1.evidentlyai / evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
+610 stars
from 7,419 · score 6.42
Trending repositories
Ranked by Attention Score: stars gained over the last 180 complete days
11 repositories by Attention Score · May 7, 2026 – Nov 2, 2026 (UTC)
2.cleanlab / cleanlab
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
+327 stars
from 11,397 · score 5.79
3.rjsf-team / react-jsonschema-form
A React component for building Web forms from JSON Schema.
+225 stars
from 15,703 · score 5.42
4.unionai-oss / pandera
A light-weight, flexible, and expressive statistical data testing library
+201 stars
from 4,306 · score 5.31
5.deepchecks / deepchecks
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
+73 stars
from 3,996 · score 4.30
6.posit-dev / pointblank
Data validation toolkit for assessing and monitoring data quality.
+70 stars
from 427 · score 4.26
7.pyeve / cerberus
Lightweight, extensible data validation library for Python
+21 stars
from 3,260 · score 3.09
8.implerhq / impler.io
Powerful CSV & Excel Import experience for SaaS 🚀 Save months building data import experience from scratch 💰
+16 stars
from 278 · score 2.83
9.mus-format / mus-go
MUS format serializer for Go
+8 stars
from 137 · score 2.20
10.provero-org / provero
Declarative data quality engine. Define checks in YAML, run anywhere.
+6 stars
from 11 · score 1.95
11.vertti / daffy
Lightweight DataFrame validation decorators for Pandas, Polars, Modin, and PyArrow. No custom types required.
+2 stars
from 58 · score 1.10