graphify

You can convert diverse file collections into an interactive knowledge graph by running graphify on a folder to parse files, extract relationships, and visualize community insights in HTML format.

Yes, graphify processes heterogeneous collections of documents, papers, images, and videos into a unified knowledge graph, extracting and inferring relationships for comprehensive discovery.

Yes, graphify relies on Python libraries to parse files, extract relationships, and visualize knowledge graphs, making it suitable for research, software architecture, and information organization.

Community detection groups related nodes within the generated knowledge graph, allowing you to analyze multi-source research data like papers and notes to uncover implicit links and structural clusters.

The best way to understand software architecture is transforming code folders into a visualized knowledge graph using graphify, which provides clear tagging of extracted or inferred relationships.

Yes, you need Python installed because graphify depends on Python libraries to parse heterogeneous file collections, extract relationships, and visualize the interactive knowledge graphs.