People want deterministic systems, and we are bringing back old ideas into the LLM age. The team at WhyHow.AI have built a Python-based reasoning and validation framework, inspired by Pydantic, that makes it simple for developers and non-technical domain experts to build complex rule and reasoning engines. One of the biggest problems that exist is creating constraints around how systems validate and reason about the information entering the system. As we consume more and more unstructured data through stochastic LLMs, the ability to enforce rules and guardrails become even more important. This process is easily extensible by developers, and we have fine-tuned a model that helps automate the construction of rules from natural language rules/SOP. We have also built a UI that allows for a human-in-the-loop experience for domain experts inserting rules in natural language, as well as developers approving the translated code into the rules engine. This symbolic reasoning and validation framework is useful where you are looking to turn SOPs and other business logic & guardrails into enforceable code. https://medium.com/enterprise-rag/python-based-reasoning-engine-for-deterministic-ai-25722f9047e8