生成并更新可视化产物 —— Obsidian 图谱配置与 Canvas 知识地图。交互式网页图谱视图位于 SPA 的 app/modules/graph.js（由 tools/serve.py 提供服务）。

To generate an Obsidian Canvas knowledge map, you can use a visualization tool that reads your wiki graph JSONL files and deterministically writes typed Canvas maps with semantic edge labels. This allows you to explore research structures visually without manual configuration.

Yes, you can automatically color code Obsidian graph nodes by entity type. The visualization process reads your knowledge graph data and produces Obsidian graph color configurations grouped by entity type, eliminating the need for manual color assignments.

You can create a focused subgraph by applying a BFS traversal to your knowledge graph data. This builds a Canvas neighborhood centered on a target node using configurable depth and optional filters for specific node and edge types.

The best way to visualize semantic edge labels is by generating a typed Canvas knowledge map. This process reads your graph datasets and outputs Canvas maps where edges are explicitly labeled by their semantic edge type for clear visual exploration.

No, the interactive knowledge graph visualization does not work as a standalone HTML file. Interactive exploration is routed through an SPA Graph module served by a local backend, replacing the deprecated standalone HTML output.

You do not need to manually configure Obsidian graph settings for your research workflow. The visualization process reads your configuration file and deterministically writes the Obsidian graph settings and Canvas outputs automatically.