Problem
The queryKnowledgeBase.mjs script currently reloads and processes the entire knowledge base JSON file on every query. This is slow and memory-intensive, especially as the knowledge base grows.
Solution
- Pre-process Inheritance: In
embedKnowledgeBase.mjs, load the full knowledge base, build an inheritance map, and then pre-calculate the full inheritanceChain for each chunk. Store this inheritanceChain array in the metadata for each chunk in ChromaDB.
- Simplify Query Script: Modify
queryKnowledgeBase.mjs to be lightweight and fast.
- Remove the code that reads the local JSON file entirely.
- For scoring, use the
inheritanceChain provided in the metadata from the query result. This avoids expensive file I/O and graph traversal on every query.
- Keep the dynamic keyword-based scoring logic within the query script, as it depends on the user's input.
Benefits
- Significantly faster and more memory-efficient queries.
- Better separation of concerns (
create -> score & embed -> query).
- More scalable architecture.
Problem
The
queryKnowledgeBase.mjsscript currently reloads and processes the entire knowledge base JSON file on every query. This is slow and memory-intensive, especially as the knowledge base grows.Solution
embedKnowledgeBase.mjs, load the full knowledge base, build an inheritance map, and then pre-calculate the fullinheritanceChainfor each chunk. Store thisinheritanceChainarray in the metadata for each chunk in ChromaDB.queryKnowledgeBase.mjsto be lightweight and fast.inheritanceChainprovided in the metadata from the query result. This avoids expensive file I/O and graph traversal on every query.Benefits
create->score & embed->query).