Architecture Overview

DeepWiki is a modern AI-powered documentation generation system built with a scalable microservices architecture. This document provides a comprehensive overview of the system’s architecture, components, and design decisions.

High-Level System Architecture

Frontend Architecture

The frontend is built with Next.js 14, leveraging modern React patterns and TypeScript for type safety.

Component Structure

Key Frontend Features

  1. Server-Side Rendering (SSR)
    • Pre-renders pages for better SEO and initial load performance
    • Dynamic route generation for repository pages
  2. Real-time Communication
    • WebSocket connection for streaming chat responses
    • Progressive content rendering
  3. Internationalization (i18n)
    • Support for 10+ languages
    • Context-based language switching
  4. Responsive Design
    • Mobile-first approach
    • Adaptive layouts for different screen sizes

Backend Architecture

The backend is built with FastAPI, providing high-performance async capabilities and automatic API documentation.

API Structure

RAG Pipeline Architecture

The Retrieval-Augmented Generation (RAG) pipeline is the core of DeepWiki’s intelligence.

Data Flow

Wiki Generation Flow

Real-time Chat Flow

Component Interactions

Core Service Dependencies

Database and Storage Design

Storage Architecture

Cache Key Structure

deepwiki_cache_{repo_type}_{owner}_{repo}_{language}.json

Example:
deepwiki_cache_github_microsoft_vscode_en.json

Caching Strategies

Multi-Level Caching

  1. Wiki Cache (Persistent)
    • Full wiki structures stored as JSON
    • Language-specific caching
    • File-based for durability
  2. Vector Cache (In-Memory)
    • FAISS indices for fast retrieval
    • Rebuilt on startup from embeddings
  3. Conversation Cache (Session)
    • Dialog history per session
    • Memory-efficient circular buffer

Cache Invalidation

Security Architecture

Authentication & Authorization

Security Features

  1. API Security
    • CORS configuration for cross-origin requests
    • Environment-based API key management
    • Input validation and sanitization
  2. Data Protection
    • Token-based repository access
    • Secure storage of credentials
    • Encrypted communication channels
  3. Rate Limiting
    • Request throttling per IP
    • WebSocket connection limits
    • Resource usage monitoring

Scalability Considerations

Horizontal Scaling

Performance Optimizations

  1. Async Processing
    • Non-blocking I/O operations
    • Concurrent request handling
    • Stream processing for large responses
  2. Resource Management
    • Memory limits (6GB max, 2GB reserved)
    • Connection pooling
    • Garbage collection optimization
  3. Caching Strategy
    • Pre-computed wiki structures
    • Embedding reuse
    • Response streaming

Technology Stack

Frontend Technologies

CategoryTechnologyPurpose
FrameworkNext.js 14React framework with SSR
LanguageTypeScriptType safety
StylingTailwind CSSUtility-first CSS
UI LibraryRadix UIAccessible components
StateReact ContextGlobal state management
HTTPFetch APIREST communication
WebSocketNative WebSocketReal-time communication
Markdownreact-markdownContent rendering
DiagramsMermaidFlowchart rendering

Backend Technologies

CategoryTechnologyPurpose
FrameworkFastAPIHigh-performance API
LanguagePython 3.11+Backend development
ServerUvicornASGI server
Vector DBFAISSSimilarity search
ML FrameworkAdalFlowRAG implementation
LoggingPython loggingApplication logs
Environmentpython-dotenvConfiguration

AI/ML Stack

CategoryTechnologyPurpose
EmbeddingsOpenAI/GeminiText embeddings
GenerationMultiple LLMsContent generation
RAGAdalFlowRetrieval augmentation
Vector SearchFAISSSemantic search

Infrastructure

CategoryTechnologyPurpose
ContainerDockerApplication packaging
OrchestrationDocker ComposeService management
StorageFile SystemPersistent storage
Process MgmtSupervisorProcess control

Deployment Architecture

Best Practices & Design Principles

Architecture Principles

  1. Separation of Concerns
    • Clear boundaries between frontend and backend
    • Modular service design
    • Independent scaling capabilities
  2. Resilience
    • Graceful error handling
    • Fallback mechanisms
    • Health monitoring
  3. Performance
    • Async-first design
    • Efficient caching
    • Resource optimization
  4. Maintainability
    • Clean code architecture
    • Comprehensive logging
    • Type safety throughout

Development Guidelines

  1. Code Organization
    • Feature-based module structure
    • Consistent naming conventions
    • Separation of business logic
  2. Testing Strategy
    • Unit tests for core logic
    • Integration tests for APIs
    • End-to-end testing for critical flows
  3. Documentation
    • Inline code documentation
    • API documentation (OpenAPI)
    • Architecture decision records

Future Enhancements

Planned Improvements

  1. Scalability
    • Kubernetes deployment support
    • Distributed caching with Redis
    • Message queue integration
  2. Features
    • Real-time collaboration
    • Advanced analytics
    • Plugin system
  3. Performance
    • GraphQL API option
    • Edge caching
    • Optimized vector search

Architecture Evolution

The architecture is designed to evolve with:
  • Microservices decomposition
  • Event-driven architecture
  • Serverless function support
  • Multi-region deployment

Conclusion

DeepWiki’s architecture balances performance, scalability, and maintainability while providing a robust platform for AI-powered documentation generation. The modular design allows for easy extension and adaptation to changing requirements.