cuda".

All 250 simulation scenarios pass (was 233 before this batch: added 17
new regression tests covering the version pin, %2B decoding, bnb
force-reinstall flags, dpkg/rpm fallback presence, and the
_backend_label helper's four-way truth table).

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Fix gemini round 6 + URL audit: amd.py defensive checks, rocm6.5+ clip to 6.4

Two rounds of fixes in one commit, plus a full URL audit of every PyPI /
download.pytorch.org / repo.radeon.com reference the PR introduces.

amd.py (4 medium gemini findings on commit b3627bc2):

1. _extract_gpu_metrics used `and vram_total_mb` as part of the vram_util
   gate. The follow-up `vram_total_mb > 0` already handles the division
   guard, but the truthiness check was redundant and slightly surprising
   for a 0.0 valid value. Replace with explicit `is not None and > 0`
   for both vram_util and power_util.

2. get_physical_gpu_count called `data.get("gpu", ...)` without guarding
   for non-dict envelopes. A scalar / string JSON response from amd-smi
   would raise AttributeError. Add an isinstance(data, dict) check and
   return None for unexpected shapes.

3. get_visible_gpu_utilization had the same .get() exposure on the outer
   envelope. Rewrite the gpu_list extraction as an explicit
   list/dict/else cascade so a malformed scalar envelope produces
   gpu_list=[data] and continues without raising.

4. The same function's per-entry loop also called gpu_data.get() on
   whatever was inside gpu_list. If a scalar ever leaks into the list
   (directly or via the previous fix's fallback), _extract_gpu_metrics
   would raise on the first .get() inside the helper. Skip non-dict
   entries in the loop before extracting metrics.

install.sh (URL audit finding, previously flagged by 20-reviewer as #13):

5. get_torch_index_url used `rocm6.*` in the rocm tag case statement,
   which matched rocm6.5 and rocm6.6 and emitted
   download.pytorch.org/whl/rocm6.5 -- which returns HTTP 403 because
   PyTorch only publishes rocm 5.7, 6.0-6.4, 7.0-7.2. Enumerate the
   supported 6.x minors explicitly and add a rocm6.* fallback branch
   that clips to rocm6.4 (the last supported 6.x wheel set).

URL audit results (all URLs PR 4720 references):
- 14/14 download.pytorch.org/whl/{cpu,cu118,cu124,cu126,cu128,cu130,
  rocm6.0..6.4,rocm7.0..7.2} return HTTP 200.
- 9/9 repo.radeon.com/rocm/manylinux/rocm-rel-{5.7,6.0,6.1,6.2,6.3,
  6.4,7.0,7.1,7.2}/ return HTTP 200.
- X.Y.Z patch directories exist for 7.0.2, 7.1.1, 7.2.1 but NOT for
  6.3.0, 6.4.0, 6.2.1 -- install.sh already handles this via the X.Y.Z
  -> X.Y fallback sed in the Radeon wheel install block.
- Docs links (rocm.docs.amd.com, docs.unsloth.ai AMD guide) and the
  llama.cpp GitHub releases API endpoint all return 200.

Test suite: 255 -> 258. New regression coverage:
- U17: get_physical_gpu_count tolerates scalar amd-smi envelope
- U18: get_visible_gpu_utilization tolerates scalar envelope
- U19a-c: vram_util / power_util return None on zero total, but
  vram_total_gb still echoes 0.0 (not None)
- A_rocm{6.5,6.6,6.9}_clips_to_rocm64: install.sh clips unsupported
  6.x minors to rocm6.4 instead of producing a 403 index URL

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Fix reviewer.py round 2: tokenizer AMD multi-GPU, --no-torch bnb, main.py backend label

Three high-confidence findings from a second 20-parallel reviewer.py run
on commit 7effb3ae. Triaged 15 total findings and applied the three that
were confirmed as real bugs; the rest were either false positives (e.g.
"migrated AMD venv not repaired" -- _ensure_rocm_torch runs downstream
via setup.sh regardless), design decisions (e.g. visibility mask env
vars not consulted in installer detection), or edge cases the existing
fallback logic already handles.

1. unsloth/tokenizer_utils.py [6/20]: the multi-GPU guard's shell probe
   runs `nvidia-smi --query-gpu=memory.used`, catches the failure, then
   only raises if `torch.cuda.is_available()` is False. On ROCm torch,
   torch.cuda.is_available() returns True (ROCm reuses the torch.cuda.*
   API), so the guard becomes dead code on AMD hosts and multi-GPU AMD
   setups slip through even though unsloth does not support them yet.
   Add a torch.cuda.device_count() > 1 fallback inside the except so
   AMD multi-visible-device setups are flagged consistently with the
   original CUDA memory check.

2. install.sh [1/20]: the fresh-install bitsandbytes block for AMD ROCm
   ran unconditionally when TORCH_INDEX_URL matched `*/rocm*`, even when
   SKIP_TORCH=true (from --no-torch or Intel Mac auto-detect). A user
   running `install.sh --no-torch` on an AMD host would still pull in
   bitsandbytes despite explicitly asking for GGUF-only mode. Wrap the
   case block in an outer `[ "$SKIP_TORCH" = false ]` guard.

3. studio/backend/main.py [3/20]: the /api/system endpoint returned
   `"device_backend": get_device().value`, which is "cuda" on ROCm
   hosts (because ROCm torch piggybacks on torch.cuda). Other endpoints
   (hardware.py) already use the _backend_label helper which swaps
   "cuda" -> "rocm" when IS_ROCM. Route /api/system through the same
   helper so the Studio UI reports the backend consistently across all
   endpoints.

4. studio/backend/tests/test_utils.py: update test_backend_matches_device
   to call _backend_label(get_device()) instead of raw get_device().value
   so the test matches the new contract and still passes on CUDA hosts.

Tests: 258 -> 261. New regression coverage:
- X08 main.py /api/system uses _backend_label
- X09 tokenizer multi-GPU guard has device_count() fallback
- X10 fresh-install bnb case block gated on SKIP_TORCH=false

* fix: prevent bitsandbytes from overwriting ROCm torch with CUDA wheels

During install, bitsandbytes was installed without --no-deps, causing
uv to resolve torch from PyPI (CUDA build) and silently overwrite the
ROCm wheels that were just installed in the previous step.

This happened in three places:
- install.sh: bitsandbytes install in both migrated and fresh paths
- install_python_stack.py: bitsandbytes install inside _ensure_rocm_torch()

Additionally, multiple install steps in install_python_stack.py (extras,
overrides, studio deps) can pull in CUDA torch via transitive
dependencies. A final _ensure_rocm_torch() call at the end of the
install sequence ensures ROCm torch is always in place at runtime.

All changes are gated behind ROCm-specific conditions and do not affect
NVIDIA, CPU-only, macOS, or Windows install paths.

Tested on AMD Instinct MI300X VF with ROCm 7.2.0 -- confirms
torch==2.10.0+rocm7.1 with HIP 7.1.25424 after install.

* fix: ROCm inference fallback -- skip Unsloth patching and bnb 4-bit on HIP

On AMD ROCm (HIP), two issues prevent the normal Unsloth inference path:

1. Unsloth's global monkey-patching of transformers model classes
   (LlamaRotaryEmbedding, attention modules) triggers
   _assert_async_cuda_kernel crashes on HIP during generation.
   Training uses different code paths and works fine.

2. bitsandbytes 4-bit matmul kernels also trigger HIP assertion
   failures on MI300X (CDNA3 / gfx942), even without Unsloth patching.

This commit adds a ROCm-specific inference fallback that:
- Skips importing Unsloth at module level (prevents global patching)
- Loads models in 16-bit with plain transformers + PEFT instead
- Resolves pre-quantized model names (e.g. "xxx-bnb-4bit" -> "xxx")
  since pre-quantized HF repos still trigger bnb codepaths
- Guards get_chat_template calls (unavailable without Unsloth import)
- Fixes max_seq_length=0 being passed to from_pretrained (GGUF
  semantics don't apply to transformers path)

The NVIDIA path is completely unchanged -- Unsloth import and
for_inference() optimization remain active. GGUF inference (via
llama-server/HIP) is unaffected since it never imports Python model
classes. AMD GPUs typically have large VRAM (e.g. 192GB on MI300X)
so 16-bit loading is practical for inference.

Tested on AMD Instinct MI300X VF (ROCm 7.2, HIP 7.1.25424):
- Simple generation: PASS
- Compare mode (base vs finetuned): PASS
- GGUF inference + tool calling: PASS (unaffected by this change)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix: guard audio/vision inference on ROCm, remove unused import

- Add clear RuntimeError for audio/vision model inference on ROCm
  (these paths use Unsloth's FastModel/FastVisionModel which would
  crash on HIP; GGUF inference is the supported path on AMD)
- Remove unused `import os as _os` from the ROCm changes

* fix: amd-smi parsing for newer output format (gpu_data wrapper, mem_usage, temperature)

amd-smi on recent ROCm versions (7.x) wraps metric output in a
{"gpu_data": [...]} envelope instead of returning a raw list. This
caused get_primary_gpu_utilization() and get_visible_gpu_utilization()
to fail silently (returning available=False) because the GPU data
dict was never unwrapped.

Additionally:
- VRAM data moved from "vram" to "mem_usage" with "total_vram" /
  "used_vram" keys. Added fallback key lookup.
- Temperature "edge" sensor returns "N/A" on MI300X VF; the previous
  dict.get() chain returned the "N/A" string instead of falling
  through to "hotspot". Changed to a loop that checks each key until
  a parseable value is found.

Tested on AMD Instinct MI300X VF (ROCm 7.2, amd-smi 24.x):
- GPU utilization: 0% (idle), up to 100% during training
- Temperature: 40-44C (from hotspot sensor)
- VRAM: 0.28/191.69 GB (idle)
- Power: 158-211W draw

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Bug fix detecting radeon (#4940)

* Bug fix detecting radeon

* Expanding GPU target for gfx1100*

* Generalize gfx family-prefix filter to cover gfx10/gfx12 as well

rocminfo on ROCm 6.1+ emits LLVM generic-family ISA lines alongside the
specific GPU (e.g. gfx11-generic next to gfx1100). The outer grep captures
the bare family prefix from the generic line, and passing that to
-DGPU_TARGETS breaks the HIP build because clang only accepts specific
gfxNNN ids.

The previous filter only special-cased gfx11. Generalize it so any bare
2-digit family prefix (gfx10, gfx11, gfx12, ...) is dropped whenever a
specific sibling target is present in the same list. No real AMD GPU has
a 2-digit gfx id, so the filter can only ever drop family prefixes and
never a real target.

Covers the existing gfx11 cases unchanged, and extends the same fix to
gfx10-1-generic / gfx10-3-generic (RDNA1/2) and gfx12-generic (RDNA4),
which would otherwise hit the same build failure on newer rocminfo.

---------

Co-authored-by: Iswarya Alex <iswarya.alex@amd.com>
Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com>

---------

Co-authored-by: Eda Z <eda.zhou@amd.com>
Co-authored-by: GoldenGrapeGentleman <yueyuan@amd.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: billishyahao <bill.he@amd.com>
Co-authored-by: Iswarya Alex <47045679+iswaryaalex@users.noreply.github.com>
Co-authored-by: Iswarya Alex <iswarya.alex@amd.com>
Co-authored-by: Daniel Han <danielhanchen@users.noreply.github.com>
2026-04-10 01:56:12 -07:00

