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
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.
| 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 |
# 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.dbsql/ 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
| 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 |
- Platform: https://github.com/aurekai/aurekai
- Native runtime: https://github.com/aurekai/native-runtime
- Integration registry: https://github.com/aurekai/aurekai/blob/main/registry/integrations.json
- Ecosystem map: https://github.com/aurekai/aurekai/blob/main/ECOSYSTEM_NAMES.md