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.