Overview
- Skill Key
- homeofe/openclaw-memory-core
- Author
- homeofe
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/homeofe/openclaw-memory-core
- Latest Commit SHA
- 59a1276e500635577abac5b9182c44ea842723e3
Core utilities for OpenClaw memory plugins (redaction, local store, embeddings).
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请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 openclaw-memory-core 技能。 若已安装,则直接安装 openclaw-memory-core 技能。
# OpenClaw Memory Core Shared library powering OpenClaw's memory plugins (`openclaw-memory-brain` and `openclaw-memory-docs`). Provides three core modules: ## Redaction Automatically detects and redacts secrets before they reach memory storage. Covers: - API keys (OpenAI, Anthropic, Stripe, Google, GitHub PATs) - AWS credentials (access keys, secret keys) - Azure storage keys, HashiCorp Vault tokens - JWTs, Bearer tokens, PEM private key blocks Usage: pipe any text through the redactor before storing — secrets are replaced with safe `[REDACTED:TYPE]` placeholders. ## JSONL Store Local file-based memory store using append-only `.jsonl` files. Features: - CRUD for memory items (kinds: `fact`, `decision`, `doc`, `note`) - Expiration support (`expiresAt` field) - Semantic search via cosine similarity on embeddings - No external database required — everything lives in flat files ## Embeddings Deterministic, offline, dependency-free text embedder (`HashEmbedder`): - FNV-1a hash-based vector generation (default 256 dimensions) - L2 normalization for cosine similarity search - No API calls, no model downloads — works fully offline - Not SOTA semantics, but stable and fast for local vector search ## Integration This is a dependency library, not a standalone plugin. Install it as a package dependency: ```bash npm install @elvatis_com/openclaw-memory-core ``` Used internally by `openclaw-memory-brain` (auto-capture) and `openclaw-memory-docs` (explicit capture).
# @elvatis_com/openclaw-memory-core
Core utilities for building OpenClaw memory plugins - redaction, embeddings, and JSONL-backed vector search.
## Installation
```bash
npm install @elvatis_com/openclaw-memory-core
```
Requires Node.js 18+.
## Quick start
```ts
import {
JsonlMemoryStore,
createEmbedder,
DefaultRedactor,
uuid,
} from "@elvatis_com/openclaw-memory-core";
// 1. Set up the store
const embedder = createEmbedder();
const store = new JsonlMemoryStore({
filePath: "./data/memories.jsonl",
embedder,
});
// 2. Redact secrets before storing
const redactor = new DefaultRedactor();
const { redactedText } = redactor.redact("My API key is sk-proj-abc123def456ghi789");
// 3. Store a memory
await store.add({
id: uuid(),
kind: "note",
text: redactedText,
createdAt: new Date().toISOString(),
tags: ["api", "credentials"],
});
// 4. Search by natural language
const results = await store.search("API key");
console.log(results[0]?.item.text);
// => "My API key is [REDACTED:OPENAI_KEY]"
```
## API reference
All exports are available from the package root:
```ts
import { /* any export */ } from "@elvatis_com/openclaw-memory-core";
```
---
### Types
#### `MemoryKind`
```ts
type MemoryKind = "fact" | "decision" | "doc" | "note";
```
The four supported item categories.
#### `MemoryItem`
```ts
interface MemoryItem {
id: string;
kind: MemoryKind;
text: string;
createdAt: string; // ISO 8601
expiresAt?: string; // ISO 8601 - optional TTL
source?: {
channel?: string;
from?: string;
conversationId?: string;
messageId?: string;
};
tags?: string[];
meta?: Record<string, unknown>;
}
```
The fundamental data unit stored by a `MemoryStore`.
#### `SearchHit`
```ts
interface SearchHit {
item: MemoryItem;
score: number; // 0..1 (1 = best match)
}
```
Returned by `store.search()`. Results are sorted by score descending.
#### `SearchOpts`
```ts
interface SearchOpts {
limit?: number;...
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