Awesome! I am completely new to Elixir but have played around with the Python CLIPS libraries. I’m building a product that has a domain ontology encoded with Postgres LTREE as a network of DAG taxonomies with a custom triple store schema. There are trees for normal taxa stuff like topics, but also for procedures of rules. It needs breadth-fist search to match potential rules against iterative, mostly synchronous user input sessions, e.g. checking a fact pattern that emerges from interviews against laws.
From doing a couple throwaway prototypes I have become less and less convinced that a “real” graph (lib or db) is needed. Basic trees are fine because I can’t think of cases where multiple roots or cycles must exist, or even if they did, why they must be handled in the actual traversal algorithm if I can just use SQL relations and code to stitch together many branches when initializing a Rete network (not an expert on that so could be missing something). The attraction of Rete for me is doing breadth-first search for rule/action nodes and not having to think about pruning dead-end paths during execution. Any other theoretical capability feels like conceptual overhead, but I can appreciate the appeal
Since this is the only pure Elixir Rete lib I could find, I hope to give it a spin soon.
Have you looked at GitHub - afiniate/seresye: SERESYE means Swarm oriented ERlang Expert SYstem Engine. It is a library to write expert systems and rule processing engines using the Erlang programming language. It allows to create multiple engines, each one with its own facts and rules to be processed. · GitHub as well? They seem to just use tuples, which would seem to be quite nice fit with pattern matching. It is also the approach taken by some projects in other languages like GitHub - project-flogo/rules: Golang based Rules for Real-time Contextual Decisions · GitHub.
Hope to see more people on this!
