gpt-researcher vs ray
gpt-researcher and ray share 30 technologies: FastAPI, anyio, starlette, AIOHTTP, uvicorn, React, fonttools, soupsieve, tinycss2, SQLAlchemy, cryptography, nltk, tokenizers, LangChain, tiktoken, jinja2, lxml, markupsafe, webencodings, beautifulsoup4, markdown, mistune, pillow, annotated-types, jsonschema, jsonschema-specifications, pydantic-core, referencing, Pydantic, and psutil. Both are written in Python.
LinkedInWhat they share and what sets them apart
assafelovic
gpt-researcher
An autonomous agent that conducts deep research on any data using any LLM providers
Python30.5kRead on November 7, 2026, at commit 3582a68What is gpt-researcher built with?Only in gpt-researcher
- Next.js
- @next/third-parties
- langdetect
- LangGraph
langgraph-sdk
- langsmith
litellm
- MCP
- Ollama
OpenAI- tavily-python
- unstructured-client
- langchain-community
langchain-openai
langchain-mcp-adapters
- langchain-text-splitters
deepagents
- langchain-classic
- cssselect2
feedparser
- filetype
- html5lib
- markdown2
olefile
- pydyf
pymupdf
pypdf
- python-magic
- python-oxmsg
- python-pptx
- tinyhtml5
unstructured
- python-docx
- weasyprint
marshmallow
loguru
- Tailwind CSS
react-hot-toast
- Framer
react-dropzone
@langchain/langgraph-sdk
- isomorphic-dompurify
- remark
remark-gfm
remark-html
ag2
- langchain-core
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
- 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
- Hugging Face
- Google Cloud Storage
- Kafka
- asgiref
- Flask
- flask-cors
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
werkzeug
- Ray
- Lightning
tornado
react-router-dom
- alabaster
- cycler
jupyterlab-pygments
- pydata-sphinx-theme
- sphinx-design
contourpy
- glfw
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
- Plotly
prompt-toolkit
pyopengl
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- ipywidgets
matplotlib
- Rich
- pydot
- alembic
peewee
sqlglot
- argon2-cffi
- argon2-cffi-bindings
- azure-identity
- flask-basicauth
itsdangerous
joserfc
- jwcrypto
- keyring
- msal
- msal-extensions
- oauth2client
oauthlib
- pyjwt
requests-oauthlib
- albucore
- bitsandbytes
cmdstanpy
- crcmod
cupy-cuda12x
- einops
- fairscale
gradio-client
- gym
- llvmlite
lm-eval
- ml-dtypes
- MLflow
- ONNX
- onnxruntime
onnxscript
openai-whisper
- opt-einsum
- orbax-checkpoint
peft
prophet
rouge-score
- sacrebleu
safetensors
scikit-image
- sentencepiece
skops
tf-keras
timm
torchtext
- triton
gymnasium
- torch
- transformers
- TensorFlow
jax
torchvision
- xgboost
lightgbm
- scikit-learn
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
- mako
markdown-it-py
- mdurl
- moviepy
- nbconvert
- nh3
- openpyxl
- pandocfilters
ruamel-yaml
- xlrd
- xmltodict
- docutils
av
- nbformat
- torchcodec
- fastjsonschema
- fqdn
- pathvalidate
- rfc3339-validator
- rfc3986
- rfc3986-validator
- validators
- openapi-schema-validator
- aiobotocore
- azure-mgmt-compute
- azure-mgmt-resource
- colorlog
- Gunicorn
- opentelemetry-api
opentelemetry-instrumentation
opentelemetry-semantic-conventions
- python-json-logger
- boto3
- botocore
prometheus-client
- OpenTelemetry
kubernetes
- docker
- typeface-roboto
- MUI
usehooks-ts
- lowlight
react-window
react-icons
- @mui/icons-material
- js-yaml
Side by side
gpt-researcherray
SizeLines written by people and agents, without generated ones; code files, without tests.
gpt-researcher51,624 lines written233 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.
gpt-researcher3.2% of its commits signed by AIWith Claude Code, Cursor, GitHub Copilot, Jules, and Codex
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.
gpt-researcherLast push October 10, 20262,477 commits30,542 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.
gpt-researcher149 test files36.5% 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, gpt-researcher or ray?
ray, with 1,531,664 lines written; gpt-researcher has 51,624.
The proof: ray-project/ray's code at commit 77567c5
Which has more GitHub stars, gpt-researcher or ray?
ray, with 44,213 stars; gpt-researcher has 30,542.
The proof: ray-project/ray on GitHub
Which has more tests, gpt-researcher or ray?
ray, with 2,168 test files; gpt-researcher has 149.
The proof: ray-project/ray's code at commit 77567c5
Which was updated more recently, gpt-researcher or ray?
ray: its last push was on November 6, 2026, and gpt-researcher's on October 10, 2026.
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, gpt-researcher or ray?
ray: an AI signed 3.6% of its commits, with Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex; in gpt-researcher, 3.2%.
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