AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
翻译准备中
A rag + rag-graph native code intelligence layer for Java microservice estates, exposed to LLM agents via CLI
翻译准备中
开发工具Python · JavaGitHub @HumanBean17自行安装运营者未确认
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正在加载完整 README。 以下为已保存的摘录。
A graph-native code intelligence layer for Java microservice estates, surfaced through the jrag CLI — one command per engineering intent. A legacy MCP server (search / find / describe / neighbors / resolve) is also available for existing setups. Both are thin surfaces over the same AST Graph: a deterministic property graph extracted from Java source with tree-sitter, stored locally in LadybugDB (graph) alongside a LanceDB vector index (chunks). There is no server to host and no cloud round-trip — the index lives on your disk and your source never leaves the machine.查看完整 README ↗目前无法加载完整 README。请通过原文链接阅读。 以下为已保存的摘录。
A graph-native code intelligence layer for Java microservice estates, surfaced through the jrag CLI — one command per engineering intent. A legacy MCP server (search / find / describe / neighbors / resolve) is also available for existing setups. Both are thin surfaces over the same AST Graph: a deterministic property graph extracted from Java source with tree-sitter, stored locally in LadybugDB (graph) alongside a LanceDB vector index (chunks). There is no server to host and no cloud round-trip — the index lives on your disk and your source never leaves the machine.查看完整 README ↗