QAnything vs ray
QAnything and ray share 12 technologies: cryptography, rouge-score, scikit-learn, LangChain, onnxruntime, transformers, tiktoken, nltk, xgboost, openpyxl, mistune, and boto3. Both are written in Python.
What they share and what sets them apart
netease-youdao
QAnything
Question and Answer based on Anything.
Python14.2kRead on November 9, 2026, at commit 0698b62What is QAnything built with?Only in QAnything
- aiomysql
mysql-connector-python
- pymilvus
- MySQL
OpenAI- Streamlit
- Sanic
sanic-ext
- Vite
- Vue
vue-router
- ModelScope
sentence-transformers
- zhipuai
- langchain-core
langchain-openai
- lxml-html-clean
- python-docx
pymupdf
unstructured
- docx2txt
- markdownify
- html2text
- pdfplumber
pypdf2
- concurrent-log-handler
ant-design-vue
echarts
- nprogress
@ant-design/icons-vue
- html2canvas
- vue-office
highlight.js
markdown-it
In common
ray-project
ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Python44.2kRead on November 6, 2026, at commit 77567c5What is ray built with?Only in ray
- FastAPI
- amqp
- async-lru
- azure-common
- azure-datalake-store
- azure-storage-blob
confluent-kafka
- diskcache
expiringdict
- gitdb
google-cloud-core
h5py
kombu
pickleshare
- pylance
- pymongo
pyarrow
- aioboto3
- MongoDB
- Redis
- adlfs
- smart-open
pyiceberg
- pymysql
clickhouse-connect
deltalake
- gcsfs
- Celery
- fastavro
- pyzmq
- s3fs
webdataset
Google- Hugging Face
- Google Cloud Storage
- Kafka
- asgiref
- Flask
- flask-cors
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
werkzeug
- Ray
starlette
- AIOHTTP
- Lightning
- anyio
tornado
uvicorn
- React
react-router-dom
- alabaster
- cycler
fonttools
jupyterlab-pygments
- pydata-sphinx-theme
- soupsieve
sphinx-design
- tinycss2
contourpy
- glfw
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
- Plotly
prompt-toolkit
pyopengl
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- ipywidgets
matplotlib
- Rich
- pydot
- alembic
peewee
sqlglot
- SQLAlchemy
- argon2-cffi
- argon2-cffi-bindings
- azure-identity
- flask-basicauth
google-auth-oauthlib
itsdangerous
joserfc
- jwcrypto
- keyring
- msal
- msal-extensions
- oauth2client
oauthlib
- pyjwt
requests-oauthlib
google-auth-httplib2
- albucore
- bitsandbytes
cmdstanpy
- crcmod
cupy-cuda12x
cupy-cuda13x
- einops
- fairscale
gradio-client
- gym
- llvmlite
lm-eval
- ml-dtypes
- MLflow
- ONNX
onnxscript
openai-whisper
- opt-einsum
- orbax-checkpoint
peft
prophet
- sacrebleu
safetensors
scikit-image
- sentencepiece
skops
tf-keras
timm
tokenizers
torchtext
- triton
- gymnasium
- torch
- TensorFlow
jax
torchvision
lightgbm
accelerate
- datasets
- pytorch-lightning
evaluate
flax
- Keras
- torchmetrics
albumentations
deepspeed
diffusers
- hyperopt
- Optuna
- pettingzoo
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
- mdurl
- moviepy
- nbconvert
- nh3
- pandocfilters
ruamel-yaml
webencodings
- xlrd
- xmltodict
pillow
- docutils
- jinja2
- beautifulsoup4
av
- nbformat
- torchcodec
- annotated-types
- fastjsonschema
- fqdn
- jsonschema-specifications
- pathvalidate
- pydantic-core
- referencing
- rfc3339-validator
- rfc3986
- rfc3986-validator
- validators
- Pydantic
- jsonschema
- openapi-schema-validator
- aiobotocore
- azure-mgmt-compute
- azure-mgmt-resource
- colorlog
- Gunicorn
- opentelemetry-api
opentelemetry-instrumentation
- opentelemetry-semantic-conventions
- python-json-logger
psutil
- botocore
prometheus-client
- OpenTelemetry
kubernetes
opentelemetry-exporter-prometheus
- docker
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-instrumentation-fastapi
- typeface-roboto
- MUI
usehooks-ts
- lowlight
react-window
react-icons
- @mui/icons-material
- js-yaml
Side by side
QAnythingray
SizeLines written by people and agents, without generated ones; code files, without tests.
QAnything51,554 lines written227 code files
ray1,531,664 lines written2,777 code files
Who writes itA commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
QAnything0% of its commits signed by AI
ray3.6% of its commits signed by AIWith Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex
ActivityFrom GitHub and its history, on the day SeeRepo read it.
QAnythingLast push September 23, 2026683 commits14,206 stars
rayLast push November 6, 202632,373 commits44,213 stars
TestsThe files that test the code, and the share of code files a test imports.
QAnything3 test files0.4% of its code files have a test that imports them
ray2,168 test files9.7% of its code files have a test that imports them
Frequently asked questions
Which is bigger, QAnything or ray?
ray, with 1,531,664 lines written; QAnything has 51,554.
The proof: ray-project/ray's code at commit 77567c5
Which has more GitHub stars, QAnything or ray?
ray, with 44,213 stars; QAnything has 14,206.
The proof: ray-project/ray on GitHub
Which has more tests, QAnything or ray?
ray, with 2,168 test files; QAnything has 3.
The proof: ray-project/ray's code at commit 77567c5
Which was updated more recently, QAnything or ray?
ray: its last push was on November 6, 2026, and QAnything's on September 23, 2026.
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, QAnything or ray?
ray: an AI signed 3.6% of its commits, with Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex.
See inside your code, today.
Paste your repo and see it drawn, part by part: a medium one in under a minute.
Free, no account.