5506 lines
195 KiB
Python
Executable file

#!/usr/bin/env python3
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Cross platform llama.cpp prebuilt installer for Unsloth Studio"""
from __future__ import annotations
import argparse
import errno
import fnmatch
import hashlib
import json
import os
import platform
import random
import re
import shutil
import site
import socket
import subprocess
import sys
import tarfile
import tempfile
import textwrap
import time
import urllib.error
import urllib.parse
import urllib.request
import zipfile
from contextlib import contextmanager
from dataclasses import dataclass, field
try:
from filelock import FileLock, Timeout as FileLockTimeout
except ImportError:
FileLock = None
FileLockTimeout = None
from pathlib import Path
from typing import Any, Iterable, Iterator
EXIT_SUCCESS = 0
EXIT_FALLBACK = 2
EXIT_ERROR = 1
EXIT_BUSY = 3
def env_int(name: str, default: int, *, minimum: int | None = None) -> int:
raw = os.environ.get(name)
if raw is None:
value = default
else:
try:
value = int(str(raw).strip())
except (TypeError, ValueError):
value = default
if minimum is not None:
value = max(minimum, value)
return value
# Prefer "latest" over "master" -- "master" bypasses the prebuilt resolver
# (no matching GitHub release), forces a source build, and causes HTTP 422
# errors. Only use "master" temporarily when the latest release is missing
# support for a new model architecture.
DEFAULT_LLAMA_TAG = os.environ.get("UNSLOTH_LLAMA_TAG", "latest")
# Default published repo for prebuilt release resolution. Linux uses
# Unsloth prebuilts; setup.sh/setup.ps1 pass --published-repo explicitly
# for macOS/Windows to override with ggml-org/llama.cpp when needed.
DEFAULT_PUBLISHED_REPO = "unslothai/llama.cpp"
DEFAULT_PUBLISHED_TAG = os.environ.get("UNSLOTH_LLAMA_RELEASE_TAG")
DEFAULT_PUBLISHED_MANIFEST_ASSET = os.environ.get(
"UNSLOTH_LLAMA_RELEASE_MANIFEST_ASSET", "llama-prebuilt-manifest.json"
)
DEFAULT_PUBLISHED_SHA256_ASSET = os.environ.get(
"UNSLOTH_LLAMA_RELEASE_SHA256_ASSET", "llama-prebuilt-sha256.json"
)
UPSTREAM_REPO = "ggml-org/llama.cpp"
UPSTREAM_RELEASES_API = f"https://api.github.com/repos/{UPSTREAM_REPO}/releases/latest"
TEST_MODEL_URL = (
"https://huggingface.co/ggml-org/models/resolve/main/tinyllamas/stories260K.gguf"
)
TEST_MODEL_SHA256 = "270cba1bd5109f42d03350f60406024560464db173c0e387d91f0426d3bd256d"
VALIDATION_MODEL_CACHE_DIRNAME = ".cache"
VALIDATION_MODEL_CACHE_FILENAME = "stories260K.gguf"
INSTALL_LOCK_TIMEOUT_SECONDS = 300
INSTALL_STAGING_ROOT_NAME = ".staging"
GITHUB_AUTH_HOSTS = {"api.github.com", "github.com"}
RETRYABLE_HTTP_STATUS = {408, 429, 500, 502, 503, 504}
HTTP_FETCH_ATTEMPTS = 4
HTTP_FETCH_BASE_DELAY_SECONDS = 0.75
JSON_FETCH_ATTEMPTS = 3
DEFAULT_GITHUB_RELEASE_SCAN_MAX_PAGES = env_int(
"UNSLOTH_LLAMA_GITHUB_RELEASE_SCAN_MAX_PAGES",
5,
minimum = 1,
)
SERVER_PORT_BIND_ATTEMPTS = 3
SERVER_BIND_RETRY_WINDOW_SECONDS = 5.0
TTY_PROGRESS_START_DELAY_SECONDS = 0.5
DEFAULT_MAX_PREBUILT_RELEASE_FALLBACKS = env_int(
"UNSLOTH_LLAMA_MAX_PREBUILT_RELEASE_FALLBACKS",
2,
minimum = 1,
)
FORCE_COMPILE_DEFAULT_REF = os.environ.get("UNSLOTH_LLAMA_FORCE_COMPILE_REF", "master")
DIRECT_LINUX_BUNDLE_PROFILES: dict[str, dict[str, Any]] = {
"cuda12-older": {
"runtime_line": "cuda12",
"coverage_class": "older",
"supported_sms": ["70", "75", "80", "86", "89"],
"min_sm": 70,
"max_sm": 89,
"rank": 10,
},
"cuda12-newer": {
"runtime_line": "cuda12",
"coverage_class": "newer",
"supported_sms": ["86", "89", "90", "100", "120"],
"min_sm": 86,
"max_sm": 120,
"rank": 20,
},
"cuda12-portable": {
"runtime_line": "cuda12",
"coverage_class": "portable",
"supported_sms": ["70", "75", "80", "86", "89", "90", "100", "120"],
"min_sm": 70,
"max_sm": 120,
"rank": 30,
},
"cuda13-older": {
"runtime_line": "cuda13",
"coverage_class": "older",
"supported_sms": ["75", "80", "86", "89"],
"min_sm": 75,
"max_sm": 89,
"rank": 40,
},
"cuda13-newer": {
"runtime_line": "cuda13",
"coverage_class": "newer",
"supported_sms": ["86", "89", "90", "100", "120"],
"min_sm": 86,
"max_sm": 120,
"rank": 50,
},
"cuda13-portable": {
"runtime_line": "cuda13",
"coverage_class": "portable",
"supported_sms": ["75", "80", "86", "89", "90", "100", "120"],
"min_sm": 75,
"max_sm": 120,
"rank": 60,
},
}
@dataclass
class HostInfo:
system: str
machine: str
is_windows: bool
is_linux: bool
is_macos: bool
is_x86_64: bool
is_arm64: bool
nvidia_smi: str | None
driver_cuda_version: tuple[int, int] | None
compute_caps: list[str]
visible_cuda_devices: str | None
has_physical_nvidia: bool
has_usable_nvidia: bool
has_rocm: bool = False
@dataclass
class AssetChoice:
repo: str
tag: str
name: str
url: str
source_label: str
runtime_name: str | None = None
runtime_url: str | None = None
is_ready_bundle: bool = False
install_kind: str = ""
bundle_profile: str | None = None
runtime_line: str | None = None
coverage_class: str | None = None
supported_sms: list[str] | None = None
min_sm: int | None = None
max_sm: int | None = None
selection_log: list[str] | None = None
expected_sha256: str | None = None
@dataclass(frozen = True)
class PublishedLlamaArtifact:
asset_name: str
install_kind: str
runtime_line: str | None
coverage_class: str | None
supported_sms: list[str]
min_sm: int | None
max_sm: int | None
bundle_profile: str | None
rank: int
@dataclass
class PublishedReleaseBundle:
repo: str
release_tag: str
upstream_tag: str
manifest_sha256: str | None = None
source_repo: str | None = None
source_repo_url: str | None = None
source_ref_kind: str | None = None
requested_source_ref: str | None = None
resolved_source_ref: str | None = None
source_commit: str | None = None
source_commit_short: str | None = None
assets: dict[str, str] = field(default_factory = dict)
manifest_asset_name: str = DEFAULT_PUBLISHED_MANIFEST_ASSET
artifacts: list[PublishedLlamaArtifact] = field(default_factory = list)
selection_log: list[str] = field(default_factory = list)
@dataclass
class LinuxCudaSelection:
attempts: list[AssetChoice]
selection_log: list[str]
@property
def primary(self) -> AssetChoice:
if not self.attempts:
raise RuntimeError("linux CUDA selection unexpectedly had no attempts")
return self.attempts[0]
@dataclass
class CudaRuntimePreference:
runtime_line: str | None
selection_log: list[str]
@dataclass(frozen = True)
class ApprovedArtifactHash:
asset_name: str
sha256: str
repo: str | None
kind: str | None
@dataclass
class ApprovedReleaseChecksums:
repo: str
release_tag: str
upstream_tag: str
source_repo: str | None = None
source_repo_url: str | None = None
source_ref_kind: str | None = None
requested_source_ref: str | None = None
resolved_source_ref: str | None = None
source_commit: str | None = None
source_commit_short: str | None = None
artifacts: dict[str, ApprovedArtifactHash] = field(default_factory = dict)
@dataclass(frozen = True)
class ResolvedPublishedRelease:
bundle: PublishedReleaseBundle
checksums: ApprovedReleaseChecksums
@dataclass(frozen = True)
class SourceBuildPlan:
source_url: str
source_ref: str
source_ref_kind: str
compatibility_upstream_tag: str
source_repo: str | None = None
source_repo_url: str | None = None
requested_source_ref: str | None = None
resolved_source_ref: str | None = None
source_commit: str | None = None
@dataclass(frozen = True)
class InstallReleasePlan:
requested_tag: str
llama_tag: str
release_tag: str
attempts: list[AssetChoice]
approved_checksums: ApprovedReleaseChecksums
class PrebuiltFallback(RuntimeError):
pass
class BusyInstallConflict(RuntimeError):
pass
class ExistingInstallSatisfied(RuntimeError):
def __init__(self, choice: AssetChoice, used_fallback: bool):
super().__init__(f"existing install already matches candidate {choice.name}")
self.choice = choice
self.used_fallback = used_fallback
def _os_error_messages(exc: BaseException) -> list[str]:
messages: list[str] = []
if isinstance(exc, OSError):
for value in (
getattr(exc, "strerror", None),
getattr(exc, "filename", None),
getattr(exc, "filename2", None),
):
if isinstance(value, str) and value:
messages.append(value)
text = str(exc)
if text:
messages.append(text)
return [message.lower() for message in messages if message]
def is_busy_lock_error(exc: BaseException) -> bool:
if isinstance(exc, BusyInstallConflict):
return True
if isinstance(exc, OSError):
if exc.errno in {
errno.EACCES,
errno.EBUSY,
errno.EPERM,
errno.ETXTBSY,
}:
return True
if getattr(exc, "winerror", None) in {5, 32, 145}:
return True
for message in _os_error_messages(exc):
if any(
needle in message
for needle in (
"access is denied",
"being used by another process",
"device or resource busy",
"permission denied",
"text file busy",
"file is in use",
"process cannot access the file",
"cannot create a file when that file already exists",
)
):
return True
return False
def log(message: str) -> None:
print(f"[llama-prebuilt] {message}", file = sys.stderr)
def log_lines(lines: Iterable[str]) -> None:
for line in lines:
log(line)
def parsed_hostname(url: str | None) -> str | None:
if not url:
return None
try:
hostname = urllib.parse.urlparse(url).hostname
except Exception:
return None
if not hostname:
return None
return hostname.lower()
def should_send_github_auth(url: str | None) -> bool:
return parsed_hostname(url) in GITHUB_AUTH_HOSTS
def auth_headers(url: str | None = None) -> dict[str, str]:
headers = {
"User-Agent": "unsloth-studio-llama-prebuilt",
}
token = os.environ.get("GH_TOKEN") or os.environ.get("GITHUB_TOKEN")
if token and should_send_github_auth(url):
headers["Authorization"] = f"Bearer {token}"
return headers
def github_api_headers(url: str | None = None) -> dict[str, str]:
return {
"Accept": "application/vnd.github+json",
**auth_headers(url),
}
def is_github_api_url(url: str | None) -> bool:
return parsed_hostname(url) == "api.github.com"
def is_retryable_url_error(exc: Exception) -> bool:
if isinstance(exc, urllib.error.HTTPError):
return exc.code in RETRYABLE_HTTP_STATUS
if isinstance(exc, urllib.error.URLError):
return True
if isinstance(exc, TimeoutError):
return True
if isinstance(exc, socket.timeout):
return True
return False
def sleep_backoff(
attempt: int, *, base_delay: float = HTTP_FETCH_BASE_DELAY_SECONDS
) -> None:
delay = base_delay * (2 ** max(attempt - 1, 0))
delay += random.uniform(0.0, 0.2)
time.sleep(delay)
def atomic_write_bytes(destination: Path, data: bytes) -> None:
destination.parent.mkdir(parents = True, exist_ok = True)
with tempfile.NamedTemporaryFile(
prefix = destination.name + ".tmp-",
dir = destination.parent,
delete = False,
) as handle:
tmp_path = Path(handle.name)
handle.write(data)
handle.flush()
os.fsync(handle.fileno())
os.replace(tmp_path, destination)
def atomic_replace_from_tempfile(tmp_path: Path, destination: Path) -> None:
destination.parent.mkdir(parents = True, exist_ok = True)
os.replace(tmp_path, destination)
def source_archive_logical_name(upstream_tag: str) -> str:
return f"llama.cpp-source-{upstream_tag}.tar.gz"
def exact_source_archive_logical_name(source_commit: str) -> str:
return f"llama.cpp-source-commit-{source_commit}.tar.gz"
def sha256_file(path: Path) -> str:
digest = hashlib.sha256()
with path.open("rb") as handle:
for chunk in iter(lambda: handle.read(1024 * 1024), b""):
digest.update(chunk)
return digest.hexdigest()
def sha256_bytes(data: bytes) -> str:
return hashlib.sha256(data).hexdigest()
def normalize_sha256_digest(value: str | None) -> str | None:
if not isinstance(value, str) or not value:
return None
lowered = value.lower()
if lowered.startswith("sha256:"):
lowered = lowered.split(":", 1)[1]
if len(lowered) != 64 or any(ch not in "0123456789abcdef" for ch in lowered):
return None
return lowered
def normalize_source_ref_kind(value: str | None) -> str | None:
if not isinstance(value, str):
return None
normalized = value.strip().lower()
if normalized in {"tag", "branch", "pull", "commit", "custom"}:
return normalized
return None
def normalize_source_commit(value: str | None) -> str | None:
if not isinstance(value, str):
return None
normalized = value.strip().lower()
if len(normalized) < 7 or len(normalized) > 40:
return None
if any(ch not in "0123456789abcdef" for ch in normalized):
return None
return normalized
def validate_schema_version(payload: dict[str, Any], *, label: str) -> None:
schema_version = payload.get("schema_version")
if schema_version is None:
return
try:
normalized = int(schema_version)
except (TypeError, ValueError) as exc:
raise RuntimeError(f"{label} schema_version was not an integer") from exc
if normalized != 1:
raise RuntimeError(f"{label} schema_version={normalized} is unsupported")
def repo_slug_from_source(value: str | None) -> str | None:
if not isinstance(value, str):
return None
normalized = value.strip()
if not normalized:
return None
normalized = normalized.removesuffix(".git")
if normalized.startswith("https://github.com/"):
slug = normalized[len("https://github.com/") :]
elif normalized.startswith("http://github.com/"):
slug = normalized[len("http://github.com/") :]
elif normalized.startswith("git@github.com:"):
slug = normalized[len("git@github.com:") :]
else:
slug = normalized
slug = slug.strip("/")
parts = slug.split("/")
if len(parts) != 2 or not all(parts):
return None
return f"{parts[0]}/{parts[1]}"
def source_url_from_repo_slug(repo_slug: str | None) -> str | None:
if not isinstance(repo_slug, str) or not repo_slug:
return None
return f"https://github.com/{repo_slug}"
def source_repo_clone_url(repo: str | None, repo_url: str | None) -> str | None:
if isinstance(repo_url, str) and repo_url.strip():
return repo_url.strip().removesuffix(".git")
return source_url_from_repo_slug(repo_slug_from_source(repo))
def infer_source_ref_kind(ref: str | None) -> str:
if not isinstance(ref, str):
return "tag"
normalized = ref.strip()
lowered = normalized.lower()
if not normalized:
return "tag"
if lowered.startswith("refs/pull/") or lowered.startswith("pull/"):
return "pull"
if (
lowered.startswith("refs/heads/")
or lowered in {"main", "master", "head"}
or lowered.startswith("origin/")
):
return "branch"
normalized_commit = normalize_source_commit(normalized)
if normalized_commit is not None:
return "commit"
return "tag"
def normalized_ref_aliases(ref: str | None) -> set[str]:
if not isinstance(ref, str):
return set()
normalized = ref.strip()
if not normalized:
return set()
aliases = {normalized}
lowered = normalized.lower()
commit = normalize_source_commit(normalized)
if commit is not None:
aliases.add(commit)
if lowered.startswith("refs/heads/"):
aliases.add(normalized.split("/", 2)[2])
elif "/" not in normalized and infer_source_ref_kind(normalized) == "branch":
aliases.add(f"refs/heads/{normalized}")
if lowered.startswith("refs/pull/"):
aliases.add(normalized.removeprefix("refs/"))
elif lowered.startswith("pull/"):
aliases.add(f"refs/{normalized}")
return aliases
def refs_match(candidate_ref: str | None, requested_ref: str | None) -> bool:
candidate_aliases = normalized_ref_aliases(candidate_ref)
requested_aliases = normalized_ref_aliases(requested_ref)
if not candidate_aliases or not requested_aliases:
return False
if candidate_aliases & requested_aliases:
return True
candidate_commit = normalize_source_commit(candidate_ref)
requested_commit = normalize_source_commit(requested_ref)
if candidate_commit and requested_commit:
return candidate_commit.startswith(
requested_commit
) or requested_commit.startswith(candidate_commit)
return False
def checkout_friendly_ref(ref_kind: str | None, ref: str | None) -> str | None:
"""Normalize a source ref to a form that ``git clone --branch`` accepts.
Fully qualified branch refs like ``refs/heads/main`` are stripped to
``main``; tag refs like ``refs/tags/b8508`` are stripped to ``b8508``.
Pull refs like ``refs/pull/123/head`` are left as-is since they are
always fetched explicitly rather than cloned with ``--branch``.
"""
if not isinstance(ref, str) or not ref:
return ref
lowered = ref.lower()
if ref_kind == "branch" and lowered.startswith("refs/heads/"):
return ref.split("/", 2)[2]
if ref_kind == "tag" and lowered.startswith("refs/tags/"):
return ref.split("/", 2)[2]
return ref
def windows_cuda_upstream_asset_names(llama_tag: str, runtime: str) -> list[str]:
return [
f"llama-{llama_tag}-bin-win-cuda-{runtime}-x64.zip",
f"cudart-llama-bin-win-cuda-{runtime}-x64.zip",
]
def windows_cuda_asset_aliases(
asset_name: str,
*,
compatibility_tag: str | None = None,
) -> list[str]:
aliases: list[str] = []
legacy_match = re.fullmatch(
r"llama-(?P<tag>[^/]+)-bin-win-cuda-(?P<runtime>\d+\.\d+)-x64\.zip",
asset_name,
)
if legacy_match:
runtime = legacy_match.group("runtime")
aliases.append(f"cudart-llama-bin-win-cuda-{runtime}-x64.zip")
if compatibility_tag:
aliases.append(f"llama-{compatibility_tag}-bin-win-cuda-{runtime}-x64.zip")
return aliases
current_match = re.fullmatch(
r"cudart-llama-bin-win-cuda-(?P<runtime>\d+\.\d+)-x64\.zip",
asset_name,
)
if current_match and compatibility_tag:
runtime = current_match.group("runtime")
aliases.append(f"llama-{compatibility_tag}-bin-win-cuda-{runtime}-x64.zip")
return aliases
def format_byte_count(num_bytes: float) -> str:
units = ["B", "KiB", "MiB", "GiB", "TiB"]
value = float(num_bytes)
for unit in units:
if abs(value) < 1024.0 or unit == units[-1]:
if unit == "B":
return f"{int(value)} {unit}"
return f"{value:.1f} {unit}"
value /= 1024.0
return f"{num_bytes:.1f} B"
class DownloadProgress:
def __init__(self, label: str, total_bytes: int | None) -> None:
self.label = label
self.total_bytes = total_bytes if total_bytes and total_bytes > 0 else None
self.start_time = time.monotonic()
self.last_emit = 0.0
term_ok = os.environ.get("TERM", "").lower() != "dumb"
self.stream = (
sys.stderr
if sys.stderr.isatty()
else sys.stdout
if sys.stdout.isatty()
else sys.stderr
)
self.is_tty = term_ok and self.stream.isatty()
self.completed = False
self.last_milestone_percent = -1
self.last_milestone_bytes = 0
self.has_rendered_tty_progress = False
def _render(self, downloaded_bytes: int, *, final: bool = False) -> str:
elapsed = max(time.monotonic() - self.start_time, 1e-6)
speed = downloaded_bytes / elapsed
speed_text = f"{format_byte_count(speed)}/s"
if self.total_bytes is not None:
percent = min(100.0, (downloaded_bytes / self.total_bytes) * 100.0)
return (
f"{self.label}: {percent:5.1f}% "
f"({format_byte_count(downloaded_bytes)}/{format_byte_count(self.total_bytes)}) "
f"at {speed_text}"
)
if final:
return f"{self.label}: {format_byte_count(downloaded_bytes)} downloaded at {speed_text}"
return f"{self.label}: {format_byte_count(downloaded_bytes)} downloaded at {speed_text}"
def update(self, downloaded_bytes: int) -> None:
now = time.monotonic()
if self.is_tty:
elapsed = now - self.start_time
if not self.has_rendered_tty_progress:
if (
self.total_bytes is not None
and downloaded_bytes >= self.total_bytes
):
return
if elapsed < TTY_PROGRESS_START_DELAY_SECONDS:
return
min_interval = 0.2
if (
self.has_rendered_tty_progress
and not self.completed
and (now - self.last_emit) < min_interval
):
return
self.last_emit = now
line = self._render(downloaded_bytes)
self.stream.write("\r\033[K" + line)
self.stream.flush()
self.has_rendered_tty_progress = True
return
should_emit = False
if self.total_bytes is not None:
percent = int((downloaded_bytes * 100) / max(self.total_bytes, 1))
milestone_percent = min((percent // 25) * 25, 100)
if (
milestone_percent > self.last_milestone_percent
and milestone_percent < 100
):
self.last_milestone_percent = milestone_percent
should_emit = True
else:
byte_step = 25 * 1024 * 1024
if (
downloaded_bytes - self.last_milestone_bytes >= byte_step
and (now - self.last_emit) >= 5.0
):
self.last_milestone_bytes = downloaded_bytes
should_emit = True
if not should_emit:
return
self.last_emit = now
self.stream.write(self._render(downloaded_bytes) + "\n")
self.stream.flush()
def finish(self, downloaded_bytes: int) -> None:
self.completed = True
line = self._render(downloaded_bytes, final = True)
if self.is_tty:
if not self.has_rendered_tty_progress:
return
self.stream.write("\r\033[K")
else:
self.stream.write(line + "\n")
self.stream.flush()
def download_label_from_url(url: str) -> str:
name = Path(urllib.parse.urlparse(url).path).name
return name or url
def download_bytes(
url: str,
*,
timeout: int = 120,
attempts: int = HTTP_FETCH_ATTEMPTS,
headers: dict[str, str] | None = None,
progress_label: str | None = None,
) -> bytes:
last_exc: Exception | None = None
for attempt in range(1, attempts + 1):
try:
request = urllib.request.Request(url, headers = headers or auth_headers(url))
with urllib.request.urlopen(request, timeout = timeout) as response:
total_bytes: int | None = None
content_length = response.headers.get("Content-Length")
if content_length and content_length.isdigit():
total_bytes = int(content_length)
progress = (
DownloadProgress(progress_label, total_bytes)
if progress_label
else None
)
data = bytearray()
while True:
chunk = response.read(1024 * 1024)
if not chunk:
break
data.extend(chunk)
if progress is not None:
progress.update(len(data))
if progress is not None:
progress.finish(len(data))
return bytes(data)
except Exception as exc:
last_exc = exc
if attempt >= attempts or not is_retryable_url_error(exc):
raise
log(f"fetch failed ({attempt}/{attempts}) for {url}: {exc}; retrying")
sleep_backoff(attempt)
assert last_exc is not None
raise last_exc
def fetch_json(url: str) -> Any:
attempts = JSON_FETCH_ATTEMPTS if is_github_api_url(url) else 1
last_decode_exc: Exception | None = None
for attempt in range(1, attempts + 1):
try:
data = download_bytes(
url,
timeout = 30,
headers = github_api_headers(url)
if is_github_api_url(url)
else auth_headers(url),
)
except urllib.error.HTTPError as exc:
if exc.code == 403 and is_github_api_url(url):
hint = ""
if not (os.environ.get("GH_TOKEN") or os.environ.get("GITHUB_TOKEN")):
hint = (
"; set GH_TOKEN or GITHUB_TOKEN to avoid GitHub API rate limits"
)
raise RuntimeError(f"GitHub API returned 403 for {url}{hint}") from exc
raise
if not data:
last_decode_exc = RuntimeError(f"downloaded empty JSON payload from {url}")
else:
try:
payload = json.loads(data.decode("utf-8"))
