MPCDSEPC - AI-Enhanced Epidemic Prevention Document Collaboration System

Overview

MPCDSEPC (Multi-Person Collaborative Document System for Epidemic Prevention and Control) is an enterprise-grade web application designed for city and district-level health authorities to collaboratively manage epidemic investigation documents in real-time.

Key Features

• 🤖 AI-Powered Document Analysis: Leverages large language models (LLM) for intelligent document processing and anomaly detection
• 🔄 Real-time Collaboration: WebSocket-based multi-user editing with live presence indicators
• 📄 Intelligent Report Generation: Automated Word document generation from structured data using AI-assisted templating
• 📊 Database Management: Complete CRUD operations with MyBatis, supporting data visualization and export
• 🔔 Real-time Notifications: WebSocket push notifications for document updates and collaboration events
• 📝 Change History Tracking: Complete audit trail of all document modifications

Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Frontend (HTML/JS)                       │
├─────────────────────────────────────────────────────────────┤
│                    Spring Boot Backend                      │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐      │
│  │  Controllers │  │  Services    │  │   Mappers    │      │
│  └──────────────┘  └──────────────┘  └──────────────┘      │
├─────────────────────────────────────────────────────────────┤
│              AI Analysis Module (Python)                    │
│  ┌─────────────────────────────────────────────────────┐    │
│  │  LLM-powered Document Intelligence Engine           │    │
│  │  • Semantic Analysis    • Auto-completion           │    │
│  │  • Pattern Detection    • Anomaly Alerting          │    │
│  └─────────────────────────────────────────────────────┘    │
├─────────────────────────────────────────────────────────────┤
│                    MySQL Database                           │
└─────────────────────────────────────────────────────────────┘

Technology Stack

Backend

• Framework: Spring Boot 2.6.1
• Database: MySQL 8.0
• ORM: MyBatis
• WebSocket: Spring WebSocket
• Template Engine: FreeMarker
• PDF Generation: Apache POI, iTextPDF,Aspose

AI Module

• Runtime: Python 3.9+
• LLM Integration: OpenAI API / Anthropic Claude API
• ML Libraries: NumPy, Pandas

Installation

Prerequisites

• JDK 11+
• Maven 3.6+
• MySQL 8.0+
• Python 3.9+

Backend Setup

# Clone the repository
git clone https://github.com/your-org/mpcdsepc.git
cd mpcdsepc

# Configure database (edit src/main/resources/application.yml)
# Update MySQL connection settings

# Build the project
mvn clean install

# Run the application
mvn spring-boot:run

AI Module Setup

# Navigate to AI module
cd ai_engine

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/Mac
# or
venv\Scripts\activate     # Windows

# Install dependencies
pip install -r requirements.txt

# Configure API keys
cp config.example.yaml config.yaml
# Edit config.yaml with your API keys

AI Engine Module

The AI Engine is a Python-based module that integrates large language models for intelligent document processing:

Features

• Semantic Document Understanding: Uses transformer-based models to understand epidemic investigation document semantics
• Intelligent Auto-completion: Suggests field values based on context and historical data
• Anomaly Detection: Identifies unusual patterns in epidemiological data
• Natural Language Query: Query documents using natural language

Quick Start

from ai_engine import DocumentIntelligenceEngine

# Initialize the engine
engine = DocumentIntelligenceEngine(
    model="gpt-4",
    api_key="your-api-key",
    temperature=0.7
)

# Analyze a document
result = engine.analyze_document(document_text)
print(f"Analysis: {result}")

# Generate intelligent suggestions
suggestions = engine.generate_suggestions(context)
print(f"Suggestions: {suggestions}")

API Endpoints

Document Management

Method	Endpoint	Description
POST	/api/document/upload	Upload new document
GET	/api/document/{id}	Get document by ID
PUT	/api/document/{id}	Update document
DELETE	/api/document/{id}	Delete document
POST	/api/document/analyze	AI analysis of document

Person Management

Method	Endpoint	Description
GET	/api/person/list	List all persons
POST	/api/person/add	Add new person
PUT	/api/person/{id}	Update person info
DELETE	/api/person/{id}	Delete person

Report Generation

Method	Endpoint	Description
POST	/api/gen/word	Generate Word report
POST	/api/gen/pdf	Convert to PDF

Configuration

application.yml

server:
  port: 8080

spring:
  datasource:
    url: jdbc:mysql://localhost:3306/mpcdsepc
    username: root
    password: your-password
  servlet:
    multipart:
      max-file-size: 50MB
      max-request-size: 50MB

mybatis:
  mapper-locations: classpath:mapper/*.xml
  type-aliases-package: com.yytech.mpcdsepc.entity

Use Cases

1. Epidemic Investigation: City and district health workers collaborate on investigation documents
2. Contact Tracing: Track and manage contact relationships between confirmed cases
3. Report Generation: Automatically generate standardized epidemic investigation reports
4. Data Analysis: AI-powered insights into epidemic patterns and anomalies

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. Our contact: wrenty1985@gmail.com

License

MIT License

Acknowledgments

• Spring Boot Community
• MyBatis Community
• OpenAI/Anthropic for LLM capabilities

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Built with ❤️ for epidemic prevention efforts