MLE-Agent: Your intelligent companion for seamless AI engineering and research.

:love_letter: Fathers' love for Kaia :love_letter:

📚 Docs | 🐞 Report Issues | 👋 Join us on Discord

Overview

MLE-Agent is designed as a pairing LLM agent for machine learning engineers and researchers. It is featured by:

• 🤖 Autonomous Baseline Creation: Automatically builds ML/AI baselines.
• 🔍 Arxiv and Papers with Code Integration: Access best practices and state-of-the-art methods.
• 🐛 Smart Debugging: Ensures high-quality code through automatic debugger-coder interactions.
• 📂 File System Integration: Organizes your project structure efficiently.
• 🧰 Comprehensive Tools Integration: Includes AI/ML functions and MLOps tools for a seamless workflow.
• ☕ Interactive CLI Chat: Enhances your projects with an easy-to-use chat interface.
• 📊 Weekly Report: Automatically generates detailed summaries of your weekly works.

https://github.com/user-attachments/assets/dac7be90-c662-4d0d-8d3a-2bc4df9cffb9

Milestones

• 🚀 09/10/2024: Release the 0.4.0 with new CLIs like MLE report, MLE kaggle, MLE integration and many new models like Mistral.
• 🚀 07/25/2024: Release the 0.3.0 with huge refactoring, many integrations, etc (v0.3.0)
• 🚀 07/11/2024: Release the 0.2.0 with multiple agents interaction (v0.2.0)
• 👨‍🍼 07/03/2024: Kaia is born
• 🚀 06/01/2024: Release the first rule-based version of MLE agent (v0.1.0)

Get started

Installation

pip install mle-agent -U
# or from source
git clone git@github.com:MLSysOps/MLE-agent.git
pip install -e .

Usage

mle new <project name>

And a project directory will be created under the current path, you need to start the project under the project directory.

cd <project name>
mle start

You can also start an interactive chat in the terminal under the project directory:

mle chat

Use cases

📊 Generate Work Report

MLE agent can help you summarize your weekly report, including development progress, communication notes, and to-do lists.

cd <project name>
mle report

Then, you can visit http://localhost:3000/ to generate your report locally.

🏆 Start with Kaggle Competition

MLE agent can participate in Kaggle competitions and finish coding and debugging from data preparation to model training independently. For more details, see the MLE-Agent Tutorials.

cd <project name>
mle kaggle

Roadmap

The following is a list of the tasks we plan to do, welcome to propose something new!

Contributing

We welcome contributions from the community. We are looking for contributors to help us with the following tasks:

• Benchmark and Evaluate the agent
• Add more features to the agent
• Improve the documentation
• Write tests

Please check the CONTRIBUTING.md file if you want to contribute.

Support and Community

• Discord community. If you have any questions, please ask in the Discord community.

Star History

License

Check MIT License file for more information.