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AI-powered autonomous ML experimentation companion

Project description

ResearchPad

AI-powered autonomous ML experimentation companion.

ResearchPad provides a web UI and cursor commands for running iterative ML experiment loops. It tracks experiments, manages research artifacts, performs debug analysis, and surfaces insights -- all driven by AI coding agents.

Quick Start

pip install researchpad
researchpad init
researchpad runserver
# Open http://localhost:8888

Features

  • Dashboard -- Real-time experiment progress, summary cards, activity feed
  • Experiments -- Full history with sorting, filtering, git diffs, metric comparison
  • Research -- Structured artifacts from papers, Kaggle, blogs, and GitHub
  • Debug -- Deep outlier and error analysis with targeted experiment prompts
  • Insights -- Theme clustering, learnings journal, diminishing returns detection
  • Dark/Light Mode -- System-aware with manual toggle
  • Live Updates -- WebSocket-based real-time refresh
  • Keyboard Shortcuts -- Press ? for the full list

Cursor Commands

Command Description
/experiment Run autonomous experiment loops to improve your pipeline
/research Research a topic and produce structured artifacts
/debug Analyze model failures and outliers
/explain Explain a specific experiment in detail

Requirements

  • Python >= 3.10
  • Node.js >= 18 (for the UI server)

Documentation

Full documentation: https://researchpad.github.io/researchpad

Development

git clone https://github.com/researchpad/researchpad.git
cd researchpad
make install
make dev

License

Apache 2.0 -- see LICENSE for details.

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