except (UnicodeDecodeError, json.JSONDecodeError) as exc:
last_decode_exc = RuntimeError(
f"downloaded invalid JSON from {url}: {exc}"
)
else:
if not isinstance(payload, dict) and not isinstance(payload, list):
raise RuntimeError(
f"downloaded unexpected JSON type from {url}: {type(payload).__name__}"
)
return payload
if attempt >= attempts:
assert last_decode_exc is not None
raise last_decode_exc
log(f"json fetch failed ({attempt}/{attempts}) for {url}; retrying")
sleep_backoff(attempt)
assert last_decode_exc is not None
raise last_decode_exc
def download_file(url: str, destination: Path) -> None:
destination.parent.mkdir(parents = True, exist_ok = True)
last_exc: Exception | None = None
for attempt in range(1, HTTP_FETCH_ATTEMPTS + 1):
tmp_path: Path | None = None
try:
request = urllib.request.Request(url, headers = auth_headers(url))
with tempfile.NamedTemporaryFile(
prefix = destination.name + ".tmp-",
dir = destination.parent,
delete = False,
) as handle:
tmp_path = Path(handle.name)
with urllib.request.urlopen(request, timeout = 120) as response:
total_bytes: int | None = None
content_length = response.headers.get("Content-Length")
if content_length and content_length.isdigit():
total_bytes = int(content_length)
progress = DownloadProgress(
f"Downloading {destination.name}", total_bytes
)
downloaded_bytes = 0
while True:
chunk = response.read(1024 * 1024)
if not chunk:
break
handle.write(chunk)
downloaded_bytes += len(chunk)
progress.update(downloaded_bytes)
progress.finish(downloaded_bytes)
handle.flush()
os.fsync(handle.fileno())
if not tmp_path.exists() or tmp_path.stat().st_size == 0:
raise RuntimeError(f"downloaded empty file from {url}")
atomic_replace_from_tempfile(tmp_path, destination)
return
except Exception as exc:
last_exc = exc
if tmp_path is not None:
try:
tmp_path.unlink(missing_ok = True)
except Exception:
pass
if attempt >= HTTP_FETCH_ATTEMPTS or not is_retryable_url_error(exc):
raise
log(
f"download failed ({attempt}/{HTTP_FETCH_ATTEMPTS}) for {url}: {exc}; retrying"
)
sleep_backoff(attempt)
assert last_exc is not None
raise last_exc
def download_file_verified(
url: str,
destination: Path,
*,
expected_sha256: str | None,
label: str,
) -> None:
normalized_expected = normalize_sha256_digest(expected_sha256)
if not normalized_expected:
download_file(url, destination)
log(
f"downloaded {label} without a published sha256; relying on install validation"
)
return
for attempt in range(1, 3):
download_file(url, destination)
actual_sha256 = sha256_file(destination)
if actual_sha256 == normalized_expected:
log(f"verified {label} sha256={actual_sha256}")
return
log(
f"{label} checksum mismatch on attempt {attempt}/2: "
f"expected={normalized_expected} actual={actual_sha256}"
)
destination.unlink(missing_ok = True)
if attempt == 2:
raise PrebuiltFallback(
f"{label} checksum mismatch after retry: expected={normalized_expected} actual={actual_sha256}"
)
log(f"retrying {label} download after checksum mismatch")
def upstream_source_archive_urls(tag: str) -> list[str]:
encoded_tag = urllib.parse.quote(tag, safe = "")
return [
f"https://codeload.github.com/{UPSTREAM_REPO}/tar.gz/refs/tags/{encoded_tag}",
f"https://github.com/{UPSTREAM_REPO}/archive/refs/tags/{encoded_tag}.tar.gz",
]
def commit_source_archive_urls(repo: str, source_commit: str) -> list[str]:
encoded_commit = urllib.parse.quote(source_commit, safe = "")
return [
f"https://codeload.github.com/{repo}/tar.gz/{encoded_commit}",
f"https://github.com/{repo}/archive/{encoded_commit}.tar.gz",
]
def github_release_assets(repo: str, tag: str) -> dict[str, str]:
payload = fetch_json(
f"https://api.github.com/repos/{repo}/releases/tags/{urllib.parse.quote(tag, safe = '')}"
)
if not isinstance(payload, dict):
raise RuntimeError(f"unexpected release payload for {repo}@{tag}")
return release_asset_map(payload)
def github_release(repo: str, tag: str) -> dict[str, Any]:
payload = fetch_json(
f"https://api.github.com/repos/{repo}/releases/tags/{urllib.parse.quote(tag, safe = '')}"
)
if not isinstance(payload, dict):
raise RuntimeError(f"unexpected release payload for {repo}@{tag}")
return payload
def github_releases(
repo: str,
*,
per_page: int = 100,
max_pages: int = 0,
) -> list[dict[str, Any]]:
releases: list[dict[str, Any]] = []
page = 1
while True:
payload = fetch_json(
f"https://api.github.com/repos/{repo}/releases?per_page={per_page}&page={page}"
)
if not isinstance(payload, list):
raise RuntimeError(f"unexpected releases payload for {repo}")
page_items = [item for item in payload if isinstance(item, dict)]
releases.extend(page_items)
if len(payload) < per_page:
break
page += 1
if max_pages > 0 and page > max_pages:
break
return releases
def latest_upstream_release_tag() -> str:
payload = fetch_json(UPSTREAM_RELEASES_API)
tag = payload.get("tag_name")
if not isinstance(tag, str) or not tag:
raise RuntimeError(
f"latest release tag was missing from {UPSTREAM_RELEASES_API}"
)
return tag
def is_release_tag_like(value: str | None) -> bool:
return isinstance(value, str) and bool(re.fullmatch(r"b\d+", value.strip()))
def release_time_sort_key(release: dict[str, Any]) -> tuple[str, int]:
published_at = release.get("published_at")
created_at = release.get("created_at")
release_id = release.get("id")
timestamp = (
published_at
if isinstance(published_at, str) and published_at
else created_at
if isinstance(created_at, str) and created_at
else ""
)
try:
normalized_id = int(release_id)
except (TypeError, ValueError):
normalized_id = 0
return (timestamp, normalized_id)
def iter_release_payloads_by_time(
repo: str,
published_release_tag: str = "",
requested_tag: str = "",
) -> Iterable[dict[str, Any]]:
if published_release_tag:
yield github_release(repo, published_release_tag)
return
if (
requested_tag
and requested_tag != "latest"
and is_release_tag_like(requested_tag)
):
try:
yield github_release(repo, requested_tag)
return
except urllib.error.HTTPError as exc:
if exc.code == 404:
log(
f"release tag {requested_tag} not found in {repo}; scanning recent releases"
)
else:
raise
except Exception:
raise
releases = [
release
for release in github_releases(
repo, max_pages = DEFAULT_GITHUB_RELEASE_SCAN_MAX_PAGES
)
if isinstance(release, dict)
and not release.get("draft")
and not release.get("prerelease")
]
releases.sort(key = release_time_sort_key, reverse = True)
for release in releases:
yield release
def direct_release_matches_request(
*, release_tag: str, llama_tag: str, requested_tag: str
) -> bool:
if requested_tag == "latest":
return True
for candidate in (release_tag, llama_tag):
if refs_match(candidate, requested_tag):
return True
return False
def synthetic_checksums_for_release(
repo: str, release_tag: str, upstream_tag: str
) -> ApprovedReleaseChecksums:
return ApprovedReleaseChecksums(
repo = repo,
release_tag = release_tag,
upstream_tag = upstream_tag,
artifacts = {},
)
def parse_direct_linux_release_bundle(
repo: str, release: dict[str, Any]
) -> PublishedReleaseBundle | None:
release_tag = release.get("tag_name")
if not isinstance(release_tag, str) or not release_tag:
return None
assets = release_asset_map(release)
artifacts: list[PublishedLlamaArtifact] = []
inferred_labels: list[str] = []
linux_asset_re = re.compile(
r"^app-(?P<label>.+)-(?P<target>linux-x64(?:-cpu)?|linux-x64-(?:cuda12|cuda13)-(?:older|newer|portable))\.tar\.gz$"
)
for asset_name in sorted(assets):
match = linux_asset_re.fullmatch(asset_name)
if not match:
continue
inferred_labels.append(match.group("label"))
target = match.group("target")
if target in {"linux-x64", "linux-x64-cpu"}:
artifacts.append(
PublishedLlamaArtifact(
asset_name = asset_name,
install_kind = "linux-cpu",
runtime_line = None,
coverage_class = None,
supported_sms = [],
min_sm = None,
max_sm = None,
bundle_profile = None,
rank = 1000,
)
)
continue
bundle_profile = target.removeprefix("linux-x64-")
profile = DIRECT_LINUX_BUNDLE_PROFILES.get(bundle_profile)
if profile is None:
continue
artifacts.append(
PublishedLlamaArtifact(
asset_name = asset_name,
install_kind = "linux-cuda",
runtime_line = str(profile["runtime_line"]),
coverage_class = str(profile["coverage_class"]),
supported_sms = [str(value) for value in profile["supported_sms"]],
min_sm = int(profile["min_sm"]),
max_sm = int(profile["max_sm"]),
bundle_profile = bundle_profile,
rank = int(profile["rank"]),
)
)
if not artifacts:
return None
upstream_tag = (
release_tag
if is_release_tag_like(release_tag)
else inferred_labels[0]
if len(set(inferred_labels)) == 1 and inferred_labels
else release_tag
)
selection_log = [
f"published_release: repo={repo}",
f"published_release: tag={release_tag}",
f"published_release: upstream_tag={upstream_tag}",
"published_release: direct_asset_scan=linux",
]
return PublishedReleaseBundle(
repo = repo,
release_tag = release_tag,
upstream_tag = upstream_tag,
assets = assets,
manifest_asset_name = DEFAULT_PUBLISHED_MANIFEST_ASSET,
artifacts = artifacts,
selection_log = selection_log,
)
def direct_linux_release_plan(
release: dict[str, Any],
host: HostInfo,
repo: str,
requested_tag: str,
) -> InstallReleasePlan | None:
bundle = parse_direct_linux_release_bundle(repo, release)
if bundle is None:
return None
if not direct_release_matches_request(
release_tag = bundle.release_tag,
llama_tag = bundle.upstream_tag,
requested_tag = requested_tag,
):
return None
attempts: list[AssetChoice] = []
if host.has_usable_nvidia:
selection = linux_cuda_choice_from_release(host, bundle)
if selection is not None:
attempts.extend(selection.attempts)
cpu_choice = published_asset_choice_for_kind(bundle, "linux-cpu")
if cpu_choice is not None:
attempts.append(cpu_choice)
if not attempts:
raise PrebuiltFallback("no compatible Linux prebuilt asset was found")
return InstallReleasePlan(
requested_tag = requested_tag,
llama_tag = bundle.upstream_tag,
release_tag = bundle.release_tag,
attempts = attempts,
approved_checksums = synthetic_checksums_for_release(
repo,
bundle.release_tag,
bundle.upstream_tag,
),
)
def direct_upstream_release_plan(
release: dict[str, Any],
host: HostInfo,
repo: str,
requested_tag: str,
) -> InstallReleasePlan | None:
release_tag = release.get("tag_name")
if not isinstance(release_tag, str) or not release_tag:
return None
if not direct_release_matches_request(
release_tag = release_tag,
llama_tag = release_tag,
requested_tag = requested_tag,
):
return None
assets = release_asset_map(release)
attempts: list[AssetChoice] = []
if host.is_windows and host.is_x86_64:
if host.has_usable_nvidia:
torch_preference = detect_torch_cuda_runtime_preference(host)
attempts.extend(
windows_cuda_attempts(
host,
release_tag,
assets,
torch_preference.runtime_line,
torch_preference.selection_log,
)
)
cpu_asset = f"llama-{release_tag}-bin-win-cpu-x64.zip"
cpu_url = assets.get(cpu_asset)
if cpu_url:
attempts.append(
AssetChoice(
repo = repo,
tag = release_tag,
name = cpu_asset,
url = cpu_url,
source_label = "upstream",
install_kind = "windows-cpu",
)
)
elif host.is_macos and host.is_arm64:
asset_name = f"llama-{release_tag}-bin-macos-arm64.tar.gz"
asset_url = assets.get(asset_name)
if asset_url:
attempts.append(
AssetChoice(
repo = repo,
tag = release_tag,
name = asset_name,
url = asset_url,
source_label = "upstream",
install_kind = "macos-arm64",
)
)
elif host.is_macos and host.is_x86_64:
asset_name = f"llama-{release_tag}-bin-macos-x64.tar.gz"
asset_url = assets.get(asset_name)
if asset_url:
attempts.append(
AssetChoice(
repo = repo,
tag = release_tag,
name = asset_name,
url = asset_url,
source_label = "upstream",
install_kind = "macos-x64",
)
)
elif host.is_linux and host.is_x86_64 and not host.has_usable_nvidia:
asset_name = f"llama-{release_tag}-bin-ubuntu-x64.tar.gz"
asset_url = assets.get(asset_name)
if asset_url:
attempts.append(
AssetChoice(
repo = repo,
tag = release_tag,
name = asset_name,
url = asset_url,
source_label = "upstream",
install_kind = "linux-cpu",
)
)
if not attempts:
raise PrebuiltFallback("no compatible upstream prebuilt asset was found")
return InstallReleasePlan(
requested_tag = requested_tag,
llama_tag = release_tag,
release_tag = release_tag,
attempts = attempts,
approved_checksums = synthetic_checksums_for_release(
repo,
release_tag,
release_tag,
),
)
def resolve_simple_install_release_plans(
llama_tag: str,
host: HostInfo,
published_repo: str,
published_release_tag: str,
*,
max_release_fallbacks: int = DEFAULT_MAX_PREBUILT_RELEASE_FALLBACKS,
) -> tuple[str, list[InstallReleasePlan]]:
repo = published_repo or DEFAULT_PUBLISHED_REPO
requested_tag = normalized_requested_llama_tag(llama_tag)
allow_older_release_fallback = (
requested_tag == "latest" and not published_release_tag
)
release_limit = max(1, max_release_fallbacks)
plans: list[InstallReleasePlan] = []
last_error: PrebuiltFallback | None = None
try:
releases = iter_release_payloads_by_time(
repo, published_release_tag, requested_tag
)
for release in releases:
try:
if host.is_linux and repo == "unslothai/llama.cpp":
plan = direct_linux_release_plan(release, host, repo, requested_tag)
else:
plan = direct_upstream_release_plan(
release, host, repo, requested_tag
)
if plan is None:
continue
except PrebuiltFallback as exc:
last_error = exc
if not allow_older_release_fallback:
raise
release_tag = release.get("tag_name") or "unknown"
log(
"published release skipped for install planning: "
f"{repo}@{release_tag} ({exc})"
)
continue
plans.append(plan)
if not allow_older_release_fallback or len(plans) >= release_limit:
break
except PrebuiltFallback:
raise
except Exception as exc:
raise PrebuiltFallback(
f"failed to inspect published releases in {repo}: {exc}"
) from exc
if plans:
return requested_tag, plans
if last_error is not None:
raise last_error
raise PrebuiltFallback(
f"no installable published llama.cpp releases were found in {repo}"
)
def normalized_requested_llama_tag(requested_tag: str | None) -> str:
if isinstance(requested_tag, str):
normalized = requested_tag.strip()
if normalized:
return normalized
return "latest"
def normalize_compute_cap(value: Any) -> str | None:
raw = str(value).strip()
if not raw:
return None
if "." in raw:
parts = raw.split(".", 1)
if len(parts) != 2:
return None
major, minor = parts
if not major.isdigit() or not minor.isdigit():
return None
return f"{int(major)}{int(minor)}"
if raw.isdigit():
return str(int(raw))
return None
def normalize_compute_caps(compute_caps: Iterable[str]) -> list[str]:
normalized: list[str] = []
seen: set[str] = set()
for raw in compute_caps:
normalized_value = normalize_compute_cap(raw)
if normalized_value is None:
continue
if normalized_value in seen:
continue
seen.add(normalized_value)
normalized.append(normalized_value)
normalized.sort(key = int)
return normalized
def parse_cuda_visible_devices(value: str | None) -> list[str] | None:
if value is None:
return None
raw = value.strip()
if not raw or raw == "-1":
return []
return [token.strip() for token in raw.split(",") if token.strip()]
def supports_explicit_visible_device_matching(
visible_devices: list[str] | None,
) -> bool:
if not visible_devices:
return False
for token in visible_devices:
lowered = token.lower()
if token.isdigit() or lowered.startswith("gpu-"):
continue
return False
return True
def select_visible_gpu_rows(
gpu_rows: Iterable[tuple[str, str, str]],
visible_devices: list[str] | None,
) -> list[tuple[str, str, str]]:
rows = list(gpu_rows)
if visible_devices is None:
return rows
if not visible_devices:
return []
by_index = {index: (index, uuid, cap) for index, uuid, cap in rows}
by_uuid = {uuid.lower(): (index, uuid, cap) for index, uuid, cap in rows}
selected: list[tuple[str, str, str]] = []
seen_indices: set[str] = set()
for token in visible_devices:
row = by_index.get(token)
if row is None:
normalized_token = token.lower()
row = by_uuid.get(normalized_token)
if row is None and normalized_token.startswith("gpu-"):
row = by_uuid.get(normalized_token)
if row is None and not normalized_token.startswith("gpu-"):
row = by_uuid.get("gpu-" + normalized_token)
if row is None:
continue
index = row[0]
if index in seen_indices:
continue
seen_indices.add(index)
selected.append(row)
return selected
def dir_provides_exact_library(directory: str | Path, library: str) -> bool:
if not library:
return False
candidate = Path(directory) / library
return candidate.exists() and (candidate.is_file() or candidate.is_symlink())
def linux_runtime_dirs_for_required_libraries(
required_libraries: Iterable[str],
) -> list[str]:
required = [library for library in required_libraries if library]
candidates: list[str | Path] = []
env_dirs = os.environ.get("CUDA_RUNTIME_LIB_DIR", "")
if env_dirs:
candidates.extend(part for part in env_dirs.split(os.pathsep) if part)
ld_library_path = os.environ.get("LD_LIBRARY_PATH", "")
if ld_library_path:
candidates.extend(part for part in ld_library_path.split(os.pathsep) if part)
cuda_roots: list[Path] = []
for name in ("CUDA_HOME", "CUDA_PATH", "CUDA_ROOT"):
value = os.environ.get(name)
if value:
cuda_roots.append(Path(value))
cuda_roots.extend(
Path(path) for path in glob_paths("/usr/local/cuda", "/usr/local/cuda-*")
)
for root in cuda_roots:
candidates.extend(
[
root / "lib",
root / "lib64",
root / "targets" / "x86_64-linux" / "lib",
]
)
candidates.extend(
Path(path)
for path in glob_paths(
"/lib",
"/lib64",
"/usr/lib",
"/usr/lib64",
"/usr/local/lib",
"/usr/local/lib64",
"/lib/x86_64-linux-gnu",
"/usr/lib/x86_64-linux-gnu",
)
)
candidates.extend(
Path(path)
for path in glob_paths("/usr/local/lib/ollama/cuda_v*", "/usr/lib/wsl/lib")
)
candidates.extend(Path(path) for path in python_runtime_dirs())
candidates.extend(Path(path) for path in ldconfig_runtime_dirs(required))
resolved = dedupe_existing_dirs(candidates)
if not required:
return resolved
matched: list[tuple[int, str]] = []
for directory in resolved:
base = Path(directory)
provided = sum(
1 for library in required if dir_provides_exact_library(directory, library)
)
if provided:
matched.append((provided, directory))
matched.sort(key = lambda item: item[0], reverse = True)
return [directory for _, directory in matched]
def detected_linux_runtime_lines() -> tuple[list[str], dict[str, list[str]]]:
line_requirements = {
"cuda13": ["libcudart.so.13", "libcublas.so.13"],
"cuda12": ["libcudart.so.12", "libcublas.so.12"],
}
detected: list[str] = []
runtime_dirs: dict[str, list[str]] = {}
for line, required in line_requirements.items():
dirs = linux_runtime_dirs_for_required_libraries(required)
library_matches: dict[str, list[str]] = {}
matching_dirs: list[str] = []
for library in required:
matched_dirs = [
directory
for directory in dirs
if any(Path(directory).glob(f"{library}*"))
]
if not matched_dirs:
library_matches = {}
matching_dirs = []
break
library_matches[library] = matched_dirs
for directory in matched_dirs:
if directory not in matching_dirs:
matching_dirs.append(directory)
if library_matches:
detected.append(line)
runtime_dirs[line] = matching_dirs
return detected, runtime_dirs
def release_asset_map(release: dict[str, Any]) -> dict[str, str]:
assets = release.get("assets")
if not isinstance(assets, list):
return {}
return {
asset["name"]: asset.get("browser_download_url", "")
for asset in assets
if isinstance(asset, dict)
and isinstance(asset.get("name"), str)
and isinstance(asset.get("browser_download_url"), str)
}
def parse_published_artifact(raw: Any) -> PublishedLlamaArtifact | None:
if not isinstance(raw, dict):
raise ValueError("artifact entry was not an object")
asset_name = raw.get("asset_name")
install_kind = raw.get("install_kind")
if not isinstance(asset_name, str) or not asset_name:
raise ValueError("artifact.asset_name was missing or not a string")
if not isinstance(install_kind, str) or not install_kind:
raise ValueError(
f"artifact {asset_name} install_kind was missing or not a string"
)
supported_sms_raw = raw.get("supported_sms", [])
if not isinstance(supported_sms_raw, (list, tuple)):
raise ValueError(f"artifact {asset_name} supported_sms must be a list or tuple")
if any(not isinstance(value, (int, str)) for value in supported_sms_raw):
raise ValueError(
f"artifact {asset_name} supported_sms entries must be ints or strings"
)
supported_sms = normalize_compute_caps(supported_sms_raw)
min_sm_raw = raw.get("min_sm")
max_sm_raw = raw.get("max_sm")
try:
min_sm = int(min_sm_raw) if min_sm_raw is not None else None
max_sm = int(max_sm_raw) if max_sm_raw is not None else None
except (TypeError, ValueError) as exc:
raise ValueError(
f"artifact {asset_name} min_sm/max_sm were not integers"
) from exc
runtime_line = raw.get("runtime_line")
coverage_class = raw.get("coverage_class")
bundle_profile = raw.get("bundle_profile")
rank_raw = raw.get("rank", 1000)
if runtime_line is not None and not isinstance(runtime_line, str):
raise ValueError(f"artifact {asset_name} runtime_line was not a string")
if coverage_class is not None and not isinstance(coverage_class, str):
raise ValueError(f"artifact {asset_name} coverage_class was not a string")
if bundle_profile is not None and not isinstance(bundle_profile, str):
raise ValueError(f"artifact {asset_name} bundle_profile was not a string")
try:
rank = int(rank_raw)
except (TypeError, ValueError):
raise ValueError(f"artifact {asset_name} rank was not an integer")
return PublishedLlamaArtifact(
asset_name = asset_name,
install_kind = install_kind,
runtime_line = runtime_line
if isinstance(runtime_line, str) and runtime_line
else None,
coverage_class = coverage_class
if isinstance(coverage_class, str) and coverage_class
else None,
supported_sms = supported_sms,
min_sm = min_sm,
max_sm = max_sm,
bundle_profile = bundle_profile
if isinstance(bundle_profile, str) and bundle_profile
else None,
rank = rank,
)
def parse_published_release_bundle(
repo: str, release: dict[str, Any]
) -> PublishedReleaseBundle | None:
release_tag = release.get("tag_name")
if not isinstance(release_tag, str) or not release_tag:
return None
assets = release_asset_map(release)
manifest_url = assets.get(DEFAULT_PUBLISHED_MANIFEST_ASSET)
if not manifest_url:
return None
# Mixed repos are filtered by an explicit release-side manifest rather than
# by release tag or asset filename conventions.
manifest_bytes = download_bytes(
