Why Rust?

Oxyde is built from the ground up in Rust — and that decision is central to its performance, safety, and long-term extensibility. Here’s why we chose Rust as the foundation for emotionally intelligent

🧠 1. Performance for Real-Time Games

  • Inference latency, memory recall, and emotion updates must happen within milliseconds

  • Rust’s zero-cost abstractions and control over memory let us build async pipelines that are both fast and predictable

  • Avoids GC pauses or runtime bottlenecks common in Python or JS

Real-time game logic can’t afford surprises. Rust delivers tight control.

🧯 2. Safety Without Sacrificing Speed

  • Borrow checker ensures no memory leaks or race conditions

  • Emotion state, memory stacks, and LLM streams are protected by design

  • Enables multi-threaded agent execution without crashing your game engine

🧩 3. Native Interop With Game Engines

  • Rust compiles to shared libraries (.dll, .so, .dylib) easily

  • Used directly by:

    • Unity (via FFI and DllImport)

    • Unreal Engine (via C++ bindings)

    • WebAssembly for browser runtimes

🔧 4. Extensibility With Strong Typing

  • trait system allows plug-and-play LLM providers and memory backends

  • Configs are deserialized safely with full schema enforcement

  • Makes the codebase maintainable and modular as the project grows

🌍 5. WebAssembly-Ready

  • Oxyde runs natively in the browser with wasm32-unknown-unknown

  • Perfect for live demos, online sandboxing, or visual novels with agent NPCs

🧪 Why Not Python?

We love Python for LLM prototyping — but:

Requirement
Python
Rust (Oxyde)

Real-time game loop

❌ GC-lag prone

✅ Frame-perfect

Embedded in engines

❌ Tricky bindings

✅ Easy FFI

Type safety

❌ Dynamic typing

✅ Strong static types

Multi-agent perf

❌ Slow threading

✅ Native threading

🛠️ Rust for AI Inference?

Yes — Oxyde wraps external LLMs via HTTP, but local model support (GGUF, Whisper, etc.) runs beautifully in Rust too, especially with libraries like tokenizers, llama-rs, or llm.

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