Files
openclaw/scripts/sqlite-vec-smoke.mjs
T
Tabula Myriad a9ae1a6778 feat: Triad development iteration complete
Matrix Protocol:
- docker-compose.matrix.yml: Dendrite homeserver + PostgreSQL + Nginx TLS
- src/channels/plugins/matrix-channel.ts: OpenClaw plugin implementation
- docs/matrix-triad-setup.md: Setup guide with auth scheme (@tm1-4:triad.local)

MCP Server Integration:
- docs/mcp-triad-integration.md: SearXNG, Playwright, GitHub MCP configs
- docs/mcp-curiosity-mapping.md: Gap-to-capability mapping

Node Sync Architecture:
- src/services/node-sync-service.ts: WebSocket peer sync + presence detection
- src/services/node-sync-service.test.ts: Unit tests
- docs/node-sync-architecture.md: Architecture docs

Triad Resilience:
- scripts/triad-corruption-check.mjs: SQLite + log + config + git integrity
- docs/triad-resilience.md: Recovery procedures
- .secure/deployment-logs/README.md: Schema v2
- skills/triad-heartbeat/SKILL.md: Corruption check integration

NPM Publish Workflow:
- scripts/npm-publish.mjs: version, changelog, validate, publish, rollback
- .github/workflows/npm-publish.yml: GitHub Actions with provenance
- docs/npm-publish-guide.md: Complete documentation

All deliverables tested in Docker before production.
2026-03-24 00:44:50 -04:00

39 lines
1002 B
JavaScript
Executable File

import { DatabaseSync } from "node:sqlite";
import { load, getLoadablePath } from "sqlite-vec";
function vec(values) {
return Buffer.from(new Float32Array(values).buffer);
}
const db = new DatabaseSync(":memory:", { allowExtension: true });
try {
load(db);
} catch (err) {
const message = err instanceof Error ? err.message : String(err);
console.error("sqlite-vec load failed:");
console.error(message);
console.error("expected extension path:", getLoadablePath());
process.exit(1);
}
db.exec(`
CREATE VIRTUAL TABLE v USING vec0(
id TEXT PRIMARY KEY,
embedding FLOAT[4]
);
`);
const insert = db.prepare("INSERT INTO v (id, embedding) VALUES (?, ?)");
insert.run("a", vec([1, 0, 0, 0]));
insert.run("b", vec([0, 1, 0, 0]));
insert.run("c", vec([0.2, 0.2, 0, 0]));
const query = vec([1, 0, 0, 0]);
const rows = db
.prepare("SELECT id, vec_distance_cosine(embedding, ?) AS dist FROM v ORDER BY dist ASC")
.all(query);
console.log("sqlite-vec ok");
console.log(rows);