pymc-devs/pymc
Bayesian Modeling and Probabilistic Programming in Python
Declarative parameters for robust Python classes and a rich API for reactive programming
Bayesian Modeling and Probabilistic Programming in Python
Build reliable customer-facing AI agents with Parlant: an interaction control harness optimized for controlled, consistent, and predictable LLM interactions.
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Structured Outputs
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
1 capture since 2026-06-02
pyproject.toml
· python · 22 dependencies