# NanoResearch

An end-to-end autonomous research agent that carries a research idea through literature search, experiment design, real GPU training, result analysis, and a complete LaTeX paper with figures drawn from actual experiment data.

NanoResearch is an autonomous research pipeline that runs actual computational experiments rather than only generating code: it submits training jobs to a GPU cluster (local or Slurm), collects the real results, and produces a full LaTeX paper whose figures and tables come from those runs.

The pipeline moves through stages: ideation (literature search across OpenAlex and Semantic Scholar, idea generation), planning (turning an idea into an experiment blueprint with datasets, baselines, metrics, and ablations), setup, coding, execution, analysis of training logs, figure generation, writing, and review. Work can resume from any stage after an interruption.

It provides both a full-screen terminal UI and a plain streaming-log CLI, integrates with Claude Code, and includes a Feishu bot entry point.

Website: https://github.com/OpenRaiser/NanoResearch