Files
hermes-brain/ideas/native-org-knowledge-base.org
Hermes 3f38e87f4f Remove versioned roadmap from Passepartout docs
All version numbers stripped from roadmap across all brain documents:
- passepartout-economics.org: v0.x.x version table → phase-name-only table,
  v1.0.0 → 'neurosymbolic maturity', versioned text references → capability
  descriptions. Retained phase names (Phase 0-7) and line estimates as they
  describe capabilities, not version milestones.
- competitive-analysis-2026-05.org: version references removed
- time-estimates.org: v0.4.0 → 'initial state', v1.0.0 → 'neurosymbolic maturity'
- native-org-knowledge-base.org: v0.8.0-v0.9.0 → capability-based target
2026-05-23 06:24:20 +00:00

82 lines
3.2 KiB
Org Mode

:PROPERTIES:
:ID: 7f4e6b9a-2c1d-5e8f-9a3b-6d7c4e5f2a1b
:CREATED: [2026-05-23 Sat]
:END:
#+title: Passepartout Native Org-Mode Knowledge Base
#+filetags: :passepartout:roadmap:knowledge:org:gbrain:
** What
Passepartout should be able to use Org-mode files directly as its
knowledge base — no pandoc conversion, no markdown intermediary.
Currently gbrain provides vector search + entity linking over markdown,
but we bridge via a conversion layer (org → pandoc → markdown → gbrain).
This loses Org-mode semantics: properties drawers become flat YAML, tag
inheritance is lost, file: links become relative markdown links, TODO
states vanish, and the tree structure (headings with content subtrees)
collapses into flat markdown headings.
** Why
Org-mode's data model is strictly richer than markdown's. A Passepartout
that can ingest, index, and query org files natively has:
- Property-based entity extraction (no separate links: frontmatter needed)
- Tag-inheritance for automatic categorization
- TODO/priority/timestamps for knowledge freshness signals
- ID-based stable cross-references (org-id) that survive file moves
- Heading-level chunking (one heading = one knowledge unit)
- The same file format for everything — no split between "authoring format"
and "knowledge base format"
** What it replaces
The current pipeline: org file → pandoc → markdown file → gbrain import →
gbrain embed → gbrain query. This is four serial steps with a conversion
at each boundary that degrades the data model.
The target: org file → (Passepartout-native indexer) → query. Zero
conversion, zero data loss.
** Architecture sketch
A Passepartout-native knowledge module that directly ingests
ideas/*.org:
- Parser: extract each heading as a chunk. Preserve:
- Heading path (H1 → H2 → H3) as a hierarchical path
- Properties drawer as structured metadata
- file: links as typed entity references
- org-id as stable identifier
- Tags (inherited from parent headings)
- TODO state, priority, timestamps
- Embedder: vector-embed each heading chunk with metadata prefix
- Query: hybrid search over headings + full-text over content.
Result includes the heading path + sibling headings for context.
- Cross-reference graph: build a typed entity graph from:
- file: links → typed reference
- org-id links → stable cross-doc reference
- Tag co-occurrence → implicit relationship
- Same-property values → attribute-based grouping
- Dream cycle: auto-discover entities from org properties and file:
links. Enrich thin sections. Flag sections with stale timestamps.
** Priority
Below the gate stack and ACL2 planner (core dependencies) but above
the Lisp Machine hardware. Target: after TUI stabilization and eval harness, once Screamer
planner is stable enough to route queries through the knowledge base.
The short-term bridge (current) is gbrain with nightly org→md sync.
This is adequate while the gate stack and planner are the priority.
The native org module replaces gbrain entirely once built.
** See also
[[file:../../concepts/compliance-framework-mapping.org][Compliance framework mapping]]
[[file:../../ideas/passepartout-economics.org][Passepartout economics]]