feat: knowledge-engine v0.1.0 — all Cerberus findings fixed

- 83/83 tests passing (was 32/45)
- New: src/http-client.ts (shared HTTP/HTTPS client, fixes C2+H1)
- Fixed: proper_noun regex exclusions (C6)
- Fixed: shutdown hooks registered in hooks.ts (C3)
- Fixed: all timers use .unref() (H6)
- Fixed: resolveConfig split into smaller functions (C4)
- Fixed: extract() split with processMatch helper (C5)
- Fixed: FactStore.addFact isLoaded guard (H3)
- Fixed: validateConfig split (H2)
- Fixed: type-safe config merge, removed as any (H4)
- Added: http-client tests, expanded coverage (H5)
- Fixed: LLM batch await (S1), fresh RegExp per call (S2)
- 1530 LOC source, 1298 LOC tests, strict TypeScript
This commit is contained in:
Claudia 2026-02-17 16:10:13 +01:00
commit 8964d93c60
28 changed files with 5092 additions and 0 deletions

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# Node.js
node_modules/
dist/
npm-debug.log*
yarn-debug.log*
yarn-error.log*
pnpm-debug.log*
# TypeScript
*.tsbuildinfo
# Test
coverage/
# OS
.DS_Store
Thumbs.db

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# Architecture: @vainplex/openclaw-knowledge-engine
## 1. Overview and Scope
`@vainplex/openclaw-knowledge-engine` is a TypeScript-based OpenClaw plugin for real-time and batch knowledge extraction from conversational data. It replaces a collection of legacy Python scripts with a unified, modern, and tightly integrated solution.
The primary goal of this plugin is to identify, extract, and store key information (entities and facts) from user and agent messages. This knowledge is then made available for long-term memory, context enrichment, and improved agent performance. It operates directly within the OpenClaw event pipeline, eliminating the need for external NATS consumers and schedulers.
### 1.1. Core Features
- **Hybrid Entity Extraction:** Combines high-speed, low-cost regex extraction with optional, high-fidelity LLM-based extraction.
- **Structured Fact Store:** Manages a durable store of facts with metadata, relevance scoring, and a temporal decay mechanism.
- **Seamless Integration:** Hooks directly into OpenClaw's lifecycle events (`message_received`, `message_sent`, `session_start`).
- **Configurable & Maintainable:** All features are configurable via a JSON schema, and the TypeScript codebase ensures type safety and maintainability.
- **Zero Runtime Dependencies:** Relies only on Node.js built-in APIs, mirroring the pattern of `@vainplex/openclaw-cortex`.
- **Optional Embeddings:** Can integrate with ChromaDB for semantic search over extracted facts.
### 1.2. Out of Scope
- **TypeDB Integration:** The legacy TypeDB dependency is explicitly removed and will not be supported.
- **Direct NATS Consumption:** The plugin relies on OpenClaw hooks, not direct interaction with NATS streams.
- **UI/Frontend:** This plugin is purely a backend data processing engine.
---
## 2. Module Breakdown
The plugin will be structured similarly to `@vainplex/openclaw-cortex`, with a clear separation of concerns between modules. All source code will reside in the `src/` directory.
| File | Responsibility |
| --------------------- | -------------------------------------------------------------------------------------------------------------- |
| `index.ts` | Plugin entry point. Registers hooks, commands, and performs initial configuration validation. |
| `src/hooks.ts` | Main integration logic. Registers and orchestrates all OpenClaw hook handlers. Manages shared state. |
| `src/types.ts` | Centralized TypeScript type definitions for configuration, entities, facts, and API interfaces. |
| `src/config.ts` | Provides functions for resolving and validating the plugin's configuration from `openclaw.plugin.json`. |
| `src/storage.ts` | Low-level file I/O utilities for reading/writing JSON files, ensuring atomic writes and handling debouncing. |
| `src/entity-extractor.ts`| Implements the entity extraction pipeline. Contains the `EntityExtractor` class. |
| `src/fact-store.ts` | Implements the fact storage and retrieval logic. Contains the `FactStore` class, including decay logic. |
| `src/llm-enhancer.ts` | Handles communication with an external LLM (e.g., Ollama) for batched, deep extraction of entities and facts. |
| `src/embeddings.ts` | Manages optional integration with ChromaDB, including batching and syncing embeddings. |
| `src/maintenance.ts` | Encapsulates background tasks like fact decay and embeddings sync, triggered by an internal timer. |
| `src/patterns.ts` | Stores default regex patterns for common entities (dates, names, locations, etc.). |
---
## 3. Type Definitions
Located in `src/types.ts`.
```typescript
// src/types.ts
/**
* The public API exposed by the OpenClaw host to the plugin.
*/
export interface OpenClawPluginApi {
pluginConfig: Record<string, unknown>;
logger: {
info: (msg: string) => void;
warn: (msg: string) => void;
error: (msg: string) => void;
};
on: (event: string, handler: (event: HookEvent, ctx: HookContext) => void, options?: { priority: number }) => void;
}
export interface HookEvent {
content?: string;
message?: string;
text?: string;
from?: string;
sender?: string;
role?: "user" | "assistant";
[key: string]: unknown;
}
export interface HookContext {
workspace: string; // Absolute path to the OpenClaw workspace
}
/**
* Plugin configuration schema, validated from openclaw.plugin.json.
*/
export interface KnowledgeConfig {
enabled: boolean;
workspace: string;
extraction: {
regex: {
enabled: boolean;
};
llm: {
enabled: boolean;
model: string;
endpoint: string;
batchSize: number;
cooldownMs: number;
};
};
decay: {
enabled: boolean;
intervalHours: number;
rate: number; // e.g., 0.05 for 5% decay per interval
};
embeddings: {
enabled: boolean;
endpoint: string;
syncIntervalMinutes: number;
collectionName: string;
};
storage: {
maxEntities: number;
maxFacts: number;
writeDebounceMs: number;
};
}
/**
* Represents an extracted entity.
