Show HN: Build agents via YAML with Prolog validation and 110 built-in tools

fabceolin.github.io

11 points by fabceolin 3 months ago

I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts.

The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project.

*Key Technical Features:*

* *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural flexibility with symbolic reasoning to help mitigate hallucinations.

* *YAML + Overlays:* Agents are defined in YAML with overlay support (similar to the Kustomize pattern in Kubernetes), making configs testable and reproducible across environments (Dev/Prod) without code duplication.

* *Hybrid Scripting:*

* *Lua:* Embedded in all binaries (Python, Rust, Wasm) for secure, lightweight logic at the Edge.

* *Python:* Full integration for data science workloads.

* *Batteries Included:* We implemented 110+ tools based on Sarwar Alam’s Agentic Design Patterns. https://github.com/sarwarbeing-ai/Agentic_Design_Patterns

* *Polyglot:* Core written in Rust/Python with Wasm support (runs in browser, Docker, or embedded).

* *Observability:* Native hooks for Comet (Opik) to track execution/cost.

The goal is to provide a solid engineering foundation for agents. I’d love to hear your feedback on the Prolog integration and the YAML-based architecture.

Repo: https://github.com/fabceolin/the_edge_agent

Demo (Wasm): https://fabceolin.github.io/the_edge_agent/wasm-demo

raphaelcangucu 3 months ago

Hi Fabricio, can I use this as a Judge?

Let me put the scenario here:

I need a truth resolution mechanism, for example who won some sports match.

I input the sources, news , data, etc and the this agent you handle the judging process.

pisrael 3 months ago

What is the main difference in results of a pure LLM loop?

  • fabceolin 3 months ago

    Clean context for each iteration will make the LLM give your better results. Using LLM loop you will full the context faster degrading the LLM responses.

thalesac 3 months ago

can you elaborate more on the human in the loop? would be nice a more comprehensive example

  • thalesac 3 months ago

    also I didn't get the name, why edge agent? seems like this is an orchestrator, not edge. seems very useful tho

    • fabceolin 3 months ago

      The project started to be a Cyclic State Graph orchestrator, statically defined via YAML, leveraging Neurosymbolic validation (Prolog) to ensure deterministic transitions in edge environments. Langraph also it is, but python and the thread mechanism make not suitable for edge environments.