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