*/
export interface Entity {
id: string; // e.g., "person:claude"
type: "person" | "location" | "organization" | "date" | "product" | "concept" | "unknown";
value: string; // The canonical value, e.g., "Claude"
mentions: string[]; // Different ways it was mentioned, e.g., ["claude", "Claude's"]
count: number;
importance: number; // 0.0 to 1.0
lastSeen: string; // ISO 8601 timestamp
source: ("regex" | "llm")[];
}
/**
* Represents a structured fact.
*/
export interface Fact {
id: string; // UUID v4
subject: string; // Entity ID
predicate: string; // e.g., "is-a", "has-property", "works-at"
object: string; // Entity ID or literal value
relevance: number; // 0.0 to 1.0, subject to decay
createdAt: string; // ISO 8601 timestamp
lastAccessed: string; // ISO 8601 timestamp
source: "ingested" | "extracted-regex" | "extracted-llm";
}
/**
* Data structure for entities.json
*/
export interface EntitiesData {
updated: string;
entities: Entity[];
}
/**
* Data structure for facts.json
*/
export interface FactsData {
updated: string;
facts: Fact[];
}
```
---
## 4. Hook Integration Points
The plugin will register handlers for the following OpenClaw core events:
| Hook Event | Priority | Handler Logic |
| ------------------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `message_received` | 100 | - Triggers the real-time entity extraction pipeline. <br> - Extracts content and sender. <br> - Adds the message to the `LlmEnhancer` batch if LLM is enabled. |
| `message_sent` | 100 | - Same as `message_received`. Ensures the agent's own messages are processed for knowledge. |
| `session_start` | 200 | - Initializes the `Maintenance` service. <br> - Starts the internal timers for fact decay and embeddings sync. <br> - Ensures workspace directories exist. |
---
## 5. Entity Extraction Pipeline
The extraction process runs on every message and is designed to be fast and efficient.
### 5.1. Regex Extraction
- **Always On (if enabled):** Runs first on every message.
- **Patterns:** A configurable set of regular expressions will be defined in `src/patterns.ts`. These will cover common entities like dates (`YYYY-MM-DD`), email addresses, URLs, and potentially user-defined patterns.
- **Performance:** This step is extremely fast and has negligible overhead.
- **Output:** Produces a preliminary list of potential entities.
### 5.2. LLM Enhancement (Batched)
- **Optional:** Enabled via configuration.
- **Batching:** The `LlmEnhancer` class collects messages up to `batchSize` or until `cooldownMs` has passed since the last message. This avoids overwhelming the LLM with single requests.
- **Process:**
1. A batch of messages is formatted into a single prompt.
2. The prompt instructs the LLM to identify entities (person, location, etc.) and structured facts (triples like `Subject-Predicate-Object`).
3. The request is sent to the configured LLM endpoint (`extraction.llm.endpoint`).
4. The LLM's JSON response is parsed.
- **Merging:** LLM-extracted entities are merged with the regex-based results. The `source` array on the `Entity` object is updated to reflect that it was identified by both methods. LLM results are generally given a higher initial `importance` score.
---
## 6. Fact Store Design
The `FactStore` class manages the `facts.json` file, providing an in-memory cache and methods for interacting with facts.
### 6.1. Data Structure (`facts.json`)
The file will contain a `FactsData` object:
```json
{
"updated": "2026-02-17T15:30:00Z",
"facts": [
{
"id": "f0a4c1b0-9b1e-4b7b-8f3a-0e9c8d7b6a5a",
"subject": "person:atlas",
"predicate": "is-a",
"object": "sub-agent",
"relevance": 0.95,
"createdAt": "2026-02-17T14:00:00Z",
"lastAccessed": "2026-02-17T15:20:00Z",
"source": "extracted-llm"
}
]
}
```
### 6.2. `FactStore` Class API
```typescript
// src/fact-store.ts
class FactStore {
constructor(workspace: string, config: KnowledgeConfig['storage'], logger: Logger);
// Load facts from facts.json into memory
load(): Promise<void>;
// Add a new fact or update an existing one
addFact(fact: Omit<Fact, 'id' | 'createdAt' | 'lastAccessed'>): Fact;
// Retrieve a fact by its ID
getFact(id: string): Fact | undefined;
// Query facts based on subject, predicate, or object
query(query: { subject?: string; predicate?: string; object?: string }): Fact[];
// Run the decay algorithm on all facts
decayFacts(rate: number): { decayedCount: number };
// Persist the in-memory store to disk (debounced)
commit(): Promise<void>;
}
```
### 6.3. Storage and Persistence
- **Debounced Writes:** All modifications to the fact store will trigger a debounced `commit()` call. This ensures that rapid, successive writes (e.g., during a fast-paced conversation) are batched into a single file I/O operation, configured by `storage.writeDebounceMs`.
- **Atomic Writes:** The `storage.ts` module will use a "write to temp file then rename" strategy to prevent data corruption if the application terminates mid-write.
---
## 7. Decay Algorithm
The decay algorithm prevents the fact store from becoming cluttered with stale, irrelevant information. It is managed by the `Maintenance` service.
- **Trigger:** Runs on a schedule defined by `decay.intervalHours`.
- **Logic:** For each fact, the relevance score is reduced by the `decay.rate`.
```
newRelevance = currentRelevance * (1 - decayRate)
```
- **Floor:** Relevance will not decay below a certain floor (e.g., 0.1) to keep it in the system.
- **Promotion:** When a fact is "accessed" (e.g., used to answer a question or mentioned again), its `relevance` score is boosted, and its `lastAccessed` timestamp is updated. A simple boost could be `newRelevance = currentRelevance + (1 - currentRelevance) * 0.5`, pushing it halfway to 1.0.
- **Pruning:** Facts with a relevance score below a configurable threshold (e.g., 0.05) after decay might be pruned from the store entirely if `storage.maxFacts` is exceeded.
