by ryoungj · Agent Tool · ★ 190
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[ICLR'24 Spotlight] A language model (LM)-based emulation framework for identifying the risks of LM agents with tool use
| Stars | 190 |
| Forks | 20 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 46.35/100 |
| Open Issues | 2 |
| Last Updated | 2024-03-22 |
| Created | 2023-09-26 |
| Platforms | python |
| Est. Tokens | ~275k |
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This is the repository for the Tool Learning survey.
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ToolEmu is [ICLR'24 Spotlight] A language model (LM)-based emulation framework for identifying the risks of LM agents with tool use. It is categorized as a Agent Tool with 190 GitHub stars.
ToolEmu is primarily written in Python. It covers topics such as agent, ai-safety, language-agent.
You can find installation instructions and usage details in the ToolEmu GitHub repository at github.com/ryoungj/ToolEmu. The project has 190 stars and 20 forks, indicating an active community.
ToolEmu is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to ToolEmu on Agent Skills Hub include anchoring-ai, chatgpt-cli, ToolOrchestra. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.