Kaia: A Pair Agent for AI Engineer / Researchers

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Overview

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

:rocket: Kaggle Mode will help you to easily participate in Kaggle competitions, prepare submissions and get a good score.
:coffee: Baseline Mode can quickly build a baseline model for your AI project according to your requirements.
:fire: Advanced Mode (Coming Soon) is designed to utilize users' favorite MLOps tools, understand SOTA methods, and suggest optimizations for users' machine learning projects.

Milestones

:rocket: June 16th, 2024: Pre-release the Kaggle Mode (need to install from the source code)

:rocket: June 1st, 2024: Release the Baseline Mode (v0.1.0)

Get started

Installation

pip install mle-agent

Configuration

You must set up an LLM and choose tools before using the agent.

mle config

Usage (Baseline Mode)

Create a new project

mle new <project name>

A workspace with <project name> will be created where you execute the mle new command.

Start a project

mle start

[!NOTE]

Debugging on the cloud may incur high costs, please ensure you have enough budget.

You can start a project under any path, the code/data generated will be stored in the target workspace.

Project-related operations

mle project ls # show all the available projects
mle project delete <project name> # delete a given project
mle project switch # switch the current working project
mle project show # show the status of the current project

Roadmap

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

:hammer: Plan, Generate, Execute and Debug Code

- [x] An easy-to-use CLI interface - [x] Create/Select/Delete a project - [x] Understand users' requirements to suggest the file name, dataset, task, model arch, etc - [x] Generate a detailed coding plan - [x] Write baseline model code - [x] Execute the code on the local machine/cloud - [x] Debug the code and revise the code - [x] Googling the error message to debug the code - [ ] Data Augmentation - [ ] Hyperparameter tuning - [ ] Model evaluation

:star: More LLMs and Serving Tools

- [x] Ollama LLama 2/3 - [x] OpenAI GPT-3.5 - [x] OpenAI GPT-4 - [ ] Codellama - [ ] Codemitral - [ ] Anthropic Codex

:sparkling_heart: Better user experience

- [ ] Web UI (coming soon) - [ ] Discord

:jigsaw: Integrations

- [x] SkyPilot - [ ] Snowflake - [ ] Databricks - [x] Wandb - [ ] MLflow - [ ] DBT - [ ] Airflow

:globe_with_meridians: Search Enhancement

- [x] Google - [x] GitHub - [ ] HuggingFace - [ ] Paper with Code - [ ] Arxiv

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.

License

Check LICENSE file for more information.

MLSysOps / MLE-agent

readme