graphbookai/graphbook
Visual AI development framework for training and inference of ML models, scaling pipelines, and automating workflows with Python
Build and manage complex AI-powered data pipelines with a visual drag-and-drop interface. Input raw data or models, define processing steps using Python nodes, and get cleaned datasets, experimental results, or functional AI applications. This tool is ideal for data scientists, ML engineers, and researchers who need to efficiently develop and deploy machine learning workflows.
Available on PyPI.
Use this if you need a visual way to assemble, monitor, and scale AI and machine learning data processing workflows without extensive coding.
Not ideal if you prefer command-line-only tools, have very simple, static data pipelines, or are not working with AI/ML.
Stars
46
Forks
7
Language
Python
License
MIT
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
Dependencies
7
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/graphbookai/graphbook"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
Cloud-CV/EvalAI
:cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
fireindark707/Python-Schema-Matching
A python tool using XGboost and sentence-transformers to perform schema matching task on tables.
visual-layer/fastdup
fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and...
github/CodeSearchNet
Datasets, tools, and benchmarks for representation learning of code.
tthtlc/awesome-source-analysis
Source code understanding via Machine Learning techniques