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6b3874e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 | """Real hardware/software environment detection for the inference layer.
Every field is probed from the actual machine (platform module, subprocess
calls to nvidia-smi / rocm-smi / system_profiler, and import probes for
torch / vllm). Nothing is assumed or fabricated: absent components are
reported as absent, and probe failures carry the failure detail.
"""
from __future__ import annotations
import json
import platform
import shutil
import subprocess
import sys
from typing import List, Optional
from pydantic import BaseModel, Field
class GPUInfo(BaseModel):
vendor: str # nvidia | amd | apple | intel | unknown
model: str
memory_mb: Optional[int] = None # dedicated VRAM if known; None for unified
unified_memory: bool = False # Apple Silicon shares system RAM
driver_version: Optional[str] = None
compute_capability: Optional[str] = None
detail: str = ""
class TorchInfo(BaseModel):
installed: bool
version: Optional[str] = None
cuda_available: bool = False
cuda_version: Optional[str] = None
rocm_version: Optional[str] = None
mps_available: bool = False
detail: str = ""
class EnvironmentReport(BaseModel):
os_name: str
os_version: str
machine_arch: str
is_macos: bool
is_apple_silicon: bool
python_version: str
torch: TorchInfo
gpus: List[GPUInfo] = Field(default_factory=list)
cuda_toolkit_version: Optional[str] = None # from nvcc, if present
rocm_installed: bool = False
nvidia_smi_present: bool = False
rocm_smi_present: bool = False
vllm_installed: bool = False
vllm_version: Optional[str] = None
ollama_endpoint: Optional[str] = None # reachable Ollama server, if any
ollama_models: List[str] = Field(default_factory=list)
notes: List[str] = Field(default_factory=list)
def _run(cmd: List[str], timeout: float = 5.0) -> Optional[str]:
try:
out = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout)
if out.returncode == 0:
return out.stdout
except (OSError, subprocess.SubprocessError):
pass
return None
def _detect_nvidia() -> List[GPUInfo]:
if not shutil.which("nvidia-smi"):
return []
out = _run(["nvidia-smi", "--query-gpu=name,memory.total,driver_version,compute_cap",
"--format=csv,noheader,nounits"])
gpus: List[GPUInfo] = []
for line in (out or "").strip().splitlines():
parts = [p.strip() for p in line.split(",")]
if len(parts) >= 2:
gpus.append(GPUInfo(
vendor="nvidia", model=parts[0],
memory_mb=int(float(parts[1])) if parts[1].replace(".", "").isdigit() else None,
driver_version=parts[2] if len(parts) > 2 else None,
compute_capability=parts[3] if len(parts) > 3 else None,
detail="detected via nvidia-smi"))
return gpus
def _detect_amd() -> List[GPUInfo]:
if not shutil.which("rocm-smi"):
return []
out = _run(["rocm-smi", "--showproductname", "--json"])
gpus: List[GPUInfo] = []
if out:
try:
data = json.loads(out)
for card, fields in data.items():
name = (fields.get("Card series") or fields.get("Card SKU")
or fields.get("Card model") or card)
gpus.append(GPUInfo(vendor="amd", model=str(name),
detail="detected via rocm-smi"))
except (json.JSONDecodeError, AttributeError):
gpus.append(GPUInfo(vendor="amd", model="unknown AMD GPU",
detail="rocm-smi present but output unparseable"))
return gpus
def _detect_apple() -> List[GPUInfo]:
if platform.system() != "Darwin":
return []
out = _run(["system_profiler", "SPDisplaysDataType", "-json"], timeout=15.0)
gpus: List[GPUInfo] = []
if out:
try:
data = json.loads(out)
for item in data.get("SPDisplaysDataType", []):
model = item.get("sppci_model", "Apple GPU")
cores = item.get("sppci_cores")
detail = "detected via system_profiler"
if cores:
detail += f"; {cores} GPU cores"
gpus.append(GPUInfo(vendor="apple", model=model, unified_memory=True,
detail=detail))
except json.JSONDecodeError:
pass
if not gpus:
