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

cheemera

v1.0.2

Published

deCheem v3 for serverside use

Downloads

5

Readme

The repo of the Cheemera Service, an Express app that serves a Typescript implementation of the deCheem inference engine. The Cheemera Custom GPT is the best place to explore the capabilities of the deCheem inference engine, as it understands the format of the belief system and transposes your natural language rules, principles and beliefs into the right format for you.

Structure:

The structure of the various entities in deCheem are defined in /src/types/interfaces.ts. Basically, systems of thought and beliefs are represented by Belief Sets. Each Belief Set is a collection of Beliefs, which are made up of Antecedents (basically IFs) and Consequences (THENs).

An Explore is a question made up of a set of properties, and can be used to explore a Belief Set to find out what the consequences are of these starting points. Beliefs are transposed and broken down into its underlying assertions, which are used to compute the implications and deductions of the starting point.

For examples on how to structure Beliefs, refer to this doc.

Functionalities

The deCheem inference engine is able to make both explicit and implicit deductions using beliefs written in human language, which is a big distinction from other logic programming frameworks. It was originally built for legal, philosophical and solution engineering reasoning, and is now being repurposed for connection to Custom GPTs to extend their reasoning abilities.

For example, consider this rule "If A and B are true, then C and D must be true."

When A and B are true, deCheem will of course be able to deduce that C and D are true. But when exploring the situation when C is not true and A is, it will also be able to deduce that B cannot be true (an implicit deduction).

It can do this for tens of thousands of rules on consumer hardware in a second, and potentially even more with more efficient implementations of the engine in the future.

It is also:

  • Rule-sequence agnostic
  • Back-chaining and forward-chaining are both supported (in deCheem is a matter of semantics)
  • Allows for reasoning across any number of domains and languages (due to it not depending on (data)types or predefined data structures), working just with human language. Basically anything that is a 'string' can be put in a Belief.

Instructions:

To run the service on localhost, just do yarn build && yarn start.

  • /exploreBeliefSet: The primary endpoint to use. takes in an Explore and a Belief Set, and returns deductions and reasoning steps for the Explore.
  • /returnAssertionSet: this is more for troubleshooting, and returns the intermediate assertion set used to perform the exploration.

Implementations:

  • A basic Heroku deployment of this Cheemera Service can be found at https://cheemera-8cd49e85c8f5.herokuapp.com.
  • Cheemera, the Custom GPT that extends ChatGPT's capabilities with the deCheem inference engine.
  • Postman example of how to use the Cheemera backend service can be found in /public.