PaiPai - Instant Messaging IM based on GoZero microservices and AI large model applications

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📋 Project Overview

A modern social service platform based on microservices architecture, focusing on providing high-quality instant messaging, rich social interactions, and intelligent AI-enhanced experiences. The project adopts cloud-native design principles, combines mainstream technology stacks, and further integrates AI large model applications, aiming to build a secure, reliable, high-performance, and easily scalable social service solution.

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🚀 Overall Architecture

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🛠️ Core Technology Stack

Category	Technology Components	Recommended Version	Usage Description
Programming Language	Golang	1.21+	Primary backend development language
Microservices Framework	GoZero	1.8.5	Microservices development framework
Database	MySQL	8.0+	Relational data storage
	Redis	7.0+	Caching, session management
	MongoDB	6.0+	Document-based data storage
Message Queue	Kafka	3.5+	High-throughput message processing
	RabbitMQ	3.11+	Complex routing message queue
Service Discovery	ETCD	3.5+	Service discovery and configuration management
API Gateway	Apisix	3.7+	API gateway and traffic management
Monitoring & Observability	Prometheus	latest	Metrics collection and monitoring
	Grafana	latest	Data visualization dashboard
	Jaeger	latest	Distributed tracing
Logging System	Elasticsearch	latest	Log storage and retrieval
	Logstash	latest	Log collection and processing
	Kibana	latest	Log visualization and analysis
Container Orchestration	Docker	latest	Container runtime
	Kubernetes	latest	Container orchestration management
AI Applications/Integration	DeepSeek	-	Intelligent code review
	Eino	latest	Large model application framework

🏗️Architecture Layers

Architecture Layer	Technology Components	Functional Description
Access Layer	Apisix, Docker, Kubernetes	Traffic access, load balancing, container management
Service Layer	Golang, GoZero, ETCD	Business logic processing, service discovery and registration
Data Layer	MySQL, Redis, MongoDB	Data storage, caching, persistence
Message Layer	Kafka, RabbitMQ	Asynchronous message processing, system decoupling
Observability Layer	Prometheus, Grafana, Jaeger, ELK	System monitoring, log analysis, distributed tracing
Intelligence Layer	DeepSeek, Eino	AI large model integration, intelligent business processing

🔄System Data Flow

Data Flow	Technology Components	Protocol/Interface
Client Requests	Apisix → GoZero Microservices	HTTP/HTTPS/WebSocket
Inter-service Communication	Microservices inter-calls	gRPC/HTTP + ETCD service discovery
Message Processing	Kafka/RabbitMQ → Business processing	AMQP/MQTT/Custom
Data Persistence	→ MySQL/Redis/MongoDB	SQL/NoSQL interfaces
Monitoring Data	→ Prometheus/ELK	Metrics collection/Log collection
AI Large Model Integration	→ DeepSeek/Eino	REST API/gRPC

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📂 Project Structure

PaiPai/
├── apps/            # Core business services
│   ├── im/          # Instant Messaging service
│   ├── social/      # Social service
│   ├── task/        # Task message queue
│   ├── user/        # User service
│   └── eino_chat/   # AI service
├── components/      # Infrastructure components
│   ├── apisix/           # API gateway configuration
│   ├── apisix-dashboard/ # API gateway admin dashboard
│   ├── filebeat/         # Log collection
│   ├── grafana/          # Monitoring visualization
│   ├── kibana/           # Log analysis
│   ├── logstash/         # Log processing
│   ├── prometheus/       # Monitoring system
│   └── sail/             # Service orchestration
├── deploy/          # Deployment configuration files
│   ├── cicd/             # CI/CD, code review
│   ├── dockerfile/       # Docker builds
│   ├── makefile/         # Build scripts
│   ├── script/           # Startup and test scripts
│   └── sql/              # Database initialization
├── pkg/             # Common utility packages
├── test/            # Test code and examples
├── go.mod           
├── go.sum           
├── docker-compose.yaml   # Container orchestration configuration
├── PORT_MAP.md      # Port mapping documentation
└── README.md        # Project documentation

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🌟 Key Features

• High Availability Microservices Architecture
  • Rate limiting, circuit breaking, and fallback mechanisms
  • High availability, high performance, and high scalability design
• Efficient IM Communication Engine
  • WebSocket + gRPC high-efficiency communication
  • Intelligent routing node message relay optimization
  • Ensures high concurrency and low latency
• Comprehensive Message System
  • Full scenario coverage: text/image/voice/video/file/location support
  • Message roaming with cloud-based historical message storage
  • Message security encryption and privacy protection
• Deep Integration of AI + Cloud Native
  • AI-powered intelligent code audit
  • AI large model application integration
  • LLM-driven intelligent response capabilities
  • Message semantic analysis and risk identification
  • Efficient enterprise knowledge base construction
  • AIOps for automatic anomaly traffic identification and prevention
• Automated Containerized Deployment
  • Full Docker containerization
  • Intelligent orchestration deployment
• Full-Link Monitoring and Assurance
  • Metrics/Logging/Tracing integrated monitoring
  • Comprehensive monitoring with Prometheus + Grafana + Jaeger

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🤝 Contributing Guidelines

We welcome contributions to the project! Thank you for your interest!

1. Fork the repository and clone it locally
2. Create a branch for your development (git checkout -b feature/your-feature)
3. Commit your code and ensure all tests pass
4. Create a Pull Request describing your changes
5. Wait for code review and make modifications based on feedback

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✨ Continuously Improving and Updating... ✨