Developer Tool / AI Research Toolkit
A Python CLI and research toolkit for simulating AI training math before model training. It estimates memory, training time, token budget, config risks, benchmark speed, and reliability, with optional native Rust and C backends.
The page shows a concrete AI-adjacent developer tool with a clear purpose, runnable commands, and implementation details. The README explains what HoprLabs does, how to install and use it, and what outputs it provides, which is enough for a useful public listing.
The snapshot does not show real outputs, screenshots, benchmark results, or documentation beyond the quick-start commands, so a visitor cannot judge accuracy, maturity, or how well the estimates match real training setups.
Last evaluated 66 days ago. Current rank #1504. Up 2 spots in the rankings.
A Rust Blu-ray disc analyzer that reimplements BDInfo for BDMV folders and ISO images, with CLI, desktop, and browser/WASM front ends.
WebLLM is a high-performance in-browser LLM inference engine that runs locally in the browser with WebGPU acceleration. It exposes an OpenAI-compatible API, supports streaming and JSON mode, and includes examples for building chat apps and browser extensions.
Molt is an open protocol for letting an AI agent make bounded purchases through disposable, single-use payment credentials. The repo includes a clear quickstart, MCP integration, a threat model, and a working test-mode demo.
Self-hosted observability and control plane for production and coding AI agents, with live timelines, fleet-wide feeds, token budgets, MCP allow/block rules, and support for Claude Code plus a Python sensor.
