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mirror of https://github.com/cocktailpeanut/dalai synced 2024-11-20 23:07:32 +01:00
dalai/llama.js
cocktailpeanut dc8658ae07
Merge pull request #107 from matbee-eth/main
Add threads support to front end ui, showing system cpu count by default
2023-03-22 01:27:53 -04:00

169 lines
5.6 KiB
JavaScript

const path = require('path');
const term = require( 'terminal-kit' ).terminal;
const git = require('isomorphic-git');
const Downloader = require("nodejs-file-downloader");
const http = require('isomorphic-git/http/node');
const os = require('os');
const fs = require("fs");
const platform = os.platform()
class LLaMA {
constructor(root) {
this.root = root
this.home = path.resolve(this.root.home, "llama")
this.url = "https://github.com/candywrap/llama.cpp.git"
}
async make() {
console.log("make")
let success
if (platform === "win32") {
// CMake on Windows
const venv_path = path.join(this.root.home, "venv")
const cmake_path = path.join(venv_path, "Scripts", "cmake")
await this.root.exec("mkdir build", this.home)
await this.root.exec(`Remove-Item -path ${path.resolve(this.home, "build", "CMakeCache.txt")}`, this.home)
let PS_COUNTER = 0
await this.root.exec(`${cmake_path} ..`, path.resolve(this.home, "build"), (proc, data) => {
console.log("# data", data);
if (/^PS .*/.test(data)) {
PS_COUNTER++;
if (PS_COUNTER >= 2) {
console.log("KILL")
proc.kill()
}
}
})
PS_COUNTER = 0;
await this.root.exec(`${cmake_path} --build . --config Release`, path.resolve(this.home, "build"), (proc, data) => {
console.log("# data", data);
if (/^PS .*/.test(data)) {
PS_COUNTER++;
if (PS_COUNTER >= 2) {
console.log("KILL2")
proc.kill()
}
}
})
} else {
// Make on linux + mac
success = await this.root.exec(`make`, this.home)
if (!success) {
throw new Error("running 'make' failed")
return
}
}
}
async add (...models) {
if (models.length === 0) models = ["7B"]
models = models.map((m) => {
return m.toUpperCase()
})
for(let model of models) {
if (!["7B", "13B", "30B", "65B"].includes(model)) {
console.log(`##########################################################
#
# ERROR
# The arguments must be one or more of the following:
#
# 7B, 13B, 30B, 65B
#
##########################################################
[Example]
# install just 7B (default)
npx dalai install
# install 7B manually
npx dalai install 7B
# install 7B and 13B
npx dalai install 7B 13B
`)
throw new Error("The model name must be one of: 7B, 13B, 30B, and 65B")
return
}
}
const venv_path = path.join(this.root.home, "venv")
const python_path = platform == "win32" ? path.join(venv_path, "Scripts", "python.exe") : path.join(venv_path, 'bin', 'python')
/**************************************************************************************************************
*
* 5. Download models + convert + quantize
*
**************************************************************************************************************/
for(let model of models) {
await this.download(model)
const outputFile = path.resolve(this.home, 'models', model, 'ggml-model-f16.bin')
// if (fs.existsSync(outputFile)) {
// console.log(`Skip conversion, file already exists: ${outputFile}`)
// } else {
await this.root.exec(`${python_path} convert-pth-to-ggml.py models/${model}/ 1`, this.home)
// }
await this.quantize(model)
}
}
async quantize(model) {
let num = {
"7B": 1,
"13B": 2,
"30B": 4,
"65B": 8,
}
for(let i=0; i<num[model]; i++) {
const suffix = (i === 0 ? "" : `.${i}`)
const outputFile1 = path.resolve(this.home, `./models/${model}/ggml-model-f16.bin${suffix}`)
const outputFile2 = path.resolve(this.home, `./models/${model}/ggml-model-q4_0.bin${suffix}`)
if (fs.existsSync(outputFile1) && fs.existsSync(outputFile2)) {
console.log(`Skip quantization, files already exists: ${outputFile1} and ${outputFile2}}`)
continue
}
const bin_path = platform === "win32" ? path.resolve(this.home, "build", "Release") : this.home
await this.root.exec(`./quantize ${outputFile1} ${outputFile2} 2`, bin_path)
}
}
async download(model) {
console.log(`Download model ${model}`)
const venv_path = path.join(this.root.home, "venv")
const python_path = platform == "win32" ? path.join(venv_path, "Scripts", "python.exe") : path.join(venv_path, 'bin', 'python')
const num = {
"7B": 1,
"13B": 2,
"30B": 4,
"65B": 8,
}
const files = ["checklist.chk", "params.json"]
for(let i=0; i<num[model]; i++) {
files.push(`consolidated.0${i}.pth`)
}
const resolvedPath = path.resolve(this.home, "models", model)
await fs.promises.mkdir(resolvedPath, { recursive: true }).catch((e) => { })
for(let file of files) {
if (fs.existsSync(path.resolve(resolvedPath, file))) {
console.log(`Skip file download, it already exists: ${file}`)
continue;
}
const url = `https://agi.gpt4.org/llama/LLaMA/${model}/${file}`
await this.root.down(url, path.resolve(resolvedPath, file), {
"User-Agent": "Mozilla/5.0"
})
}
const files2 = ["tokenizer_checklist.chk", "tokenizer.model"]
for(let file of files2) {
// if (fs.existsSync(path.resolve(this.home, "models", file))) {
// console.log(`Skip file download, it already exists: ${file}`)
// continue;
// }
const url = `https://agi.gpt4.org/llama/LLaMA/${file}`
const dir = path.resolve(this.home, "models")
await this.root.down(url, path.resolve(dir, file), {
"User-Agent": "Mozilla/5.0"
})
}
}
}
module.exports = LLaMA