Langflow is a powerful tool for building and deploying AI-powered agents and workflows.

AssetOpsBench - Industry 4.0: A unified benchmark and framework for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance, with 460+ sc…

[ICLR 2026 Oral] BIRD-INTERACT: Re-imagines Text-to-SQL evaluation via lens of dynamic interactions.

Prompt Declaration Language (PDL) is a declarative prompt programming language.

FailureSensorIQ, a dataset and benchmark to probe LLMs’ reasoning and comprehension of sensor–failure relationships in industrial systems.

Planning annotated Reinforcement Learning (PaRL) Agent annotations

Planning annotated Reinforcement Learning (PaRL) Agents

Planning annotated Reinforcement Learning (PaRL) Agent minigrid enviroment

aider is AI pair programming in your terminal

Agentics is a Python framework that transform LLM computation into functional code.

Long-form factuality assessor for large language models

Enabling IBM Granite models to reason via GRPO

Learning representations for RL in Healthcare under a POMDP assumption

Sepsis cohort from MIMIC dataset

Open AI Gym Environment For MIMIC Dataset Sepsis Patient

K* search based implementation of top-k and top-quality planners

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

This is the official implementation of NeurIPS 2022 paper "Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning"

Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning

Implementation codes and datasets used in ICLR'22 Spotlight paper AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning.

UAI competition benchmark instances

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

LTL2PDDL tool

Random syntax generator with reasoner and LSTM

Convert Machine Learning Code Between Frameworks

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Code for "Planning from Pixels using Inverse Dynamics Models"

Code for "Learning to Reach Goals via Iterated Supervised Learning"