piSTAR Lab is a modular platform built to make AI experimentation accessible and fun. (pistar.ai)

piSTAR Lab

Last update: Aug 1, 2022

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Overview

piSTAR Lab

WARNING: This is an early release.

Overview

piSTAR Lab is a modular deep reinforcement learning platform built to make AI experimentation accessible and fun.

Documentation https://pistarlab.readthedocs.io

Features

Web UI
Extension System for adding new agents, environments or tasks types
Python API, anthing you can do in the UI, you can do in Python as well
Run agents in single and multi player environments
Experiment tracking
Uses Ray Project (https://ray.io/) under the hood for distributed processing
Includes piSTAR Landia a hackable Multi Agent Envrionment
More to come

Known Issues/Limitations

Cluster mode is under development and not recommended at this time
Running remotely requires SSH tunneling. All services must be running on localhost
Mac not tested

UI Screenshots

Quick Start

More detailed documentation is available at https://pistarlab.readthedocs.io

Requirements

Ubuntu suggested but also tested on Windows 10. We suggest using Docker for other setups.
Python 3.7 or 3.8 (Conda is recommended)
- Miniconda
- Anaconda
FFMPEG (Optional)
- Required for episode recordings
- Windows install instructions
Xvfb (Optional, Ubuntu Only)
- Helps some environments run without opening a window.
- Useful when running piSTAR Lab remotely

Installation

For non-standard installations see: https://pistarlab.readthedocs.io/en/latest/installation.html

Create and Activate Conda Virtual Environment

conda create -n pistarlab python=3.7
conda activate pistarlab
conda install pip

Install with pip

pip install https://github.com/pistarlab/pistarlab/archive/refs/heads/main.zip#egg=pistarlab[all]

Usage

To launch piSTAR Lab UI, run:

pistarlab_launcher

Open browser to: http://localhost:7777

Contributing

We are still in an early phase of this release but if you are interested in contributing to piSTAR Lab, please reach out.

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Comments

Create portable version for each platform
Though installation via conda and pip or docker are fine for many, some users may not be familiar with these tools. Ideally, we would have installers for each supported platform.

Some tools to look into:

pyinstaller

https://conda.github.io/conda-pack/
opened by bkusenda 0
[Feature Request] Add support for reading Tensorboard data
Request: Add support for reading Tensorboard data

Libraries such as Stable Baselines use Tensorboard for logging and provide no mechanism for external logging. It would be helpful have a way to display this data logged to Tensorboard.

Options:

Inject a replacement class to use at runtime instead of Tensorboard logging

Read from Tensorboard files. Reference: https://github.com/Spenhouet/tensorboard-aggregator/blob/master/aggregator.py

(Recommended) Both 1 and 2 and use interface as default logger. Pros: can use Tensorboard to view all pistarlab data, can add additional hooks for realtime notifications.

enhancement
opened by bkusenda 0