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Architecture

Overview

Etz Chaim AI is organized in three layers :

  1. Specification corpus (internal) — 1696 specification items with epistemic labeling, concepts, mappings, and cross-references.
  2. Specification bridge (internal) — indexed loader exposing the corpus via a five-method API (load by id, by concept, by module, search).
  3. Operational modules — Python packages implementing the cognitive faculties, mature configurations, and probes, respecting layered composition discipline and adversarial testing.

For details on the structural framework that inspired this organization, see docs/advanced.md. It is informational only — not required to use or contribute.

Sequential consolidation

The project follows a strict consolidation order across the cognitive faculties : the foundational faculty is built first, each subsequent faculty depending on those already consolidated. Concretely : memory → introspection → persistence → harmony → contraction → expansion → bridge → causal → insight → meta-orchestrator.

Each faculty is consolidated (qualification tests green, 7 calibration parameters exposed) before the next is started.

Module map

Core specification infrastructure

Module Role
bridge/ Specification loader (1696 items)
internal corpus Source assertions (specifications + relations + principles)

Cognitive faculty modules (v0.1.0)

Module Role
explorationengine/ Cross-domain exploration
autojudge/ Adversarial judgment
dissensuengine/ Productive tension / contradiction
insightforge/ Insight generation
causalengine/ Causal reasoning
selfmap/ Self-mapping
epistememory/ Memory foundation
failuretoinsight/ Failure learning

Mature configurations

Six configuration layers (compose internal faculties into operational units) : - Highest-level invariants - Strategic meta-orchestrator - Generative configuration - Structuring configuration - Execution configuration - Interface configuration

Public API exposes them as Configuration instances. Internal file paths use domain-specific naming — see docs/internal/architecture.md for the mapping.

Dedicated engines

Module Role
configurations/ Cross-configuration coupling + persistent faculty trace
probes/orchestrator.py Probe orchestrator
probes/rectification.py 3-mode rectification

Layered composition discipline

No module writes directly to the aggregate overall_score. Boosts pass through faculties (set_faculty) and overall is always computed from faculties. A static check rejects any code that bypasses this discipline.

Persistent trace coefficient

Every cross-configuration boost leaves a persistent trace coefficient on each faculty that accumulates across cycles (plateau 0.3, decay 5%/cycle). Stable modules gain cumulative advantage without violating the layered composition rule.

Testing layers

Layer Location Scope
Unit <module>/tests/ API contract, edge cases
Qualification 4 levels per module foundation / application / excess / opposite
Integration tests/ cross-module flows
Specification alignment scripts/check_doctrine_code_alignment.py specification ↔ code mapping
ID uniqueness scripts/check_id_uniqueness.py corpus consistency
Runtime scripts/force_probe_cycle.py end-to-end cycle

Extending the system

  • Adding a new configuration : see internal guide in docs/internal/guides/.
  • Transposing a new specification source : see internal guide docs/internal/guides/transpose_new_sefer.md.
  • Contributing : see CONTRIBUTING.md.