Simple-Efficient/RL-Factory

Health v2 · maintenance only

Adoption not part of the score

1780 stars · 165 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

RLFactory is a reinforcement learning post-training framework for training agentic LLM models, decoupling the environment from RL training via tool configs and reward functions. It supports multi-turn tool-calling, async execution for 2x faster training, model-judge rewards, and one-click DeepSearch training with models like Qwen3.

Use cases

• train an agent model with reinforcement learning
• rl post-training for tool-calling llm
• train a deepsearch agent with grpo
• build an agent that calls mcp tools
• fine-tune qwen3 for multi-turn tool use
• speed up agentic rl training with async tool calls

When to choose

• you want to RL post-train an LLM agent with custom tools and reward functions
• you need fast, async multi-turn tool-calling training
• you want one-click DeepSearch agent training on Qwen3

When to avoid

• you only need supervised fine-tuning without RL
• you need a general-purpose RL library unrelated to LLM agents
• you require multimodal or Android agent training before those features ship

Facets

framework · maturity active

llm-training agent-framework machine-learning mcp large-language-models reinforcement-learning machine-learning python reinforcement-learning post-training grpo tool-calling qwen3 deepsearch agentic-learning ai-agents gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Simple-Efficient/RL-Factory")