feat: async load binding

README.md

@@ -16,7 +16,7 @@ npm install @fugood/llama.node
 import { loadModel } from '@fugood/llama.node'
 
 // Initial a Llama context with the model (may take a while)
-const context = loadModel({
+const context = await loadModel({
   model: 'path/to/gguf/model',
   use_mlock: true,
   n_ctx: 2048,

lib/binding.ts

@@ -48,11 +48,11 @@ export interface Module {
   LlamaContext: LlamaContext
 }
 
-export const loadModule = (variant?: string): Module => {
+export const loadModule = async (variant?: string): Promise<Module> => {
   try {
     if (variant) {
-      return require(`../bin/${process.platform}-${variant}/${process.arch}/llama-node.node`) as Module
+      return await import(`../bin/${process.platform}-${variant}/${process.arch}/llama-node.node`) as Module
     }
   } catch {} // ignore errors and try the common path
-  return require(`../bin/${process.platform}/${process.arch}/llama-node.node`) as Module
+  return await import(`../bin/${process.platform}/${process.arch}/llama-node.node`) as Module
 }

lib/index.ts

@@ -1,13 +1,15 @@
 import { loadModule, LlamaModelOptions } from './binding'
-import type { LlamaContext } from './binding'
+import type { Module, LlamaContext } from './binding'
 
 export * from './binding'
 
 export interface LlamaModelOptionsExtended extends LlamaModelOptions {
   lib_variant?: string
 }
 
-export const loadModel = (options: LlamaModelOptionsExtended): LlamaContext => {
-    const { LlamaContext } = loadModule(options.lib_variant)
-    return new LlamaContext(options)
+let module: Module | null = null
+
+export const loadModel = async (options: LlamaModelOptionsExtended): Promise<LlamaContext> => {
+    module ??= await loadModule(options.lib_variant)
+    return new module.LlamaContext(options)
 }

test/index.test.ts

@@ -2,7 +2,7 @@ import path from 'path'
 import { loadModel } from '../lib'
 
 it('work fine', async () => {
-  const model = loadModel({ model: path.resolve(__dirname, './tiny-random-llama.gguf') })
+  const model = await loadModel({ model: path.resolve(__dirname, './tiny-random-llama.gguf') })
   const result = await model.completion({
     prompt: 'My name is Merve and my favorite',
     n_samples: 1,