AgentR1/Agent-R1
Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning
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Established
Implements step-level MDPs with layered abstractions to enable multi-step agent training across custom workflows and tool-augmented environments. Built on the veRL framework, it provides end-to-end RL training for agents performing sequential interactions, as demonstrated by downstream projects like TableMind (table reasoning) and PaperScout (academic search with process-aware optimization).
1,313 stars. Actively maintained with 6 commits in the last 30 days.
No Package
No Dependents
Maintenance
20 / 25
Adoption
10 / 25
Maturity
16 / 25
Community
16 / 25
Stars
1,313
Forks
86
Language
Python
License
MIT
Category
Last pushed
Mar 25, 2026
Commits (30d)
6
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