Cartai

<div align="center"> <h1 align="center">🕵️‍♀️ Cartai 🤖&mdash; The AI supervisor agent, for AI </h1> <h3>Crafting intelligent E2E supervision & documentation for trustworthy AI</h2>

<kbd><strong>👩‍💼 Agent-powered project intelligence, from PRD to production</strong></kbd> <br><br>

<a href="https://github.com/huggingface/smolagents/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/github/license/huggingface/smolagents.svg?color=blue"></a>

</div> <br>

cartai is a library that enables end-to-end traceability and lineage of your AI projects. PRDs, data lineage, training experiments, deployments, monitoring, and third-party vibe-coding platforms.

🔌 MCP Integrations

| Integration | Status | AI Governance Step | Key Features | Description | |------------|--------|-------------------|--------------|-------------| | 🏃 MLFlow | ✅ Active v0 | Model Training & Experimentation | • Experiment Tracking<br>• Model Registry<br>• Artifact Management | Comprehensive tracking of ML experiments, model versions, and metrics for reproducible AI development | | 🎲 dbt | ✅ Active v0 (Official) | Data Lineage & Feature Engineering | • Data Transformation<br>• Feature Pipeline Tracking<br>• SQL Model Management | End-to-end visibility into data transformations and feature engineering processes | | 📝 Notion | ✅ Active v0 (Official) | Project Documentation & Requirements | • PRD Management<br>• Documentation Sync<br>• Project Timeline Tracking | Seamless integration of project documentation, requirements, and AI governance documentation |

📂 Codebase Structure

WIP

⚙️ Installation

To get started with the Cartai project, follow these instructions to set up your environment:

1. Clone the repository:

   git clone https://www.github.com/ContrastoAI/cartai
   cd cartai
   

2. Ensure you have uv and pre-commit installed. You can check their installation with:

   make .uv
   make .pre-commit
   

3. Install all dependencies and set up your environment:

   make install-all
   

💻 Usage

You can run the project using the provided Makefile commands. For example, to generate the README documentation, you can use:

make run_readme

This command will execute the documentation generation process with the description "Crafting intelligent E2E documentation for trustworthy AI." and output it to README_new.md.

Other Makefile Commands

• Format code:

  make format
  

• Lint code:

  make lint
  

• Run tests:

  make test
  

• Run pre-commit hooks:

  make pre-commit
  

🚀 Deployment

To deploy the project, follow the standard deployment procedures for your environment. Ensure all dependencies are installed, and run the necessary commands as needed.

🤝 Contributing

We welcome contributions! Here's how you can contribute:

1. Fork the repository 🍴
2. Create your feature branch:

   git checkout -b feature/YourFeature
   

3. Commit your changes:

   git commit -m 'Add YourFeature'
   

4. Push to the branch:

   git push origin feature/YourFeature
   

5. Open a pull request 📬

Please follow the coding guidelines and check the Makefile or contributing docs if available.