npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2026 – Pkg Stats / Ryan Hefner

@pentoai/ml-ralph-ui

v0.2.0

Published

Autonomous ML engineering agent with TUI

Readme

@pentoai/ml-ralph-ui

npm version

An autonomous ML engineering agent with a terminal user interface (TUI).

ml-ralph helps you iterate on ML projects by automating the experiment loop: planning, execution, analysis, and learning extraction. You interact with it through a clean TUI that lets you create PRDs, monitor agent execution, and review accumulated knowledge.

Key Features

  • PRD-driven development: Define your ML project goals, constraints, and stories through conversational chat with Claude Code
  • Autonomous execution: Agent runs continuously through stories until stopped, making decisions based on evidence
  • Learning accumulation: Structured insights extracted from every iteration, searchable and actionable
  • Research integration: Agent researches approaches and documents findings
  • Training monitoring: Track long-running jobs with W&B integration

Architecture

ml-ralph is built as a TUI using Ink (React for terminals) with Bun as the runtime. It orchestrates Claude Code to perform actual ML engineering work.

┌─────────────────────────────────────────────────────────────┐
│                     ml-ralph TUI                            │
│  ┌─────────────────────┐  ┌──────────────────────────────┐  │
│  │     Planning        │  │         Monitor              │  │
│  │  ┌───────┬───────┐  │  │  ┌─────────┬──────────────┐  │  │
│  │  │  CC   │Learn- │  │  │  │ Agent   │ Experiments  │  │  │
│  │  │ Chat  │ings/  │  │  │  │ Output  │ + Metrics    │  │  │
│  │  │       │Research│  │  │  │         │              │  │  │
│  │  └───────┴───────┘  │  │  └─────────┴──────────────┘  │  │
│  └─────────────────────┘  └──────────────────────────────┘  │
└─────────────────────────────────────────────────────────────┘
                            │
                            ▼
                    ┌───────────────┐
                    │  Claude Code  │
                    └───────────────┘
                            │
                            ▼
                    ┌───────────────┐
                    │   Codebase    │
                    │   + W&B       │
                    └───────────────┘

Two Modes

Planning Mode

  • Chat with Claude Code to create/refine your PRD
  • View accumulated learnings from past iterations
  • Review research the agent has gathered
  • See your story backlog

Monitor Mode

  • Watch the agent execute stories in real-time
  • View experiment metrics and training curves
  • See current story and hypothesis
  • Control agent (start/stop)

Quick Start

# Run directly with bunx
bunx @pentoai/ml-ralph-ui

# Or install globally
bun install -g @pentoai/ml-ralph-ui
ml-ralph

Requirements

Documentation

Tech Stack

License

MIT