datamllab / HarborRL
An end-to-end framework for Agentic Reinforcement Learning.
Why this job: topics: agent-framework, llm-agents, agentic-ai, agent, agentic
What it does
HarborRL is a lightweight framework for training tool-using agents on verifiable, sandboxed tasks. It makes model serving, trajectory generation, tool execution, verifier rewards, and policy updates into a single reproducible pipeline.
Get started
uv sync --extra dev- Maintenance
- Active
- Last commit 11 days ago
- Stars
- 176
- +73 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 90% of the code
Is it looked after?
- Contributors
- 3
- Last 90 days
- Issues
- None
- No issues filed
- Pull requests
- 3 merged
- 0 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- Security policy (opens in new tab)
- No code of conduct
More: languages, topics and project record
Languages
- Python 90%
- JavaScript 5%
- CSS 2%
- Shell 2%
Topics
- agent
- agent-framework
- agentic
- agentic-ai
- agentrl
- coding-agent
- coding-agents
- dapo
- grpo
- harbor
- harbor-framework
- llm
Project record
- JobAgent frameworks
- StatusNew to our list
- Commits16
- Forks14
- Watching10
- Stars in 28 days+175
- CreatedOct 12, 2026
- First seen by usNov 7, 2026
- CheckedNov 10, 2026