Project Explanation

Runtime.MiRust.com is a project website for a custom local AI runtime stack. The active implementation target is TinyRustLM, a browser-local small language model application built from static HTML, custom CSS, handwritten JavaScript, and no-crate Rust compiled to WebAssembly.

The simplest accurate description

TinyRustLM is a small, auditable runtime that proves a local model can be loaded, validated, tokenized, run, adapted, diagnosed, and tested inside the browser without depending on a third-party front-end framework, an external inference API, or a large machine-learning runtime.

What the project is not

The current source should not be marketed as a general assistant product. It should not claim trained assistant quality, full GGUF import, Mini Browser orchestration, hosted model execution, remote inference, analytics, telemetry, or plugin-driven automation.

The site should instead describe the real thing that exists:

• a custom model file route;
• local deterministic smoke models;
• quantized runtime paths;
• adapter package validation;
• receipts and manifests;
• browser route proofs;
• a model-breeding research pipeline;
• strict boundaries around what has and has not been proven.

The project’s engineering posture

The project is intentionally small at the trusted boundary. It favors direct Rust modules, explicit file formats, deterministic test artifacts, and visible browser diagnostics over framework-level magic.

That is why the website uses the same public posture:

• no Bootstrap;
• no jQuery;
• no external CSS framework;
• no page builder dependency;
• no client-side rendering requirement for core content;
• no hidden bot-only copy;
• no “magic AI” language where evidence should be shown.

How to read the site

The site is organized as a proof map:

1. Architecture explains the parts.
2. Browser Runtime explains the runtime/app boundary.
3. Model Format explains .slm.
4. Adapters & Assembly explains ADP1, ASP1, ALR1, selector registries, module plans, and assembly receipts.
5. Model Breeding explains the offline candidate lineage and promotion pipeline.
6. Proof & Testing records what support claims should be backed by tests or smoke evidence.
7. Roadmap & Boundaries keeps future ambition separate from current support.

Public positioning

Use the phrase “browser-local Rust/WASM SLM runtime” before broader phrases like “AI system.” This keeps the project precise, searchable, and agent-readable.

Runtime.MiRust.com is a constructive local-model craft site. It should make the engineering understandable without diluting the boundaries.