ruvnet/ruflo · error

[ruvector] WASM backend unavailable (${reason}), using JS fa

Error message

[ruvector] WASM backend unavailable (${reason}), using JS fallback

What it means

Log warning in ruvector-training setup: loading the WASM learning backend (MicroLoRA/ScopedLoRA/TrajectoryBuffer) failed, so training runs on the pure-JS implementations with the reason attached.

Source

Thrown at v3/@claude-flow/cli/src/services/ruvector-training.ts:357

    microLoRA = new learningWasm.WasmMicroLoRA(dim, alpha, lr);
    features.push(`MicroLoRA/WASM (${dim}-dim, <1μs adaptation)`);

    scopedLoRA = new learningWasm.WasmScopedLoRA(dim, alpha, lr);
    scopedLoRA.set_category_fallback(true);
    features.push('ScopedLoRA/WASM (17 operators)');

    trajectoryBuffer = new learningWasm.WasmTrajectoryBuffer(
      config.trajectoryCapacity || 10000,
      dim
    );
    features.push('TrajectoryBuffer/WASM');

    activeBackend = 'wasm';
    wasmLoaded = true;
  } catch (wasmError) {
    // WASM not available - fall back to JS implementation
    const reason = wasmError instanceof Error ? wasmError.message : String(wasmError);
    console.warn(`[ruvector] WASM backend unavailable (${reason}), using JS fallback`);

    microLoRA = new JsMicroLoRA(dim, alpha, lr) as unknown as WasmMicroLoRA;
    features.push(`MicroLoRA/JS (${dim}-dim, JS fallback)`);

    scopedLoRA = new JsScopedLoRA(dim, alpha, lr) as unknown as WasmScopedLoRA;
    (scopedLoRA as any).set_category_fallback(true);
    features.push('ScopedLoRA/JS (17 operators)');

    trajectoryBuffer = new JsTrajectoryBuffer(
      config.trajectoryCapacity || 10000,
      dim
    ) as unknown as WasmTrajectoryBuffer;
    features.push('TrajectoryBuffer/JS');

    activeBackend = 'js-fallback';
  }

  // --- Attention mechanisms (optional, independent of WASM) ---

View on GitHub (pinned to fa13ee4ad6)

Solutions

1. Check the WASM backend unavailability reason; the JS fallback works — rebuild or reinstall the ruvector WASM package to restore speed.

When it happens

Trigger: Thrown at v3/@claude-flow/cli/src/services/ruvector-training.ts:357 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of ruvnet/ruflo@fa13ee4ad6 (2026-08-18). Data as JSON: /api/errors/94c6255bfe3d45d5. Report an issue: GitHub.