manifest_url,
timeout = 30,
headers = auth_headers(manifest_url),
)
manifest_sha256 = sha256_bytes(manifest_bytes)
try:
manifest_payload = json.loads(manifest_bytes.decode("utf-8"))
except (UnicodeDecodeError, json.JSONDecodeError) as exc:
raise RuntimeError(
f"published manifest {DEFAULT_PUBLISHED_MANIFEST_ASSET} was not valid JSON"
) from exc
if not isinstance(manifest_payload, dict):
raise RuntimeError(
f"published manifest {DEFAULT_PUBLISHED_MANIFEST_ASSET} was not a JSON object"
)
validate_schema_version(
manifest_payload,
label = f"published manifest {DEFAULT_PUBLISHED_MANIFEST_ASSET} in {repo}@{release_tag}",
)
component = manifest_payload.get("component")
upstream_tag = manifest_payload.get("upstream_tag")
source_repo = manifest_payload.get("source_repo")
source_repo_url = manifest_payload.get("source_repo_url")
source_ref_kind = normalize_source_ref_kind(manifest_payload.get("source_ref_kind"))
requested_source_ref = manifest_payload.get("requested_source_ref")
resolved_source_ref = manifest_payload.get("resolved_source_ref")
source_commit = normalize_source_commit(manifest_payload.get("source_commit"))
source_commit_short = manifest_payload.get("source_commit_short")
if component != "llama.cpp":
return None
if not isinstance(upstream_tag, str) or not upstream_tag:
raise RuntimeError(
f"published manifest {DEFAULT_PUBLISHED_MANIFEST_ASSET} in {repo}@{release_tag} omitted upstream_tag"
)
artifacts_payload = manifest_payload.get("artifacts")
if not isinstance(artifacts_payload, list):
raise RuntimeError(
f"published manifest {DEFAULT_PUBLISHED_MANIFEST_ASSET} in {repo}@{release_tag} omitted artifacts"
)
artifacts: list[PublishedLlamaArtifact] = []
for index, raw_artifact in enumerate(artifacts_payload):
try:
artifact = parse_published_artifact(raw_artifact)
except ValueError as exc:
log(
f"published artifact ignored for {repo}@{release_tag} artifact[{index}]: {exc}"
)
continue
if artifact is not None:
artifacts.append(artifact)
selection_log = [
f"published_release: repo={repo}",
f"published_release: tag={release_tag}",
f"published_release: manifest={DEFAULT_PUBLISHED_MANIFEST_ASSET}",
f"published_release: upstream_tag={upstream_tag}",
]
if isinstance(source_repo, str) and source_repo:
selection_log.append(f"published_release: source_repo={source_repo}")
if source_commit:
selection_log.append(f"published_release: source_commit={source_commit}")
return PublishedReleaseBundle(
repo = repo,
release_tag = release_tag,
upstream_tag = upstream_tag,
manifest_sha256 = manifest_sha256,
source_repo = source_repo
if isinstance(source_repo, str) and source_repo
else None,
source_repo_url = source_repo_url
if isinstance(source_repo_url, str) and source_repo_url
else None,
source_ref_kind = source_ref_kind,
requested_source_ref = requested_source_ref
if isinstance(requested_source_ref, str) and requested_source_ref
else None,
resolved_source_ref = resolved_source_ref
if isinstance(resolved_source_ref, str) and resolved_source_ref
else None,
source_commit = source_commit,
source_commit_short = source_commit_short
if isinstance(source_commit_short, str) and source_commit_short
else None,
assets = assets,
manifest_asset_name = DEFAULT_PUBLISHED_MANIFEST_ASSET,
artifacts = artifacts,
selection_log = selection_log,
)
def parse_approved_release_checksums(
repo: str,
release_tag: str,
payload: Any,
) -> ApprovedReleaseChecksums:
if not isinstance(payload, dict):
raise RuntimeError(
f"published checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET} was not a JSON object"
)
validate_schema_version(
payload,
label = f"published checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET}",
)
if payload.get("component") != "llama.cpp":
raise RuntimeError(
f"published checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET} did not describe llama.cpp"
)
payload_release_tag = payload.get("release_tag")
if not isinstance(payload_release_tag, str) or not payload_release_tag:
raise RuntimeError(
f"published checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET} omitted release_tag"
)
if payload_release_tag != release_tag:
raise RuntimeError(
f"published checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET} release_tag={payload_release_tag} "
f"did not match pinned release tag {release_tag}"
)
upstream_tag = payload.get("upstream_tag")
if not isinstance(upstream_tag, str) or not upstream_tag:
raise RuntimeError(
f"published checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET} omitted upstream_tag"
)
artifacts_payload = payload.get("artifacts")
if not isinstance(artifacts_payload, dict):
raise RuntimeError(
f"published checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET} omitted artifacts"
)
artifacts: dict[str, ApprovedArtifactHash] = {}
for asset_name, raw_entry in artifacts_payload.items():
if not isinstance(asset_name, str) or not asset_name:
raise RuntimeError(
"published checksum asset used a non-string artifact key"
)
if not isinstance(raw_entry, dict):
raise RuntimeError(
f"published checksum entry for {asset_name} was not an object"
)
digest = normalize_sha256_digest(raw_entry.get("sha256"))
if not digest:
raise RuntimeError(
f"published checksum entry for {asset_name} omitted a valid sha256"
)
repo_value = raw_entry.get("repo")
kind_value = raw_entry.get("kind")
artifacts[asset_name] = ApprovedArtifactHash(
asset_name = asset_name,
sha256 = digest,
repo = repo_value if isinstance(repo_value, str) and repo_value else None,
kind = kind_value if isinstance(kind_value, str) and kind_value else None,
)
source_commit = normalize_source_commit(payload.get("source_commit"))
source_commit_short = payload.get("source_commit_short")
source_repo = payload.get("source_repo")
source_repo_url = payload.get("source_repo_url")
source_ref_kind = normalize_source_ref_kind(payload.get("source_ref_kind"))
requested_source_ref = payload.get("requested_source_ref")
resolved_source_ref = payload.get("resolved_source_ref")
return ApprovedReleaseChecksums(
repo = repo,
release_tag = release_tag,
upstream_tag = upstream_tag,
source_repo = source_repo
if isinstance(source_repo, str) and source_repo
else None,
source_repo_url = source_repo_url
if isinstance(source_repo_url, str) and source_repo_url
else None,
source_ref_kind = source_ref_kind,
requested_source_ref = requested_source_ref
if isinstance(requested_source_ref, str) and requested_source_ref
else None,
resolved_source_ref = resolved_source_ref
if isinstance(resolved_source_ref, str) and resolved_source_ref
else None,
source_commit = source_commit,
source_commit_short = source_commit_short
if isinstance(source_commit_short, str) and source_commit_short
else None,
artifacts = artifacts,
)
def load_approved_release_checksums(
repo: str, release_tag: str
) -> ApprovedReleaseChecksums:
try:
release = github_release(repo, release_tag)
except Exception as exc:
raise PrebuiltFallback(
f"approved prebuilt release {repo}@{release_tag} was not available"
) from exc
assets = release_asset_map(release)
checksum_url = assets.get(DEFAULT_PUBLISHED_SHA256_ASSET)
if not checksum_url:
raise PrebuiltFallback(
f"approved prebuilt release {repo}@{release_tag} did not expose {DEFAULT_PUBLISHED_SHA256_ASSET}"
)
try:
payload = fetch_json(checksum_url)
checksums = parse_approved_release_checksums(repo, release_tag, payload)
except PrebuiltFallback:
raise
except Exception as exc:
raise PrebuiltFallback(
f"approved checksum asset {DEFAULT_PUBLISHED_SHA256_ASSET} in {repo}@{release_tag} was invalid"
) from exc
return checksums
def iter_published_release_bundles(
repo: str, published_release_tag: str = ""
) -> Iterable[PublishedReleaseBundle]:
releases = (
[github_release(repo, published_release_tag)]
if published_release_tag
else github_releases(repo, max_pages = DEFAULT_GITHUB_RELEASE_SCAN_MAX_PAGES)
)
for release in releases:
if not published_release_tag and (
release.get("draft") or release.get("prerelease")
):
continue
try:
bundle = parse_published_release_bundle(repo, release)
except Exception as exc:
release_tag = release.get("tag_name", "unknown")
log(f"published release metadata ignored for {repo}@{release_tag}: {exc}")
continue
if bundle is None:
continue
yield bundle
def linux_cuda_choice_from_release(
host: HostInfo,
release: PublishedReleaseBundle,
preferred_runtime_line: str | None = None,
selection_preamble: Iterable[str] = (),
) -> LinuxCudaSelection | None:
host_sms = normalize_compute_caps(host.compute_caps)
detected_runtime_lines, runtime_dirs = detected_linux_runtime_lines()
driver_runtime_lines = compatible_linux_runtime_lines(host)
runtime_lines = [
runtime_line
for runtime_line in detected_runtime_lines
if runtime_line in driver_runtime_lines
]
ordered_runtime_lines = list(runtime_lines)
selection_log = (
list(release.selection_log)
+ list(selection_preamble)
+ [
f"linux_cuda_selection: release={release.release_tag}",
f"linux_cuda_selection: detected_sms={','.join(host_sms) if host_sms else 'unknown'}",
"linux_cuda_selection: detected_runtime_lines="
+ (",".join(detected_runtime_lines) if detected_runtime_lines else "none"),
"linux_cuda_selection: driver_runtime_lines="
+ (",".join(driver_runtime_lines) if driver_runtime_lines else "none"),
"linux_cuda_selection: compatible_runtime_lines="
+ (",".join(runtime_lines) if runtime_lines else "none"),
]
)
for runtime_line in ("cuda13", "cuda12"):
selection_log.append(
"linux_cuda_selection: runtime_dirs "
f"{runtime_line}="
+ (
",".join(runtime_dirs.get(runtime_line, []))
if runtime_dirs.get(runtime_line)
else "none"
)
)
published_artifacts = [
artifact
for artifact in release.artifacts
if artifact.install_kind == "linux-cuda"
]
published_asset_names = sorted(
artifact.asset_name for artifact in published_artifacts
)
selection_log.append(
"linux_cuda_selection: published_assets="
+ (",".join(published_asset_names) if published_asset_names else "none")
)
if not host_sms:
selection_log.append(
"linux_cuda_selection: compute capability detection unavailable; prefer portable by runtime line"
)
if not runtime_lines:
selection_log.append(
"linux_cuda_selection: no Linux CUDA runtime line satisfied both runtime libraries and driver compatibility"
)
return None
if preferred_runtime_line:
if preferred_runtime_line in ordered_runtime_lines:
ordered_runtime_lines = [preferred_runtime_line] + [
runtime_line
for runtime_line in ordered_runtime_lines
if runtime_line != preferred_runtime_line
]
selection_log.append(
"linux_cuda_selection: torch_preferred_runtime_line="
f"{preferred_runtime_line} reordered_attempts={','.join(ordered_runtime_lines)}"
)
else:
selection_log.append(
"linux_cuda_selection: torch_preferred_runtime_line="
f"{preferred_runtime_line} unavailable_on_host"
)
attempts: list[AssetChoice] = []
seen_attempts: set[str] = set()
def add_attempt(
artifact: PublishedLlamaArtifact, asset_url: str, reason: str
) -> None:
asset_name = artifact.asset_name
if asset_name in seen_attempts:
return
seen_attempts.add(asset_name)
attempts.append(
AssetChoice(
repo = release.repo,
tag = release.release_tag,
name = asset_name,
url = asset_url,
source_label = "published",
is_ready_bundle = True,
install_kind = "linux-cuda",
bundle_profile = artifact.bundle_profile,
runtime_line = artifact.runtime_line,
coverage_class = artifact.coverage_class,
supported_sms = artifact.supported_sms,
min_sm = artifact.min_sm,
max_sm = artifact.max_sm,
selection_log = list(selection_log)
+ [
"linux_cuda_selection: selected "
f"{asset_name} runtime_line={artifact.runtime_line} coverage_class={artifact.coverage_class} reason={reason}"
],
)
)
for runtime_line in ordered_runtime_lines:
coverage_candidates: list[tuple[PublishedLlamaArtifact, str]] = []
portable_candidate: tuple[PublishedLlamaArtifact, str] | None = None
for artifact in published_artifacts:
if artifact.runtime_line != runtime_line:
continue
asset_name = artifact.asset_name
asset_url = release.assets.get(asset_name)
if not asset_url:
selection_log.append(
f"linux_cuda_selection: reject {asset_name} missing asset"
)
continue
if not host_sms and artifact.coverage_class != "portable":
selection_log.append(
"linux_cuda_selection: reject "
f"{asset_name} runtime_line={runtime_line} coverage_class={artifact.coverage_class} "
"reason=unknown_compute_caps_prefer_portable"
)
continue
if not artifact.supported_sms:
selection_log.append(
"linux_cuda_selection: reject "
f"{asset_name} runtime_line={runtime_line} coverage_class={artifact.coverage_class} "
"reason=artifact_missing_supported_sms"
)
continue
if artifact.min_sm is None or artifact.max_sm is None:
selection_log.append(
"linux_cuda_selection: reject "
f"{asset_name} runtime_line={runtime_line} coverage_class={artifact.coverage_class} "
"reason=artifact_missing_sm_bounds"
)
continue
supported_sms = {str(value) for value in artifact.supported_sms}
missing_sms = [sm for sm in host_sms if sm not in supported_sms]
out_of_range_sms = [
sm
for sm in host_sms
if not (artifact.min_sm <= int(sm) <= artifact.max_sm)
]
reasons: list[str] = []
if missing_sms:
reasons.append(f"missing_sms={','.join(missing_sms)}")
if out_of_range_sms:
reasons.append(f"out_of_range_sms={','.join(out_of_range_sms)}")
if reasons:
selection_log.append(
"linux_cuda_selection: reject "
f"{asset_name} runtime_line={runtime_line} coverage_class={artifact.coverage_class} "
f"coverage={artifact.min_sm}-{artifact.max_sm} supported={','.join(artifact.supported_sms)} "
f"reasons={' '.join(reasons)}"
)
continue
selection_log.append(
"linux_cuda_selection: accept "
f"{asset_name} runtime_line={runtime_line} coverage_class={artifact.coverage_class} "
f"coverage={artifact.min_sm}-{artifact.max_sm} supported={','.join(artifact.supported_sms)}"
)
if artifact.coverage_class == "portable":
portable_candidate = (artifact, asset_url)
else:
coverage_candidates.append((artifact, asset_url))
if coverage_candidates:
artifact, url = sorted(
coverage_candidates,
key = lambda item: (
(item[0].max_sm or 0) - (item[0].min_sm or 0),
item[0].rank,
item[0].max_sm or 0,
),
)[0]
add_attempt(artifact, url, "best coverage for runtime line")
if portable_candidate:
artifact, url = portable_candidate
add_attempt(artifact, url, "portable fallback for runtime line")
if not attempts:
return None
selection_log.append(
"linux_cuda_selection: attempt_order="
+ ",".join(choice.name for choice in attempts)
)
for attempt in attempts:
attempt.selection_log = list(selection_log) + [
"linux_cuda_selection: attempt "
f"{attempt.name} runtime_line={attempt.runtime_line} coverage_class={attempt.coverage_class}"
]
return LinuxCudaSelection(attempts = attempts, selection_log = selection_log)
def latest_published_linux_cuda_tag(host: HostInfo, published_repo: str) -> str | None:
for release in iter_published_release_bundles(published_repo):
if linux_cuda_choice_from_release(host, release):
return release.upstream_tag
return None
def iter_upstream_releases() -> Iterable[dict[str, Any]]:
for release in github_releases(
UPSTREAM_REPO, max_pages = DEFAULT_GITHUB_RELEASE_SCAN_MAX_PAGES
):
if release.get("draft") or release.get("prerelease"):
continue
yield release
def pinned_published_release_bundle(
repo: str, published_release_tag: str
) -> PublishedReleaseBundle:
bundle = next(iter_published_release_bundles(repo, published_release_tag), None)
if bundle is None:
raise PrebuiltFallback(
f"published release {repo}@{published_release_tag} did not expose a usable llama.cpp manifest"
)
return bundle
def validated_checksums_for_bundle(
repo: str, bundle: PublishedReleaseBundle
) -> ApprovedReleaseChecksums:
checksums = load_approved_release_checksums(repo, bundle.release_tag)
manifest_hash = checksums.artifacts.get(bundle.manifest_asset_name)
if manifest_hash is not None and bundle.manifest_sha256 is not None:
if manifest_hash.sha256 != bundle.manifest_sha256:
raise PrebuiltFallback(
"published manifest checksum did not match the approved checksum asset"
)
# Accept bundles that carry only an exact-commit source archive
# (e.g. llama.cpp-source-commit-<sha>.tar.gz) without requiring the
# legacy llama.cpp-source-<upstream_tag>.tar.gz entry.
if exact_source_archive_hash(checksums) is None:
require_approved_source_hash(checksums, bundle.upstream_tag)
return checksums
def published_release_matches_request(
bundle: PublishedReleaseBundle, requested_ref: str
) -> bool:
if requested_ref == "latest":
return True
for candidate in (
bundle.upstream_tag,
bundle.requested_source_ref,
bundle.resolved_source_ref,
bundle.source_commit,
):
if refs_match(candidate, requested_ref):
return True
return False
def resolve_published_release(
requested_tag: str | None,
published_repo: str,
published_release_tag: str = "",
) -> ResolvedPublishedRelease:
repo = published_repo or DEFAULT_PUBLISHED_REPO
normalized_requested = normalized_requested_llama_tag(requested_tag)
if published_release_tag:
bundle = pinned_published_release_bundle(repo, published_release_tag)
if not published_release_matches_request(bundle, normalized_requested):
raise PrebuiltFallback(
"published release "
f"{repo}@{published_release_tag} targeted upstream tag {bundle.upstream_tag}, "
f"but requested {normalized_requested}"
)
return ResolvedPublishedRelease(
bundle = bundle,
checksums = validated_checksums_for_bundle(repo, bundle),
)
skipped_invalid = 0
for bundle in iter_published_release_bundles(repo):
if not published_release_matches_request(bundle, normalized_requested):
continue
try:
checksums = validated_checksums_for_bundle(repo, bundle)
except PrebuiltFallback as exc:
skipped_invalid += 1
log(
"published release ignored for install resolution: "
f"{repo}@{bundle.release_tag} ({exc})"
)
continue
return ResolvedPublishedRelease(bundle = bundle, checksums = checksums)
if normalized_requested == "latest":
if skipped_invalid:
raise PrebuiltFallback(
f"no usable published llama.cpp releases were available in {repo}"
)
raise PrebuiltFallback(
f"no published llama.cpp releases were available in {repo}"
)
raise PrebuiltFallback(
f"no published prebuilt release in {repo} matched upstream tag {normalized_requested}"
)
def iter_resolved_published_releases(
requested_tag: str | None,
published_repo: str,
published_release_tag: str = "",
) -> Iterable[ResolvedPublishedRelease]:
repo = published_repo or DEFAULT_PUBLISHED_REPO
normalized_requested = normalized_requested_llama_tag(requested_tag)
if published_release_tag:
bundle = pinned_published_release_bundle(repo, published_release_tag)
if not published_release_matches_request(bundle, normalized_requested):
raise PrebuiltFallback(
"published release "
f"{repo}@{published_release_tag} targeted upstream tag {bundle.upstream_tag}, "
f"but requested {normalized_requested}"
)
yield ResolvedPublishedRelease(
bundle = bundle,
checksums = validated_checksums_for_bundle(repo, bundle),
)
return
matched_any = False
skipped_invalid = 0
yielded_valid = False
for bundle in iter_published_release_bundles(repo):
if not published_release_matches_request(bundle, normalized_requested):
continue
matched_any = True
try:
checksums = validated_checksums_for_bundle(repo, bundle)
except PrebuiltFallback as exc:
skipped_invalid += 1
log(
"published release ignored for install resolution: "
f"{repo}@{bundle.release_tag} ({exc})"
)
continue
yielded_valid = True
yield ResolvedPublishedRelease(bundle = bundle, checksums = checksums)
if yielded_valid:
return
if matched_any:
if skipped_invalid:
raise PrebuiltFallback(
f"no usable published llama.cpp releases were available in {repo}"
)
return
if normalized_requested == "latest":
raise PrebuiltFallback(
f"no published llama.cpp releases were available in {repo}"
)
raise PrebuiltFallback(
f"no published prebuilt release in {repo} matched upstream tag {normalized_requested}"
)
def resolve_requested_llama_tag(
requested_tag: str | None,
published_repo: str = "",
published_release_tag: str = "",
) -> str:
"""Resolve a llama.cpp tag for source-build fallback.
Resolution order:
1. Concrete tag (e.g. "b8508") -- returned as-is.
2. "latest" with published_repo -- resolve the latest usable Unsloth
published release bundle and return its upstream_tag. This is the
preferred version that matches the published prebuilt metadata.
3. "latest" without published_repo or if (2) fails -- query the upstream
ggml-org/llama.cpp repo. This may return a newer, untested tag.
The Unsloth repo is preferred because its releases are pinned to specific
upstream tags that have been validated with Unsloth Studio. Using the
upstream bleeding-edge tag risks API/ABI incompatibilities.
"""
normalized_requested = normalized_requested_llama_tag(requested_tag)
if normalized_requested != "latest":
return normalized_requested
# Prefer the Unsloth release repo tag (tested/approved) over bleeding-edge
# upstream. For example, unslothai/llama.cpp may publish b8508 while
# ggml-org/llama.cpp latest is b8514. The source-build fallback should
# compile the same version the prebuilt path would have installed.
if published_repo:
try:
return resolve_published_release(
"latest",
published_repo,
published_release_tag,
).bundle.upstream_tag
except Exception:
pass
# Fall back to upstream ggml-org latest release tag
return latest_upstream_release_tag()
def resolve_requested_install_tag(
requested_tag: str | None,
published_release_tag: str = "",
published_repo: str = DEFAULT_PUBLISHED_REPO,
) -> str:
return resolve_published_release(
requested_tag,
published_repo,
published_release_tag,
).bundle.upstream_tag
def exact_source_archive_hash(
checksums: ApprovedReleaseChecksums,
) -> ApprovedArtifactHash | None:
if not checksums.source_commit:
return None
return checksums.artifacts.get(
exact_source_archive_logical_name(checksums.source_commit)
)
def source_clone_url_from_checksums(checksums: ApprovedReleaseChecksums) -> str | None:
return source_repo_clone_url(checksums.source_repo, checksums.source_repo_url)
def source_build_plan_for_release(
release: ResolvedPublishedRelease,
) -> SourceBuildPlan:
checksums = release.checksums
exact_source = exact_source_archive_hash(checksums)
source_repo = checksums.source_repo or release.bundle.source_repo