---
## 8. Embeddings Integration
This feature allows for semantic querying of facts and is entirely optional.
### 8.1. `Embeddings` Service
- **Trigger:** Runs on a schedule defined by `embeddings.syncIntervalMinutes`.
- **Process:**
1. The service scans `facts.json` for any facts that have not yet been embedded.
2. It formats each fact into a natural language string, e.g., "Atlas is a sub-agent."
3. It sends a batch of these strings to a ChromaDB-compatible vector database via its HTTP API.
4. The fact's ID is stored as metadata alongside the vector in ChromaDB.
- **Configuration:** The `embeddings.endpoint` must be a valid URL to the ChromaDB `/api/v1/collections/{name}/add` endpoint.
- **Decoupling:** The plugin does **not** query ChromaDB. Its only responsibility is to push embeddings. Other plugins or services would be responsible for leveraging the vector store for retrieval-augmented generation (RAG).
---
## 9. Config Schema
The full `openclaw.plugin.json` schema for this plugin.
```json
{
"id": "@vainplex/openclaw-knowledge-engine",
"config": {
"enabled": true,
"workspace": "~/.clawd/plugins/knowledge-engine",
"extraction": {
"regex": {
"enabled": true
},
"llm": {
"enabled": true,
"model": "mistral:7b",
"endpoint": "http://localhost:11434/api/generate",
"batchSize": 10,
"cooldownMs": 30000
}
},
"decay": {
"enabled": true,
"intervalHours": 24,
"rate": 0.02
},
"embeddings": {
"enabled": false,
"endpoint": "http://localhost:8000/api/v1/collections/facts/add",
"collectionName": "openclaw-facts",
"syncIntervalMinutes": 15
},
"storage": {
"maxEntities": 5000,
"maxFacts": 10000,
"writeDebounceMs": 15000
}
}
}
```
---
## 10. Test Strategy
Testing will be comprehensive and follow the patterns of `@vainplex/openclaw-cortex`, using Node.js's built-in test runner.
- **Unit Tests:** Each class (`EntityExtractor`, `FactStore`, `LlmEnhancer`, etc.) will have its own test file (e.g., `fact-store.test.ts`). Tests will use mock objects for dependencies like the logger and file system.
- **Integration Tests:** `hooks.test.ts` will test the end-to-end flow by simulating OpenClaw hook events and asserting that the correct file system changes occur.
- **Configuration Tests:** `config.test.ts` will verify that default values are applied correctly and that invalid configurations are handled gracefully.
- **CI/CD:** Tests will be run automatically in a CI pipeline on every commit.
---
## 11. Migration Guide
This section outlines the process for decommissioning the old Python scripts and migrating to the new plugin.
1. **Disable Old Services:** Stop and disable the `systemd` services and timers for `entity-extractor-stream.py`, `smart-extractor.py`, `knowledge-engine.py`, and `cortex-loops-stream.py`.
```bash
systemctl stop entity-extractor-stream.service smart-extractor.timer knowledge-engine.service cortex-loops.timer
systemctl disable entity-extractor-stream.service smart-extractor.timer knowledge-engine.service cortex-loops.timer
```
2. **Install the Plugin:** Install the `@vainplex/openclaw-knowledge-engine` plugin into OpenClaw according to standard procedures.
3. **Configure the Plugin:** Create a configuration file at `~/.clawd/plugins/openclaw-knowledge-engine.json` (or the equivalent path) using the schema from section 9. Ensure the `workspace` directory is set to the desired location.
4. **Data Migration (Optional):**
- **Entities:** A one-time script (`./scripts/migrate-entities.js`) will be provided to convert the old `~/.cortex/knowledge/entities.json` format to the new `Entity` format defined in `src/types.ts`.
- **Facts:** As the old `knowledge-engine.py` had a different structure and no durable fact store equivalent to `facts.json`, facts will not be migrated. The system will start with a fresh fact store.
- **TypeDB:** No migration from TypeDB will be provided.
5. **Enable and Restart:** Enable the plugin in OpenClaw's main configuration and restart the OpenClaw instance. Monitor the logs for successful initialization.
---
## 12. Performance Requirements
- **Message Hook Overhead:** The synchronous part of the message hook (regex extraction) must complete in under **5ms** on average to avoid delaying the message processing pipeline.
- **LLM Latency:** LLM processing is asynchronous and batched, so it does not block the main thread. However, the total time to analyze a batch should be logged and monitored.
- **Memory Usage:** The plugin's heap size should not exceed **100MB** under normal load, assuming the configured `maxEntities` and `maxFacts` limits.
- **CPU Usage:** Background maintenance tasks (decay, embeddings sync) should be staggered and have low CPU impact, consuming less than 5% of a single core while running.

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// index.ts
import { resolveConfig } from './src/config.js';
import { HookManager } from './src/hooks.js';
import type { OpenClawPluginApi } from './src/types.js';
// The main entry point for the OpenClaw plugin.
// This function is called by the OpenClaw host during plugin loading.
export default (api: OpenClawPluginApi, context: { workspace: string }): void => {
const { pluginConfig, logger } = api;
const { workspace: openClawWorkspace } = context;
// 1. Resolve and validate the configuration
const config = resolveConfig(pluginConfig, logger, openClawWorkspace);
if (!config) {
logger.error('Failed to initialize Knowledge Engine: Invalid configuration. The plugin will be disabled.');
return;
}
if (!config.enabled) {
logger.info('Knowledge Engine is disabled in the configuration.');
return;
}
// 2. Initialize the Hook Manager with the resolved config
try {
const hookManager = new HookManager(api, config);
// 3. Register all the event hooks
hookManager.registerHooks();
logger.info('Knowledge Engine plugin initialized successfully.');
} catch (err) {
logger.error('An unexpected error occurred during Knowledge Engine initialization.', err as Error);
}
};

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{
"id": "@vainplex/openclaw-knowledge-engine",
"config": {
"enabled": {
"type": "boolean",
"default": true,
"description": "Whether the knowledge engine plugin is enabled."
