1.7 KiB
1.7 KiB
type, status, updated, tags
| type | status | updated | tags | |||
|---|---|---|---|---|---|---|
| service-design | active | 2026-05-21 |
|
Local RAG Index
Goal
Add retrieval over canonical workspace memory without replacing the human-readable profile project knowledge vault.
The local index is derived and disposable. If the index disagrees with Markdown, the Markdown wins.
Current Implementation
The first implementation is dependency-free and lexical:
scripts/aiw/indexer.py
It reads:
workspaces/<profile>/project-knowledge/**/*.md
and writes:
.aiw/indexes/<profile>/project-knowledge.jsonl
.aiw/indexes/<profile>/manifest.json
It skips:
workspaces/<profile>/project-knowledge/09-templates/
so Obsidian templates do not appear as real memory.
Commands
Build the index:
python3 scripts/aiw/indexer.py build --profile fidelity
Check index status:
python3 scripts/aiw/indexer.py status --profile fidelity
Search the index:
python3 scripts/aiw/indexer.py search "dismissal lifecycle" --profile fidelity
MCP Exposure
aiw-context-mcp exposes:
memory_hybrid_search
Current behavior:
- searches the derived local index when it exists
- returns cited paths, headings, snippets, scores, hashes, and mtimes
- falls back to live Markdown search when no index exists
- remains read-only
Future Upgrade Path
This layer can later add:
- full-text ranking
- embeddings
- Qdrant or Chroma as a local vector store
- hybrid lexical + semantic search
- reranking
- Mattermost evidence indexing with strict source filters
Do not make the vector store canonical. It should remain rebuildable from Markdown and selected evidence.