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https://github.com/litanlitudan/skyagi
SkyAGI: Emerging human-behavior simulation capability in LLM
https://github.com/litanlitudan/skyagi
ai-agent aigc langchain language-model llm
Last synced: 21 days ago
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SkyAGI: Emerging human-behavior simulation capability in LLM
- Host: GitHub
- URL: https://github.com/litanlitudan/skyagi
- Owner: litanlitudan
- License: apache-2.0
- Created: 2023-04-11T04:28:00.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-09-21T12:38:34.000Z (about 1 year ago)
- Last Synced: 2024-10-09T15:31:44.802Z (30 days ago)
- Topics: ai-agent, aigc, langchain, language-model, llm
- Language: TypeScript
- Homepage: https://skyagi.ai
- Size: 10.7 MB
- Stars: 757
- Watchers: 19
- Forks: 54
- Open Issues: 40
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Codeowners: CODEOWNERS
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- awesome-agi-agents - skyagi - playing game that creates a very interesting user experience.| SkyAGI 实现了 "生成式智能体 "的理念，设计了一个角色扮演游戏，创造了非常有趣的用户体验。| (前沿项目)
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README
# SkyAGI: Emerging human-behavior simulation capability in LLM
https://github.com/litanlitudan/skyagi/assets/4970420/a584b364-e659-476d-a884-932b3c04df61
`SkyAGI` is a python package that demonstrates LLM's emerging capability in simulating believable human behaviors.
Specifically, `SkyAGI` implements the idea of [Generative Agents](https://arxiv.org/abs/2304.03442) and delivers a role-playing game that creates a very interesting user experience.
Different from previous AI based NPC systems, `SkyAGI`'s NPC generates very believable human responses.
The interesting observations in this demo show a huge potential for rethinking game development in many aspects, such as NPC script writing.
To demonstrate this, `SkyAGI` provides example characters from `The Big Bang Theory` and `The Avengers` as a starting point.
Users could also define customized characters by creating config json files like [customized_character.json](https://github.com/litanlitudan/skyagi/blob/main/examples/example_agent.json)
For details about the interesting observations, refer to the [observations section](https://github.com/litanlitudan/skyagi/#interesting-observations-in-this-demo).
## Quick Start
Installation
```sh
pip install --upgrade skyagi
```
Or
```sh
make install
```
How to run
```sh
export OPENAI_API_KEY="..."
skyagi
# or
OPENAI_API_KEY="..." skyagi
```
For example if the OpenAI key is `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`, then the exact command would be the following
```sh
# make sure no quote around the token
export OPENAI_API_KEY=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
skyagi
# or
OPENAI_API_KEY=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 skyagi
```
To use example agent configs, download it from here: https://github.com/litanlitudan/skyagi/tree/main/examples
(pip install doesn't contain the agent configuration)
An example agent configuration (Sheldon) looks something like this:
```json
{
"name": "Sheldon",
"age": 27,
"personality": "Intelligent, rigid, socially challenged, quirky, and arrogant.",
"memories": [
"Sheldon is a theoretical physicist who works at Caltech.",
"Sheldon has an eidetic memory and is highly intelligent, but struggles with social skills and sarcasm.",
...
"Knock, knock, knock, Penny - This is the specific knock that Sheldon uses when he visits Penny's apartment, which he repeats three times.",
"Bazinga! - This is Sheldon's catchphrase that he uses to indicate he was joking or playing a prank on someone."
],
"current_status": "Sheldon is at the Cheesecake Factory"
}
```
## Interesting observations in this demo
Here is a screenshot of a live demo using The Big Bang Theory example.
From the conversation, we can observe three interesting points that have not been widely seen in previous systems:
1. Leonard remembered that Penny had asked him to persuade Sheldon to go for a hike, which shows the capability of some kind of memory.
2. Leonard changed his mind after Sheldon whispered to him and even tried to convince Penny to join the scientific effort, which shows that the agents had meaningful progress in the story even without human intervention.
3. All the responses are quite human-like. As a user, it's quite hard to tell whether it's actually an AI behind the responses.
## References
1. https://arxiv.org/abs/2304.03442
2. https://python.langchain.com/en/latest/use_cases/agent_simulations/characters.html#create-a-generative-character