NanoResearch
NanoResearch: An end-to-end autonomous AI research engine that automates the entire process from research ideas to a complete paper.
- Type
- Agent Skill
- Open source
- Yes
- GitHub Stars
- ★ 1.5k
- Source
- skill-github
- Repository
- github.com/OpenRaiser/NanoResearch
Overview
NanoResearch is an end-to-end autonomous AI research engine capable of generating complete experimental code from research ideas, executing training on GPU clusters, collecting real experimental results, generating figures for papers, and ultimately producing a full LaTeX paper supported by empirical data. It automates the entire workflow including literature retrieval, experiment design, code generation, GPU-based training execution, result analysis, figure generation, and paper writing. Ideal for researchers to rapidly validate prototypes, generate benchmarks in bulk, and assist in drafting initial paper versions.
Capabilities
- ▪Automatically retrieve literature
- ▪Generate experimental plans
- ▪Generate executable experimental code
- ▪Local/SLURM automated training
- ▪Parse real training logs
- ▪Generate paper figures based on real data
Use cases
Setup
pip install nanoresearch
This information was compiled by AI from public sources and may contain inaccuracies — please refer to the source.
FAQ
Which literature databases does NanoResearch support?
Supports OpenAlex and Semantic Scholar.
Is GPU environment configuration required?
Yes, local or SLURM GPU environment needs to be configured.
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