Can't understand GitHub code? This AI tool just made every GitHub project in the world speak
AI technology makes code reading and understanding easier than ever before. The DeepWiki project provides real-time communication and instantly updated documentation support for GitHub projects around the world.
Core content:
1. Introduction to the DeepWiki project and how to use it
2. Feature highlights: conversational documentation, in-depth research, on-demand indexing, etc.
3. Technical exploration: understanding the global structure and submission history, and building a project knowledge graph
Remember Devin, the world's first AI software engineer? Its creator, Cognition Labs, has just launched a project called DeepWiki . In short, this is a grand plan: to provide real-time communication and instant update documents for every GitHub code repository (Repo) in the world.
You can think of it as a "deep dive" tool specifically for GitHub, powered by Devin technology.
Highlights: Free, no registration required, available immediately
The most important thing is that for open source projects, this service is completely free and does not even require registration.
How to use it? It's very simple:
1. Visit deepwiki.com to explore the Wikis of popular open source projects that have been included 2. Or, more directly: put the URL of any GitHub repository you are browsing in github.comReplace withdeepwiki.com, you can seamlessly jump to the DeepWiki page of the repository
What can be done?
Conversational documentation: You can "ask" questions directly to the code base, and DeepWiki will try to understand your questions and give document-level answers
Deep Research: For complex questions, you can turn on this feature to allow AI Agent to conduct more in-depth analysis and answers
On-demand indexing: If the public repository you care about has not been included, you can request DeepWiki to index it for you.
Private warehouse support: For private warehouses, you can get services by registering a Devin account (devin.ai)
Easy sharing: Generated Wiki pages and Q&A results can be shared via links, making it easier for team members to keep information synchronized
Investment and scale
Cognition Labs has invested a lot in DeepWiki:
• About 30,000 GitHub repositories have been indexed • Processed over 4 billion lines of code • The computational cost of the indexing process alone was over $300,000 • A total of more than 100 billion tokens have been processed
It is said that the average cost of indexing a repository is about $12, but it is currently completely free for all open source projects.
Technical Exploration: Understanding Global Structure and Commit History
We know that LLM is already very capable of understanding local code, but it is really difficult to grasp the global structure of a large code base. DeepWiki's core technology is designed to solve this problem:
1. Hierarchical system decomposition: It first decomposes the code base into a hierarchical high-level systems structure 2. System-level Wiki generation: Generate a corresponding Wiki page for each identified system to build a knowledge graph for the entire project
In addition, DeepWiki also uses a very valuable signal: code commit history . By analyzing "which files are often modified by which developers together" (which can be represented as a graph), DeepWiki can mine hidden patterns, module boundaries, and developer collaboration relationships in the code base, which are key information for understanding complex projects.
