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An implementations of "Generative Agents: Interactive Simulacra of Human Behavior".

Home Page: https://arxiv.org/abs/2304.03442

License: MIT License

Python 100.00%
artificial-intelligence generative-agents large-language-models

generative-agents's Introduction

Generative Agents:
Interactive Simulacra
of Human Behavior

Stars

Generative agents proposed by this paper extend LLMs (like ChatGPT) with memory, reflection, planing and a sandbox environment.

We're building our Python implementation that allows you to add Generative Agents to your own worlds.

TODO and contributing

We have a #dev chanel on Discord.

Answer questions.

Check out the issues and projects tabs, there are also # TODOs scatered around the code.

  • Python 3.10+
  • Black
  • isort

Parts

  • 4.1 Memory represents the most basic type of memory, an observation. Importance calculation is done here.
  • 4.2 Reflection a reflection.
  • 4.3 Plan a plan.
  • 4.1 MemoryStream a stream of memories. Memory retrival is done here.
  • 4 Agent
  • 5 Sandbox tick, time,
  • Figure 2 World
  • Figure 2 Area
  • Figure 2 Object

Usage

pip install openai

Authentication

Create a openai_secrets.py file and set your key there.

Note https://platform.openai.com/docs/api-reference/authentication

import openai

openai.api_key = 'Your OpenAI API key'

generative-agents's People

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