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

💌 Fathers' love for Kaia 💌

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.

mle_v030.mp4

Milestones

• 🚀 25 July 2024: Release the 0.3.0 with huge refactoring, many integrations, etc (v0.3.0)
• 🚀 11 July 2024: Release the 0.2.0 with multiple agents interaction (v0.2.0)
• 🚀 June 1st, 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 [email protected]: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

Roadmap

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

🔨 General Features

• Understand users' requirements to create an end-to-end AI project
• Suggest the SOTA data science solutions by using the web search
• Plan the ML engineering tasks with human interaction
• Execute the code on the local machine/cloud, debug and fix the errors
• Leverage the built-in functions to complete ML engineering tasks
• Interactive chat: A human-in-the-loop mode to help improve the existing ML projects
• Kaggle mode: to finish a Kaggle task without humans
• Summary and reflect the whole ML/AI pipeline
• Integration with Cloud data and testing and debugging platforms
• Local RAG support to make personal ML/AI coding assistant
• Function zoo: generate AI/ML functions and save them for future usage

⭐ More LLMs and Serving Tools

• Ollama LLama3
• OpenAI GPTs
• Anthropic Claude 3.5 Sonnet

💖 Better user experience

• CLI Application
• Web UI
• Discord

🧩 Functions and Integrations

• Local file system
• Local code exectutor
• Arxiv.org search
• Papers with Code search
• General keyword search
• Hugging Face
• SkyPilot cloud deployment
• Snowflake data
• AWS S3 data
• Databricks data catalog
• Wandb experiment monitoring
• MLflow management
• DBT data transform

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

If you are interested in contributing, please check the CONTRIBUTING.md file.

Support and Community

• Discord community. If you have any questions, please feel free to ask in the Discord community.
• Twitter. Follow us on Twitter to get the latest updates.

Star History

License

Check LICENSE file for more information.