DeepWiki-Open’s core feature is intelligent wiki generation that transforms any repository into comprehensive, navigable documentation. This guide covers all aspects of wiki generation, customization, and optimization.

How Wiki Generation Works

1

Repository Analysis

DeepWiki clones and analyzes the repository structure, identifying:
  • File types and programming languages
  • Directory organization and architecture patterns
  • Dependencies and configuration files
  • Documentation and README files
  • Test structures and examples
Repository successfully analyzed and indexed
2

Code Embedding

Creates vector embeddings of code content for intelligent retrieval:
  • Function and class definitions
  • Comments and documentation
  • Configuration settings
  • API endpoints and interfaces
  • Database schemas and models
Embeddings enable semantic search and context-aware documentation generation.
3

AI-Powered Documentation

Uses your selected AI model to generate:
  • Project overview and purpose
  • Installation and setup instructions
  • Architecture explanations
  • Component relationships
  • Usage examples and best practices
Different AI models produce varying documentation styles. Experiment to find your preference.
4

Visual Diagram Generation

Automatically creates Mermaid diagrams showing:
  • System architecture
  • Data flow and processing
  • Component relationships
  • Database schemas
  • API endpoint structures
Interactive diagrams generated and embedded in documentation

Generation Options

Model Selection

Choose the best AI model for your documentation needs:

Generation Parameters

Repository Types & Optimization

Programming Languages

DeepWiki optimizes documentation generation for different languages:
JavaScript/TypeScript:
  • React, Vue, Angular component analysis
  • Node.js server architecture
  • API endpoint documentation
  • Package.json and dependency analysis
Python:
  • Django/Flask application structure
  • FastAPI endpoint documentation
  • Class and function analysis
  • Requirements and virtual environment setup
Examples:
  • Express.js servers → API endpoint documentation
  • React apps → Component hierarchy and props
  • Django projects → Model, view, template analysis

Repository Size Optimization

Customizing Generated Documentation

Content Customization

1

Repository-Specific Prompts

DeepWiki automatically adapts to repository types, but you can customize the focus:
{
  "focus_areas": [
    "architecture_patterns",
    "api_documentation", 
    "deployment_setup",
    "security_implementation"
  ],
  "exclude_areas": [
    "test_files",
    "generated_code",
    "vendor_dependencies"
  ]
}
2

Documentation Depth

Control the level of detail in generated documentation:
  • High Detail: Complete analysis of all components
  • Medium Detail: Focus on public APIs and main components
  • Overview: High-level architecture and key features only
{
  "detail_level": "medium",
  "include_private_methods": false,
  "focus_on_public_api": true
}
3

Diagram Types

Specify which types of diagrams to generate:
  • Architecture diagrams: System components and relationships
  • Data flow diagrams: Information processing flow
  • Database diagrams: Schema and relationships
  • API diagrams: Endpoint structure and data flow
  • Process diagrams: Workflow and business logic
{
  "diagram_types": [
    "architecture",
    "data_flow", 
    "api_structure"
  ]
}

Output Format Options

Format: Hierarchical pages with cross-referencesBest for:
  • General documentation browsing
  • Team onboarding
  • Project understanding
  • Code exploration
Features:
  • Navigation tree
  • Search functionality
  • Cross-page linking
  • Embedded diagrams

Quality Optimization

Improving Documentation Quality

Troubleshooting Generation Issues

Advanced Features

Multi-Language Support

DeepWiki automatically detects and optimizes for repository languages:
Automatic detection of:
  • Primary language (most files)
  • Secondary languages
  • Framework combinations
  • Build system integration
Smart documentation:
  • Language-specific setup instructions
  • Cross-language integration points
  • Build pipeline explanation
  • Dependency management per language

Integration Workflows

1

CI/CD Integration

Automate wiki generation in your development pipeline:
# GitHub Actions example
name: Generate Documentation
on:
  push:
    branches: [main]
  pull_request:
    branches: [main]

jobs:
  docs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Generate Wiki
        run: |
          curl -X POST "${{ secrets.DEEPWIKI_URL }}/wiki/generate" \
            -H "Content-Type: application/json" \
            -d '{
              "repo_url": "${{ github.server_url }}/${{ github.repository }}",
              "model_provider": "google",
              "force_regenerate": true
            }'
2

Webhook Integration

Automatically update documentation on repository changes:
// Webhook handler example
app.post('/webhook/repository', (req, res) => {
  const { repository, commits } = req.body;
  
  // Check if significant changes occurred
  const significantFiles = commits.some(commit => 
    commit.modified.some(file => 
      file.includes('src/') || 
      file.includes('README') ||
      file.includes('package.json')
    )
  );
  
  if (significantFiles) {
    // Trigger documentation regeneration
    generateWiki({
      repo_url: repository.html_url,
      force_regenerate: true
    });
  }
});

Next Steps