# Apple Silicon always has an integrated GPU even if profiling failed.
gpus.append(GPUInfo(vendor="apple", model=f"Apple GPU ({platform.machine()})",
unified_memory=True,
detail="system_profiler unavailable; inferred from platform"))
return gpus
def _detect_torch() -> TorchInfo:
try:
import torch # type: ignore
except ImportError as exc:
return TorchInfo(installed=False, detail=f"torch not importable: {exc}")
info = TorchInfo(installed=True, version=getattr(torch, "__version__", None))
try:
info.cuda_available = bool(torch.cuda.is_available())
info.cuda_version = getattr(torch.version, "cuda", None)
info.rocm_version = getattr(torch.version, "hip", None)
mps = getattr(torch.backends, "mps", None)
info.mps_available = bool(mps and mps.is_available())
info.detail = "torch probed successfully"
except Exception as exc: # torch runtime probing should never crash detection
info.detail = f"torch installed but probing failed: {exc}"
return info
def _detect_nvcc() -> Optional[str]:
out = _run(["nvcc", "--version"]) if shutil.which("nvcc") else None
if out:
for line in out.splitlines():
if "release" in line:
return line.strip()
return None
def _detect_ollama(endpoints: Optional[List[str]] = None) -> tuple[Optional[str], List[str]]:
import httpx
for base in endpoints or ["http://localhost:11434"]:
try:
res = httpx.get(f"{base}/api/tags", timeout=2.0)
if res.status_code == 200:
models = [m.get("name", "?") for m in res.json().get("models", [])]
return base, models
except Exception:
continue
return None, []
def detect_environment(probe_ollama: bool = True) -> EnvironmentReport:
"""Probe the actual machine. Safe to call anywhere; never raises."""
system = platform.system()
arch = platform.machine()
is_macos = system == "Darwin"
is_apple_silicon = is_macos and arch == "arm64"
gpus = _detect_nvidia() + _detect_amd()
if not gpus and is_macos:
gpus = _detect_apple()
try:
import vllm # type: ignore
vllm_installed, vllm_version = True, getattr(vllm, "__version__", "unknown")
except ImportError:
vllm_installed, vllm_version = False, None
ollama_ep, ollama_models = (None, [])
if probe_ollama:
ollama_ep, ollama_models = _detect_ollama()
notes: List[str] = []
if is_macos:
notes.append("macOS detected: vLLM does not run on macOS (no CUDA, no ROCm); "
"Apple GPU acceleration is Metal/MPS which vLLM does not target.")
if is_apple_silicon:
notes.append("Apple Silicon (arm64) with unified memory; local LLM inference "
"is possible via Ollama (Metal), not vLLM.")
if not shutil.which("nvidia-smi") and not shutil.which("rocm-smi"):
notes.append("Neither nvidia-smi nor rocm-smi found on PATH: no CUDA or "
"ROCm capable GPU stack is installed on this machine.")
return EnvironmentReport(
os_name=system,
os_version=platform.mac_ver()[0] if is_macos else platform.release(),
machine_arch=arch,
is_macos=is_macos,
is_apple_silicon=is_apple_silicon,
python_version=".".join(map(str, sys.version_info[:3])),
torch=_detect_torch(),
gpus=gpus,
cuda_toolkit_version=_detect_nvcc(),
rocm_installed=shutil.which("rocm-smi") is not None,
nvidia_smi_present=shutil.which("nvidia-smi") is not None,
rocm_smi_present=shutil.which("rocm-smi") is not None,
vllm_installed=vllm_installed,
vllm_version=vllm_version,
ollama_endpoint=ollama_ep,
ollama_models=ollama_models,
notes=notes,
)
if __name__ == "__main__":
print(detect_environment().model_dump_json(indent=2))
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