},
"workspace": {
"type": "string",
"default": "~/.clawd/plugins/knowledge-engine",
"description": "The directory to store knowledge files (entities.json, facts.json)."
},
"extraction": {
"type": "object",
"properties": {
"regex": {
"type": "object",
"properties": {
"enabled": {
"type": "boolean",
"default": true,
"description": "Enable or disable high-speed regex-based entity extraction."
}
}
},
"llm": {
"type": "object",
"properties": {
"enabled": {
"type": "boolean",
"default": true,
"description": "Enable or disable high-fidelity LLM-based entity and fact extraction."
},
"model": {
"type": "string",
"default": "mistral:7b",
"description": "The model name to use for the LLM API call (e.g., Ollama model)."
},
"endpoint": {
"type": "string",
"default": "http://localhost:11434/api/generate",
"description": "The HTTP endpoint for the LLM generation API."
},
"batchSize": {
"type": "number",
"default": 10,
"description": "Number of messages to batch together before sending to the LLM."
},
"cooldownMs": {
"type": "number",
"default": 30000,
"description": "Milliseconds to wait after the last message before sending a batch to the LLM."
}
}
}
}
},
"decay": {
"type": "object",
"properties": {
"enabled": {
"type": "boolean",
"default": true,
"description": "Enable or disable the periodic decay of fact relevance."
},
"intervalHours": {
"type": "number",
"default": 24,
"description": "How often (in hours) to run the decay process."
},
"rate": {
"type": "number",
"default": 0.02,
"description": "The percentage of relevance to decay in each interval (e.g., 0.02 is 2%)."
}
}
},
"embeddings": {
"type": "object",
"properties": {
"enabled": {
"type": "boolean",
"default": false,
"description": "Enable or disable syncing of facts to a vector database."
},
"endpoint": {
"type": "string",
"default": "http://localhost:8000/api/v1/collections/facts/add",
"description": "The HTTP endpoint for the vector database's add API (ChromaDB compatible)."
},
"collectionName": {
"type": "string",
"default": "openclaw-facts",
"description": "The name of the collection to use in the vector database."
},
"syncIntervalMinutes": {
"type": "number",
"default": 15,
"description": "How often (in minutes) to sync new facts to the vector database."
}
}
},
"storage": {
"type": "object",
"properties": {
"maxEntities": {
"type": "number",
"default": 5000,
"description": "The maximum number of entities to store before pruning."
},
"maxFacts": {
"type": "number",
"default": 10000,
"description": "The maximum number of facts to store before pruning."
},
"writeDebounceMs": {
"type": "number",
"default": 15000,
"description": "Milliseconds to wait after a change before writing data to disk."
}
}
}
}
}

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{
"name": "@vainplex/openclaw-knowledge-engine",
"version": "0.1.0",
"description": "An OpenClaw plugin for real-time and batch knowledge extraction from conversational data.",
"main": "dist/index.js",
"types": "dist/index.d.ts",
"scripts": {
"build": "tsc",
"test": "tsx --test test/*.test.ts",
"lint": "eslint . --ext .ts",
"prepublishOnly": "npm run build"
},
"keywords": [
"openclaw",
"plugin",
"knowledge-extraction",
"nlp",
"entity-extraction"
],
"author": "Vainplex",
"license": "MIT",
"repository": {
"type": "git",
"url": "https://github.com/your-repo/openclaw-knowledge-engine.git"
},
"openclaw": {
"id": "@vainplex/openclaw-knowledge-engine"
},
"devDependencies": {
"@types/node": "^20.11.24",
"eslint": "^8.57.0",
"typescript": "^5.3.3",
"tsx": "^4.7.1"
},
"type": "module"
}

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// src/config.ts
import * as path from 'node:path';
import { KnowledgeConfig, Logger } from './types.js';
/**
* The default configuration values for the plugin.
* These are merged with the user-provided configuration.
*/
export const DEFAULT_CONFIG: Omit<KnowledgeConfig, 'workspace'> = {
enabled: true,
extraction: {
regex: { enabled: true },
llm: {
enabled: true,
model: 'mistral:7b',
endpoint: 'http://localhost:11434/api/generate',
batchSize: 10,
cooldownMs: 30000,
},
},
decay: {
enabled: true,
intervalHours: 24,
rate: 0.02,
},
embeddings: {
enabled: false,
endpoint: 'http://localhost:8000/api/v1/collections/facts/add',
collectionName: 'openclaw-facts',
syncIntervalMinutes: 15,
},
storage: {
maxEntities: 5000,
maxFacts: 10000,
writeDebounceMs: 15000,
},
};
/** Type-safe deep merge: spread source into target for Record values. */
function deepMerge<T extends Record<string, unknown>>(
target: T,
source: Record<string, unknown>
): T {
const result = { ...target } as Record<string, unknown>;
for (const key of Object.keys(source)) {
const srcVal = source[key];
const tgtVal = result[key];
if (isPlainObject(srcVal) && isPlainObject(tgtVal)) {
result[key] = deepMerge(
tgtVal as Record<string, unknown>,
srcVal as Record<string, unknown>
);
} else if (srcVal !== undefined) {
result[key] = srcVal;
}
}
return result as T;
}
function isPlainObject(val: unknown): val is Record<string, unknown> {
return typeof val === 'object' && val !== null && !Array.isArray(val);
}
/** Merge user config over defaults and resolve workspace. */
function mergeConfigDefaults(
userConfig: Record<string, unknown>,
openClawWorkspace: string
): KnowledgeConfig {
const merged = deepMerge(
DEFAULT_CONFIG as unknown as Record<string, unknown>,
userConfig
);
const ws = typeof userConfig.workspace === 'string' && userConfig.workspace
? userConfig.workspace
: path.join(openClawWorkspace, 'knowledge-engine');
return { ...merged, workspace: ws } as KnowledgeConfig;
}
/** Replace a leading tilde with the user's home directory. */
function resolveTilde(ws: string, logger: Logger, fallback: string): string {
if (!ws.startsWith('~')) return ws;
const homeDir = process.env.HOME || process.env.USERPROFILE;
if (homeDir) return path.join(homeDir, ws.slice(1));
logger.warn('Could not resolve home directory for workspace path.');
return fallback;
}
/**
* Resolves and validates the plugin's configuration.
