epitome

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Epitome

Pioneering an Experimental Platform for AI-Social Science Integration

🎯 Introduction

Epitome is the world's first experimental open platform dedicated to the deep integration of artificial intelligence and social sciences. Through seven major modules, the platform provides intelligent assistance across the entire process—ranging from experimental intervention, experimental environment, to experimental participants—helping researchers easily design and conduct complex human-computer interaction experimental scenarios. This enables systematic research on AI's social impact and exploration of comprehensive solutions, advancing the harmonious integration of artificial intelligence into human society.

For more information, please refer to the introduction video.

🎓 Application Scenarios

Social science experimental research
Human-computer interaction behavior analysis
AI social impact assessment
Group dynamics simulation
Interdisciplinary experimental design

✨ Key Features

🎭 Innovative Interactive Scenarios

Role-Playing Robots

🤖 Simulate diverse social roles such as judges and historical figures
🌐 Enable cross-temporal and cross-identity dialogue experiments
📊 Provide standardized and replicable interactive elements for abstract social problem research

Human-AI Hybrid Chat Rooms

👥 Support multi-party interaction patterns of "human-human-AI-AI"
🔄 Simulate complex social networks and group interaction contexts
🔬 Open new possibilities for group behavior and social dynamics research

Social Simulation

💼 Simulate human economic transactions, social conflicts, and other behaviors through intelligent agents
⏱️ Provide large-scale, long-term social scenario simulations
💰 Enable low-cost policy effect prediction and social norm evolution research

🔄 Complete-Flow Closed-Loop Support

🎯 Experiment Management: Complete lifecycle management from design to execution
📦 Material Management: Centralized management of multimodal experimental materials
📋 Questionnaire Management: Flexible questionnaire design and data collection
⚙️ Workflow Management: Visual orchestration of modular components
📈 Data Analysis: Real-time data collection and export functionality

🔓 Open Research Design

Diverse Material Support

📝 Text, images, videos
📄 PDFs, PPTs, and various other formats
🤖 Multimodal large models supporting experimental material preparation

Open Architecture Design

🔧 Customized workflow design
🧩 Flexible agent system configuration
🎨 Adaptable to complex experimental paradigms across multiple disciplines

🎮 Controllable Experimental Advancement

🔍 Scalable Experimental Scale: Break through the venue and personnel limitations of traditional offline experiments
⚡ Precise Process Control: Preset interaction processes that balance experimental control and realistic simulation
♻️ Enhanced Reproducibility: Standardized experimental processes improve reproducibility and verifiability
📊 Real-time Data Collection: Record experimental data throughout, supporting multi-dimensional analysis

🏗️ Tech Stack

Core Technologies

Category	Technology	Version
Framework	Spring Boot	2.7.3
Persistence	MyBatis-Plus	-
Database	MySQL	8.x
Cache	Redis (Jedis)	-
Security	Apache Shiro	-
Session Sharing	Shiro-Redis	-
API Docs	Knife4j (Swagger)	-
Export	EasyExcel, EasyPoi	-
File Storage	MinIO	-
Real-time Communication	WebSocket	-
Utilities	Hutool, FastJSON, Druid	-

📋 Requirements

Essential Environment

☕ JDK: 1.8+
📦 Maven: 3.x
🗄️ MySQL: 8.x
🔴 Redis: 5.x+

🚀 Quick Start

Step 1: Clone and Build

# Clone the repository
git clone https://github.com/epitome-AISS/epitome.git

# Enter project directory
cd epitome

# Install dependencies and package (including local lib)
mvn clean install -DskipTests

Step 2: Modify Configuration Files

Main configuration file src/main/resources/application.yml:

The active profile is set via spring.profiles.active in application.yml (e.g., testLocal)

spring:
  profiles:
    active: testLocal  # Select the active environment configuration

Configure in the corresponding profile file (e.g., application-testLocal.yml):

MySQL: spring.datasource.url / username / password
Redis: spring.redis.host / port, etc.

spring:
  datasource:
    url: jdbc:mysql://{your_mysql_ip}:3306/ailab?useSSL=false&characterEncoding=utf8
    username: {your_mysql_username}
    password: {your_mysql_password}
    
  redis:
    host: {your_redis_ip}
    port: 6379
    password: {your_redis_password}

💡 Tip: Replace placeholders like {your_mysql_ip} with actual values

Step 3: Run the Project

Run with Maven

# Run with Maven (uses the active profile)
mvn spring-boot:run

# Or package first, then run
mvn clean package -DskipTests
java -jar target/ailab-1.0.0.jar

Default port is defined in each profile config (e.g., 8085 for local).

Step 4: Verify Startup

Access Knife4j documentation to verify the service is running (adjust context-path if needed):

📚 API Documentation Example: http://localhost:8085/doc.html

Installation Time: If all dependent software and the environment need to be installed, the typical installation time is approximately 10 hours.

📁 Project Structure

src/
└── main/
    ├── java/com/nbtech/ailab/
    │   ├── AiLabApplication.java           # 🚀 Application entry
    │   ├── biz/                             # 💼 Business layer
    │   │   ├── controller/                  # 🎮 Controllers
    │   │   ├── dao/                         # 🗄️ Data access layer
    │   │   ├── dto/                         # 📦 Data transfer objects
    │   │   ├── entity/                      # 📋 Entities
    │   │   └── service/                     # ⚙️ Service layer
    │   ├── common/                          # 🔧 Common modules
    │   ├── config/                          # ⚙️ Configuration classes
    │   ├── facade/                          # 🎭 Facade/aggregation services
    │   ├── security/                        # 🔒 Security configuration
    │   ├── util/                            # 🛠️ Utilities
    │   ├── vo/                              # 👁️ View objects
    │   └── websocket/                       # 🔌 WebSocket
    └── resources/                           # SQL scripts and change logs
        └── mapper/                          # MyBatis mapper files

⚙️ Configuration Guide

Multi-environment: Switch via spring.profiles.active (e.g., testLocal, testDev, formalDev)
File Upload: Configured in application.yml under spring.servlet.multipart (e.g., 500MB limit)
Database: MyBatis-Plus with logical delete field is_deleted.

🐳 Other

Local Dependency: lib/common-0.0.1-release.jar must exist and be installed or referenced via system scope
Deployment: A Dockerfile is provided for building and deploying the image as needed

📄 License

This project is licensed under the MIT License.

MIT License

Copyright (c) 2025 Epitome Team

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction...

📞 Contact Us

If you are interested in this platform or have social experiment needs, please feel free to contact us through the following methods:

📧 Contact Email

epitome_AI4SS@163.com

WeChat Official Account

_Epitome-AI

Bilibili

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🌐 Online Resources

🏠 Official Website: https://www.epitome-ai.com/
📄 Research Paper: arXiv:2507.01061
💻 GitHub: https://github.com/epitome-AISS/epitome

📖 Citation

If you use the Epitome platform in your research, please cite our paper:

@misc{qu2025epitomepioneeringexperimentalplatform,
  title={Epitome: Pioneering an Experimental Platform for AI-Social Science Integration}, 
  author={Jingjing Qu and Kejia Hu and Jun Zhu and Yulei Ye and Wenhao Li and Teng Wang and Zhiyun Chen and Chaochao Lu and Aimin Zhou and Xiangfeng Wang and Xia Hu and James Evans},
  year={2025},
  eprint={2507.01061},
  archivePrefix={arXiv},
  primaryClass={cs.CY},
  url={https://arxiv.org/abs/2507.01061}
}

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