source_repo_url = checksums.source_repo_url or release.bundle.source_repo_url
requested_source_ref = (
checksums.requested_source_ref or release.bundle.requested_source_ref
)
resolved_source_ref = (
checksums.resolved_source_ref or release.bundle.resolved_source_ref
)
source_commit = checksums.source_commit or release.bundle.source_commit
source_ref_kind = checksums.source_ref_kind or release.bundle.source_ref_kind
source_url = source_repo_clone_url(source_repo, source_repo_url)
if exact_source is not None and source_url and source_commit:
return SourceBuildPlan(
source_url = source_url,
source_ref = source_commit,
source_ref_kind = "commit",
compatibility_upstream_tag = release.bundle.upstream_tag,
source_repo = source_repo,
source_repo_url = source_repo_url,
requested_source_ref = requested_source_ref,
resolved_source_ref = resolved_source_ref,
source_commit = source_commit,
)
source_ref = checkout_friendly_ref(
source_ref_kind, resolved_source_ref or requested_source_ref
)
if (
source_url
and source_ref
and source_ref_kind in {"tag", "branch", "pull", "commit"}
):
return SourceBuildPlan(
source_url = source_url,
source_ref = source_ref,
source_ref_kind = source_ref_kind,
compatibility_upstream_tag = release.bundle.upstream_tag,
source_repo = source_repo,
source_repo_url = source_repo_url,
requested_source_ref = requested_source_ref,
resolved_source_ref = resolved_source_ref,
source_commit = source_commit,
)
return SourceBuildPlan(
source_url = source_url_from_repo_slug(UPSTREAM_REPO)
or "https://github.com/ggml-org/llama.cpp",
source_ref = release.bundle.upstream_tag,
source_ref_kind = "tag",
compatibility_upstream_tag = release.bundle.upstream_tag,
source_repo = source_repo,
source_repo_url = source_repo_url,
requested_source_ref = requested_source_ref,
resolved_source_ref = resolved_source_ref,
source_commit = source_commit,
)
def resolve_source_build_plan(
requested_tag: str | None,
published_repo: str,
published_release_tag: str = "",
) -> SourceBuildPlan:
normalized_requested = normalized_requested_llama_tag(requested_tag)
if normalized_requested != "latest":
try:
release = resolve_published_release(
normalized_requested,
published_repo,
published_release_tag,
)
return source_build_plan_for_release(release)
except Exception:
pass
inferred_kind = infer_source_ref_kind(normalized_requested)
return SourceBuildPlan(
source_url = "https://github.com/ggml-org/llama.cpp",
source_ref = checkout_friendly_ref(inferred_kind, normalized_requested)
or normalized_requested,
source_ref_kind = inferred_kind,
compatibility_upstream_tag = normalized_requested,
)
if published_repo:
try:
release = resolve_published_release(
"latest",
published_repo,
published_release_tag,
)
return source_build_plan_for_release(release)
except Exception:
pass
latest_tag = latest_upstream_release_tag()
return SourceBuildPlan(
source_url = "https://github.com/ggml-org/llama.cpp",
source_ref = latest_tag,
source_ref_kind = "tag",
compatibility_upstream_tag = latest_tag,
)
def run_capture(
command: list[str],
*,
timeout: int = 30,
check: bool = False,
env: dict[str, str] | None = None,
) -> subprocess.CompletedProcess[str]:
result = subprocess.run(
command,
capture_output = True,
text = True,
timeout = timeout,
env = env,
)
if check and result.returncode != 0:
raise subprocess.CalledProcessError(
result.returncode, command, result.stdout, result.stderr
)
return result
def detect_host() -> HostInfo:
system = platform.system()
machine = platform.machine().lower()
is_windows = system == "Windows"
is_linux = system == "Linux"
is_macos = system == "Darwin"
is_x86_64 = machine in {"x86_64", "amd64"}
is_arm64 = machine in {"arm64", "aarch64"}
nvidia_smi = shutil.which("nvidia-smi")
driver_cuda_version = None
compute_caps: list[str] = []
visible_cuda_devices = os.environ.get("CUDA_VISIBLE_DEVICES")
visible_device_tokens = parse_cuda_visible_devices(visible_cuda_devices)
has_physical_nvidia = False
has_usable_nvidia = False
if nvidia_smi:
# Require `nvidia-smi -L` to actually list a GPU before treating the
# host as NVIDIA. The banner text "NVIDIA-SMI ..." is printed even
# when the command fails to communicate with the driver (e.g. stale
# container leftovers), which would otherwise misclassify an AMD
# ROCm host as NVIDIA and short-circuit the ROCm path.
try:
listing = run_capture([nvidia_smi, "-L"], timeout = 20)
gpu_lines = [
line for line in listing.stdout.splitlines() if line.startswith("GPU ")
]
if gpu_lines:
has_physical_nvidia = True
has_usable_nvidia = visible_device_tokens != []
except Exception:
pass
try:
result = run_capture([nvidia_smi], timeout = 20)
merged = "\n".join(part for part in (result.stdout, result.stderr) if part)
for line in merged.splitlines():
if "CUDA Version:" in line:
raw = line.split("CUDA Version:", 1)[1].strip().split()[0]
major, minor = raw.split(".", 1)
driver_cuda_version = (int(major), int(minor))
break
except Exception:
pass
try:
caps = run_capture(
[
nvidia_smi,
"--query-gpu=index,uuid,compute_cap",
"--format=csv,noheader",
],
timeout = 20,
)
visible_gpu_rows: list[tuple[str, str, str]] = []
for raw in caps.stdout.splitlines():
parts = [part.strip() for part in raw.split(",")]
if len(parts) != 3:
continue
index, uuid, cap = parts
visible_gpu_row = select_visible_gpu_rows(
[(index, uuid, cap)],
visible_device_tokens,
)
if not visible_gpu_row:
continue
visible_gpu_rows.extend(visible_gpu_row)
normalized_cap = normalize_compute_cap(cap)
if normalized_cap is None:
continue
if normalized_cap not in compute_caps:
compute_caps.append(normalized_cap)
if visible_gpu_rows:
has_usable_nvidia = True
# Older nvidia-smi versions (pre -L support) hit the
# except in the first try block but still succeed here,
# leaving has_physical_nvidia unset. Mirror the -L path
# so downstream diagnostics on line ~4390 still run.
if not has_physical_nvidia:
has_physical_nvidia = True
elif visible_device_tokens == []:
has_usable_nvidia = False
elif supports_explicit_visible_device_matching(visible_device_tokens):
has_usable_nvidia = False
elif has_physical_nvidia:
has_usable_nvidia = True
except Exception:
pass
# Detect AMD ROCm (HIP) -- require actual GPU, not just tools installed
def _amd_smi_has_gpu(stdout: str) -> bool:
"""Check for 'GPU: <number>' data rows, not just a table header."""
return bool(re.search(r"(?im)^gpu\s*[:\[]\s*\d", stdout))
has_rocm = False
if is_linux:
for _cmd, _check in (
# rocminfo: look for "gfxNNNN" with nonzero first digit (gfx000 is CPU agent)
(["rocminfo"], lambda out: bool(re.search(r"gfx[1-9]", out.lower()))),
(["amd-smi", "list"], _amd_smi_has_gpu),
):
_exe = shutil.which(_cmd[0])
if not _exe:
continue
try:
_result = run_capture([_exe, *_cmd[1:]], timeout = 10)
except Exception:
continue
if _result.returncode == 0 and _result.stdout.strip():
if _check(_result.stdout):
has_rocm = True
break
elif is_windows:
# Windows: prefer active probes that validate GPU presence
for _cmd, _check in (
(["hipinfo"], lambda out: "gcnarchname" in out.lower()),
(["amd-smi", "list"], _amd_smi_has_gpu),
):
_exe = shutil.which(_cmd[0])
if not _exe:
continue
try:
_result = run_capture([_exe, *_cmd[1:]], timeout = 10)
except Exception:
continue
if _result.returncode == 0 and _result.stdout.strip():
if _check(_result.stdout):
has_rocm = True
break
# Note: amdhip64.dll presence alone is NOT treated as GPU evidence
# since the HIP SDK can be installed without an AMD GPU.
return HostInfo(
system = system,
machine = machine,
is_windows = is_windows,
is_linux = is_linux,
is_macos = is_macos,
is_x86_64 = is_x86_64,
is_arm64 = is_arm64,
nvidia_smi = nvidia_smi,
driver_cuda_version = driver_cuda_version,
compute_caps = compute_caps,
visible_cuda_devices = visible_cuda_devices,
has_physical_nvidia = has_physical_nvidia,
has_usable_nvidia = has_usable_nvidia,
has_rocm = has_rocm,
)
def pick_windows_cuda_runtime(host: HostInfo) -> str | None:
if not host.driver_cuda_version:
return None
major, minor = host.driver_cuda_version
if major > 13 or (major == 13 and minor >= 1):
return "13.1"
if major > 12 or (major == 12 and minor >= 4):
return "12.4"
return None
def compatible_linux_runtime_lines(host: HostInfo) -> list[str]:
if not host.driver_cuda_version:
return []
major, _minor = host.driver_cuda_version
if major >= 13:
return ["cuda13", "cuda12"]
if major >= 12:
return ["cuda12"]
return []
def windows_runtime_line_info() -> dict[str, tuple[str, ...]]:
return {
"cuda13": ("cudart64_13*.dll", "cublas64_13*.dll", "cublasLt64_13*.dll"),
"cuda12": ("cudart64_12*.dll", "cublas64_12*.dll", "cublasLt64_12*.dll"),
}
def detected_windows_runtime_lines() -> tuple[list[str], dict[str, list[str]]]:
dirs = windows_runtime_dirs()
detected: list[str] = []
runtime_dirs: dict[str, list[str]] = {}
for runtime_line, required_patterns in windows_runtime_line_info().items():
matching_dirs = windows_runtime_dirs_for_patterns(required_patterns, dirs)
if matching_dirs:
detected.append(runtime_line)
runtime_dirs[runtime_line] = matching_dirs
return detected, runtime_dirs
def compatible_windows_runtime_lines(host: HostInfo) -> list[str]:
driver_runtime = pick_windows_cuda_runtime(host)
if driver_runtime == "13.1":
return ["cuda13", "cuda12"]
if driver_runtime == "12.4":
return ["cuda12"]
return []
def runtime_line_from_cuda_version(cuda_version: str | None) -> str | None:
if not cuda_version:
return None
raw = str(cuda_version).strip()
if not raw:
return None
major, _, _ = raw.partition(".")
if major == "12":
return "cuda12"
if major == "13":
return "cuda13"
return None
def detect_torch_cuda_runtime_preference(host: HostInfo) -> CudaRuntimePreference:
selection_log: list[str] = []
if host.is_macos:
selection_log.append("torch_cuda_preference: skipped on macOS")
return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
if not (host.has_usable_nvidia and (host.is_linux or host.is_windows)):
selection_log.append(
"torch_cuda_preference: skipped because CUDA host prerequisites were not met"
)
return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
try:
import torch
except Exception as exc:
selection_log.append(f"torch_cuda_preference: import failed: {exc}")
return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
cuda_version = getattr(getattr(torch, "version", None), "cuda", None)
if not isinstance(cuda_version, str) or not cuda_version.strip():
selection_log.append(
"torch_cuda_preference: torch.version.cuda missing; skipping Torch shortcut"
)
return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
try:
cuda_available = bool(torch.cuda.is_available())
except Exception as exc:
selection_log.append(
f"torch_cuda_preference: torch.cuda.is_available() failed: {exc}"
)
return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
if not cuda_available:
selection_log.append(
"torch_cuda_preference: torch.cuda.is_available() returned False; falling back to normal selection"
)
return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
runtime_line = runtime_line_from_cuda_version(cuda_version)
if runtime_line is None:
selection_log.append(
f"torch_cuda_preference: unsupported torch.version.cuda={cuda_version}; falling back to normal selection"
)
return CudaRuntimePreference(runtime_line = None, selection_log = selection_log)
selection_log.append(
"torch_cuda_preference: selected runtime_line="
f"{runtime_line} from torch.version.cuda={cuda_version}"
)
return CudaRuntimePreference(runtime_line = runtime_line, selection_log = selection_log)
def windows_cuda_attempts(
host: HostInfo,
llama_tag: str,
upstream_assets: dict[str, str],
preferred_runtime_line: str | None,
selection_preamble: Iterable[str] = (),
) -> list[AssetChoice]:
selection_log = list(selection_preamble)
runtime_by_line = {"cuda12": "12.4", "cuda13": "13.1"}
driver_runtime = pick_windows_cuda_runtime(host)
detected_runtime_lines, runtime_dirs = detected_windows_runtime_lines()
compatible_runtime_lines = compatible_windows_runtime_lines(host)
normal_runtime_lines: list[str]
if detected_runtime_lines:
normal_runtime_lines = [
line for line in compatible_runtime_lines if line in detected_runtime_lines
]
else:
normal_runtime_lines = compatible_runtime_lines
selection_log.append(
"windows_cuda_selection: driver_runtime="
+ (driver_runtime if driver_runtime else "unknown")
)
selection_log.append(
"windows_cuda_selection: detected_runtime_lines="
+ (",".join(detected_runtime_lines) if detected_runtime_lines else "none")
)
for runtime_line in ("cuda13", "cuda12"):
selection_log.append(
"windows_cuda_selection: runtime_dirs "
f"{runtime_line}="
+ (
",".join(runtime_dirs.get(runtime_line, []))
if runtime_dirs.get(runtime_line)
else "none"
)
)
if detected_runtime_lines:
selection_log.append(
"windows_cuda_selection: host_runtime_order="
+ (",".join(normal_runtime_lines) if normal_runtime_lines else "none")
)
else:
selection_log.append(
"windows_cuda_selection: no CUDA runtime DLL line detected; falling back to driver order"
)
if not normal_runtime_lines:
if detected_runtime_lines:
selection_log.append(
"windows_cuda_selection: detected CUDA runtime DLLs were incompatible with the reported driver"
)
fallback_runtime_lines = (
["cuda13", "cuda12"]
if driver_runtime == "13.1"
else (["cuda12"] if driver_runtime == "12.4" else [])
)
normal_runtime_lines = fallback_runtime_lines
runtime_order: list[str] = []
if preferred_runtime_line and preferred_runtime_line in normal_runtime_lines:
runtime_order.append(preferred_runtime_line)
selection_log.append(
"windows_cuda_selection: torch_preferred_runtime_line="
f"{preferred_runtime_line} reordered_attempts"
)
elif preferred_runtime_line:
selection_log.append(
"windows_cuda_selection: torch_preferred_runtime_line="
f"{preferred_runtime_line} unavailable_or_incompatible"
)
else:
selection_log.append(
"windows_cuda_selection: no Torch runtime preference available"
)
runtime_order.extend(
runtime_line
for runtime_line in normal_runtime_lines
if runtime_line not in runtime_order
)
selection_log.append(
"windows_cuda_selection: normal_runtime_order="
+ (",".join(normal_runtime_lines) if normal_runtime_lines else "none")
)
selection_log.append(
"windows_cuda_selection: attempt_runtime_order="
+ (",".join(runtime_order) if runtime_order else "none")
)
attempts: list[AssetChoice] = []
for runtime_line in runtime_order:
runtime = runtime_by_line[runtime_line]
selected_name = None
asset_url = None
for candidate_name in windows_cuda_upstream_asset_names(llama_tag, runtime):
asset_url = upstream_assets.get(candidate_name)
if asset_url:
selected_name = candidate_name
break
if not asset_url or not selected_name:
selection_log.append(
"windows_cuda_selection: skip missing assets "
+ ",".join(windows_cuda_upstream_asset_names(llama_tag, runtime))
)
continue
attempts.append(
AssetChoice(
repo = UPSTREAM_REPO,
tag = llama_tag,
name = selected_name,
url = asset_url,
source_label = "upstream",
install_kind = "windows-cuda",
runtime_line = runtime_line,
selection_log = list(selection_log)
+ [
f"windows_cuda_selection: selected {selected_name} runtime={runtime}"
],
)
)
return attempts
def published_windows_cuda_attempts(
host: HostInfo,
release: PublishedReleaseBundle,
preferred_runtime_line: str | None,
selection_preamble: Iterable[str] = (),
) -> list[AssetChoice]:
selection_log = list(release.selection_log) + list(selection_preamble)
runtime_by_line = {"cuda12": "12.4", "cuda13": "13.1"}
runtime_order = windows_cuda_attempts(
host,
release.upstream_tag,
{
f"llama-{release.upstream_tag}-bin-win-cuda-{runtime}-x64.zip": "published"
for runtime in runtime_by_line.values()
},
preferred_runtime_line,
selection_log,
)
published_artifacts = [
artifact
for artifact in release.artifacts
if artifact.install_kind == "windows-cuda"
]
artifacts_by_runtime: dict[str, list[PublishedLlamaArtifact]] = {}
for artifact in published_artifacts:
if not artifact.runtime_line:
continue
artifacts_by_runtime.setdefault(artifact.runtime_line, []).append(artifact)
attempts: list[AssetChoice] = []
for ordered_attempt in runtime_order:
runtime_line = ordered_attempt.runtime_line
if not runtime_line:
continue
candidates = sorted(
artifacts_by_runtime.get(runtime_line, []),
key = lambda artifact: (artifact.rank, artifact.asset_name),
)
for artifact in candidates:
asset_url = release.assets.get(artifact.asset_name)
if not asset_url:
continue
attempts.append(
AssetChoice(
repo = release.repo,
tag = release.release_tag,
name = artifact.asset_name,
url = asset_url,
source_label = "published",
install_kind = "windows-cuda",
runtime_line = runtime_line,
selection_log = list(ordered_attempt.selection_log or [])
+ [
"windows_cuda_selection: selected published asset "
f"{artifact.asset_name} for runtime_line={runtime_line}"
],
)
)
break
return attempts
def resolve_windows_cuda_choices(
host: HostInfo, llama_tag: str, upstream_assets: dict[str, str]
) -> list[AssetChoice]:
torch_preference = detect_torch_cuda_runtime_preference(host)
attempts = windows_cuda_attempts(
host,
llama_tag,
upstream_assets,
torch_preference.runtime_line,
torch_preference.selection_log,
)
return attempts
def resolve_linux_cuda_choice(
host: HostInfo, release: PublishedReleaseBundle
) -> LinuxCudaSelection:
torch_preference = detect_torch_cuda_runtime_preference(host)
selection = linux_cuda_choice_from_release(
host,
release,
preferred_runtime_line = torch_preference.runtime_line,
selection_preamble = torch_preference.selection_log,
)
if selection is not None:
return selection
raise PrebuiltFallback("no compatible published Linux CUDA bundle was found")
def published_asset_choice_for_kind(
release: PublishedReleaseBundle,
install_kind: str,
) -> AssetChoice | None:
candidates = sorted(
(
artifact
for artifact in release.artifacts
if artifact.install_kind == install_kind
),
key = lambda artifact: (artifact.rank, artifact.asset_name),
)
for artifact in candidates:
asset_url = release.assets.get(artifact.asset_name)
if not asset_url:
continue
return AssetChoice(
repo = release.repo,
tag = release.release_tag,
name = artifact.asset_name,
url = asset_url,
source_label = "published",
install_kind = install_kind,
runtime_line = artifact.runtime_line,
selection_log = list(release.selection_log)
+ [
f"published_selection: selected {artifact.asset_name} install_kind={install_kind}"
],
)
return None
def _detect_host_rocm_version() -> tuple[int, int] | None:
"""Return (major, minor) of the installed ROCm runtime, or None.
Best-effort read from /opt/rocm/.info/version, amd-smi version, and
hipconfig --version. Used to pick a compatible upstream llama.cpp
ROCm prebuilt rather than always taking the numerically newest one
(which can be newer than the host runtime).
"""
rocm_root = os.environ.get("ROCM_PATH") or "/opt/rocm"
for path in (
os.path.join(rocm_root, ".info", "version"),
os.path.join(rocm_root, "lib", "rocm_version"),
):
try:
with open(path) as fh:
parts = fh.read().strip().split("-")[0].split(".")
# Explicit length guard avoids relying on the broad except
# below to swallow IndexError when the version file contains
# a single component (e.g. "6\n" on a partial install).
if len(parts) >= 2:
return int(parts[0]), int(parts[1])
except Exception:
pass
amd_smi = shutil.which("amd-smi")
if amd_smi:
try:
result = subprocess.run(
[amd_smi, "version"],
stdout = subprocess.PIPE,
stderr = subprocess.DEVNULL,
text = True,
timeout = 5,
)
if result.returncode == 0:
m = re.search(r"ROCm version:\s*(\d+)\.(\d+)", result.stdout)
if m:
return int(m.group(1)), int(m.group(2))
except Exception:
pass
hipconfig = shutil.which("hipconfig")
if hipconfig:
try:
result = subprocess.run(
[hipconfig, "--version"],
stdout = subprocess.PIPE,
stderr = subprocess.DEVNULL,
text = True,
timeout = 5,
)
if result.returncode == 0:
raw = (result.stdout or "").strip().split("\n")[0]
parts = raw.split(".")
if (
len(parts) >= 2
and parts[0].isdigit()
and parts[1].split("-")[0].isdigit()
):
return int(parts[0]), int(parts[1].split("-")[0])
except Exception:
pass
# Distro package-manager fallbacks. Mirrors install.sh::get_torch_index_url
# and _detect_rocm_version() in install_python_stack.py so package-managed
# ROCm hosts without /opt/rocm/.info/version still report a usable version
# and the <= host version filter in resolve_upstream_asset_choice picks
# the correct upstream prebuilt instead of the newest-regardless fallback.
for _cmd in (
["dpkg-query", "-W", "-f=${Version}\n", "rocm-core"],
["rpm", "-q", "--qf", "%{VERSION}\n", "rocm-core"],
):
_exe = shutil.which(_cmd[0])
if not _exe:
continue
try:
_result = subprocess.run(
[_exe, *_cmd[1:]],
stdout = subprocess.PIPE,
stderr = subprocess.DEVNULL,
text = True,
timeout = 5,
)
except Exception:
continue
if _result.returncode != 0 or not _result.stdout.strip():
continue
_raw = _result.stdout.strip()
# dpkg can prepend an epoch ("1:6.3.0-1"); strip it before parsing.
_raw = re.sub(r"^\d+:", "", _raw)
_m = re.match(r"(\d+)[.-](\d+)", _raw)
if _m:
return int(_m.group(1)), int(_m.group(2))
return None
def resolve_upstream_asset_choice(host: HostInfo, llama_tag: str) -> AssetChoice:
upstream_assets = github_release_assets(UPSTREAM_REPO, llama_tag)
if host.is_linux and host.is_x86_64:
# AMD ROCm: try upstream ROCm prebuilt first, then fall back to source build.
# Source build (via setup.sh) compiles with -DGGML_HIP=ON and auto-detects
# the exact GPU target via rocminfo, which is more reliable for consumer
# GPUs (e.g. gfx1151) that may not be in the prebuilt.
if host.has_rocm and not host.has_usable_nvidia:
# Scan upstream assets for any rocm-<version> prebuilt. When the
# host ROCm runtime version is known, pick the newest candidate
# whose major.minor is <= host version -- otherwise a ROCm 6.4
# host would download the rocm-7.2 tarball, fail preflight, and
# fall back to a source build even though a compatible 6.4
# prebuilt exists. If no compatible candidate matches (e.g. host
# runtime is older than every published prebuilt), fall back to
# the numerically newest so we at least try something.
_rocm_pattern = re.compile(
rf"llama-{re.escape(llama_tag)}-bin-ubuntu-rocm-([0-9]+(?:\.[0-9]+)*)-x64\.tar\.gz"
)
rocm_candidates: list[tuple[tuple[int, ...], str]] = []
for _name in upstream_assets:
_m = _rocm_pattern.match(_name)
