News

User Story

Engineering

Culture

Tyler Griggs

Philipp Moritz

Explore a technical comparison of leading Reinforcement Learning (RL) libraries for LLMs from Ray. This guide analyzes frameworks like TRL, Verl, and RAGEN to help developers choose the best tools for RLHF, reasoning, and agentic AI.

The architecture of a Reinforcement Learning (RL) library is split into two primary components: Generation and Training. During the generation phase, an LLM Engine performs multi-turn rollouts within an environment to produce data and reward signals. This output is then fed into the training phase to update the model's parameters. This process forms a feedback loop, where the progressively improved model generates the next iteration of data for continuous refinement.

Open Source RL Libraries for LLMs Graph

Open Source RL Libraries for LLMs

The Ray Summit 2025 CfP is now open for submissions. The premier AI conference will be held November 3-5 in San Francisco, and the due date for CfPs is July 14th, 2025.  

Ray Summit 2025 CFP Open

Ray Summit 2025: Call for Proposals Closes on July 14th, 2025

Google + Anyscale

Google Cloud Integrates Anyscale's RayTurbo with GKE

Simplifying AI Development at Scale: Google Cloud Integrates Anyscale's RayTurbo with GKE

At Ray Summit 2024, we brought together AI experts and practitioners to dive into the future of distributed AI and scalable machine learning.

image3

Ray Summit 2024: Breaking Through the AI Complexity Wall

This section is used to order the "Types" and "Tags" that show up for filters on the Blog Index

Types

Products / Libraries

Blog

Anyscale is the leading AI application platform. With Anyscale, developers can build, run and scale AI applications instantly.

Posts by Tyler Griggs

No posts found.