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GenerativeAgents - Werewolves of Miller's Hollow

Japanese Readme | Simulation Video | Research Paper Referenced

"Werewolves of Miller's Hollow" is a popular social deduction game where players are assigned roles as townfolks, werewolves, or special characters, and the goal is to either eliminate all the werewolves or have the werewolves outnumber the villagers or complete all the assigned tasks.

During the game, players participate in a series of day and night phases. During the night, the werewolves choose a villager to eliminate, and certain special characters may perform their unique abilities. During the day, the surviving players discuss and vote on who they believe is a werewolf. The player with the most votes is "lynched" and removed from the game.

The game continues with alternating day and night phases until either all the werewolves are eliminated, or the werewolves outnumber the villagers, or until all the villagers complete all the tasks. It requires strategy, deduction, and persuasive skills to deceive or uncover the identities of the werewolves.

The code has Japanese comments for better understanding.

Tech Stacks

Game Image

Table Of Content

Installation

Fork the repository using the button at the top or this link.

Clone the repository by typing in the Terminal

git clone https://github.com/< USERNAME >/GenerativeAgents.git

Navigate inside the directory

cd GenerativeAgents

Install all the libraries by entering the following commands

pip install -r requirements.txt

Go to Config folder and create a .env file.

Run the Main.py file


You can also pull the Docker image from this link

  • To run the image run the following command
docker pull harshagrawal523/werewolves-game-v5:latest
docker run -it -p 8080:8080 werewolves-game-v5

Configuration

Setting up .env file

MongoDB_ID = < your MongoDB url for connection >
OpenAI_API_KEY = < your API_KEY from OPENAI >
OpenAI_Type = < your Type from OPENAI >
OpenAI_Base = < your OpenAI_Base >
OpenAI_Version = < your OpenAI_Version >

Game Instruction

You can setup your own parameters to change the game balance as per your requirements. These are the following parameters which you can change or add more :-

Inside Params.py file

  • agentsDetails - has the name and description of agents
agentsDetails = [
    {"name": "Yumi Okada", "description": "Yumi is a werewolf; Yumi is smart, good at lying, and a farmer who works in the Cattle Farm. Also, Yumi tries to sabotage the tasks of the townfolks."},
    {"name": "Yuka Suzuki", "description": "Yuka is a townfolk; Yuka gets easily convinced by others' arguments and takes care of the well and its maintenance."},
    {"name": "Riku Mori", "description": "Riku is a townfolk; Riku is smart, has good deduction skills, and loves fishing in the Fishing area."},
    {"name": "Hina Sato", "description": "Hina is a townfolk; Hina is analytical and is a monk who works in the Shrine."},
    {"name": "Mana Yoshida", "description": "Mana is a werewolf; Mana is brilliant and an electrician who works in the Electricity House. Also, Mana tries to sabotage the tasks of the townfolks."},
    {"name": "Taichi Kato", "description": "Taichi is a townfolk and an electrician who does tasks at the Electricity House; Taichi is dumb."},
    {"name": "Yuria Shimizu", "description": "Yuria is a townfolk; Yuria has good convincing skills and is a farmer who works in the Cattle Farm."},
    {"name": "Haruka Itō", "description": "Haruka is a townfolk; Haruka has low convincing skills and is a fisherperson who works in the Fishing area. Haruka is friendly and loves talking"},
    # {"name": " ADD A NAME ", "description":" ADD A DESCRIPTION "}
]
  • TaskWin - number of tasks needed to be completed for Townfolks to win
TasksWin = < Your number of tasks >

You can go through the code and change other parameters too, but you must be careful as you need to change multiple files and occurrences.

Contributors



Acknowledgement

We would like to thank all the mentors for there valuable suggestions. Without them this project could never be the way it is. We all have learned a lot of skills in the course of this project. Their dedication and expertise have been pivotal in shaping our project's success, and we are deeply grateful for their constant encouragement and support. The knowledge and skills we have acquired under their guidance will undoubtedly have a lasting impact on our personal and professional growth. Thank you for being instrumental in making this journey a truly enriching and transformative experience for all of us.

We also thank the authors of the research paper, we got to learn a lot from the paper and that helped us make the project.


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