ray vs ml-agents
ray and ml-agents share 4 technologies: h5py, gymnasium, torch, and pillow. Both are written in Python.
What they share and what sets them apart
ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Python44.3kRead on November 10, 2026, at commit c99c603What is ray built with?Only in ray
- FastAPI
- aimrecords
- aimrocks
- amqp
- array-record
- arro3-core
- async-lru
- azure-common
- azure-datalake-store
- azure-storage-blob
confluent-kafka
- delta-kernel-rust-sharing-wrapper
- diskcache
expiringdict
- feather-format
- gitdb
google-cloud-core
- huey
kombu
- partd
pickleshare
- py-partiql-parser
- pylance
- pymongo
- s3torchconnectorclient
- s3transfer
taskiq
tensorboard-data-server
- zict
pyarrow
mcap
- aioboto3
- MongoDB
- Redis
- adlfs
pyiceberg
- smart-open
- pymysql
clickhouse-connect
daft
deltalake
- gcsfs
lance-namespace
- obstore
- Celery
delta-sharing
- fastavro
hudi
- pyzmq
- s3fs
- s3torchconnector
- taskiq-redis
webdataset
Google- Hugging Face
- Google Cloud Storage
- Kafka
- Databricks
- adagio
- asgiref
- Flask
- flask-cors
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
pygame
pymars
werkzeug
- Ray
starlette
- AIOHTTP
pyspark
- Lightning
raydp
- anyio
tornado
uvicorn
- React
react-router-dom
- accessible-pygments
- alabaster
- cycler
fonttools
jupyterlab-pygments
pydata-sphinx-theme
- soupsieve
sphinx-design
- tinycss2
- aim-ui
- alive-progress
bokeh
contourpy
- glfw
halo
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
- Plotly
prompt-toolkit
pyglet
pyopengl
- spinners
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- ipywidgets
matplotlib
- Rich
- pydot
- alembic
peewee
sqlglot
- SQLAlchemy
- adal
- argon2-cffi
- argon2-cffi-bindings
- azure-identity
- flask-basicauth
- gcs-oauth2-boto-plugin
google-auth-oauthlib
- google-oauth
- google-reauth
- id
itsdangerous
joserfc
- jwcrypto
- keyring
- msal
- msal-extensions
- oauth2client
oauthlib
- pyjwt
- pyu2f
requests-oauthlib
- cryptography
google-auth-httplib2
- albucore
- autograd
ax-platform
- bayesian-optimization
- bitsandbytes
botorch
- cma
cmdstanpy
- crcmod
cupy-cuda100
cupy-cuda12x
cupy-cuda13x
- einops
- fairscale
- gpytorch
gradio-client
- gym
jaxlib
- labmaze
- LangChain
- lightning-utilities
- linear-operator
- llvmlite
lm-eval
- minigrid
- ml-dtypes
- mlflow-skinny
- moocore
mosaicml
nltk
- ONNX
onnx-ir
- onnxruntime
onnxscript
openai-whisper
- opt-einsum
optax
- orbax-checkpoint
peft
prophet
pymoo
pyro-ppl
- pytorch-ranger
rouge-score
- sacrebleu
safetensors
scikit-image
- sentencepiece
skops
stanio
statsforecast
- tensorflow-estimator
tf-keras
- tiktoken
timm
tokenizers
- torch-geometric
torchtext
- triton
- transformers
- TensorFlow
jax
torchvision
- xgboost
lightgbm
- scikit-learn
- MLflow
- tensorflow-metadata
accelerate
- datasets
- pytorch-lightning
- comet-ml
- dm-env
evaluate
flax
- Keras
- torchmetrics
- aim
albumentations
ale-py
configspace
deepspeed
diffusers
- dm-control
- hpbandster
- hyperopt
- nevergrad
- open-spiel
- Optuna
pettingzoo
- supersuit
tensordict
tensorflow-datasets
tensorflow-probability
torchaudio
- bleach
- defusedxml
et-xmlfile
imageio
imageio-ffmpeg
- imagesize
- jsonlines
- linkify-it-py
lxml
- mako
- markdown
markdown-it-py
markupsafe
- mdit-py-plugins
- mdurl
mistune
- moviepy
myst-parser
- nbconvert
- nh3
- openpyxl
- pandocfilters
- readme-renderer
ruamel-yaml
ruamel-yaml-clib
- strictyaml
- tinyscaler
webencodings
- xlrd
- xmltodict
- docutils
- jinja2
- beautifulsoup4
av
- decord
jupytext
- nbformat
- torchcodec
- annotated-types
- fastjsonschema
- fqdn
- jsonschema-path
- jsonschema-specifications
- openapi-spec-validator
- pathvalidate
- pydantic-core
- referencing
- rfc3339-validator
- rfc3986
- rfc3986-validator
- validators
- Pydantic
- jsonschema
- openapi-schema-validator
- aiobotocore
- applicationinsights
- aws-sam-translator
aws-xray-sdk
- azure-cli-core
- azure-cli-telemetry
- azure-core
- azure-mgmt-compute
- azure-mgmt-core
- azure-mgmt-network
- azure-mgmt-resource
- azure-mgmt-resource-deployments
- boto
- cloud-tpu-diagnostics
- colorlog
- execnet
- Gunicorn
- log-symbols
- ml-goodput-measurement
- msrestazure
- opencensus-context
- opentelemetry-api
opentelemetry-instrumentation
opentelemetry-instrumentation-asgi
opentelemetry-semantic-conventions
opentelemetry-util-http
- python-json-logger
- supervisor
psutil
- boto3
- botocore
prometheus-client
- OpenTelemetry
kubernetes
opentelemetry-exporter-prometheus
- docker
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-instrumentation-fastapi
- ray-haproxy
- typeface-roboto
- MUI
usehooks-ts
- lowlight
react-window
react-icons
- @mui/icons-material
- js-yaml
In common
ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Python19.8kRead on November 5, 2026, at commit 4649106What is ml-agents built with?Side by side
Frequently asked questions
Which is bigger, ray or ml-agents?
The proof: ray-project/ray's code at commit c99c603
Which has more GitHub stars, ray or ml-agents?
The proof: ray-project/ray on GitHub
Which has more tests, ray or ml-agents?
The proof: ray-project/ray's code at commit c99c603
Which was updated more recently, ray or ml-agents?
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, ray or ml-agents?
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