Introduction

This page gives background and terminology.

If you are new to AGILab, do not start here. Start with Newcomer Guide and Quick-Start.

What AGILab is

AGILab is a framework and web UI for running Python data, ML, and RL projects through one visible workflow.

It has two main user interfaces:

  • agi-core: the Python API you can call directly from code or notebooks

  • agilab: the web UI that helps select projects, install them, run them, and inspect outputs

Shared components include:

  • agi-env for environment setup

  • agi-node for worker/runtime packaging

  • agi-cluster for local and distributed execution

Historical note

AGILab started as a playground around agi-core.

That is still visible in the product structure today:

  • you can use the web UI for an app-oriented workflow

  • or you can use agi-core directly when you only need the execution layer

Why the project is built this way

The design goal is not to replace every MLOps or orchestration tool. The design goal is to make experimentation easier to run, replay, and inspect before a team commits to heavier platform choices.

The technical choices are driven by three practical goals:

  • Portability: keep projects runnable across local machines and SSH-accessed workers without full VM or container infrastructure as a starting point

  • Simplicity: keep environment setup, execution, and analysis visible in one workflow

  • Performance: allow different execution modes such as pure Python, Cython, and local or distributed runs

Main dependencies

AGILab relies on a small set of core technologies:

  • uv for Python environment management

  • Streamlit for the web UI

  • Dask for distributed execution support

  • asyncssh for SSH-based remote execution

  • Cython for optional compiled execution paths

Optional helpers include OpenAI-compatible models and local assistants such as Ollama and GPT-OSS when configured.

Note

Windows support is still catching up. Some local-assistant features remain partial while that work continues.