{"repo":"pentoai/ml-ralph","free":true,"listed":false,"github":"https://github.com/pentoai/ml-ralph","clone":"git clone https://github.com/pentoai/ml-ralph.git","description":"Autonomous ML agent for running experiments using Claude.","language":"TypeScript","stars":38,"topics":["agents","aicoding","claude-code","codex","python","ralph","wandb","machine-learning"],"license":null,"category":"machine-learning","readme_excerpt":"ml-ralph An autonomous ML engineering agent with a terminal user interface. ml-ralph automates the experiment loop — planning, execution, analysis, and learning extraction — so you can iterate on ML projects faster. You define your goals through a PRD. The agent works through stories autonomously, runs experiments, tracks metrics, and accumulates structured learnings across iterations. Getting started That's it. Run it inside any ML project directory and the TUI will launch in tmux. Requirements - Bun v1.0+ - tmux ( brew install tmux ) - Claude Code CLI, installed and authenticated The cognitive framework ml-ralph operates as a paranoid scientist. Its core assumption: results are probably misleading, data is probably corrupted, and conclusions should be broken before they're trusted. It allocates roughly 70% of effort to understanding and verification, 20% to strategy, and 10% to execution. The agent works through a 4-phase cognitive cycle: Understand — Verify data integrity (row counts, label distributions, sample inspection). Run exploratory analysis. Research prior art. Build a mental model and explicitly list all assumptions. Nothing happens until this is done. Strategize — Generate 3–5 competing hypotheses. For each: what's expected, why, and what will be learned. Think 5–6 steps ahead. Pick the path with the best learning-to-effort ratio. Run the smallest experiment that tests the hypothesis. Execute — Run the experiment. Log metrics and observations as work happens, no","default_branch":null,"files":null,"tree":[],"storefront":"/r/pentoai","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/pentoai/ml-ralph/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."}