DeepWiki Application Integration Guide

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Introduction

This guide provides comprehensive instructions for integrating and utilizing the DeepWiki application within ELITEA. DeepWiki is an advanced AI-powered documentation generator that analyzes code repositories (GitHub, GitLab, Bitbucket, ADO Repos) to create comprehensive wikis through intelligent code analysis and natural language processing. By following this guide, you will enable your ELITEA Agents to automatically generate documentation, answer questions about codebases, and perform deep research on repository functionality. Brief Overview of DeepWiki DeepWiki is a specialized application that transforms code repositories into searchable, structured documentation. It combines multiple AI technologies to provide:

• Automated Wiki Generation: Creates comprehensive documentation from repository analysis, including architecture overviews, API documentation, and code explanations.
• Intelligent Code Analysis: Uses Enhanced Unified Graph Builder (EUGB) to understand code structure, dependencies, and relationships across the repository.
• Interactive Q&A: Enables natural language questions about the codebase with context-aware answers based on the generated knowledge base.
• Deep Research Capabilities: Performs multi-step analysis with planning and investigation to answer complex questions about repository functionality.
• Diagram Generation: Automatically creates Mermaid diagrams to visualize architecture and technical concepts.

Integrating DeepWiki with ELITEA empowers your Agents to understand, document, and explain codebases automatically, making it easier to onboard new team members, maintain documentation, and answer technical questions about your projects.

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Prerequisites

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System Integration with ELITEA

DeepWiki integrates with ELITEA as an Application accessible through the Apps menu. It provides specialized documentation generation and analysis tools with a built-in user interface for managing wiki content and repository analysis workflows.

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Create DeepWiki Application

1. Navigate to Apps Menu: Open the sidebar and select Apps.
2. Create New App: Click the + Create button.
3. Select DeepWiki: Choose Deepwiki as the application type.
4. Configure Application Settings:

   Parameter	Required	Description	Example
   Toolkit Name	Yes	Descriptive name for the application	”Project Documentation Generator”
   Description	No	Optional description of the application’s purpose	”Generates wiki documentation for main project repo”
   LLM Model	Yes	LLM model for text generation and wiki content creation	”gpt-4”, “claude-sonnet-3-5”
   Embedding Model	No	Embedding model for vector search and retrieval (default: text-embedding-3-small)	“text-embedding-3-small”
   Code Toolkit	Yes	Code toolkit (GitHub, GitLab, Bitbucket, or ADO Repos) for accessing repository data	Select from configured toolkits
   Max Tokens	Yes	Maximum tokens for LLM responses (default: 64000)	64000, 128000
   Tools	No	Select which tools to enable (default: all tools)	generate_wiki, ask, deep_research

5. Save Application: Click Create to save the configuration.

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Available Tools

DeepWiki provides three primary tools for documentation generation and repository analysis:

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How DeepWiki Analyzes Repositories

DeepWiki automatically analyzes your code repositories to create comprehensive documentation. The analysis process runs in the background when you use the generate_wiki tool and includes:

• Code Structure Analysis: Examines repository organization, file relationships, and dependencies
• Content Extraction: Processes source code, documentation files, and comments
• Knowledge Graph Creation: Builds connections between different parts of your codebase
• Vector Store Generation: Creates searchable indexes for intelligent question answering

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Using the DeepWiki Interface

Once you create a DeepWiki application, you can access its built-in user interface to generate documentation and interact with your repository’s wiki. Accessing the Interface

1. Open DeepWiki App: Navigate to the Apps menu in the sidebar
2. Select Your App: Click on your DeepWiki application from the list
3. View Interface: The DeepWiki interface opens, displaying:
   • Left Sidebar: Navigation panel for browsing generated wiki pages organized by sections
   • Main Content Area: Displays wiki content with formatted markdown, code blocks, and diagrams
   • Chat Panel: (Right side) For asking questions about your codebase using natural language

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Wiki Generation Workflow

Once you’re in the DeepWiki application interface, follow these steps to generate documentation: Step 1: Initiate Wiki Generation

1. In the left sidebar, locate the “Generate Wiki” button
2. Check the slot availability indicator:
   • Green indicator = slots available, generation can start
   • If all slots are busy, wait for running generations to complete
3. Click “Generate Wiki” button
4. A confirmation dialog appears: “Generate Wiki Documentation?”
   • Click “Update” to proceed with generation, or “Cancel” to abort

Step 2: Monitor Generation Progress Once generation starts, monitor progress through the interface:

• Progress Bar: Appears below the Generate Wiki button
• Status Messages: Real-time updates show current operations (e.g., “Analyzing repository structure…”, “Building knowledge graph…”)
• Elapsed Time: Counter displays how long generation has been running

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Access Generated Documentation

Once generation completes:

1. The left sidebar populates with navigation sections
2. Click on any section to expand and view wiki pages
3. Select a page to view its content in the main area
4. Generated content includes:
   • Formatted markdown documentation
   • Code examples with syntax highlighting
   • Mermaid diagrams for visualizations
   • Cross-references between related topics

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Edit Wiki Pages

DeepWiki allows you to edit generated documentation directly in the interface to refine or customize content: To Edit a Page:

1. Navigate to the wiki page you want to modify
2. Click the Edit button (pencil icon) in the top-right corner of the page
3. The page opens in an editor with markdown formatting
4. Make your changes to the content
5. Click Save to apply changes or Cancel to discard

Editing Capabilities:

• Markdown Editing: Full markdown support for formatting text, adding links, creating lists, and more
• Code Blocks: Modify or add code examples with syntax highlighting
• Diagrams: Edit Mermaid diagram definitions to update visualizations
• Content Organization: Restructure sections, add new information, or clarify existing content

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Update Generated Wiki

When your repository code changes, you can regenerate the wiki to update all sections with the latest information from your codebase. To Update Documentation:

1. Make changes to your repository code, comments, or documentation files
2. Commit and push your changes to the repository
3. Return to the DeepWiki application interface
4. Click the “Generate Wiki” button in the left sidebar
5. Confirm the regeneration in the dialog
6. DeepWiki will re-analyze the repository and update all sections

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Wiki Artifacts Storage

When you generate a wiki, DeepWiki automatically creates a bucket named wiki_artifacts and stores all generated documentation files there. You can access and manage these files through the Artifacts Menu in ELITEA. Generated Documentation Files:

• Wiki Pages: Markdown files containing documentation about your repository (architecture, APIs, code explanations)
• Diagrams: Visual representations of your code structure and relationships
• Organization Structure: Files are grouped by sections and topics for easy navigation

All generated artifacts remain available in the bucket for download, sharing, or archival purposes.

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Managing Settings

The Settings panel allows you to view and modify your DeepWiki application configuration. Opening Settings:

1. In the left sidebar, click the “Settings” button (below Generate Wiki button)
2. The Settings panel opens from the right side

Settings Parameters: Managing Wiki Data:

• Delete Wiki: Removes all generated wiki artifacts from the bucket
  • Use this to clean up old documentation before regenerating
  • This action cannot be undone

Saving Changes:

1. Modify any editable configuration field
2. Click “Save Settings” button at the bottom
3. Settings are immediately applied to the toolkit

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Use the Chat Interface

After wiki generation completes, use the chat interface to query your repository’s documentation and get AI-powered answers about your codebase. Opening the Chat:

1. Click the Chat icon on the right edge of the interface
2. The chat panel slides open from the right side

Selecting a Query Tool: DeepWiki provides two tools for different types of questions: Using the Chat:

1. Select your preferred tool by clicking on the Ask or Research tab
2. Type your question in natural language
3. Press Enter or click Send
4. Review the AI-generated answer with references to the wiki content

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Best Practices

Wiki Generation

1. Clear Query Descriptions: Provide specific, detailed queries for generate_wiki to get focused documentation
2. Incremental Documentation: Generate wikis for specific areas rather than entire large repositories at once
3. Asynchronous for Large Repos: Use async invocation for repositories with thousands of files
4. Monitor Slots: Check slot availability before starting generation to avoid queuing

Question Asking

1. Specific Questions: Ask focused questions rather than broad “explain everything” queries
2. Use Context Overrides: Pin to specific wiki versions when consistency is important
3. Progressive Refinement: Start with ask for quick answers, use deep_research for complex topics
4. Reference Generated Wiki: Review generated wiki pages before asking questions to understand available context

Resource Management

1. Cleanup Old Wikis: Regularly remove outdated wiki artifacts from the bucket
2. Slot Monitoring: Be aware of DEEPWIKI_MAX_PARALLEL_WORKERS limits in your environment
3. Cache Reuse: Use repo_identifier_override to leverage existing caches across multiple queries
4. Bucket Organization: Use separate buckets for different projects or teams

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Troubleshooting

Wiki Generation Fails

Possible causes:

• Repository too large or complex
• Insufficient LLM token limits
• Code toolkit authentication issues
• Missing bucket permissions

Solutions:

• Verify code toolkit is properly configured and authenticated
• Increase max_tokens parameter if needed
• Check bucket exists and has write permissions
• Review application configuration for correct code toolkit ID
• Check server logs for detailed error messages

Service Busy - Slots Full

Possible causes:

• Maximum parallel workers reached (controlled by DEEPWIKI_MAX_PARALLEL_WORKERS)
• Other wiki generations in progress

Solutions:

• Wait for current generations to complete
• Check slot status in the UI
• Contact administrator to increase worker limits if needed
• Consider using asynchronous invocation and polling

Ask/Deep Research Returns Empty or Incorrect Answers

Possible causes:

• Wiki not generated yet
• Question outside scope of indexed repository
• Embedding model mismatch between generation and query

Solutions:

• Ensure generate_wiki completed successfully
• Verify embedding model configuration matches generation
• Check wiki artifacts were created in the bucket
• Rephrase question to match repository context
• Review generated wiki pages to understand available information

Slow Performance

Possible causes:

• Using GitHub API-based indexing instead of filesystem
• Large repository with many files
• Network latency issues

Solutions:

• Verify filesystem-based indexing is enabled (default)
• Use asynchronous invocation for large repositories
• Consider generating wikis for specific subdirectories
• Check network connectivity if using API-based indexing

Code Toolkit Configuration Error

Possible causes:

• Code toolkit not properly configured or expanded
• Missing repository authentication credentials
• Invalid toolkit ID reference
• Toolkit deleted or no longer accessible

Solutions:

• Verify code toolkit exists and is properly configured in Toolkits menu
• Check authentication credentials (access tokens, SSH keys) are valid
• Ensure toolkit has permissions to access the target repository
• Re-select the code toolkit in DeepWiki application settings
• Test code toolkit independently before using with DeepWiki

LLM or Embedding Model Configuration Issues

Possible causes:

• LLM model not accessible or quota exceeded
• Embedding model mismatch between generation and querying
• Model configuration changed after wiki generation
• Insufficient tokens allocated for large repositories

Solutions:

• Verify LLM model is properly configured and accessible
• Confirm API keys and credentials are valid
• Check model quota limits haven’t been exceeded
• Ensure embedding model remains consistent across operations
• Increase max_tokens setting for large codebases
• Review model compatibility in ELITEA integrations

Memory or Resource Exhaustion

Possible causes:

• Repository too large for available memory
• Too many concurrent wiki generations
• Insufficient system resources allocated
• Memory leak in long-running operations

Solutions:

• Generate wikis for specific subdirectories instead of entire repository
• Reduce max_files parameter to limit scope
• Wait for other generations to complete before starting new ones
• Contact administrator to increase memory limits
• Monitor system resources during generation
• Consider using K8s deployment with resource limits

Repository Access or Clone Failures

Possible causes:

• Network connectivity issues
• Repository authentication failures
• Repository deleted or moved
• Branch doesn’t exist or is protected
• Firewall blocking Git operations

Solutions:

• Verify repository URL and branch name are correct
• Check network connectivity to repository host
• Ensure access tokens have proper permissions (read access minimum)
• Confirm repository still exists and is accessible
• Test repository access using code toolkit independently
• Check for firewall or proxy issues blocking Git operations
• Verify branch exists in the repository

Bucket or Storage Permission Issues

Possible causes:

• Bucket doesn’t exist or was deleted
• Insufficient write permissions to bucket
• Bucket name contains invalid characters
• Storage quota exceeded
• Network issues accessing storage

Solutions:

• Verify bucket exists in Artifacts menu
• Check bucket name uses only lowercase letters, numbers, and hyphens
• Ensure service account has write permissions to bucket
• Confirm storage quota hasn’t been exceeded
• Test bucket access by uploading a test file
• Contact administrator to verify storage configuration
• Review bucket permissions in storage settings

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FAQ

How long does wiki generation take?

Generation time depends on repository size and complexity:

• Small repositories (< 100 files): 2-5 minutes
• Medium repositories (100-1000 files): 5-15 minutes
• Large repositories (> 1000 files): 15-30+ minutes

Use asynchronous invocation for large repositories to avoid timeouts.

Can I generate wikis for private repositories?

Yes, as long as your configured code toolkit (GitHub, GitLab, etc.) has proper authentication and permissions to access the private repository.

How do I update the wiki when the repository changes?

Run generate_wiki again with the same or different query. DeepWiki will:

• Detect repository changes
• Update the vector store and knowledge graph
• Regenerate wiki content
• Preserve the analysis cache where appropriate

What happens if I run out of worker slots?

You’ll receive a [SERVICE_BUSY] message indicating slots are full. You can:

• Wait for current generations to complete
• Contact your administrator to increase DEEPWIKI_MAX_PARALLEL_WORKERS

Can multiple agents use the same DeepWiki application?

Yes, multiple agents can use the same application for ask and deep_research operations. However, generate_wiki operations are subject to slot limits and may need to queue.

What LLM models work best with DeepWiki?

DeepWiki works with any configured LLM model in ELITEA. For best results:

• Use models with large context windows (32k+ tokens)
• GPT-4 or Claude Sonnet recommended for complex documentation
• Ensure max_tokens is set appropriately for your model

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