47bd3ded44
Add an optional PostgreSQL backend (QMD_BACKEND=pg) alongside the unchanged default SQLite path. PG store uses pgvector (HNSW) for vectors and pg_jieba + pg_trgm for full-text/Chinese tokenization, with a namespace column isolating multi-agent memory (openclaw/hermes). - src/pg/: config, db-pg, schema bootstrap, memory store - MCP memory_add/memory_search/memory_get tools; qmd pg status + memory CLI - connection via QMD_PG_URL/DATABASE_URL/qmd config, stunnel TLS 5443 - tests: pg-config (unit) + pg-memory integration (gated on QMD_PG_URL) + pg-compose - docs/plan: plan, usage, test report, changelog; track docs/**/*.md SQLite path: zero regression (typecheck clean, 249 passed / 6 skipped). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
71 lines
1.9 KiB
TypeScript
71 lines
1.9 KiB
TypeScript
/**
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* pg/index.ts - Entry point for the PostgreSQL memory bridge.
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*
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* Wires qmd's LlamaCpp embedder (external OpenAI-compatible API by default,
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* optional local models) to the PG-backed memory store and returns a handle
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* that disposes both the LLM and the connection pool on close.
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*/
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import { LlamaCpp } from "../llm.js";
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import { resolvePgConfig, isPgBackend, type PgConnectionConfig } from "./config.js";
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import { PgMemoryStore } from "./memory-store.js";
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export { PgMemoryStore } from "./memory-store.js";
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export type {
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AddMemoryInput,
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AddMemoryResult,
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MemorySearchResult,
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MemoryRecord,
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SearchOptions,
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Embedder,
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} from "./memory-store.js";
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export {
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resolveBackend,
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isPgBackend,
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resolveNamespace,
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resolvePgConfig,
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redactConnectionString,
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DEFAULT_NAMESPACE,
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} from "./config.js";
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export type { Backend, PgConnectionConfig } from "./config.js";
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export interface MemoryBridge {
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store: PgMemoryStore;
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config: PgConnectionConfig;
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dispose(): Promise<void>;
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}
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/**
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* Open the memory bridge from the environment. Throws a clear error if the PG
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* backend is not configured.
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*/
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export async function openMemoryBridge(
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env: NodeJS.ProcessEnv = process.env,
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): Promise<MemoryBridge> {
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if (!isPgBackend(env)) {
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throw new Error(
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"PostgreSQL backend is not selected. Set QMD_BACKEND=pg and QMD_PG_URL to use memory commands.",
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);
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}
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const config = resolvePgConfig(env);
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// A dedicated embedder for the bridge — lazy-loads models on first use and
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// auto-unloads after inactivity. Uses the same external embed API as the
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// SQLite engine so vectors are comparable across hosts.
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const llm = new LlamaCpp({
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inactivityTimeoutMs: 5 * 60 * 1000,
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disposeModelsOnInactivity: true,
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});
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const store = await PgMemoryStore.open(config, llm);
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return {
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store,
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config,
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dispose: async () => {
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await store.close();
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await llm.dispose();
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},
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};
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}
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