DyLAN Official Implementation of Dynamic LLM-Agent Network: An LLM-agent Collaboration Framework with Agent Team Optimization Authors: Zijun Liu, Yanzhe Zhang, Peng Li, Yang Liu, Diyi Yang Overview Abstract Large language model (LLM) agents have been shown effective on a wide range of tasks, and by ensembling multiple LLM agents, their performances could be further improved. Existing approaches employ a fixed set of agents to interact with each other in a static architecture, which limits their generalizability to various tasks and requires strong human prior in designing these agents.
| Stars | 196 |
| Forks | 28 |
| Language | Python |
| Category | AI 工具 |
| License | MIT |
| Quality Score | 36.75/100 |
| Open Issues | 8 |
| Last Updated | 2024-05-16 |
| Created | 2023-10-03 |
| Platforms | python |
| Est. Tokens | ~1603k |
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DyLAN is Official Implementation of Dynamic LLM-Agent Network: An LLM-agent Collaboration Framework with Agent Team Optimization. It is categorized as a AI 工具 with 196 GitHub stars.
DyLAN is primarily written in Python. It covers topics such as chatgpt, gpt4, llm.
You can find installation instructions and usage details in the DyLAN GitHub repository at github.com/SALT-NLP/DyLAN. The project has 196 stars and 28 forks, indicating an active community.
DyLAN is released under the MIT license, making it free to use and modify according to the license terms.