NanoResearch

NanoResearch

NanoResearch: An end-to-end autonomous AI research engine that automates the entire process from research ideas to a complete paper.

Agent SkillDevOpen source
Type
Agent Skill
Open source
Yes
GitHub Stars
★ 1.5k
Source
skill-github

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

Research prototype validationAutonomous experimentsBulk benchmark generationPaper draft assistance

Setup

Requires: Python 3.10+API KeyGPU 环境
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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