{"repo":"ProjectDXAI/labrat","free":true,"listed":false,"github":"https://github.com/ProjectDXAI/labrat","clone":"git clone https://github.com/ProjectDXAI/labrat.git","description":"Autonomous multi-branch research lab. Branches compete for compute budget. The system converges on what works.","language":"Python","stars":241,"topics":["ai-agents","autonomous-research","claude-code","experiment-management","multi-agent","research-automation","market-allocation"],"license":"MIT","category":"ai-agents","readme_excerpt":"labrat English 简体中文 labrat is a local-first runtime that puts Claude Code or Codex on a real research problem with a scoreboard and enough structure to run for hours. Population search, not single-thread: families of ideas compete for compute budget, and the ones that produce real signal earn more room to keep going. Live example run: the baseline still leads on the main selection metric, while classifier search has already won two decisive held-out challenges and earned extra funding. labrat treats Claude Code and Codex as peer operator interfaces. Stronger reasoning models still help most on synthesis, audit, and consolidation, but the runtime contract and file layout stay the same across both. Jump to → Run it in 5 minutes · Start from a profile · Create your own lab · Why it exists In plain English: - you define a problem and a baseline - the agent explores multiple families of ideas - the runtime keeps the queue moving - the evaluator scores results consistently - families gain real status by winning hard held-out challenges, not just by overfitting the local hill-climb Why it exists - Async population search : no global cycle barrier; workers keep evaluating descendants as soon as slots free up. - Funding over families : credits are minted by stable, reproducible progress and spent on new descendants. - Consistent external evaluation : workers produce artifacts, not authoritative verdicts. - Supervisor + worker model : the agent supervises the runtime, while probe / mut","default_branch":null,"files":null,"tree":[],"storefront":"/r/ProjectDXAI","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ProjectDXAI/labrat/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}