fzliu/radient

Radient turns many data types (not just text) into vectors for similarity search, RAG, regression analysis, and more.

54
/ 100
Established

Radient helps data professionals, researchers, and analysts convert various types of raw data—like text documents, images, audio files, graphs, or chemical structures—into numerical representations called vectors. These vectors can then be used for tasks like similarity search, building recommendation engines, or preparing data for machine learning analysis. It's designed for anyone needing to standardize diverse data formats into a comparable, analyzable form.

283 stars. Available on PyPI.

Use this if you need to transform a wide variety of unstructured data types into a consistent, numerical format for search, retrieval, or further analysis.

Not ideal if your primary goal is to build context-aware systems around large language models (LLMs) like those for Retrieval Augmented Generation (RAG), as Radient focuses on vectorization rather than full LLM integration.

data-preparation information-retrieval multimodal-data-analysis search-systems machine-learning-engineering
Maintenance 10 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 9 / 25

How are scores calculated?

Stars

283

Forks

11

Language

Python

License

BSD-2-Clause

Last pushed

Mar 02, 2026

Commits (30d)

0

Dependencies

3

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/fzliu/radient"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.