if _m is None:
continue
_parts = tuple(int(p) for p in _m.group(1).split("."))
rocm_candidates.append((_parts, _name))
rocm_candidates.sort(reverse = True)
_host_rocm_version = _detect_host_rocm_version()
_compatible: list[tuple[tuple[int, ...], str]] = rocm_candidates
if _host_rocm_version is not None:
_compatible = [
item
for item in rocm_candidates
if item[0][:2] <= _host_rocm_version
]
if rocm_candidates and not _compatible:
# Fall back to the newest candidate so a source build is
# not forced when the host runtime is older than every
# published prebuilt: preflight will still catch a true
# incompatibility and trigger a fallback.
_compatible = rocm_candidates[:1]
if _compatible:
rocm_name = _compatible[0][1]
if _host_rocm_version is not None:
log(
f"AMD ROCm {_host_rocm_version[0]}.{_host_rocm_version[1]} "
f"detected -- trying upstream prebuilt {rocm_name}"
)
else:
log(f"AMD ROCm detected -- trying upstream prebuilt {rocm_name}")
log(
"Note: if your ROCm runtime version differs significantly, "
"this may fail preflight and fall back to a source build (safe)"
)
return AssetChoice(
repo = UPSTREAM_REPO,
tag = llama_tag,
name = rocm_name,
url = upstream_assets[rocm_name],
source_label = "upstream",
install_kind = "linux-rocm",
)
# No ROCm prebuilt available -- fall back to source build
raise PrebuiltFallback(
"AMD ROCm detected but no upstream ROCm prebuilt found; "
"falling back to source build with HIP support"
)
upstream_name = f"llama-{llama_tag}-bin-ubuntu-x64.tar.gz"
if upstream_name not in upstream_assets:
raise PrebuiltFallback("upstream Linux CPU asset was not found")
return AssetChoice(
repo = UPSTREAM_REPO,
tag = llama_tag,
name = upstream_name,
url = upstream_assets[upstream_name],
source_label = "upstream",
install_kind = "linux-cpu",
)
if host.is_windows and host.is_x86_64:
if host.has_usable_nvidia:
attempts = resolve_windows_cuda_choices(host, llama_tag, upstream_assets)
if attempts:
return attempts[0]
raise PrebuiltFallback("no compatible Windows CUDA asset was found")
# AMD ROCm on Windows: try HIP prebuilt
if host.has_rocm:
hip_name = f"llama-{llama_tag}-bin-win-hip-radeon-x64.zip"
if hip_name in upstream_assets:
log(
f"AMD ROCm detected on Windows -- trying upstream HIP prebuilt {hip_name}"
)
return AssetChoice(
repo = UPSTREAM_REPO,
tag = llama_tag,
name = hip_name,
url = upstream_assets[hip_name],
source_label = "upstream",
install_kind = "windows-hip",
)
log(
"AMD ROCm detected on Windows but no HIP prebuilt found -- falling back to CPU"
)
upstream_name = f"llama-{llama_tag}-bin-win-cpu-x64.zip"
if upstream_name not in upstream_assets:
raise PrebuiltFallback("upstream Windows CPU asset was not found")
return AssetChoice(
repo = UPSTREAM_REPO,
tag = llama_tag,
name = upstream_name,
url = upstream_assets[upstream_name],
source_label = "upstream",
install_kind = "windows-cpu",
)
if host.is_macos and host.is_arm64:
upstream_name = f"llama-{llama_tag}-bin-macos-arm64.tar.gz"
if upstream_name not in upstream_assets:
raise PrebuiltFallback("upstream macOS arm64 asset was not found")
return AssetChoice(
repo = UPSTREAM_REPO,
tag = llama_tag,
name = upstream_name,
url = upstream_assets[upstream_name],
source_label = "upstream",
install_kind = "macos-arm64",
)
if host.is_macos and host.is_x86_64:
upstream_name = f"llama-{llama_tag}-bin-macos-x64.tar.gz"
if upstream_name not in upstream_assets:
raise PrebuiltFallback("upstream macOS x64 asset was not found")
return AssetChoice(
repo = UPSTREAM_REPO,
tag = llama_tag,
name = upstream_name,
url = upstream_assets[upstream_name],
source_label = "upstream",
install_kind = "macos-x64",
)
raise PrebuiltFallback(
f"no prebuilt policy exists for {host.system} {host.machine}"
)
def resolve_asset_choice(host: HostInfo, llama_tag: str) -> AssetChoice:
if host.is_linux and host.is_x86_64 and host.has_usable_nvidia:
raise PrebuiltFallback(
"Linux CUDA installs require a compatible published bundle; upstream fallback is not available"
)
return resolve_upstream_asset_choice(host, llama_tag)
def resolve_release_asset_choice(
host: HostInfo,
llama_tag: str,
release: PublishedReleaseBundle,
checksums: ApprovedReleaseChecksums,
) -> list[AssetChoice]:
if host.is_windows and host.is_x86_64 and host.has_usable_nvidia:
torch_preference = detect_torch_cuda_runtime_preference(host)
published_attempts = published_windows_cuda_attempts(
host,
release,
torch_preference.runtime_line,
torch_preference.selection_log,
)
if published_attempts:
try:
return apply_approved_hashes(published_attempts, checksums)
except PrebuiltFallback as exc:
log(
"published Windows CUDA assets ignored for install planning: "
f"{release.repo}@{release.release_tag} ({exc})"
)
upstream_assets = github_release_assets(UPSTREAM_REPO, llama_tag)
return apply_approved_hashes(
resolve_windows_cuda_choices(host, llama_tag, upstream_assets),
checksums,
)
published_choice: AssetChoice | None = None
if host.is_windows and host.is_x86_64:
# AMD Windows hosts should prefer a hash-approved published
# Windows HIP bundle when one exists, but otherwise fall through
# to resolve_asset_choice() so the upstream HIP prebuilt is
# tried before the CPU fallback. Hard-pinning the published
# windows-cpu bundle here would make the new HIP path
# unreachable.
if host.has_rocm:
published_choice = published_asset_choice_for_kind(release, "windows-hip")
else:
published_choice = published_asset_choice_for_kind(release, "windows-cpu")
elif host.is_macos and host.is_arm64:
published_choice = published_asset_choice_for_kind(release, "macos-arm64")
elif host.is_macos and host.is_x86_64:
published_choice = published_asset_choice_for_kind(release, "macos-x64")
if published_choice is not None:
try:
return apply_approved_hashes([published_choice], checksums)
except PrebuiltFallback as exc:
log(
"published platform asset ignored for install planning: "
f"{release.repo}@{release.release_tag} {published_choice.name} ({exc})"
)
return apply_approved_hashes([resolve_asset_choice(host, llama_tag)], checksums)
def extract_archive(archive_path: Path, destination: Path) -> None:
def safe_extract_path(base: Path, member_name: str) -> Path:
normalized = member_name.replace("\\", "/")
member_path = Path(normalized)
if member_path.is_absolute():
raise PrebuiltFallback(
f"archive member used an absolute path: {member_name}"
)
target = (base / member_path).resolve()
base_resolved = base.resolve()
try:
target.relative_to(base_resolved)
except ValueError as exc:
raise PrebuiltFallback(
f"archive member escaped destination: {member_name}"
) from exc
return target
def safe_link_target(
base: Path, member_name: str, link_name: str, target: Path
) -> tuple[str, Path]:
normalized = link_name.replace("\\", "/")
link_path = Path(normalized)
if link_path.is_absolute():
raise PrebuiltFallback(
f"archive link used an absolute target: {member_name} -> {link_name}"
)
if not normalized:
raise PrebuiltFallback(f"archive link used an empty target: {member_name}")
resolved = (target.parent / link_path).resolve()
base_resolved = base.resolve()
try:
resolved.relative_to(base_resolved)
except ValueError as exc:
raise PrebuiltFallback(
f"archive link escaped destination: {member_name} -> {link_name}"
) from exc
return normalized, resolved
def extract_zip_safely(source: Path, base: Path) -> None:
with zipfile.ZipFile(source) as archive:
for member in archive.infolist():
target = safe_extract_path(base, member.filename)
mode = (member.external_attr >> 16) & 0o170000
if mode == 0o120000:
raise PrebuiltFallback(
f"zip archive contained a symlink entry: {member.filename}"
)
if member.is_dir():
target.mkdir(parents = True, exist_ok = True)
continue
target.parent.mkdir(parents = True, exist_ok = True)
with archive.open(member, "r") as src, target.open("wb") as dst:
shutil.copyfileobj(src, dst)
def extract_tar_safely(source: Path, base: Path) -> None:
pending_links: list[tuple[tarfile.TarInfo, Path]] = []
with tarfile.open(source, "r:gz") as archive:
for member in archive.getmembers():
target = safe_extract_path(base, member.name)
if member.isdir():
target.mkdir(parents = True, exist_ok = True)
continue
if member.islnk() or member.issym():
pending_links.append((member, target))
continue
if not member.isfile():
raise PrebuiltFallback(
f"tar archive contained an unsupported entry: {member.name}"
)
target.parent.mkdir(parents = True, exist_ok = True)
extracted = archive.extractfile(member)
if extracted is None:
raise PrebuiltFallback(
f"tar archive entry could not be read: {member.name}"
)
with extracted, target.open("wb") as dst:
shutil.copyfileobj(extracted, dst)
unresolved = list(pending_links)
while unresolved:
next_round: list[tuple[tarfile.TarInfo, Path]] = []
progressed = False
for member, target in unresolved:
normalized_link, resolved_target = safe_link_target(
base, member.name, member.linkname, target
)
if not resolved_target.exists() and not resolved_target.is_symlink():
next_round.append((member, target))
continue
if resolved_target.is_dir():
raise PrebuiltFallback(
f"archive link targeted a directory: {member.name} -> {member.linkname}"
)
target.parent.mkdir(parents = True, exist_ok = True)
if target.exists() or target.is_symlink():
target.unlink()
if member.issym():
target.symlink_to(normalized_link)
else:
shutil.copy2(resolved_target, target)
progressed = True
if not progressed:
details = ", ".join(
f"{member.name} -> {member.linkname}" for member, _ in next_round
)
raise PrebuiltFallback(
f"tar archive contained unresolved link entries: {details}"
)
unresolved = next_round
destination.mkdir(parents = True, exist_ok = True)
if archive_path.name.endswith(".zip"):
extract_zip_safely(archive_path, destination)
return
if archive_path.name.endswith(".tar.gz"):
extract_tar_safely(archive_path, destination)
return
raise PrebuiltFallback(f"unsupported archive format: {archive_path.name}")
def copy_globs(
source_dir: Path, destination: Path, patterns: list[str], *, required: bool = True
) -> None:
destination.mkdir(parents = True, exist_ok = True)
matched_sources: dict[str, Path] = {}
for path in sorted(
(candidate for candidate in source_dir.rglob("*") if candidate.is_file()),
key = lambda candidate: (
len(candidate.relative_to(source_dir).parts),
str(candidate),
),
):
for pattern in patterns:
if fnmatch.fnmatch(path.name, pattern):
previous = matched_sources.get(path.name)
if previous is not None and previous != path:
raise PrebuiltFallback(
f"ambiguous archive layout for {path.name}: "
f"{previous.relative_to(source_dir)} and {path.relative_to(source_dir)}"
)
matched_sources[path.name] = path
break
if required and not matched_sources:
raise PrebuiltFallback(f"required files missing from {source_dir}: {patterns}")
for name, path in matched_sources.items():
shutil.copy2(path, destination / name)
def ensure_converter_scripts(install_dir: Path, llama_tag: str) -> None:
canonical = install_dir / "convert_hf_to_gguf.py"
if not canonical.exists():
# Hydrated source tree should have placed this file already.
# Fall back to a network fetch so the install is not blocked.
raw_base = f"https://raw.githubusercontent.com/ggml-org/llama.cpp/{llama_tag}"
source_url = f"{raw_base}/convert_hf_to_gguf.py"
data = download_bytes(
source_url,
progress_label = f"Downloading {download_label_from_url(source_url)}",
)
if not data:
raise RuntimeError(f"downloaded empty converter script from {source_url}")
if b"import " not in data and b"def " not in data and b"#!/" not in data:
raise RuntimeError(
f"downloaded converter script did not look like Python source: {source_url}"
)
atomic_write_bytes(canonical, data)
legacy = install_dir / "convert-hf-to-gguf.py"
if legacy.exists() or legacy.is_symlink():
legacy.unlink()
try:
legacy.symlink_to("convert_hf_to_gguf.py")
except OSError:
shutil.copy2(canonical, legacy)
def extracted_archive_root(extract_dir: Path) -> Path:
children = [path for path in extract_dir.iterdir()]
if len(children) == 1 and children[0].is_dir():
return children[0]
return extract_dir
def copy_directory_contents(source_dir: Path, destination: Path) -> None:
destination.mkdir(parents = True, exist_ok = True)
for item in source_dir.iterdir():
target = destination / item.name
if item.is_dir():
shutil.copytree(item, target, dirs_exist_ok = True)
else:
shutil.copy2(item, target)
def hydrate_source_tree(
source_ref: str,
install_dir: Path,
work_dir: Path,
*,
source_repo: str = UPSTREAM_REPO,
expected_sha256: str | None,
source_label: str | None = None,
exact_source: bool = False,
) -> None:
archive_path = work_dir / f"llama.cpp-source-{source_ref}.tar.gz"
source_urls = (
commit_source_archive_urls(source_repo, source_ref)
if exact_source
else upstream_source_archive_urls(source_ref)
)
label = source_label or f"llama.cpp source tree for {source_ref}"
extract_dir = Path(tempfile.mkdtemp(prefix = "source-extract-", dir = work_dir))
try:
log(f"downloading {label}")
last_exc: Exception | None = None
downloaded = False
for index, source_url in enumerate(source_urls):
try:
if index > 0:
log(
f"retrying source tree download from fallback URL: {source_url}"
)
download_file_verified(
source_url,
archive_path,
expected_sha256 = expected_sha256,
label = label,
)
downloaded = True
break
except Exception as exc:
last_exc = exc
if index == len(source_urls) - 1:
raise
log(f"source tree download failed from {source_url}: {exc}")
if not downloaded:
assert last_exc is not None
raise last_exc
extract_archive(archive_path, extract_dir)
source_root = extracted_archive_root(extract_dir)
required_paths = [
source_root / "CMakeLists.txt",
source_root / "convert_hf_to_gguf.py",
source_root / "gguf-py",
]
missing = [
str(path.relative_to(source_root))
for path in required_paths
if not path.exists()
]
if missing:
raise PrebuiltFallback(
"upstream source archive was missing required repo files: "
+ ", ".join(missing)
)
copy_directory_contents(source_root, install_dir)
except PrebuiltFallback:
raise
except Exception as exc:
raise PrebuiltFallback(f"failed to hydrate {label}: {exc}") from exc
finally:
remove_tree(extract_dir)
def normalize_install_layout(install_dir: Path, host: HostInfo) -> tuple[Path, Path]:
build_bin = install_dir / "build" / "bin"
if host.is_windows:
exec_dir = build_bin / "Release"
exec_dir.mkdir(parents = True, exist_ok = True)
return exec_dir / "llama-server.exe", exec_dir / "llama-quantize.exe"
install_dir.mkdir(parents = True, exist_ok = True)
build_bin.mkdir(parents = True, exist_ok = True)
return install_dir / "llama-server", install_dir / "llama-quantize"
def discover_installed_executable(install_dir: Path, executable_name: str) -> Path:
direct = install_dir / executable_name
if direct.exists() and direct.is_file():
return direct
candidate = next(
(path for path in install_dir.rglob(executable_name) if path.is_file()), None
)
if candidate is None:
raise PrebuiltFallback(f"{executable_name} was not installed")
return candidate
def write_exec_wrapper(entrypoint: Path, target: Path) -> None:
relative_target = os.path.relpath(target, entrypoint.parent)
script = "\n".join(
[
"#!/bin/sh",
f'exec "$(dirname "$0")/{relative_target}" "$@"',
"",
]
)
atomic_write_bytes(entrypoint, script.encode("utf-8"))
os.chmod(entrypoint, 0o755)
def create_exec_entrypoint(entrypoint: Path, target: Path) -> None:
if entrypoint == target:
return
if entrypoint.exists() or entrypoint.is_symlink():
entrypoint.unlink()
try:
entrypoint.symlink_to(os.path.relpath(target, entrypoint.parent))
except Exception:
write_exec_wrapper(entrypoint, target)
def overlay_directory_for_choice(
install_dir: Path, choice: AssetChoice, host: HostInfo
) -> Path:
if host.is_windows or choice.install_kind.startswith("windows"):
path = install_dir / "build" / "bin" / "Release"
else:
path = install_dir / "build" / "bin"
path.mkdir(parents = True, exist_ok = True)
return path
def runtime_patterns_for_choice(choice: AssetChoice) -> list[str]:
if choice.install_kind in {"linux-cpu", "linux-cuda", "linux-rocm"}:
return [
"llama-server",
"llama-quantize",
"libllama.so*",
"libggml.so*",
"libggml-base.so*",
"libmtmd.so*",
"libggml-cpu-*.so*",
"libggml-cuda.so*",
"libggml-hip.so*",
"libggml-rpc.so*",
]
if choice.install_kind in {"macos-arm64", "macos-x64"}:
return ["llama-server", "llama-quantize", "lib*.dylib"]
if choice.install_kind in {"windows-cpu", "windows-cuda", "windows-hip"}:
return ["*.exe", "*.dll"]
raise PrebuiltFallback(
f"unsupported install kind for runtime overlay: {choice.install_kind}"
)
def metadata_patterns_for_choice(choice: AssetChoice) -> list[str]:
patterns = ["BUILD_INFO.txt", "THIRD_PARTY_LICENSES.txt"]
if choice.install_kind.startswith("windows"):
patterns.append("LICENSE.txt")
else:
patterns.append("LICENSE")
return patterns
@contextmanager
def install_lock(lock_path: Path) -> Iterator[None]:
lock_path.parent.mkdir(parents = True, exist_ok = True)
if FileLock is None:
# Fallback: exclusive file creation as a simple lock.
# Write our PID so stale locks from crashed processes can be detected.
fd: int | None = None
deadline = time.monotonic() + INSTALL_LOCK_TIMEOUT_SECONDS
while True:
try:
fd = os.open(str(lock_path), os.O_CREAT | os.O_EXCL | os.O_RDWR)
try:
os.write(fd, f"{os.getpid()}\n".encode())
os.fsync(fd)
except Exception:
os.close(fd)
fd = None
lock_path.unlink(missing_ok = True)
raise
break
except FileExistsError:
# Check if the holder process is still alive
stale = False
try:
raw = lock_path.read_text().strip()
except FileNotFoundError:
# Lock vanished between our open attempt and read -- retry
continue
if not raw:
# File exists but PID not yet written -- another process
# just created it. Wait briefly for the write to land.
if time.monotonic() >= deadline:
raise BusyInstallConflict(
f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
)
time.sleep(0.1)
continue
try:
holder_pid = int(raw)
os.kill(holder_pid, 0) # signal 0 = existence check
except ValueError:
# PID unreadable (corrupted file)
stale = True
except ProcessLookupError:
# Process is dead
stale = True
except PermissionError:
# Process is alive but owned by another user -- not stale
pass
if stale:
lock_path.unlink(missing_ok = True)
continue
if time.monotonic() >= deadline:
raise BusyInstallConflict(
f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
)
time.sleep(0.5)
try:
yield
finally:
if fd is not None:
os.close(fd)
lock_path.unlink(missing_ok = True)
return
try:
with FileLock(lock_path, timeout = INSTALL_LOCK_TIMEOUT_SECONDS):
yield
except FileLockTimeout as exc:
raise BusyInstallConflict(
f"timed out after {INSTALL_LOCK_TIMEOUT_SECONDS}s waiting for concurrent install lock: {lock_path}"
) from exc
def install_lock_path(install_dir: Path) -> Path:
return install_dir.parent / f".{install_dir.name}.install.lock"
def install_staging_root(install_dir: Path) -> Path:
root = install_dir.parent / INSTALL_STAGING_ROOT_NAME
root.mkdir(parents = True, exist_ok = True)
return root
def prune_install_staging_root(install_dir: Path) -> None:
root = install_dir.parent / INSTALL_STAGING_ROOT_NAME
try:
root.rmdir()
except OSError:
pass
def create_install_staging_dir(install_dir: Path) -> Path:
staging_dir = Path(
tempfile.mkdtemp(
prefix = f"{install_dir.name}.staging-", dir = install_staging_root(install_dir)
)
)
log(f"created install staging dir {staging_dir}")
return staging_dir
def unique_install_side_path(install_dir: Path, label: str) -> Path:
root = install_staging_root(install_dir)
timestamp = time.strftime("%Y%m%d%H%M%S", time.gmtime())
prefix = f"{install_dir.name}.{label}-{timestamp}-{os.getpid()}"
candidate = root / prefix
counter = 0
while candidate.exists():
counter += 1
candidate = root / f"{prefix}-{counter}"
return candidate
def remove_tree(path: Path | None) -> None:
if path and path.exists():
shutil.rmtree(path, ignore_errors = True)
def remove_tree_logged(path: Path | None, label: str) -> None:
if not path:
return
if not path.exists():
log(f"{label} already absent at {path}")
return
log(f"removing {label} at {path}")
try:
shutil.rmtree(path)
except Exception as exc:
log(f"failed to remove {label} at {path}: {exc}")
raise
def cleanup_install_side_paths(
install_dir: Path,
*,
staging_dir: Path | None = None,
rollback_dir: Path | None = None,
failed_dir: Path | None = None,
active_dir: Path | None = None,
) -> None:
cleanup_failures: list[str] = []
for label, path in (
("failed install path", failed_dir),
("rollback path", rollback_dir),
("active install path", active_dir),
("staging dir", staging_dir),
):
if not path:
continue
try:
remove_tree_logged(path, label)
except Exception as exc:
cleanup_failures.append(f"{label} ({path}): {exc}")
prune_install_staging_root(install_dir)
if cleanup_failures:
raise RuntimeError("cleanup failed for " + "; ".join(cleanup_failures))
def confirm_install_tree(install_dir: Path, host: HostInfo) -> None:
if host.is_windows:
expected = [
install_dir / "build" / "bin" / "Release" / "llama-server.exe",
install_dir / "build" / "bin" / "Release" / "llama-quantize.exe",
install_dir / "convert_hf_to_gguf.py",
install_dir / "gguf-py",
]
else:
expected = [
install_dir / "llama-server",
install_dir / "llama-quantize",
install_dir / "build" / "bin" / "llama-server",
install_dir / "build" / "bin" / "llama-quantize",
install_dir / "convert_hf_to_gguf.py",
install_dir / "gguf-py",
]
expected.append(install_dir / "UNSLOTH_PREBUILT_INFO.json")
missing = [str(path) for path in expected if not path.exists()]
if missing:
raise RuntimeError(
"activated install was missing expected files: " + ", ".join(missing)
)
def activate_install_tree(staging_dir: Path, install_dir: Path, host: HostInfo) -> None:
rollback_dir: Path | None = None
failed_dir: Path | None = None
try:
if install_dir.exists():
rollback_dir = unique_install_side_path(install_dir, "rollback")
log(f"moving existing install to rollback path {rollback_dir}")
os.replace(install_dir, rollback_dir)
log(f"moved existing install to rollback path {rollback_dir.name}")
log(f"activating staged install {staging_dir} -> {install_dir}")
os.replace(staging_dir, install_dir)
log(f"activated staged install at {install_dir}")
log(f"confirming activated install tree at {install_dir}")
