LightAutoDS-Tab

LightAutoDS-Tab, a multi-AutoML agentic system for tasks with tabular data, which combines an LLM-based code generation with several AutoML tools.

✨ Demo

Watch the Video

🧑‍💻 User interface

The interface includes two main panels:

1. The right panel provides detailed technical insights into each step of the ML pipeline construction, offering transparency for expert users.
2. The left panel presents a simplified, non-technical summary of the process, making it easy for non-experts to follow along and understand the results

🚀 Quick Start

Step 1: Clone the repository

git clone https://github.com/sb-ai-lab/LADS.git
cd LADS

Step 2: Create conda environment

conda env create -f environment.yml
conda activate LightAutoDS

Step 3. Set up environment variables

You need to create a .env file in the root directory of the project.

cp .env_example .env

You will need to fill in the required API keys and other environment variables in the .env file.

You can also change some parameters in config.yml.

Step 4: Run the application

streamlit run app.py

Your application will be hosted on http://localhost:8501 by default.

📊 Result

We evaluated our framework on eight Kaggle ML datasets and compared it with two state-of-the-art open-source solutions: AutoKaggle and AIDE.

To ensure consistency across competitions, we use the Normalized Performance Score (NPS). This score standardizes the results, with a higher value indicating better performance.

📜 License

Distributed under the BSD 3-Clause License. See LICENSE for more information.