Show HN: Onetone – A full-stack framework with custom C interpreter

github.com

2 points by tactics6655 11 hours ago

Hey HN,

I've been working on Onetone Framework for the past few years and finally releasing it as open source (AGPL 3.0).

*What is it?*

Onetone is an ambitious full-stack development framework that includes:

- Custom C interpreter with its own scripting language (.otc files)

- 27,000+ line OpenGL 3D graphics engine with PBR materials, skeletal animation, physics, and particle systems

- PHP web framework with MVC architecture

- Python utilities and tooling

- 716,000+ lines of code across 17 programming languages

*The scripting language features:*

- Classes, inheritance, generators, async/await

- Records, enums, pattern matching

- Built-in collections (ArrayList, HashMap, HashSet, TreeMap, etc.)

- Template strings, destructuring, spread operators

- Native bindings for OpenGL, Windows API, audio, networking

*Why build this?*

I run a game localization and needed a unified toolset for:

- Visual novel engines

- Translation management tools

- Quick prototyping with native performance

Instead of gluing together multiple languages and frameworks, I built one cohesive system.

*Current status:*

- Windows-focused (uses WinAPI extensively)

- Some features still in development (generators, full async support)

- Documentation is a work in progress

GitHub: https://github.com/onetoneframework/framework

Would love feedback from the community.

*Roadmap & Vision*

My goal is to evolve Onetone's scripting language to reach Python-level usability and ecosystem richness. I want developers to be able to pick it up as easily as Python while retaining native performance.

*A note on development process*

I want to be transparent: this project was developed with significant assistance from Claude (Anthropic's LLM). The codebase is a mix of hand-written code and LLM-generated code, with me directing the architecture, debugging, and integration.

I found this workflow surprisingly effective for a project of this scale – the LLM helped with boilerplate, documentation, and exploring implementation approaches, while I focused on design decisions and fixing the subtle bugs that AI still struggles with.

Whether you see this as "cheating" or the future of development, I think it's worth discussing. The 700K+ lines wouldn't exist without this collaboration, and I'm curious how others feel about AI-assisted open source projects.

There were many errors and strange bits of code produced by the LLM, and I spent a lot of time tracking down memory leaks; in fact, there isn’t a single piece of LLM-generated code that I didn’t end up modifying. I still think "vibe coding" has a number of issues.