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mbodied agents initial commit
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nqyy committed May 30, 2024
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47 changes: 47 additions & 0 deletions .github/workflows/macos.yml
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name: "MacOS | Python 3.12|3.11|3.10"

on:
push:
branches: [main]
pull_request:
branches: [main]
workflow_dispatch:

permissions:
contents: read
pull-requests: write

jobs:
test:
name: Python ${{ matrix.python-version }}
runs-on: macos-latest
strategy:
matrix:
python-version: ["3.12", "3.11", "3.10"]

steps:
- name: Checkout code
uses: actions/checkout@v3

- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v3
with:
python-version: ${{ matrix.python-version }}

- name: Run install script
run: |
chmod +x ./install.bash
./install.bash
- name: Cache packages
uses: actions/cache@v3
env:
cache-name: cache-packages
with:
path: ~/Library/Caches/Homebrew
key: ${{ runner.os }}-${{ env.cache-name }}-${{ hashFiles('install.bash') }}
restore-keys: |
${{ runner.os }}-${{ env.cache-name }}-
- name: Run tests
run: |
hatch run test
61 changes: 61 additions & 0 deletions .github/workflows/ubuntu.yml
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name: "Ubuntu"

on:
push:
branches: [main]
pull_request:
branches: [main]
workflow_dispatch:

permissions:
contents: write
pull-requests: write

jobs:
ubuntu:
name: ${{ matrix.os }}
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-20.04, ubuntu-latest]

steps:
- name: Checkout
uses: actions/checkout@v3

- name: Set up Python 3.11
uses: actions/setup-python@v3
with:
python-version: 3.11

- name: Run install script
run: |
chmod +x ./install.bash
./install.bash
- name: Cache packages
uses: actions/cache@v3
env:
cache-name: cache-packages
with:
path: ~/.local/bin ~/.local/lib .mbodied/envs/mbodied
key: ${{ runner.os }}-${{ env.cache-name }}-${{ hashFiles('install.bash') }}
restore-keys: |
${{ runner.os }}-${{ env.cache-name }}-
- name: Check disk usage
run: df -h

- name: Clean up before running tests
run: |
# Add commands to clean up unnecessary files
sudo apt-get clean
sudo rm -rf /usr/share/dotnet /etc/mysql /etc/php /etc/apt/sources.list.d
# Add more cleanup commands as needed
- name: Check disk usage after cleanup
run: df -h

- name: Run tests
run: |
hatch run test
191 changes: 191 additions & 0 deletions .gitignore
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
/docs/generated
# C extensions
*.so

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Translations
*.mo
*.pot

# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal

# Flask stuff:
instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
.pybuilder/
target/

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version

# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock

# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock

# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml

# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/

# Celery stuff
celerybeat-schedule
celerybeat.pid

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject
.spyproject

# Rope project settings
.ropeproject

# mkdocs documentation
/site

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# Pyre type checker
.pyre/

# pytype static type analyzer
.pytype/
.logfire
.pytest*
.*_cache

# Cython debug symbols
cython_debug/

# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
.idea/

# Additionanl files
*.hdf5
*.ckpt
*.jsonl
images/
*.zip
dataset_cache/
*frames
*.mp4
*.pt
*.h5
*.gpt_runner
.DS_Store
outputs/*
**/*/outs/**/*
outs/
src/mbodied/outs
.command_history*
wandb/
# Additional files
*.hdf5outputs/
.log
.jpeg
.jpg
.tmp_listen*
.tmp_speak*
saved_datasets/
38 changes: 38 additions & 0 deletions CONTRIBUTING.md
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# Contributing

## Development Practices

### Git Workflow

To ensure a clean and linear project history, we enforce specific Git practices:

### Commit Messages

- Always use gitlens (preferred), easycode, or write good commit messages.


### Pulling Changes

Always try to pull with `--ff-only` or `--rebase` when pulling changes from the `main` branch:

```bash
git pull --rebase
```

We recommend setting up your Git configuration as:

```bash
git config --global pull.ff only

git config --global pull.rebase true

```

### Style Guide

1. Lint with Ruff
2. Place tests in a dedicated tests/ directory, with each test file named with a test_ prefix.
3. Prefix all test function names with test_ to enable Pytest to automatically identify and execute them.
4. Use Google-style docstrings to document all public classes, methods, functions, and modules.
5. Include an example usage in the docstring for each important class, method, and function.
6. Pydantic models should be tested for json serialization, deserialization, and saving to h5 files.
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