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Probe for CUDA before attempting GPU embeddings

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ONNX Runtime crashes with an uncatchable native error when CUDA
libraries are missing. This adds a lightweight probe (nvidia-smi +
libcublasLt.so.12 path check) before selecting the CUDA device,
falling back to CPU gracefully on systems without NVIDIA GPUs.

Fixes #53

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Carlos 2026-02-23 22:50:46 -05:00
parent e76d007aaf
commit d221dccbdb
1 changed files with 27 additions and 1 deletions
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28
gitnexus/src/core/embeddings/embedder.ts
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@ -15,8 +15,32 @@ if (!process.env.ORT_LOG_LEVEL) {
}
import { pipeline, env, type FeatureExtractionPipeline } from '@huggingface/transformers';
import { existsSync } from 'fs';
import { execSync } from 'child_process';
import { DEFAULT_EMBEDDING_CONFIG, type EmbeddingConfig, type ModelProgress } from './types.js';
/**
* Check whether CUDA libraries are actually available on this system.
* ONNX Runtime's native layer crashes (uncatchable) if we attempt CUDA
* without the required shared libraries, so we probe first.
*/
function isCudaAvailable(): boolean {
// Quick check: nvidia-smi exists and runs
try {
execSync('nvidia-smi', { stdio: 'ignore', timeout: 3000 });
return true;
} catch {
// No driver or no nvidia-smi
}
// Fallback: check for the specific library ONNX needs
const libPaths = [
'/usr/lib/x86_64-linux-gnu/libcublasLt.so.12',
'/usr/local/cuda/lib64/libcublasLt.so.12',
'/usr/lib64/libcublasLt.so.12',
];
return libPaths.some(p => existsSync(p));
}
// Module-level state for singleton pattern
let embedderInstance: FeatureExtractionPipeline | null = null;
let isInitializing = false;
@ -62,8 +86,10 @@ export const initEmbedder = async (
const finalConfig = { ...DEFAULT_EMBEDDING_CONFIG, ...config };
// On Windows, use DirectML for GPU acceleration (via DirectX12)
// CUDA is only available on Linux x64 with onnxruntime-node
// Probe for CUDA first — ONNX Runtime crashes (uncatchable native error)
// if we attempt CUDA without the required shared libraries
const isWindows = process.platform === 'win32';
const gpuDevice = isWindows ? 'dml' : 'cuda';
const gpuDevice = isWindows ? 'dml' : (isCudaAvailable() ? 'cuda' : 'cpu');
let requestedDevice = forceDevice || (finalConfig.device === 'auto' ? gpuDevice : finalConfig.device);
initPromise = (async () => {