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News for “load”
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Moozonian News
news.ycombinator.com• Jul 4, 2026• 1 min read
I built a environment reloader for Windows ShellsHello Guys!So I built an environment/path reloader for Windows. I also compiled the project for Linux and macOS (even though there is no real purpose in using that tool on those). I wanted to share this little tool I made here on hacker news because I think some people could actually benefit from it or some people could be interested in checking the code? I don't know, anyway here I am sharing the tool XD.So why did I build it? Well I found myself very annoyed by the fact I had to restart my vsc and shells every single time I installed a new cli tool. I knew there was the "source ~./bashrc" command on linux and I was looking on google for something similar for windows. I couldn't find a tool at that time. I DO KNOW NOW that there is this tool called "refreshenv" from chocolatey but I made the project now so I just released it anyway, don't judge me for that please :
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Moozonian News
github.com• Jun 28, 2026• 1 min read
Show HN: LLMSim – a fast OpenAI LLM API simulator for load-testing LLM appsTesting LLM apps and agent frameworks against real APIs is expensive, rate-limited, slow, and non-reproducible. LLMSim is a Rust simulator for the OpenAI Chat Completions, OpenResponses and in future other protocols.LLMSim could be used in two forms, one is the server, with high concurrency for load/stress testing (~40k req/s with p99 ≈ 5ms on 4 vCPUs, scaling with cores); and second it embeds directly as a crate in your tests - no separate process, no network, deterministic.It focuses on traffic realism, not answer quality: configurable time-to-first-token and inter-token latency (normal distributions, per-model GPT/Claude/Gemini profiles), SSE streaming, real tiktoken token counting, and error injection (429/5xx/timeouts) for chaos testing.Usage is super simple,cargo install llmsim --features tuillmsim serve --port 8080 --host 0.0.0.0 --generator lorem --target-tokens 150 --tuiAnd then any LLM client `http://localhost:8080/openai/v1`MIT