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Architecture

GroundRecall is the grounded knowledge substrate in a larger stack:

GroundRecall: canonical knowledge ingestion, promotion, query, export, and future sync
Didactopus: learner-facing workflows and educational tooling
GenieHive: model and routing layer where runtime assistant/service resolution is needed

Core Design

The system is built around one canonical flow:

ingest weakly structured sources
normalize them into stable knowledge objects
lint and queue them for review
promote reviewed objects into a canonical store
query and export promoted state

Core Objects

The canonical store is built from these object families:

Source
Fragment
Artifact
Observation
Claim
Concept
Relation
ReviewCandidate
PromotionRecord
GroundRecallSnapshot

These objects are assistant-neutral. Assistant-specific formatting belongs at the adapter layer.

Package Surface

The main standalone package surface is:

groundrecall.ingest
groundrecall.lint
groundrecall.models
groundrecall.store
groundrecall.promotion
groundrecall.query
groundrecall.export
groundrecall.assistant_export
groundrecall.inspect
groundrecall.source_adapters.*
groundrecall.assistants.*

There are also compatibility-style helper modules prefixed with groundrecall_ inside the package. Those exist because the standalone repo was extracted from an earlier monorepo layout.

Source Adapters

Adapters handle source-shape-specific discovery and mapping while the downstream pipeline stays generic.

Current adapter families include:

llmwiki
markdown_notes
transcript
didactopus_pack

Assistant Boundary

Assistant integration is intentionally outside the core store and query semantics.

The rule is:

core GroundRecall owns truth, provenance, lifecycle, and retrieval semantics
assistant adapters own presentation, bundle shaping, and tool-specific exports

Current adapters include:

codex
claude_code

Alpha Boundary

The current alpha is strong enough for:

local import and promotion
canonical query and export
assistant-neutral bundles
assistant-targeted bundle generation

It is not yet complete for:

multi-node sync and merge
re-import/update semantics
richer review adjudication
large-scale distributed corpus integration

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