confirm_install_tree(install_dir, host)
log(f"activated install tree confirmed at {install_dir}")
except Exception as exc:
log(f"activation failed for staged install: {exc}")
try:
if install_dir.exists():
failed_dir = unique_install_side_path(install_dir, "failed")
log(f"moving failed active install to {failed_dir}")
os.replace(install_dir, failed_dir)
elif staging_dir.exists():
failed_dir = staging_dir
staging_dir = None
log(f"retaining failed staging tree at {failed_dir}")
if rollback_dir and rollback_dir.exists():
log(f"restoring rollback path {rollback_dir} -> {install_dir}")
os.replace(rollback_dir, install_dir)
log(f"restored previous install from rollback path {rollback_dir.name}")
if is_busy_lock_error(exc):
raise BusyInstallConflict(
"staged prebuilt validation passed but the existing install could not be replaced "
"because llama.cpp appears to still be in use; restored previous install "
f"({textwrap.shorten(str(exc), width = 200, placeholder = '...')})"
) from exc
raise PrebuiltFallback(
"staged prebuilt validation passed but activation failed; restored previous install "
f"({textwrap.shorten(str(exc), width = 200, placeholder = '...')})"
) from exc
except (BusyInstallConflict, PrebuiltFallback):
raise
except Exception as rollback_exc:
log(f"rollback after failed activation also failed: {rollback_exc}")
log(
"rollback restoration failed; cleaning staging, install, and rollback paths before source build fallback"
)
cleanup_error: Exception | None = None
try:
cleanup_install_side_paths(
install_dir,
staging_dir = staging_dir,
rollback_dir = rollback_dir,
failed_dir = failed_dir,
active_dir = install_dir,
)
except Exception as cleanup_exc:
cleanup_error = cleanup_exc
log(f"cleanup after rollback failure also failed: {cleanup_exc}")
details = textwrap.shorten(str(exc), width = 200, placeholder = "...")
if cleanup_error is not None:
raise PrebuiltFallback(
"staged prebuilt validation passed but activation and rollback failed; "
f"cleanup also reported errors ({details}; cleanup={cleanup_error})"
) from exc
raise PrebuiltFallback(
"staged prebuilt validation passed but activation and rollback failed; "
f"cleaned install state for fresh source build ({details})"
) from exc
else:
if rollback_dir:
try:
remove_tree_logged(rollback_dir, "rollback path")
except Exception as cleanup_exc:
log(
f"non-fatal: rollback cleanup failed after successful activation: {cleanup_exc}"
)
finally:
remove_tree(failed_dir)
remove_tree(staging_dir)
prune_install_staging_root(install_dir)
def install_from_archives(
choice: AssetChoice, host: HostInfo, install_dir: Path, work_dir: Path
) -> tuple[Path, Path]:
main_archive = work_dir / choice.name
log(f"downloading {choice.name} from {choice.source_label} release")
download_file_verified(
choice.url,
main_archive,
expected_sha256 = choice.expected_sha256,
label = f"prebuilt archive {choice.name}",
)
install_dir.mkdir(parents = True, exist_ok = True)
extract_dir = Path(tempfile.mkdtemp(prefix = "extract-", dir = work_dir))
try:
extract_archive(main_archive, extract_dir)
source_dir = extract_dir
overlay_dir = overlay_directory_for_choice(install_dir, choice, host)
copy_globs(
source_dir, overlay_dir, runtime_patterns_for_choice(choice), required = True
)
copy_globs(
source_dir,
install_dir,
metadata_patterns_for_choice(choice),
required = False,
)
finally:
remove_tree(extract_dir)
if host.is_windows:
exec_dir = install_dir / "build" / "bin" / "Release"
server_src = next(exec_dir.glob("llama-server.exe"), None)
quantize_src = next(exec_dir.glob("llama-quantize.exe"), None)
if server_src is None or quantize_src is None:
raise PrebuiltFallback("windows executables were not installed correctly")
return server_src, quantize_src
build_bin = install_dir / "build" / "bin"
source_server = build_bin / "llama-server"
source_quantize = build_bin / "llama-quantize"
if not source_server.exists() or not source_quantize.exists():
raise PrebuiltFallback(
"unix executables were not installed correctly into build/bin"
)
os.chmod(source_server, 0o755)
os.chmod(source_quantize, 0o755)
root_server = install_dir / "llama-server"
root_quantize = install_dir / "llama-quantize"
if source_server != root_server:
create_exec_entrypoint(root_server, source_server)
if source_quantize != root_quantize:
create_exec_entrypoint(root_quantize, source_quantize)
build_server = build_bin / "llama-server"
build_quantize = build_bin / "llama-quantize"
if source_server != build_server:
create_exec_entrypoint(build_server, source_server)
if source_quantize != build_quantize:
create_exec_entrypoint(build_quantize, source_quantize)
return source_server, source_quantize
def ensure_repo_shape(install_dir: Path) -> None:
required = [
install_dir / "CMakeLists.txt",
install_dir / "convert_hf_to_gguf.py",
install_dir / "gguf-py",
]
missing = [
str(path.relative_to(install_dir)) for path in required if not path.exists()
]
if missing:
raise PrebuiltFallback(
"hydrated llama.cpp source tree was missing: " + ", ".join(missing)
)
def validation_model_cache_path(install_dir: Path) -> Path:
cache_dir = install_dir.parent / VALIDATION_MODEL_CACHE_DIRNAME
cache_dir.mkdir(parents = True, exist_ok = True)
return cache_dir / VALIDATION_MODEL_CACHE_FILENAME
def validated_validation_model_bytes(data: bytes) -> bytes:
if not data:
raise RuntimeError(f"downloaded empty validation model from {TEST_MODEL_URL}")
digest = hashlib.sha256(data).hexdigest()
if digest != TEST_MODEL_SHA256:
raise RuntimeError(
"validation model checksum mismatch: "
f"expected={TEST_MODEL_SHA256} actual={digest}"
)
return data
def download_validation_model(path: Path, cache_path: Path | None = None) -> None:
try:
data: bytes | None = None
if cache_path and cache_path.exists():
try:
data = validated_validation_model_bytes(cache_path.read_bytes())
log(f"using cached tiny GGUF validation model from {cache_path}")
except Exception as exc:
log(
f"cached tiny GGUF validation model was invalid; refreshing cache ({exc})"
)
data = None
if data is None:
log("downloading tiny GGUF validation model")
data = validated_validation_model_bytes(
download_bytes(
TEST_MODEL_URL,
progress_label = f"Downloading {download_label_from_url(TEST_MODEL_URL)}",
)
)
if cache_path is not None:
atomic_write_bytes(cache_path, data)
atomic_write_bytes(path, data)
except Exception as exc:
raise PrebuiltFallback(f"validation model unavailable: {exc}") from exc
def free_local_port() -> int:
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.bind(("127.0.0.1", 0))
_, port = sock.getsockname()
sock.close()
return int(port)
def read_log_excerpt(log_path: Path, *, max_lines: int = 60) -> str:
try:
content = log_path.read_text(encoding = "utf-8", errors = "replace")
except FileNotFoundError:
return ""
return "\n".join(content.splitlines()[-max_lines:])
def is_retryable_server_bind_error(
exc: Exception | None,
output: str = "",
*,
exited_quickly: bool = False,
) -> bool:
haystack = output.lower()
bind_markers = (
"address already in use",
"only one usage of each socket address",
"failed to bind",
"bind failed",
"failed to listen",
"errno 98",
"errno 10048",
)
if any(marker in haystack for marker in bind_markers):
return True
if isinstance(exc, urllib.error.URLError):
reason = exc.reason
if exited_quickly and isinstance(reason, ConnectionRefusedError):
return True
if isinstance(reason, OSError) and reason.errno in {
98,
99,
111,
10048,
10049,
10061,
}:
return exited_quickly
if exited_quickly and isinstance(exc, ConnectionRefusedError):
return True
if isinstance(exc, OSError) and exc.errno in {98, 99, 111, 10048, 10049, 10061}:
return exited_quickly
return False
def dedupe_existing_dirs(paths: Iterable[str | Path]) -> list[str]:
unique: list[str] = []
seen: set[str] = set()
for raw in paths:
if not raw:
continue
path = Path(raw).expanduser()
if not path.is_dir():
continue
resolved = str(path.resolve())
if resolved in seen:
continue
seen.add(resolved)
unique.append(resolved)
return unique
def linux_missing_libraries(
binary_path: Path, *, env: dict[str, str] | None = None
) -> list[str]:
try:
result = run_capture(["ldd", str(binary_path)], timeout = 20, env = env)
except Exception:
return []
missing: list[str] = []
for line in (result.stdout + result.stderr).splitlines():
line = line.strip()
if "=> not found" not in line:
continue
library = line.split("=>", 1)[0].strip()
if library and library not in missing:
missing.append(library)
return missing
def python_runtime_dirs() -> list[str]:
candidates: list[Path] = []
search_roots = [Path(entry) for entry in sys.path if entry]
try:
search_roots.extend(Path(path) for path in site.getsitepackages())
except Exception:
pass
try:
user_site = site.getusersitepackages()
if user_site:
search_roots.append(Path(user_site))
except Exception:
pass
for root in search_roots:
if not root.is_dir():
continue
candidates.extend(root.glob("nvidia/*/lib"))
candidates.extend(root.glob("nvidia/*/bin"))
candidates.extend(root.glob("torch/lib"))
return dedupe_existing_dirs(candidates)
def ldconfig_runtime_dirs(required_libraries: Iterable[str]) -> list[str]:
try:
result = run_capture(["ldconfig", "-p"], timeout = 20)
except Exception:
return []
required = set(required_libraries)
candidates: list[str] = []
for line in result.stdout.splitlines():
if "=>" not in line:
continue
library, _, location = line.partition("=>")
library = library.strip().split()[0]
if required and library not in required:
continue
path = Path(location.strip()).parent
candidates.append(str(path))
return dedupe_existing_dirs(candidates)
def linux_runtime_dirs(binary_path: Path) -> list[str]:
missing = linux_missing_libraries(binary_path)
if not missing:
return []
return linux_runtime_dirs_for_required_libraries(missing)
def preflight_linux_installed_binaries(
binaries: Iterable[Path],
install_dir: Path,
host: HostInfo,
) -> None:
if not host.is_linux:
return
issues: list[str] = []
for binary_path in binaries:
env = binary_env(binary_path, install_dir, host)
missing = linux_missing_libraries(binary_path, env = env)
if not missing:
continue
runtime_dirs = [
part for part in env.get("LD_LIBRARY_PATH", "").split(os.pathsep) if part
]
issues.append(
f"{binary_path.name}: missing={','.join(missing)} "
f"ld_library_path={','.join(runtime_dirs) if runtime_dirs else 'none'}"
)
if issues:
raise PrebuiltFallback(
"linux extracted binary preflight failed:\n" + "\n".join(issues)
)
def glob_paths(*patterns: str) -> list[str]:
matches: list[str] = []
for pattern in patterns:
if any(char in pattern for char in "*?[]"):
matches.extend(str(path) for path in Path("/").glob(pattern.lstrip("/")))
else:
matches.append(pattern)
return matches
def windows_runtime_dirs() -> list[str]:
candidates: list[str | Path] = []
env_dirs = os.environ.get("CUDA_RUNTIME_DLL_DIR", "")
if env_dirs:
candidates.extend(part for part in env_dirs.split(os.pathsep) if part)
path_dirs = os.environ.get("PATH", "")
if path_dirs:
candidates.extend(part for part in path_dirs.split(os.pathsep) if part)
cuda_roots: list[Path] = []
for name in ("CUDA_PATH", "CUDA_HOME", "CUDA_ROOT"):
value = os.environ.get(name)
if value:
cuda_roots.append(Path(value))
for root in cuda_roots:
candidates.extend([root / "bin", root / "lib" / "x64"])
program_files = os.environ.get("ProgramFiles", r"C:\Program Files")
toolkit_base = Path(program_files) / "NVIDIA GPU Computing Toolkit" / "CUDA"
if toolkit_base.is_dir():
candidates.extend(toolkit_base.glob("v*/bin"))
candidates.extend(toolkit_base.glob("v*/lib/x64"))
candidates.extend(Path(path) for path in python_runtime_dirs())
return dedupe_existing_dirs(candidates)
def windows_runtime_dirs_for_patterns(
required_patterns: Iterable[str],
candidate_dirs: Iterable[str] | None = None,
) -> list[str]:
directories = (
list(candidate_dirs) if candidate_dirs is not None else windows_runtime_dirs()
)
matching_dirs: list[str] = []
for pattern in required_patterns:
matched_dirs = [
directory for directory in directories if any(Path(directory).glob(pattern))
]
if not matched_dirs:
return []
for directory in matched_dirs:
if directory not in matching_dirs:
matching_dirs.append(directory)
return matching_dirs
def windows_runtime_dirs_for_runtime_line(runtime_line: str | None) -> list[str]:
if not runtime_line:
return []
patterns = windows_runtime_line_info().get(runtime_line)
if not patterns:
return []
return windows_runtime_dirs_for_patterns(patterns)
def binary_env(
binary_path: Path,
install_dir: Path,
host: HostInfo,
*,
runtime_line: str | None = None,
) -> dict[str, str]:
env = os.environ.copy()
if host.is_windows:
path_dirs = [
str(binary_path.parent),
*windows_runtime_dirs_for_runtime_line(runtime_line),
]
existing = [part for part in env.get("PATH", "").split(os.pathsep) if part]
env["PATH"] = os.pathsep.join(dedupe_existing_dirs([*path_dirs, *existing]))
elif host.is_linux:
ld_dirs = [
str(binary_path.parent),
str(install_dir),
*linux_runtime_dirs(binary_path),
]
existing = [
part for part in env.get("LD_LIBRARY_PATH", "").split(os.pathsep) if part
]
env["LD_LIBRARY_PATH"] = os.pathsep.join(
dedupe_existing_dirs([*ld_dirs, *existing])
)
elif host.is_macos:
dyld_dirs = [str(binary_path.parent), str(install_dir)]
existing = [
part for part in env.get("DYLD_LIBRARY_PATH", "").split(os.pathsep) if part
]
env["DYLD_LIBRARY_PATH"] = os.pathsep.join(
dedupe_existing_dirs([*dyld_dirs, *existing])
)
return env
def validate_quantize(
quantize_path: Path,
probe_path: Path,
quantized_path: Path,
install_dir: Path,
host: HostInfo,
*,
runtime_line: str | None = None,
) -> None:
command = [str(quantize_path), str(probe_path), str(quantized_path), "Q6_K", "2"]
result = subprocess.run(
command,
capture_output = True,
text = True,
timeout = 120,
env = binary_env(quantize_path, install_dir, host, runtime_line = runtime_line),
)
if (
result.returncode != 0
or not quantized_path.exists()
or quantized_path.stat().st_size == 0
):
raise PrebuiltFallback(
"llama-quantize validation failed:\n"
+ result.stdout
+ ("\n" + result.stderr if result.stderr else "")
)
def validate_server(
server_path: Path,
probe_path: Path,
host: HostInfo,
install_dir: Path,
*,
runtime_line: str | None = None,
install_kind: str | None = None,
) -> None:
last_failure: PrebuiltFallback | None = None
for port_attempt in range(1, SERVER_PORT_BIND_ATTEMPTS + 1):
port = free_local_port()
command = [
str(server_path),
"-m",
str(probe_path),
"--host",
"127.0.0.1",
"--port",
str(port),
"-c",
"32",
"--parallel",
"1",
"--threads",
"1",
"--ubatch-size",
"32",
"--batch-size",
"32",
]
# Only enable GPU offload for assets that actually ship GPU code.
# Gating on `host.has_rocm` alone breaks the intentional CPU
# fallback on AMD Windows hosts without a HIP prebuilt: the CPU
# binary would be launched with `--n-gpu-layers 1` and fail
# validation. Use the resolved install_kind as the source of
# truth and fall back to host detection when the caller did not
# pass one (keeps backwards compatibility with older call sites).
_gpu_kinds = {
"linux-cuda",
"linux-rocm",
"windows-cuda",
"windows-hip",
"macos-arm64",
}
if install_kind is not None:
_enable_gpu_layers = install_kind in _gpu_kinds
else:
# Older call sites that don't pass install_kind: keep ROCm
# hosts in the GPU-validation path so an AMD-only Linux host
# is exercised against the actual hardware rather than the
# CPU fallback. NVIDIA and macOS-arm64 are already covered.
_enable_gpu_layers = (
host.has_usable_nvidia
or host.has_rocm
or (host.is_macos and host.is_arm64)
)
if _enable_gpu_layers:
command.extend(["--n-gpu-layers", "1"])
log_fd, log_name = tempfile.mkstemp(prefix = "llama-server-", suffix = ".log")
os.close(log_fd)
log_path = Path(log_name)
process: subprocess.Popen[str] | None = None
try:
with log_path.open("w", encoding = "utf-8", errors = "replace") as log_handle:
process = subprocess.Popen(
command,
stdout = log_handle,
stderr = subprocess.STDOUT,
text = True,
env = binary_env(
server_path, install_dir, host, runtime_line = runtime_line
),
)
deadline = time.time() + 20
startup_started = time.time()
response_body = ""
last_error: Exception | None = None
while time.time() < deadline:
if process.poll() is not None:
process.wait(timeout = 5)
log_handle.flush()
output = read_log_excerpt(log_path)
exited_quickly = (
time.time() - startup_started
) <= SERVER_BIND_RETRY_WINDOW_SECONDS
failure = PrebuiltFallback(
"llama-server exited during startup:\n" + output
)
if (
port_attempt < SERVER_PORT_BIND_ATTEMPTS
and is_retryable_server_bind_error(
last_error,
output,
exited_quickly = exited_quickly,
)
):
log(
f"llama-server startup hit a port race on {port}; retrying with a fresh port "
f"({port_attempt}/{SERVER_PORT_BIND_ATTEMPTS})"
)
last_failure = failure
break
raise failure
payload = json.dumps({"prompt": "a", "n_predict": 1}).encode(
"utf-8"
)
request = urllib.request.Request(
f"http://127.0.0.1:{port}/completion",
data = payload,
headers = {"Content-Type": "application/json"},
)
try:
with urllib.request.urlopen(request, timeout = 5) as response:
status_code = response.status
response_body = response.read().decode("utf-8", "replace")
if status_code == 200:
return
last_error = RuntimeError(
f"unexpected HTTP status {status_code}"
)
except urllib.error.HTTPError as exc:
response_body = exc.read().decode("utf-8", "replace")
last_error = exc
except Exception as exc:
last_error = exc
time.sleep(0.5)
else:
log_handle.flush()
output = read_log_excerpt(log_path)
raise PrebuiltFallback(
"llama-server completion validation timed out"
+ (f" ({last_error})" if last_error else "")
+ ":\n"
+ output
+ ("\n" + response_body if response_body else "")
)
finally:
if process is not None and process.poll() is None:
process.terminate()
try:
process.wait(timeout = 5)
except subprocess.TimeoutExpired:
process.kill()
process.wait(timeout = 5)
try:
log_path.unlink(missing_ok = True)
except Exception:
pass
if last_failure is not None:
raise last_failure
raise PrebuiltFallback("llama-server validation failed unexpectedly")
def collect_system_report(
host: HostInfo, choice: AssetChoice | None, install_dir: Path
) -> str:
lines = [
f"platform={host.system} machine={host.machine}",
f"driver_cuda_version={host.driver_cuda_version}",
f"compute_caps={','.join(host.compute_caps) if host.compute_caps else 'unknown'}",
f"cuda_visible_devices={host.visible_cuda_devices if host.visible_cuda_devices is not None else 'unset'}",
f"has_physical_nvidia={host.has_physical_nvidia}",
f"has_usable_nvidia={host.has_usable_nvidia}",
f"chosen_asset={(choice.name if choice else 'none')}",
f"asset_source={(choice.source_label if choice else 'none')}",
]
if host.is_linux and host.has_physical_nvidia:
runtime_lines, runtime_dirs = detected_linux_runtime_lines()
lines.append(
"linux_runtime_lines="
+ (",".join(runtime_lines) if runtime_lines else "none")
)
for runtime_line in ("cuda13", "cuda12"):
lines.append(
f"linux_runtime_dirs_{runtime_line}="
+ (
",".join(runtime_dirs.get(runtime_line, []))
if runtime_dirs.get(runtime_line)
else "none"
)
)
if choice and choice.selection_log:
lines.append("selection_log:")
lines.extend(choice.selection_log)
if host.nvidia_smi:
try:
smi = run_capture([host.nvidia_smi], timeout = 20)
excerpt = "\n".join((smi.stdout + smi.stderr).splitlines()[:20])
lines.append("nvidia-smi:")
lines.append(excerpt)
except Exception as exc:
lines.append(f"nvidia-smi error: {exc}")
if host.is_linux:
server_binary = install_dir / "llama-server"
if server_binary.exists():
server_env = binary_env(server_binary, install_dir, host)
lines.append(
"linux_missing_libs="
+ (
",".join(linux_missing_libraries(server_binary, env = server_env))
or "none"
)
)
lines.append(
"linux_runtime_dirs="
+ (
",".join(
[
part
for part in server_env.get("LD_LIBRARY_PATH", "").split(
os.pathsep
)
if part
]
)
or "none"
)
)
try:
ldd = run_capture(
["ldd", str(server_binary)], timeout = 20, env = server_env
)
lines.append("ldd llama-server:")
lines.append((ldd.stdout + ldd.stderr).strip())
except Exception as exc:
lines.append(f"ldd error: {exc}")
elif host.is_windows:
lines.append(
"windows_runtime_dirs=" + (",".join(windows_runtime_dirs()) or "none")
)
runtime_lines, runtime_dirs = detected_windows_runtime_lines()
lines.append(
"windows_runtime_lines="
+ (",".join(runtime_lines) if runtime_lines else "none")
)
for runtime_line in ("cuda13", "cuda12"):
lines.append(
f"windows_runtime_dirs_{runtime_line}="
+ (
",".join(runtime_dirs.get(runtime_line, []))
if runtime_dirs.get(runtime_line)
else "none"
)
)
elif host.is_macos:
server_binary = install_dir / "llama-server"
if server_binary.exists():
try:
otool = run_capture(["otool", "-L", str(server_binary)], timeout = 20)
lines.append("otool -L llama-server:")
lines.append((otool.stdout + otool.stderr).strip())
except Exception as exc:
lines.append(f"otool error: {exc}")
return "\n".join(lines)
def apply_approved_hashes(
attempts: Iterable[AssetChoice],
checksums: ApprovedReleaseChecksums,
) -> list[AssetChoice]:
def approved_hash_for_attempt(attempt: AssetChoice) -> ApprovedArtifactHash | None:
candidate_names = [attempt.name]
if (
isinstance(attempt.tag, str)
and attempt.tag
and attempt.tag != checksums.upstream_tag
and attempt.name.startswith("llama-")
):
legacy_prefix = f"llama-{attempt.tag}-"
compatibility_prefix = f"llama-{checksums.upstream_tag}-"
compatibility_name = (
attempt.name.replace(legacy_prefix, compatibility_prefix, 1)
if attempt.name.startswith(legacy_prefix)
else attempt.name
)
candidate_names.append(compatibility_name)
candidate_names.extend(
windows_cuda_asset_aliases(
attempt.name,
compatibility_tag = checksums.upstream_tag,
)
)
seen_names: set[str] = set()
for candidate_name in candidate_names:
if candidate_name in seen_names:
continue
seen_names.add(candidate_name)
approved = checksums.artifacts.get(candidate_name)
if approved is not None:
return approved
return None
approved_attempts: list[AssetChoice] = []
missing_assets: list[str] = []
for attempt in attempts:
approved = approved_hash_for_attempt(attempt)
if approved is None:
missing_assets.append(attempt.name)
continue
attempt.expected_sha256 = approved.sha256
approved_attempts.append(attempt)
if not approved_attempts:
