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Aurekai

aurekai-sqlite

Aurekai integration surface for SQLite — lightweight, serverless, embedded data-ml storage for model memory, SAE dictionaries, semantic cache, manifests, and proof bundles.

Status: active Type: data-ml

Overview

aurekai-sqlite provides DDL schemas and scripts to persist and query Aurekai artifacts using SQLite (sqlite3). No server required — everything runs embedded. Works with akai CLI, the Python aurekai SDK, and any standard SQLite tooling.

Core Template Set

Template Description
doctor-deep Connectivity check, schema integrity, and akai doctor --deep
manifest-verify Validate aurekai.deploy.v1 manifest row in the database
model-memory-pack Insert .akmodel / .bfmodel artifacts into model_memory table
sae-audit Audit SAE dictionary rows in sae_dictionaries table
semantic-cache-bench Benchmark semantic cache read/write throughput against SQLite
proof-bundle-export Export proof bundle rows to out/proof-bundle.json
release-gate Verify all artifact tables are populated before publish

Quick Start

# 1. Install Aurekai runtime
npm install -g @aurekai/runtime@0.8.0-alpha.4

# 2. Init the database
bash scripts/init-db.sh /tmp/aurekai.db

# 3. Run doctor deep
bash scripts/doctor-deep.sh /tmp/aurekai.db

# 4. Pack a model memory artifact
bash scripts/model-memory-pack.sh /tmp/aurekai.db path/to/artifact.akmodel

# 5. Run the release gate
bash scripts/release-gate.sh /tmp/aurekai.db

Directory Layout

sql/                   DDL schema files
scripts/               Template scripts (doctor-deep, model-memory-pack, …)
examples/              Sample inputs and usage
tests/                 Validation scripts
docs/                  Quickstart, schema reference, script reference

SQL Schemas

File Tables
sql/schema-model-memory.sql model_memory
sql/schema-sae.sql sae_dictionaries
sql/schema-semantic-cache.sql semantic_cache
sql/schema-manifests.sql manifests
sql/schema-proof-bundles.sql proof_bundles

Canonical References

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SQLite integration templates for Aurekai local runtime and cache workflows

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