The Concept: Semantic Ontology Ingestion
Currently, the SQLite Native Edge Graph focuses primarily on physical/literal structure (e.g., mapping CLASS to FILE or ISSUE). However, Neo.mjs is heavily driven by abstract concepts—like "Application Engine", "Off the main thread", "Reactivity", and the "Agent SDK".
While these concepts exist in our markdown guides (e.g., learn/benefits/Introduction.md) and are vectorized in ChromaDB for similarity searches, they are completely absent from the structural topology of the graph itself.
We propose adding a Semantic Ontology Ingestor that extracts these concepts from markdown guides and structurally anchors them into the Native Graph.
The Rationale
- Closing the "Codebase Gap" hallucination: Once concepts are formal Nodes (e.g.
[Concept: Application Engine]), our algorithms will understand that these are conceptual constructs, not missing .js files. This aligns perfectly with our recent strict Type-Aware filtering optimizations.
- True Hybrid RAG: We can natively map
IMPLEMENTS edges between physical classes (like AppWorker) and abstract concepts (like Off the main thread). This allows subagents to traverse the graph from a conceptual feature request directly down to the literal classes that implement that pattern, rather than relying solely on fuzzy vector similarity.
Open Questions
- Extraction Mechanism: Should we use an LLM (Gemma4) pass during
sandman digestion to extract concepts from new guides automatically, or maintain a deterministic, source-of-truth concepts.json dictionary?
- Node Lifecycle: How do we handle updating or deprecating concepts as the framework strategy evolves?
- Relationship Typing: What should the Edge taxonomy look like? Should we use
IMPLEMENTS, DESCRIBED_IN, RELATED_TO_CONCEPT?
The Concept: Semantic Ontology Ingestion
Currently, the SQLite Native Edge Graph focuses primarily on physical/literal structure (e.g., mapping
CLASStoFILEorISSUE). However, Neo.mjs is heavily driven by abstract concepts—like "Application Engine", "Off the main thread", "Reactivity", and the "Agent SDK".While these concepts exist in our markdown guides (e.g.,
learn/benefits/Introduction.md) and are vectorized in ChromaDB for similarity searches, they are completely absent from the structural topology of the graph itself.We propose adding a Semantic Ontology Ingestor that extracts these concepts from markdown guides and structurally anchors them into the Native Graph.
The Rationale
[Concept: Application Engine]), our algorithms will understand that these are conceptual constructs, not missing.jsfiles. This aligns perfectly with our recent strict Type-Aware filtering optimizations.IMPLEMENTSedges between physical classes (likeAppWorker) and abstract concepts (likeOff the main thread). This allows subagents to traverse the graph from a conceptual feature request directly down to the literal classes that implement that pattern, rather than relying solely on fuzzy vector similarity.Open Questions
sandmandigestion to extract concepts from new guides automatically, or maintain a deterministic, source-of-truthconcepts.jsondictionary?IMPLEMENTS,DESCRIBED_IN,RELATED_TO_CONCEPT?