*
* @param userConfig The user-provided configuration from OpenClaw's pluginConfig.
* @param logger A logger instance for logging warnings or errors.
* @param openClawWorkspace The root workspace directory provided by OpenClaw.
* @returns A fully resolved KnowledgeConfig, or null if validation fails.
*/
export function resolveConfig(
userConfig: Record<string, unknown>,
logger: Logger,
openClawWorkspace: string
): KnowledgeConfig | null {
const config = mergeConfigDefaults(userConfig, openClawWorkspace);
const fallbackWs = path.join(openClawWorkspace, 'knowledge-engine');
config.workspace = resolveTilde(config.workspace, logger, fallbackWs);
const errors = validateConfig(config);
if (errors.length > 0) {
errors.forEach(e => logger.error(`Invalid configuration: ${e}`));
return null;
}
logger.info('Knowledge Engine configuration resolved successfully.');
return config;
}
// ── Validation ──────────────────────────────────────────────
function validateConfig(config: KnowledgeConfig): string[] {
return [
...validateRoot(config),
...validateExtraction(config.extraction),
...validateDecay(config.decay),
...validateEmbeddings(config.embeddings),
...validateStorage(config.storage),
];
}
function validateRoot(c: KnowledgeConfig): string[] {
const errs: string[] = [];
if (typeof c.enabled !== 'boolean') errs.push('"enabled" must be a boolean.');
if (typeof c.workspace !== 'string' || c.workspace.trim() === '') {
errs.push('"workspace" must be a non-empty string.');
}
return errs;
}
function validateExtraction(ext: KnowledgeConfig['extraction']): string[] {
const errs: string[] = [];
if (ext.llm.enabled) {
if (!isValidHttpUrl(ext.llm.endpoint)) {
errs.push('"extraction.llm.endpoint" must be a valid HTTP/S URL.');
}
if ((ext.llm.batchSize ?? 0) < 1) {
errs.push('"extraction.llm.batchSize" must be at least 1.');
}
}
return errs;
}
function validateDecay(d: KnowledgeConfig['decay']): string[] {
const errs: string[] = [];
if (d.rate < 0 || d.rate > 1) errs.push('"decay.rate" must be between 0 and 1.');
if ((d.intervalHours ?? 0) <= 0) errs.push('"decay.intervalHours" must be greater than 0.');
return errs;
}
function validateEmbeddings(e: KnowledgeConfig['embeddings']): string[] {
const errs: string[] = [];
if (e.enabled && !isValidHttpUrl(e.endpoint)) {
errs.push('"embeddings.endpoint" must be a valid HTTP/S URL.');
}
return errs;
}
function validateStorage(s: KnowledgeConfig['storage']): string[] {
const errs: string[] = [];
if ((s.writeDebounceMs ?? 0) < 0) {
errs.push('"storage.writeDebounceMs" must be a non-negative number.');
}
return errs;
}
function isValidHttpUrl(str: string): boolean {
try {
const url = new URL(str);
return url.protocol === 'http:' || url.protocol === 'https:';
} catch {
return false;
}
}

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// src/embeddings.ts
import { Fact, KnowledgeConfig, Logger } from './types.js';
import { httpPost } from './http-client.js';
/** ChromaDB v2 API payload format. */
interface ChromaPayload {
ids: string[];
documents: string[];
metadatas: Record<string, string>[];
}
/**
* Manages optional integration with a ChromaDB-compatible vector database.
*/
export class Embeddings {
private readonly config: KnowledgeConfig['embeddings'];
private readonly logger: Logger;
constructor(config: KnowledgeConfig['embeddings'], logger: Logger) {
this.config = config;
this.logger = logger;
}
/** Checks if the embeddings service is enabled. */
public isEnabled(): boolean {
return this.config.enabled;
}
/**
* Syncs a batch of facts to the vector database.
* @returns The number of successfully synced facts.
*/
public async sync(facts: Fact[]): Promise<number> {
if (!this.isEnabled() || facts.length === 0) return 0;
this.logger.info(`Starting embedding sync for ${facts.length} facts.`);
const payload = this.constructChromaPayload(facts);
const url = this.buildEndpointUrl();
try {
await httpPost(url, payload);
this.logger.info(`Successfully synced ${facts.length} facts to ChromaDB.`);
return facts.length;
} catch (err) {
this.logger.error('Failed to sync embeddings to ChromaDB.', err as Error);
return 0;
}
}
/** Builds the full endpoint URL with collection name substituted. */
private buildEndpointUrl(): string {
return this.config.endpoint
.replace('{name}', this.config.collectionName)
.replace('//', '//') // preserve protocol double-slash
.replace(/([^:])\/\//g, '$1/'); // collapse any other double-slashes
}
/**
* Constructs the payload for ChromaDB v2 API.
* Metadata values are all strings (v2 requirement).
*/
private constructChromaPayload(facts: Fact[]): ChromaPayload {
const payload: ChromaPayload = { ids: [], documents: [], metadatas: [] };
for (const fact of facts) {
payload.ids.push(fact.id);
payload.documents.push(
`${fact.subject} ${fact.predicate.replace(/-/g, ' ')} ${fact.object}.`
);
payload.metadatas.push({
subject: fact.subject,
predicate: fact.predicate,
object: fact.object,
source: fact.source,
createdAt: fact.createdAt,
});
}
return payload;
}
}

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// src/entity-extractor.ts
import { Entity, Logger } from './types.js';
import { REGEX_PATTERNS } from './patterns.js';
// A map to associate regex pattern names with entity types.
const PATTERN_TYPE_MAP: Record<string, Entity['type']> = {
email: 'email',
url: 'url',
iso_date: 'date',
common_date: 'date',
german_date: 'date',
english_date: 'date',
proper_noun: 'unknown',
product_name: 'product',
organization_suffix: 'organization',
};
/**
* Extracts entities from text using predefined regular expressions.
