94 lines
2.3 KiB
Markdown
94 lines
2.3 KiB
Markdown
# Architecture
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`GroundRecall` is the grounded knowledge substrate in a larger stack:
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- `GroundRecall`: canonical knowledge ingestion, promotion, query, export, and future sync
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- `Didactopus`: learner-facing workflows and educational tooling
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- `GenieHive`: model and routing layer where runtime assistant/service resolution is needed
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## Core Design
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The system is built around one canonical flow:
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1. ingest weakly structured sources
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2. normalize them into stable knowledge objects
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3. lint and queue them for review
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4. promote reviewed objects into a canonical store
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5. query and export promoted state
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## Core Objects
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The canonical store is built from these object families:
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- `Source`
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- `Fragment`
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- `Artifact`
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- `Observation`
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- `Claim`
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- `Concept`
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- `Relation`
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- `ReviewCandidate`
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- `PromotionRecord`
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- `GroundRecallSnapshot`
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These objects are assistant-neutral. Assistant-specific formatting belongs at the adapter layer.
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## Package Surface
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The main standalone package surface is:
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- `groundrecall.ingest`
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- `groundrecall.lint`
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- `groundrecall.models`
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- `groundrecall.store`
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- `groundrecall.promotion`
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- `groundrecall.query`
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- `groundrecall.export`
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- `groundrecall.assistant_export`
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- `groundrecall.inspect`
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- `groundrecall.source_adapters.*`
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- `groundrecall.assistants.*`
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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.
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## Source Adapters
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Adapters handle source-shape-specific discovery and mapping while the downstream pipeline stays generic.
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Current adapter families include:
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- `llmwiki`
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- `markdown_notes`
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- `transcript`
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- `didactopus_pack`
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## Assistant Boundary
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Assistant integration is intentionally outside the core store and query semantics.
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The rule is:
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- core `GroundRecall` owns truth, provenance, lifecycle, and retrieval semantics
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- assistant adapters own presentation, bundle shaping, and tool-specific exports
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Current adapters include:
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- `codex`
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- `claude_code`
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## Alpha Boundary
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The current alpha is strong enough for:
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- local import and promotion
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- canonical query and export
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- assistant-neutral bundles
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- assistant-targeted bundle generation
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It is not yet complete for:
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- multi-node sync and merge
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- re-import/update semantics
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- richer review adjudication
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- large-scale distributed corpus integration
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