
Security News
Attackers Are Hunting High-Impact Node.js Maintainers in a Coordinated Social Engineering Campaign
Multiple high-impact npm maintainers confirm they have been targeted in the same social engineering campaign that compromised Axios.
LLMs NodeJS addon. Run your LLM easily in nodejs or electron application.
Before installation, make sure your device environment is able to compile c++ source code. We will use cmake-js to build a .node file.
npm i node-llm
Simple usage:
import { Chat } from 'node-llm';
const chat = new Chat({
modelPath: path.resolve(__dirname, '../llms/chatglm3-6b.q4_0.bin'),
engine: 'chatglm',
});
const res = await chat.prompt('What is RAG?');
console.log(res);
Paramerters of Chat constructor:
chatglm and llamaStream mode:
chat.prompt('What is RAG?', {
onmessage(msg) {
process.stdout.write(msg);
}
});
Session usage:
import { Session } from 'node-llm';
const session = new Session({
modelPath: path.resolve(__dirname, '../llms/chatglm3-6b.q4_0.bin'),
engine: 'chatglm',
});
const res1 = await session.chat('What is RAG?');
console.log(res1);
const res2 = await session.chat('give more detail');
console.log(res2);
Chat in one session, you can use chat method times in a memory management.
Parameters of Session constructor:
chatglm and llamaprompt and chat methods have the same params:
type ChatParams = {
temperature?: number;
/** top_p */
topP?: number;
/** top_k */
topK?: number;
/** callback function with the answered text by LLM */
onmessage?: (msg: string) => void;
/** callback function when LLM answer end */
onend?: () => void;
/** callback function when error ocurs */
onerror?: (e: Error) => void;
};
const chat = new Chat({
modelPath,
engine,
systemPrompt,
});
chat.prompt(prompt, {
temperature,
topP,
topK,
onmessage(str) {},
onend() {},
onerror(e) {},
});
const session = new Session({
modelPath,
engine,
kvPath,
sessionId,
systemPrompt,
temperature,
topK,
topP,
});
session.chat(message, {
temperature,
topP,
topK,
onmessage(str) {},
onend() {},
onerror(e) {},
});
Copyright (c) 2024 Shuang Tang
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
FAQs
LLMs NodeJS addon. Run your LLM easily in nodejs or electron application.
We found that node-llm demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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