Aim

Aim

Aim is a self-hosted, open-source experiment tracking tool. It logs training metadata — metrics, hyperparameters, text, images, audio, video — and provides a powerful web UI for exploring thousands of runs simultaneously. Unlike hosted solutions, all data stays on your infrastructure.

Key Features

• Local-first: all tracking data stays in a local .aim repo — no account needed
• Exploratory UI: query runs with a SQL-like expression language and visualize anything
• Multi-modal logging: metrics, images, audio, video, text, distributions, figures
• Remote tracking server: centralize tracking for a team without SaaS
• Deep integrations: PyTorch Lightning, Keras, XGBoost, Optuna, Hugging Face, Comet
• Python SDK for fine-grained control

Quick Start

from aim import Run

run = Run()
run["hparams"] = {"lr": 0.001, "batch_size": 32}

for step in range(100):
    run.track(loss, name="loss", step=step)
    run.track(acc, name="accuracy", step=step)

# Launch the UI
aim up

Install via ai-supply

npx ai-supply add aim-training-metadata-ui

Curated mirror of the open-source Aim (Apache-2.0). Get it from the source.