*/
export class EntityExtractor {
private readonly logger: Logger;
constructor(logger: Logger) {
this.logger = logger;
}
/**
* Extracts entities from a given text based on the regex patterns.
* @param text The input text to process.
* @returns An array of found entities.
*/
public extract(text: string): Entity[] {
const foundEntities: Map<string, Entity> = new Map();
for (const key in REGEX_PATTERNS) {
// Each access returns a fresh RegExp (via Proxy), avoiding /g state-bleed.
const regex = REGEX_PATTERNS[key];
if (!regex.global) {
this.logger.warn(`Regex for "${key}" is not global. Skipping.`);
continue;
}
const entityType = PATTERN_TYPE_MAP[key] || 'unknown';
let match;
while ((match = regex.exec(text)) !== null) {
const value = match[0].trim();
if (!value) continue;
this.processMatch(key, value, entityType, foundEntities);
}
}
return Array.from(foundEntities.values());
}
/**
* Processes a single regex match and upserts it into the entity map.
*/
private processMatch(
_key: string,
value: string,
entityType: Entity['type'],
entities: Map<string, Entity>
): void {
const canonicalValue = this.canonicalize(value, entityType);
const id = `${entityType}:${canonicalValue.toLowerCase().replace(/\s+/g, '-')}`;
if (entities.has(id)) {
const existing = entities.get(id)!;
if (!existing.mentions.includes(value)) existing.mentions.push(value);
existing.count++;
if (!existing.source.includes('regex')) existing.source.push('regex');
} else {
entities.set(id, {
id,
type: entityType,
value: canonicalValue,
mentions: [value],
count: 1,
importance: this.calculateInitialImportance(entityType, value),
lastSeen: new Date().toISOString(),
source: ['regex'],
});
}
}
/**
* Cleans and standardizes an entity value based on its type.
*/
private canonicalize(value: string, type: Entity['type']): string {
if (type === 'organization') {
const suffixes = /,?\s?(?:Inc\.|LLC|Corp\.|GmbH|AG|Ltd\.)$/i;
return value.replace(suffixes, '').trim();
}
return value.replace(/[.,!?;:]$/, '').trim();
}
/**
* Calculates an initial importance score for an entity.
*/
private calculateInitialImportance(type: Entity['type'], value: string): number {
switch (type) {
case 'organization': return 0.8;
case 'person': return 0.7;
case 'product': return 0.6;
case 'location': return 0.5;
case 'date':
case 'email':
case 'url': return 0.4;
default: return value.split(/\s|-/).length > 1 ? 0.5 : 0.3;
}
}
/**
* Merges two lists of entities by ID.
*/
public static mergeEntities(listA: Entity[], listB: Entity[]): Entity[] {
const merged: Map<string, Entity> = new Map();
for (const e of listA) merged.set(e.id, { ...e });
for (const entity of listB) {
if (merged.has(entity.id)) {
const ex = merged.get(entity.id)!;
ex.count += entity.count;
ex.mentions = [...new Set([...ex.mentions, ...entity.mentions])];
ex.source = [...new Set([...ex.source, ...entity.source])];
ex.lastSeen = new Date() > new Date(ex.lastSeen)
? new Date().toISOString() : ex.lastSeen;
ex.importance = Math.max(ex.importance, entity.importance);
} else {
merged.set(entity.id, { ...entity });
}
}
return Array.from(merged.values());
}
}

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// src/fact-store.ts
import { randomUUID } from 'node:crypto';
import { AtomicStorage } from './storage.js';
import type { Fact, FactsData, KnowledgeConfig, Logger } from './types.js';
/**
* Manages an in-memory and on-disk store of structured facts.
* Provides methods for loading, querying, modifying, and persisting facts.
*/
export class FactStore {
private readonly storage: AtomicStorage;
private readonly config: KnowledgeConfig['storage'];
private readonly logger: Logger;
private facts: Map<string, Fact> = new Map();
private isLoaded: boolean = false;
public readonly commit: () => Promise<void>;
constructor(
workspace: string,
config: KnowledgeConfig['storage'],
logger: Logger
) {
this.storage = new AtomicStorage(workspace, logger);
this.config = config;
this.logger = logger;
// Create a debounced version of the persist method.
this.commit = AtomicStorage.debounce(
this.persist.bind(this),
this.config.writeDebounceMs
);
}
/**
* Loads facts from the `facts.json` file into the in-memory store.
* If the file doesn't exist, it initializes an empty store.
*/
public async load(): Promise<void> {
if (this.isLoaded) {
this.logger.debug('Fact store is already loaded.');
return;
}
await this.storage.init();
const data = await this.storage.readJson<FactsData>('facts.json');
if (data && Array.isArray(data.facts)) {
this.facts = new Map(data.facts.map(fact => [fact.id, fact]));
this.logger.info(`Loaded ${this.facts.size} facts from storage.`);
} else {
this.logger.info('No existing fact store found. Initializing a new one.');
this.facts = new Map();
}
this.isLoaded = true;
}
/**
* Adds a new fact to the store or updates an existing one based on content.
* @param newFactData The data for the new fact, excluding metadata fields.
* @returns The newly created or found Fact object.
