npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

poon-llm

v1.2.0

Published

Connect to and stream from any OpenAI/Anthropic API

Downloads

9

Readme

Connect to and stream from any OpenAI/Anthropic API. Lightweight, high performance, and simple, thoughtful API made for developers, encouraging use of CoT. Tested on OpenAI, Ollama, and Claude. Get better results from your LLM's using techniques that are made simple by poon-llm.

npm install poon-llm

OpenAI Example

import { OpenAI } from 'poon-llm';

const llm = new OpenAI({'secretKey': 'key', 'model': 'gpt-4o'});
const response = await llm.chat('Why is the sky blue?');

Ollama Example

const llm = new OpenAI({'apiBase': 'http://10.0.0.20', 'model': 'llama3'});
const response = await llm.chat('Why is the sky blue?');

Anthropic Example

import { Anthropic } from 'poon-llm';

const llm = new Anthropic({
    'secretKey': 'key',
    'model': 'claude-3-opus-20240229',
    'headers': {'Anthropic-Version': '2023-06-01'},
});
const response = await llm.chat('Why is the sky blue?');

Streaming

Streaming events occur at a fast rate, so to avoid crashing your server, poon-llm employs an efficient method to combat this: While an async onUpdate is executing, any chunks that come in will be ignored so that onUpdate will only be called as fast as your code can handle it. For example, if you are on a shared database that takes 1 second to write, your callbacks will fire back to back, after each write, and then once more at the very end.

const response = await llm.chat('Why is the sky blue?', {
    'onUpdate': text => Drafts.updateAsync({'_id': id}, {
        $set: {'body': text}
    }),
});

API Documentation

New Client - Options

Applies to new OpenAI(options), new Anthropic(options)

| Name | Description | |----------------|--------------------------------------------------------------------| | secretKey | Secret API key (Required for most API's) | | apiBase | Specifies new base URL. Overrides the built-in defaults (Optional) | | systemPrompt | Prompt to use for all chats | | headers | Object containing headers to send (Required for Anthropic) |

Chat Options

Applies to individual chat calls - llm.chat(message, options).

| Option | Description | |---------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | json | Enable JSON output: Requests underlying LLM API to respond in JSON, also JSON-parses and returns response. You must request the reply to be in JSON form in the system prompt. An error message will appear if the word JSON is not detected in the prompt. | | xml | Array containing XML tags to parse. Causes the output to be an object with the keys specified by the array. | | onUpdate | Callback function that is called every time the model has more chunks to append to the response. | | context | Chat history for the conversation, must be an array of objects like {'role': String ('user' or 'assistant'), 'content': String}. | | temperature | Float value controlling randomness in boltzmann sampling. Lower is less random, higher is more random. | | maxTokens | Integer value controlling the maximum number of tokens generated. | | prefill | String to prefill the LLM's response with. Useful for CoT. |

Chain of Thought Example

Although JSON option is available, XML is generally better for prompts with Chain of Thought, because the LLM has an easier time formatting it, as it just needs to understand delimiters, rather than strict adherence to a certain syntax. XML is also easier to stream.

const response = await llm.chat(chatString, {
    'prefill': '<scratchpad>',
    'maxTokens': 2048,
    'xml': true,
});