by QuangBK · Agent Tool · ★ 288
Generative Agents with Guidance, Langchain, and local LLMs This is the implementation of paper "Generative Agents: Interactive Simulacra of Human Behavior". This is based on the Langchain implementation. We improve and add more features to make it like the original paper as much as possible. For more explaination, please check my medium post. Note that: I just fixed a conflict between current prompts and the guidance. I recommend using the guidance==0.063 because of the stability.
| Stars | 288 |
| Forks | 39 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| Quality Score | 69.0702101869593/100 |
| Open Issues | 3 |
| Last Updated | 2023-09-04 |
| Created | 2023-06-02 |
| Est. Tokens | ~12k |
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generativeAgent_LLM is Implementation of "Generative Agents: Interactive Simulacra of Human Behavior" paper with Guidance and Langchain. Full features and work with local LLMs.. It is categorized as a Agent Tool with 288 GitHub stars.
generativeAgent_LLM is primarily written in Jupyter Notebook. It covers topics such as generative-agents, guidance, langchain.
You can find installation instructions and usage details in the generativeAgent_LLM GitHub repository at github.com/QuangBK/generativeAgent_LLM. The project has 288 stars and 39 forks, indicating an active community.