LLM-based code reader for legacy, obfuscated, or undocumented codebases
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CodeAsk is an LLM-powered desktop application designed to help developers understand and maintain complex codebases. It addresses common pain points like poorly documented or legacy code by providing AI-driven analysis, security vulnerability detection, and code quality assessments. The target audience includes individual developers and teams struggling with code comprehension, aiming to boost productivity and reduce maintenance overhead.
How It Works
CodeAsk leverages Electron for its desktop application framework, integrating React for the UI and Monaco Editor for code viewing. It utilizes Large Language Models (LLMs) to perform code analysis, with users able to configure various models and custom prompts via a plugin system. The application supports both single-file and global code analysis, generating reports that can be viewed within the application or shared via a .codeaskdata
file. An IntelliJ plugin is also available for IDE integration.
Quick Start & Requirements
npm install --legacy-peer-deps
npm run start
Highlighted Details
Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
The project is primarily developed in Chinese, with English and Japanese translations provided. Prompt templates are largely generated by DeepSeek and may require user testing and adjustment based on specific models and code. The IntelliJ plugin is not yet available on the official marketplace and requires manual installation.
3 months ago
1 day