*/
public addFact(
newFactData: Omit<Fact, 'id' | 'createdAt' | 'lastAccessed' | 'relevance'>
): Fact {
if (!this.isLoaded) {
throw new Error('FactStore has not been loaded yet. Call load() first.');
}
const now = new Date().toISOString();
// Check if a similar fact already exists to avoid duplicates
for (const existingFact of this.facts.values()) {
if (
existingFact.subject === newFactData.subject &&
existingFact.predicate === newFactData.predicate &&
existingFact.object === newFactData.object
) {
// Fact already exists, let's just boost its relevance and update timestamp
existingFact.relevance = this.boostRelevance(existingFact.relevance);
existingFact.lastAccessed = now;
this.commit();
return existingFact;
}
}
const newFact: Fact = {
...newFactData,
id: randomUUID(),
createdAt: now,
lastAccessed: now,
relevance: 1.0, // New facts start with maximum relevance
};
this.facts.set(newFact.id, newFact);
this.prune(); // Check if we need to prune old facts
this.commit();
return newFact;
}
/**
* Retrieves a fact by its unique ID.
* @param id The UUID of the fact.
* @returns The Fact object, or undefined if not found.
*/
public getFact(id: string): Fact | undefined {
const fact = this.facts.get(id);
if (fact) {
fact.lastAccessed = new Date().toISOString();
fact.relevance = this.boostRelevance(fact.relevance);
this.commit();
}
return fact;
}
/**
* Queries the fact store based on subject, predicate, or object.
* @param query An object with optional subject, predicate, and/or object to match.
* @returns An array of matching facts, sorted by relevance.
*/
public query(query: { subject?: string; predicate?: string; object?: string }): Fact[] {
const results: Fact[] = [];
for (const fact of this.facts.values()) {
const subjectMatch = !query.subject || fact.subject === query.subject;
const predicateMatch = !query.predicate || fact.predicate === query.predicate;
const objectMatch = !query.object || fact.object === query.object;
if (subjectMatch && predicateMatch && objectMatch) {
results.push(fact);
}
}
// Sort by relevance, descending
return results.sort((a, b) => b.relevance - a.relevance);
}
/**
* Applies a decay factor to the relevance score of all facts.
* @param rate The decay rate (e.g., 0.05 for 5%).
* @returns An object with the count of decayed facts.
*/
public decayFacts(rate: number): { decayedCount: number } {
let decayedCount = 0;
const minRelevance = 0.1; // Floor to prevent facts from disappearing completely
for (const fact of this.facts.values()) {
const newRelevance = fact.relevance * (1 - rate);
if (newRelevance !== fact.relevance) {
fact.relevance = Math.max(minRelevance, newRelevance);
decayedCount++;
}
}
if (decayedCount > 0) {
this.logger.info(`Applied decay rate of ${rate * 100}% to ${decayedCount} facts.`);
this.commit();
}
return { decayedCount };
}
/**
* Persists the current in-memory fact store to `facts.json`.
*/
private async persist(): Promise<void> {
if (!this.isLoaded) {
this.logger.warn('Attempted to persist fact store before it was loaded. Aborting.');
return;
}
const data: FactsData = {
updated: new Date().toISOString(),
facts: Array.from(this.facts.values()),
};
try {
await this.storage.writeJson('facts.json', data);
this.logger.debug(`Successfully persisted ${data.facts.length} facts.`);
} catch (err) {
this.logger.error('Failed to persist fact store.', err as Error);
}
}
/**
* Removes the least relevant facts if the store exceeds its configured max size.
*/
private prune(): void {
const factCount = this.facts.size;
if (factCount <= this.config.maxFacts) {
return;
}
const factsToPrune = factCount - this.config.maxFacts;
if (factsToPrune <= 0) return;
// Get all facts, sort by relevance (ascending) and then by lastAccessed (ascending)
const sortedFacts = Array.from(this.facts.values()).sort((a, b) => {
if (a.relevance !== b.relevance) {
return a.relevance - b.relevance;
}
return new Date(a.lastAccessed).getTime() - new Date(b.lastAccessed).getTime();
});
for (let i = 0; i < factsToPrune; i++) {
this.facts.delete(sortedFacts[i].id);
}
this.logger.info(`Pruned ${factsToPrune} least relevant facts to maintain store size.`);
}
/**
* Boosts the relevance of a fact upon access.
* @param currentRelevance The current relevance score.
* @returns The new, boosted relevance score.
*/
private boostRelevance(currentRelevance: number): number {
// Push the relevance 50% closer to 1.0
const boost = (1.0 - currentRelevance) * 0.5;
return Math.min(1.0, currentRelevance + boost);
}
/**
* Returns a list of all facts that have not been embedded yet.
*/
public getUnembeddedFacts(): Fact[] {
const results: Fact[] = [];
for (const fact of this.facts.values()) {
if (!fact.embedded) {
results.push(fact);
}
}
return results;
}
/**
* Marks a list of facts as having been embedded.
* @param factIds An array of fact IDs to update.
*/
public markFactsAsEmbedded(factIds: string[]): void {
const now = new Date().toISOString();
let updatedCount = 0;
for (const id of factIds) {
const fact = this.facts.get(id);
if (fact) {
fact.embedded = now;
updatedCount++;
}
}
if (updatedCount > 0) {
this.commit();
}
}
}

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// src/hooks.ts
import {
OpenClawPluginApi,
HookEvent,
KnowledgeConfig,
Logger,
} from './types.js';
import { EntityExtractor } from './entity-extractor.js';
import { FactStore } from './fact-store.js';
import { LlmEnhancer } from './llm-enhancer.js';
import { Maintenance } from './maintenance.js';
import { Embeddings } from './embeddings.js';
/**
* Manages the registration and orchestration of all plugin hooks.
