If this is useful, a ❤️ helps others find it. Everything I keep looking up when building Tauri v2 apps — in one place. // Define #[tauri::command] fn greet(name: String) -> String { format!("Hello, {}!", name) } // With error handling #[tauri::command] fn read_file(path: String) -> Result { std::fs::read_to_string(path).map_err(|e| e.to_string()) } // Async #[tauri::command] async fn fet
Repo: https://github.com/richer-richard/socratic-council Stack: Tauri 2 (Rust + React/TypeScript), pnpm monorepo, Apache-2.0 Latest release: v2.0.0 If you ask one frontier model a hard question, you get a confident answer. If you ask sixteen, you get an argument. Socratic Council is a desktop app that runs a structured seminar between sixteen LLM agents drawn from eight providers — OpenAI, Anthr
All tests run on an 8-year-old MacBook Air. The default: Tauri commands When commands aren't enough: events Targeting specific windows The channel API for streaming data async fn stream_data(on_event: Channel) -> Result<(), AppError> { What I don't use The pattern I follow User action → invoke command → return result Three patterns. That's the whole IPC layer. If this was useful, a ❤️ helps more t
The Problem Most engineers deploy to Kubernetes by clicking buttons in a UI. I built Archnet — a fully automated Internal Developer Platform What is an Internal Developer Platform? An IDP is the infrastructure layer that sits between your code How code gets deployed How secrets are managed How the system monitors itself How failures get detected and fixed Most companies pay Humanitec or Backsta
All tests run on an 8-year-old MacBook Air. Most AI integration tutorials assume you're paying for API access. HiyokoLogcat is built entirely on Gemini's free tier — and designed so users bring their own free API key. Here's what's possible, what the limits are, and how to design around them. Gemini 2.5 Flash Preview: 15 requests per minute (RPM) 1,000,000 tokens per day 250 requests per day For a
We had ArgoCD running perfectly. Every deployment was reconciled from Git. Drift detection worked. Rollbacks were one-click. Our GitOps setup was clean. Developers still couldn't provision a staging environment without pinging the platform team. That gap — between "GitOps in place" and "developers can actually self-serve" — is where most platform engineering teams get stuck. GitOps solves a real p