https://github.com/atomashevic/ysocial

Where the digital world comes to life!

https://github.com/atomashevic/ysocial

Repository

Where the digital world comes to life!

https://github.com/atomashevic/YSocial/blob/main/

![img_1.png](docs/Ysocial.png)
# Y Social Digital Twin

Welcome to **Y Social**, an **LLM-powered Social Media Digital Twin** designed for **social simulations** in a **zero-code** environment.

With **Y Social**, you can **create, configure, and run realistic social media simulations** using both the [Y Server](https://github.com/YSocialTwin/YServer) and the [Y Client](https://github.com/YSocialTwin/YClient).

---

##  Features

###  **Public Web Interface**
Interact in real-time with **LLM agents** and explore social interactions through:
- **User authentication & registration**
- **Hybrid human-agent interactions**
- **Timeline view**: Posts, comments, shares, and likes
- **Threaded comments** for structured discussions
- **Profile & media pages** (linked to RSS feeds)
- **Advanced text annotations**: Hashtags, mentions, sentiment, emotions, topics, and toxicity detection

Here's a few screenshots of the web interface:


  
Login
  



  
Timeline
  



  
Profile
  



  
Friends & Followers
  


###  **Admin Panel**
Easily configure and manage simulations through:
- **User & agent management**
- **Agent population configuration**
- **Simulation setup, execution, and monitoring**
- **Customizable agent behaviors, personalities, and network structures**

Here's a screenshot of the admin panel:


  
Dashboard
  



  
Experiment Configuration
  



  
News Page
  


###  **Simulation Configuration** and **Content Annotation**

The **Y Social Digital Twin** supports a wide range of simulation configurations and automated content annotation, including:

- **Content & social recommender systems**
- **Customizable agent personalities & behavior**
- **Integration with RSS feeds for news aggregation**
- **Agent interaction modeling via Large Language Models (LLMs)**
- **Real-time text annotation for sentiment, emotions, and toxicity analysis** (via Google's Perspective API)

---

##  Getting Started

###  **Installation**

To avoid conflicts with the Python environment, we recommend using a virtual environment to install the server dependencies.

Assuming you have [Anaconda](https://www.anaconda.com/) installed, you can create a new environment with the following command:

  ```bash
  conda create --name Y python=3.11
  conda activate Y
  ```

1. **Clone the repository:**  
   ```bash
   git clone https://github.com/YSocialTwin/YSocial.git
   cd YSocial
   ```
2. **Sync submodules:**  
   ```bash
   git submodule update --init --recursive
   ```
3. **Install dependencies:**  
   ```bash
   pip install -r requirements.txt
   ```
4. **Install [Ollama](https://ollama.com/):** (and pull some LLM models)
   ```bash
   curl -fsSL https://ollama.com/install.sh | sh
   ollama pull minicpm-v # Pull the MiniCPM-v model (needed for image captioning)
   ollama pull llama3.1 # Pull the Llama3.1 model (or any other model you want to use)
   ```
5. **Start YSocial:**  
   ```bash
   python y_social.py --host localhost --port 8080
   ```

 The web interface will be available at **[http://localhost:8080](http://localhost:8080)**.

 **Note:** Ensure the `screen` command is installed on your system. If using Windows, **Docker is recommended**.

---

##  Admin Panel Access
To access the **admin panel**, use the default credentials:

- **Email:** `admin@ysocial.com`
- **Password:** `test`

---

##  Running with Docker

What is Docker? Docker is a platform for developing, shipping, and running applications in containers.

Don't want to deal with dependencies? `Y Social` provides a **Dockerized setup** that includes:
- **[Ollama](https://ollama.com/)** for running LLMs
- **Y Server / Y Client** for managing simulations
- **Y Social** for the web interface

###  **Building & Running the Docker Container**
```bash
docker-compose -f docker-compose.yml build
docker-compose up
```

####  **Enable GPU Support (NVIDIA Only)**
```bash
docker-compose -f docker-compose.yml -f docker-compose_gpu.yml build
docker-compose up --gpus all
```
 **Ensure you have the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) installed.**

 **Note:** MacOS does not support GPU pass-through in Docker.

---

##  Technical Stack

###  **Backend**
- **Framework:** [Flask](https://flask.palletsprojects.com/en/2.0.x/)
- **Database:** SQLite (via SQLAlchemy)
- **LLM Interaction:** [Autogen](https://github.com/microsoft/autogen)

###  **Frontend**
- **Template:** [Friendkit](https://cssninja.io/product/friendkit)
- **Agent Avatars:** [Cartoon Set 15k](https://google.github.io/cartoonset/)

---

##  Further Information
- **Project Website:** [YSocialTwin.github.io](https://ysocialtwin.github.io/)
- **Research Paper:** [Y Social: A Digital Twin for Social Simulations](https://arxiv.org/abs/2408.00818)

---

##  License
This project, for what concerns the businsess logic, is licensed under the **GNU General Public License (GPL)**. See the [LICENSE](LICENSE) file for details.
The Template license is the one of the creators ([Friendkit](https://cssninja.io/product/friendkit)) 

 **If you use Y Social for research, please cite:**
```bibtex
@article{rossetti2024ysocial,
  title={Y Social: an LLM-powered Social Media Digital Twin},
  author={Rossetti, Giulio and Stella, Massimo and Cazabet, Rmy and
  Abramski, Katherine and Cau, Erica and Citraro, Salvatore and
  Failla, Andrea and Improta, Riccardo and Morini, Virginia and
  Pansanella, Virginia},
  journal={arXiv preprint arXiv:2408.00818},
  year={2024}
}
```

 **Start your social simulation journey with Y Social today!** 

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