graphify

Name: graphify
Availability: InStock
Author: irootpro

Build knowledge graphs from code, documentation, and images.

Updated Jan 13, 2024

Search Tags:#code analysis #data extraction #knowledge graph #document analysis #graph traversal

Ready to run

npx skills add https://github.com/iRootPro/dotfiles --skill graphify-irootpro

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: graphify
Source: https://github.com/iRootPro/dotfiles/tree/main/.config/opencode/skills/graphify
Command: npx skills add https://github.com/iRootPro/dotfiles --skill graphify-irootpro

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires graphifyy, networkx, requests, spacy, pandas, numpy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill converts codebases, documentation, and other digital content into navigable knowledge graphs, enabling deeper understanding and analysis.

Core Features & Use Cases

Knowledge Graph Creation: Transform any folder of code, documents, or images into a knowledge graph.
Graph Traversal: Perform searches and query the graph to explore relationships and patterns.
Output Generation: Export the graph as interactive HTML, JSON, or export to Neo4j, FalkorDB, etc.
Use Case: If you have a complex codebase and you want to understand the relationships between components or find the shortest path between two modules, this Skill can help.

Quick Start

Use the graphify skill to create a knowledge graph from the current directory.

Frequently Asked Questions about graphify

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate a knowledge graph from a codebase to understand module relationships?▼

To generate a knowledge graph from a codebase, this Skill extracts entities, relationships, and semantic information from your files to create a navigable graph representation. It transforms directories of code into interactive HTML or JSON outputs for deeper analysis.

What is graph traversal and how does it help analyze complex codebases?▼

Graph traversal in this context involves querying the generated knowledge graph to explore relationships and patterns. It enables you to find the shortest path between two modules or trace component interactions within your codebase.

Do I need Python and specific libraries to extract knowledge graphs from documents?▼

Yes, extracting knowledge graphs from documents requires Python and specific libraries including graphifyy, networkx, spacy, pandas, and numpy. These dependencies handle text and code processing to build the semantic graph representation.

Can I export the generated knowledge graph to Neo4j or FalkorDB?▼

You can export the generated knowledge graph directly to Neo4j, FalkorDB, or output it as interactive HTML and JSON. This allows you to integrate the extracted entity relationships into your existing graph database infrastructure.

Does this knowledge graph generation tool work with images and documentation?▼

This tool builds knowledge graphs from code, documentation, and images. It extracts semantic information across these digital artifacts, allowing you to analyze relationships within diverse folders of mixed digital content.