missing_text = ", ".join(missing_assets) if missing_assets else "none"
raise PrebuiltFallback(
"approved checksum asset did not contain the selected prebuilt archive(s): "
f"{missing_text}"
)
return approved_attempts
def require_approved_source_hash(
checksums: ApprovedReleaseChecksums, llama_tag: str
) -> ApprovedArtifactHash:
source_asset_name = source_archive_logical_name(llama_tag)
approved_source = checksums.artifacts.get(source_asset_name)
if approved_source is None:
raise PrebuiltFallback(
f"approved checksum asset did not contain source archive {source_asset_name}"
)
return approved_source
def preferred_source_archive(
checksums: ApprovedReleaseChecksums, llama_tag: str
) -> tuple[str, str, ApprovedArtifactHash | None, bool]:
exact_source = exact_source_archive_hash(checksums)
exact_repo = repo_slug_from_source(checksums.source_repo) or repo_slug_from_source(
checksums.source_repo_url
)
if exact_source is not None and exact_repo and checksums.source_commit:
return (
exact_repo,
checksums.source_commit,
exact_source,
True,
)
legacy = checksums.artifacts.get(source_archive_logical_name(llama_tag))
return (
UPSTREAM_REPO,
llama_tag,
legacy,
False,
)
def selected_source_archive_metadata(
checksums: ApprovedReleaseChecksums,
llama_tag: str,
) -> tuple[str, str | None]:
_source_repo, _source_ref, source_archive, _exact_source = preferred_source_archive(
checksums, llama_tag
)
if source_archive is None:
return source_archive_logical_name(llama_tag), None
return source_archive.asset_name, source_archive.sha256
def resolve_install_attempts(
llama_tag: str,
host: HostInfo,
published_repo: str,
published_release_tag: str,
) -> tuple[str, str, list[AssetChoice], ApprovedReleaseChecksums]:
requested_tag, plans = resolve_install_release_plans(
llama_tag,
host,
published_repo,
published_release_tag,
)
if not plans:
raise PrebuiltFallback("no prebuilt release plans were available")
plan = plans[0]
return requested_tag, plan.llama_tag, plan.attempts, plan.approved_checksums
def resolve_install_release_plans(
llama_tag: str,
host: HostInfo,
published_repo: str,
published_release_tag: str,
*,
max_release_fallbacks: int = DEFAULT_MAX_PREBUILT_RELEASE_FALLBACKS,
) -> tuple[str, list[InstallReleasePlan]]:
requested_tag = normalized_requested_llama_tag(llama_tag)
allow_older_release_fallback = (
requested_tag == "latest" and not published_release_tag
)
release_limit = max(1, max_release_fallbacks)
plans: list[InstallReleasePlan] = []
last_error: PrebuiltFallback | None = None
for resolved_release in iter_resolved_published_releases(
llama_tag,
published_repo,
published_release_tag,
):
bundle = resolved_release.bundle
checksums = resolved_release.checksums
resolved_tag = bundle.upstream_tag
try:
if host.is_linux and host.is_x86_64 and host.has_usable_nvidia:
linux_cuda_selection = resolve_linux_cuda_choice(host, bundle)
attempts = apply_approved_hashes(
linux_cuda_selection.attempts, checksums
)
if not attempts:
raise PrebuiltFallback("no compatible Linux CUDA asset was found")
log_lines(linux_cuda_selection.selection_log)
else:
attempts = resolve_release_asset_choice(
host,
resolved_tag,
bundle,
checksums,
)
if not attempts:
raise PrebuiltFallback("no compatible prebuilt asset was found")
if attempts[0].selection_log:
log_lines(attempts[0].selection_log)
except PrebuiltFallback as exc:
last_error = exc
if not allow_older_release_fallback:
raise
log(
"published release skipped for install planning: "
f"{bundle.repo}@{bundle.release_tag} upstream_tag={resolved_tag} ({exc})"
)
continue
plans.append(
InstallReleasePlan(
requested_tag = requested_tag,
llama_tag = resolved_tag,
release_tag = bundle.release_tag,
attempts = attempts,
approved_checksums = checksums,
)
)
if not allow_older_release_fallback or len(plans) >= release_limit:
break
if plans:
return requested_tag, plans
if last_error is not None:
raise last_error
raise PrebuiltFallback("no installable published llama.cpp releases were found")
def write_prebuilt_metadata(
install_dir: Path,
*,
requested_tag: str,
llama_tag: str,
release_tag: str,
choice: AssetChoice,
approved_checksums: ApprovedReleaseChecksums,
prebuilt_fallback_used: bool,
) -> None:
source_asset_name, source_sha256 = selected_source_archive_metadata(
approved_checksums,
llama_tag,
)
fingerprint_payload = {
"published_repo": approved_checksums.repo,
"release_tag": release_tag,
"upstream_tag": llama_tag,
"asset": choice.name,
"asset_sha256": choice.expected_sha256,
"source": choice.source_label,
"source_asset": source_asset_name,
"source_sha256": source_sha256,
"runtime_line": choice.runtime_line,
"bundle_profile": choice.bundle_profile,
"coverage_class": choice.coverage_class,
}
fingerprint = hashlib.sha256(
json.dumps(fingerprint_payload, sort_keys = True, separators = (",", ":")).encode(
"utf-8"
)
).hexdigest()
metadata = {
"requested_tag": requested_tag,
"tag": llama_tag,
"release_tag": release_tag,
"published_repo": approved_checksums.repo,
"asset": choice.name,
"asset_sha256": choice.expected_sha256,
"source": choice.source_label,
"source_asset": source_asset_name,
"source_sha256": source_sha256,
"source_commit": approved_checksums.source_commit,
"source_commit_short": approved_checksums.source_commit_short,
"source_repo": approved_checksums.source_repo,
"source_repo_url": approved_checksums.source_repo_url,
"source_ref_kind": approved_checksums.source_ref_kind,
"requested_source_ref": approved_checksums.requested_source_ref,
"resolved_source_ref": approved_checksums.resolved_source_ref,
"bundle_profile": choice.bundle_profile,
"runtime_line": choice.runtime_line,
"coverage_class": choice.coverage_class,
"install_fingerprint": fingerprint,
"prebuilt_fallback_used": prebuilt_fallback_used,
"installed_at_utc": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
}
(install_dir / "UNSLOTH_PREBUILT_INFO.json").write_text(
json.dumps(metadata, indent = 2) + "\n"
)
def expected_install_fingerprint(
*,
llama_tag: str,
release_tag: str,
choice: AssetChoice,
approved_checksums: ApprovedReleaseChecksums,
) -> str | None:
source_asset_name, source_sha256 = selected_source_archive_metadata(
approved_checksums,
llama_tag,
)
payload = {
"published_repo": approved_checksums.repo,
"release_tag": release_tag,
"upstream_tag": llama_tag,
"asset": choice.name,
"asset_sha256": choice.expected_sha256,
"source": choice.source_label,
"source_asset": source_asset_name,
"source_sha256": source_sha256,
"runtime_line": choice.runtime_line,
"bundle_profile": choice.bundle_profile,
"coverage_class": choice.coverage_class,
}
return hashlib.sha256(
json.dumps(payload, sort_keys = True, separators = (",", ":")).encode("utf-8")
).hexdigest()
def load_prebuilt_metadata(install_dir: Path) -> dict[str, Any] | None:
metadata_path = install_dir / "UNSLOTH_PREBUILT_INFO.json"
if not metadata_path.is_file():
return None
try:
payload = json.loads(metadata_path.read_text(encoding = "utf-8"))
except Exception:
return None
if not isinstance(payload, dict):
return None
return payload
def runtime_payload_health_groups(choice: AssetChoice) -> list[list[str]]:
if choice.install_kind == "linux-cpu":
return [
["libllama.so*"],
["libggml.so*"],
["libggml-base.so*"],
["libggml-cpu-*.so*"],
["libmtmd.so*"],
]
if choice.install_kind == "linux-cuda":
return [
["libllama.so*"],
["libggml.so*"],
["libggml-base.so*"],
["libggml-cpu-*.so*"],
["libmtmd.so*"],
["libggml-cuda.so*"],
]
if choice.install_kind in {"macos-arm64", "macos-x64"}:
return [
["libllama*.dylib"],
["libggml*.dylib"],
["libmtmd*.dylib"],
]
if choice.install_kind == "linux-rocm":
return [
["libllama.so*"],
["libggml.so*"],
["libggml-base.so*"],
["libggml-cpu-*.so*"],
["libmtmd.so*"],
["libggml-hip.so*"],
]
if choice.install_kind == "windows-cpu":
return [["llama.dll"]]
if choice.install_kind == "windows-cuda":
return [["llama.dll"], ["ggml-cuda.dll"]]
if choice.install_kind == "windows-hip":
return [["llama.dll"], ["*hip*.dll"]]
return []
def install_runtime_dir(install_dir: Path, host: HostInfo) -> Path:
if host.is_windows:
return install_dir / "build" / "bin" / "Release"
return install_dir / "build" / "bin"
def runtime_payload_is_healthy(
install_dir: Path, host: HostInfo, choice: AssetChoice
) -> bool:
runtime_dir = install_runtime_dir(install_dir, host)
if not runtime_dir.exists():
return False
for pattern_group in runtime_payload_health_groups(choice):
matched = False
for pattern in pattern_group:
if any(runtime_dir.glob(pattern)):
matched = True
break
if not matched:
return False
return True
def existing_install_matches_choice(
install_dir: Path,
host: HostInfo,
*,
llama_tag: str,
release_tag: str,
choice: AssetChoice,
approved_checksums: ApprovedReleaseChecksums,
) -> bool:
if not install_dir.exists():
return False
metadata = load_prebuilt_metadata(install_dir)
if metadata is None:
return False
try:
confirm_install_tree(install_dir, host)
except Exception:
return False
if not runtime_payload_is_healthy(install_dir, host, choice):
return False
# Verify primary executables still exist (catches partial deletion)
runtime_dir = install_runtime_dir(install_dir, host)
ext = ".exe" if host.is_windows else ""
for binary in ("llama-server", "llama-quantize"):
if not (runtime_dir / f"{binary}{ext}").exists():
return False
expected_fingerprint = expected_install_fingerprint(
llama_tag = llama_tag,
release_tag = release_tag,
choice = choice,
approved_checksums = approved_checksums,
)
if not expected_fingerprint:
return False
recorded_fingerprint = metadata.get("install_fingerprint")
if not isinstance(recorded_fingerprint, str) or not recorded_fingerprint:
return False
if recorded_fingerprint != expected_fingerprint:
return False
expected_pairs = {
"release_tag": release_tag,
"published_repo": approved_checksums.repo,
"tag": llama_tag,
"asset": choice.name,
"asset_sha256": choice.expected_sha256,
"source": choice.source_label,
"runtime_line": choice.runtime_line,
"bundle_profile": choice.bundle_profile,
"coverage_class": choice.coverage_class,
}
for key, expected in expected_pairs.items():
if metadata.get(key) != expected:
return False
return True
def existing_install_matches_plan(
install_dir: Path,
host: HostInfo,
plan: InstallReleasePlan,
) -> bool:
if not plan.attempts:
return False
return existing_install_matches_choice(
install_dir,
host,
llama_tag = plan.llama_tag,
release_tag = plan.release_tag,
choice = plan.attempts[0],
approved_checksums = plan.approved_checksums,
)
def validate_prebuilt_choice(
choice: AssetChoice,
host: HostInfo,
install_dir: Path,
work_dir: Path,
probe_path: Path,
*,
requested_tag: str,
llama_tag: str,
release_tag: str,
approved_checksums: ApprovedReleaseChecksums,
prebuilt_fallback_used: bool,
quantized_path: Path,
) -> tuple[Path, Path]:
source_repo, source_ref, source_archive, exact_source = preferred_source_archive(
approved_checksums, llama_tag
)
if exact_source:
log(
f"hydrating exact llama.cpp source for {source_repo}@{source_ref} into {install_dir}"
)
else:
log(f"hydrating upstream llama.cpp source for {llama_tag} into {install_dir}")
hydrate_source_tree(
source_ref,
install_dir,
work_dir,
source_repo = source_repo,
expected_sha256 = source_archive.sha256 if source_archive is not None else None,
source_label = (
f"llama.cpp source tree for {source_repo}@{source_ref}"
if exact_source
else f"llama.cpp source tree for {llama_tag}"
),
exact_source = exact_source,
)
log(f"overlaying prebuilt bundle {choice.name} into {install_dir}")
server_path, quantize_path = install_from_archives(
choice, host, install_dir, work_dir
)
preflight_linux_installed_binaries((server_path, quantize_path), install_dir, host)
ensure_repo_shape(install_dir)
write_prebuilt_metadata(
install_dir,
requested_tag = requested_tag,
llama_tag = llama_tag,
release_tag = release_tag,
choice = choice,
approved_checksums = approved_checksums,
prebuilt_fallback_used = prebuilt_fallback_used,
)
validate_quantize(
quantize_path,
probe_path,
quantized_path,
install_dir,
host,
runtime_line = choice.runtime_line,
)
validate_server(
server_path,
probe_path,
host,
install_dir,
runtime_line = choice.runtime_line,
install_kind = choice.install_kind,
)
log(f"staged prebuilt validation succeeded for {choice.name}")
return server_path, quantize_path
def validate_prebuilt_attempts(
attempts: Iterable[AssetChoice],
host: HostInfo,
install_dir: Path,
work_dir: Path,
probe_path: Path,
*,
requested_tag: str,
llama_tag: str,
release_tag: str,
approved_checksums: ApprovedReleaseChecksums,
initial_fallback_used: bool = False,
existing_install_dir: Path | None = None,
) -> tuple[AssetChoice, Path, bool]:
attempt_list = list(attempts)
if not attempt_list:
raise PrebuiltFallback("no prebuilt bundle attempts were available")
tried_fallback = initial_fallback_used
for index, attempt in enumerate(attempt_list):
if index > 0:
tried_fallback = True
log(
"retrying CUDA prebuilt "
f"{attempt.name} install_kind={attempt.install_kind} "
f"runtime_line={attempt.runtime_line} coverage_class={attempt.coverage_class}"
)
if existing_install_dir is not None and existing_install_matches_choice(
existing_install_dir,
host,
llama_tag = llama_tag,
release_tag = release_tag,
choice = attempt,
approved_checksums = approved_checksums,
):
log(
"existing llama.cpp install already matches fallback candidate "
f"{attempt.name}; skipping reinstall"
)
raise ExistingInstallSatisfied(attempt, tried_fallback)
staging_dir = create_install_staging_dir(install_dir)
quantized_path = work_dir / f"stories260K-q4-{index}.gguf"
if quantized_path.exists():
quantized_path.unlink()
try:
validate_prebuilt_choice(
attempt,
host,
staging_dir,
work_dir,
probe_path,
requested_tag = requested_tag,
llama_tag = llama_tag,
release_tag = release_tag,
approved_checksums = approved_checksums,
prebuilt_fallback_used = tried_fallback,
quantized_path = quantized_path,
)
except Exception as exc:
remove_tree(staging_dir)
prune_install_staging_root(install_dir)
if isinstance(exc, PrebuiltFallback):
attempt_error = exc
else:
attempt_error = PrebuiltFallback(
f"candidate attempt failed before activation for {attempt.name}: {exc}"
)
if index == len(attempt_list) - 1:
raise attempt_error from exc
log(
"selected CUDA bundle failed before activation; trying next prebuilt fallback "
f"({textwrap.shorten(str(attempt_error), width = 200, placeholder = '...')})"
)
continue
return attempt, staging_dir, tried_fallback
raise PrebuiltFallback("no prebuilt bundle passed validation")
def install_prebuilt(
install_dir: Path,
llama_tag: str,
published_repo: str,
published_release_tag: str,
*,
simple_policy: bool = False,
) -> None:
host = detect_host()
choice: AssetChoice | None = None
try:
with install_lock(install_lock_path(install_dir)):
if install_dir.exists():
log(
f"existing llama.cpp install detected at {install_dir}; validating staged prebuilt update before replacement"
)
else:
log(
f"no existing llama.cpp install detected at {install_dir}; performing fresh prebuilt install"
)
if simple_policy:
requested_tag, release_plans = resolve_simple_install_release_plans(
llama_tag,
host,
published_repo,
published_release_tag,
)
else:
requested_tag, release_plans = resolve_install_release_plans(
llama_tag,
host,
published_repo,
published_release_tag,
)
if release_plans and existing_install_matches_plan(
install_dir, host, release_plans[0]
):
current = release_plans[0]
log(
"existing llama.cpp install already matches selected release "
f"{current.release_tag} upstream_tag={current.llama_tag}; skipping download and install"
)
return
with tempfile.TemporaryDirectory(prefix = "unsloth-llama-prebuilt-") as tmp:
work_dir = Path(tmp)
probe_path = work_dir / "stories260K.gguf"
download_validation_model(
probe_path, validation_model_cache_path(install_dir)
)
release_count = len(release_plans)
for release_index, plan in enumerate(release_plans):
choice = plan.attempts[0]
if existing_install_matches_plan(install_dir, host, plan):
log(
"existing llama.cpp install already matches fallback release "
f"{plan.release_tag} upstream_tag={plan.llama_tag}; skipping reinstall"
)
return
log(
"selected "
f"{choice.name} ({choice.source_label}) from published release "
f"{plan.release_tag} for {host.system} {host.machine}"
)
try:
choice, selected_staging_dir, _ = validate_prebuilt_attempts(
plan.attempts,
host,
install_dir,
work_dir,
probe_path,
requested_tag = requested_tag,
llama_tag = plan.llama_tag,
release_tag = plan.release_tag,
approved_checksums = plan.approved_checksums,
initial_fallback_used = release_index > 0,
existing_install_dir = install_dir,
)
except ExistingInstallSatisfied:
return
except PrebuiltFallback as exc:
if release_index == release_count - 1:
raise
log(
"published release "
f"{plan.release_tag} upstream_tag={plan.llama_tag} failed; "
"trying the next older published prebuilt "
f"({textwrap.shorten(str(exc), width = 200, placeholder = '...')})"
)
continue
activate_install_tree(selected_staging_dir, install_dir, host)
try:
ensure_converter_scripts(install_dir, plan.llama_tag)
except Exception as exc:
log(
"converter script fetch failed after activation; install remains valid "
f"({textwrap.shorten(str(exc), width = 200, placeholder = '...')})"
)
return
except BusyInstallConflict as exc:
log("prebuilt install path is blocked by an in-use llama.cpp install")
log(f"prebuilt busy reason: {exc}")
raise SystemExit(EXIT_BUSY) from exc
except PrebuiltFallback as exc:
log("prebuilt install path failed; falling back to source build")
log(f"prebuilt fallback reason: {exc}")
report = collect_system_report(host, choice, install_dir)
print(report)
raise SystemExit(EXIT_FALLBACK) from exc
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(
description = "Install and validate a prebuilt llama.cpp bundle for Unsloth Studio."
)
parser.add_argument("--install-dir", help = "Target ~/.unsloth/llama.cpp directory")
parser.add_argument(
"--llama-tag",
default = DEFAULT_LLAMA_TAG,
help = (
"llama.cpp release tag. Defaults to the latest usable published Unsloth "
"release unless UNSLOTH_LLAMA_TAG overrides it."
),
)
parser.add_argument(
"--published-repo",
default = DEFAULT_PUBLISHED_REPO,
help = "Published bundle repository",
)
parser.add_argument(
"--published-release-tag",
default = DEFAULT_PUBLISHED_TAG,
help = (
"Published GitHub release tag to pin. By default, scan releases "
"until a usable published llama.cpp release bundle is found."
),
)
parser.add_argument(
"--simple-policy",
action = "store_true",
help = "Use the simplified platform-specific prebuilt selection policy.",
)
resolve_group = parser.add_mutually_exclusive_group()
resolve_group.add_argument(
"--resolve-llama-tag",
nargs = "?",
const = "latest",
help = "Resolve a llama.cpp tag such as 'latest' to the logical upstream release tag.",
)
resolve_group.add_argument(
"--resolve-install-tag",
nargs = "?",
const = "latest",
help = (
"Resolve a llama.cpp tag such as 'latest' to the concrete upstream tag "
"selected by the current published-release policy."
),
)
resolve_group.add_argument(
"--resolve-source-build",
nargs = "?",
const = "latest",
help = ("Resolve the source-build fallback plan."),
)
parser.add_argument(
"--output-format",
choices = ("plain", "json"),
default = "plain",
help = "Resolver output format. Defaults to plain.",
)
return parser.parse_args()
def emit_resolver_output(payload: dict[str, Any], *, output_format: str) -> None:
if output_format == "json":
print(json.dumps(payload, sort_keys = True))
return
if "llama_tag" in payload:
print(payload["llama_tag"])
return
if {
"source_url",
"source_ref_kind",
"source_ref",
}.issubset(payload):
print(
"\t".join(
(
str(payload["source_url"]),
str(payload["source_ref_kind"]),
str(payload["source_ref"]),
)
)
)
return
print(json.dumps(payload, sort_keys = True))
def main() -> int:
args = parse_args()
if args.resolve_llama_tag is not None:
resolved = resolve_requested_llama_tag(
args.resolve_llama_tag,
args.published_repo,
args.published_release_tag or "",
)
emit_resolver_output(
{
"requested_tag": normalized_requested_llama_tag(args.resolve_llama_tag),
"llama_tag": resolved,
},
output_format = args.output_format,
)
return EXIT_SUCCESS
if args.resolve_install_tag is not None:
resolved = resolve_requested_install_tag(
args.resolve_install_tag,
args.published_release_tag or "",
args.published_repo,
)
emit_resolver_output(
{
"requested_tag": normalized_requested_llama_tag(
args.resolve_install_tag
),
"llama_tag": resolved,
},
output_format = args.output_format,
)
return EXIT_SUCCESS
if args.resolve_source_build is not None:
plan = resolve_source_build_plan(
args.resolve_source_build,
args.published_repo,
args.published_release_tag or "",
)
emit_resolver_output(
{
"requested_tag": normalized_requested_llama_tag(
args.resolve_source_build
),
"source_url": plan.source_url,
"source_ref_kind": plan.source_ref_kind,
"source_ref": plan.source_ref,
"compatibility_upstream_tag": plan.compatibility_upstream_tag,
},
output_format = args.output_format,
)
return EXIT_SUCCESS
if not args.install_dir:
raise SystemExit(
"install_llama_prebuilt.py: --install-dir is required unless --resolve-llama-tag, --resolve-install-tag, or --resolve-source-build is used"
)
install_prebuilt(
install_dir = Path(args.install_dir).expanduser().resolve(),
llama_tag = args.llama_tag,
published_repo = args.published_repo,
published_release_tag = args.published_release_tag or "",
simple_policy = args.simple_policy,
)
return EXIT_SUCCESS
if __name__ == "__main__":
try:
raise SystemExit(main())
except SystemExit:
raise
except BusyInstallConflict as exc:
log(
f"fatal helper busy conflict: {textwrap.shorten(str(exc), width = 400, placeholder = '...')}"
)
raise SystemExit(EXIT_BUSY)
except PrebuiltFallback as exc:
# Expected when the published repo (e.g. ggml-org/llama.cpp) has no
# prebuilt manifest. Exit quietly with EXIT_FALLBACK so the caller
# falls back to source build without a noisy "fatal helper error".
log(textwrap.shorten(str(exc), width = 400, placeholder = "..."))
raise SystemExit(EXIT_FALLBACK)
except Exception as exc:
message = textwrap.shorten(str(exc), width = 400, placeholder = "...")
log(f"fatal helper error: {message}")
raise SystemExit(EXIT_ERROR)