Karpathy

Karpathy

**Note:** For more advanced capabilities and end-to-end machine learning, visit [www.k-dense.ai](https://www.k-dense.ai).

[](https://opensource.org/licenses/MIT) [](https://github.com/K-Dense-AI/karpathy/pulls)

An agentic Machine Learning Engineer that trains state-of-the-art ML models using Claude Code SDK and Google ADK. This is a very simple implemenation demonstraing the power of Claude Scientific Skills for machine learning.

Prerequisites

• Python 3.13 or higher
• uv package manager
• Claude Code installed and authenticated (see installation guide)

Setup

1. Clone the Repository

git clone https://github.com/K-Dense-AI/karpathy.git
cd karpathy

2. Install Dependencies

Install dependencies using `uv`:

uv sync

3. Environment Variables

Create a `.env` file in the `karpathy` directory with your API keys:

OPENROUTER_API_KEY=your_openrouter_api_key_here
AGENT_MODEL=your_model_name_here

The `OPENROUTER_API_KEY` is required for the agent to function properly.

This is the same environment variable that will be copied to the `sandbox` directory so the agents can use any API keys you provide here.

Quick Start

Run the startup script to set up the sandbox and start the ADK web interface:

python start.py

This automatically:

1. Creates a sandbox directory with scientific skills from Claude Scientific Skills
2. Sets up a Python virtual environment with ML packages (PyTorch, transformers, scikit-learn, etc.)
3. Copies your .env file to the sandbox
4. Starts the ADK web interface
5. Navigate to http://localhost:8000 in your browser
6. Select karpathy in the top left under 'Select an agent'
7. All outputs will be in the sandbox directory so continue to m