Data

Tools

Indexes

Applications

Experiments

Awesome

An open API service indexing awesome lists of open source software.

https://github.com/gmkung/cheemera

A Node.js backend that exposes a Typescript implementation of the deCheem inference engine.
https://github.com/gmkung/cheemera

ai expert-advisor expert-system gpt inference-api inference-engine

Last synced: 3 months ago
JSON representation

A Node.js backend that exposes a Typescript implementation of the deCheem inference engine.

Awesome Lists containing this project

README 

          
The repo of the Cheemera Service, an Express app that serves a Typescript implementation of the deCheem inference engine. 

The [Cheemera Custom GPT](https://chat.openai.com/g/g-7JIMFzSAI-cheemera) 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](https://joyous-talos-902.notion.site/Cheemera-belief-structuring-examples-7a5810796cd342e2a77be5694cc94ebd?pvs=4).



## 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](https://chat.openai.com/g/g-7JIMFzSAI-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`.