*/
export class HookManager {
private readonly api: OpenClawPluginApi;
private readonly config: KnowledgeConfig;
private readonly logger: Logger;
private entityExtractor: EntityExtractor;
private factStore: FactStore;
private llmEnhancer?: LlmEnhancer;
private maintenance?: Maintenance;
constructor(api: OpenClawPluginApi, config: KnowledgeConfig) {
this.api = api;
this.config = config;
this.logger = api.logger;
this.entityExtractor = new EntityExtractor(this.logger);
this.factStore = new FactStore(
this.config.workspace,
this.config.storage,
this.logger
);
if (this.config.extraction.llm.enabled) {
this.llmEnhancer = new LlmEnhancer(this.config.extraction.llm, this.logger);
}
}
/** Registers all the necessary hooks with the OpenClaw host. */
public registerHooks(): void {
if (!this.config.enabled) {
this.logger.info('Knowledge Engine is disabled. No hooks registered.');
return;
}
this.api.on('session_start', this.onSessionStart.bind(this), { priority: 200 });
this.api.on('message_received', this.onMessage.bind(this), { priority: 100 });
this.api.on('message_sent', this.onMessage.bind(this), { priority: 100 });
this.api.on('gateway_stop', this.onShutdown.bind(this), { priority: 900 });
this.logger.info('Registered all Knowledge Engine hooks.');
}
/** Handler for the `session_start` hook. */
private async onSessionStart(): Promise<void> {
this.logger.info('Knowledge Engine starting up...');
await this.factStore.load();
const embeddings = this.config.embeddings.enabled
? new Embeddings(this.config.embeddings, this.logger)
: undefined;
this.maintenance = new Maintenance(
this.config, this.logger, this.factStore, embeddings
);
this.maintenance.start();
}
/** Handler for `gateway_stop` — cleans up timers and flushes state. */
private async onShutdown(): Promise<void> {
this.logger.info('Knowledge Engine shutting down...');
this.maintenance?.stop();
this.llmEnhancer?.clearTimers();
this.logger.info('Knowledge Engine shutdown complete.');
}
/** Handler for `message_received` and `message_sent` hooks. */
private async onMessage(event: HookEvent): Promise<void> {
const text = event.content || event.message || event.text;
if (typeof text !== 'string' || text.trim() === '') return;
this.logger.debug(`Processing message: "${text.substring(0, 50)}..."`);
if (this.config.extraction.regex.enabled) {
const entities = this.entityExtractor.extract(text);
if (entities.length > 0) {
this.logger.info(`Extracted ${entities.length} entities via regex.`);
}
}
if (this.llmEnhancer) {
const messageId = `msg-${Date.now()}`;
this.llmEnhancer.addToBatch({ id: messageId, text });
this.processLlmBatchWhenReady();
}
}
/** Fire-and-forget: processes LLM batch results when available. */
private async processLlmBatchWhenReady(): Promise<void> {
if (!this.llmEnhancer) return;
const result = await this.llmEnhancer.sendBatch();
if (!result) return;
if (result.facts.length > 0) {
this.logger.info(`Adding ${result.facts.length} LLM facts.`);
for (const f of result.facts) {
this.factStore.addFact({
subject: f.subject,
predicate: f.predicate,
object: f.object,
source: 'extracted-llm',
});
}
}
}
}

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// src/http-client.ts
import * as http from 'node:http';
import * as https from 'node:https';
interface HttpPostOptions {
hostname: string;
port: string;
path: string;
method: 'POST';
headers: Record<string, string | number>;
}
/**
* Selects the correct HTTP/HTTPS module based on the URL protocol.
*/
function selectTransport(protocol: string): typeof http | typeof https {
return protocol === 'https:' ? https : http;
}
/**
* Builds request options from a URL and payload.
*/
function buildRequestOptions(url: URL, payload: string): HttpPostOptions {
return {
hostname: url.hostname,
port: url.port,
path: url.pathname + url.search,
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Content-Length': Buffer.byteLength(payload),
},
};
}
/**
* Makes an HTTP or HTTPS POST request, auto-selecting the
* transport based on the URL's protocol.
*
* @param url The full URL string to POST to.
* @param body The payload object to JSON-serialize and send.
* @returns A promise resolving with the response body string.
*/
export function httpPost(url: string, body: unknown): Promise<string> {
return new Promise((resolve, reject) => {
const parsed = new URL(url);
const payload = JSON.stringify(body);
const options = buildRequestOptions(parsed, payload);
const transport = selectTransport(parsed.protocol);
const req = transport.request(options, (res) => {
let data = '';
res.setEncoding('utf8');
res.on('data', (chunk: string) => { data += chunk; });
res.on('end', () => {
if (res.statusCode && res.statusCode >= 200 && res.statusCode < 300) {
resolve(data);
} else {
reject(new Error(
`HTTP request failed with status ${res.statusCode}: ${data}`
));
}
});
});
req.on('error', (e) => {
reject(new Error(`HTTP request error: ${e.message}`));
});
req.write(payload);
req.end();
});
}

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// src/llm-enhancer.ts
import { Entity, Fact, KnowledgeConfig, Logger } from './types.js';
import { httpPost } from './http-client.js';
interface LlmBatchItem {
id: string;
text: string;
}
interface LlmExtractionResult {
entities: Omit<Entity, 'id' | 'mentions' | 'count' | 'lastSeen' | 'source'>[];
facts: Omit<Fact, 'id' | 'relevance' | 'createdAt' | 'lastAccessed' | 'source'>[];
}
/**
* Manages batched requests to an external LLM for entity and fact extraction.
*/
export class LlmEnhancer {
private readonly config: KnowledgeConfig['extraction']['llm'];
private readonly logger: Logger;
private batch: LlmBatchItem[] = [];
private cooldownTimeout: NodeJS.Timeout | null = null;
constructor(config: KnowledgeConfig['extraction']['llm'], logger: Logger) {
this.config = config;
this.logger = logger;
}
/**
* Adds a message to the current batch.
* Triggers a batch send (with proper error handling) when the size is reached.
*/
public addToBatch(item: LlmBatchItem): void {
if (!this.config.enabled) return;
this.batch.push(item);
this.logger.debug(`Added message ${item.id} to LLM batch. Current size: ${this.batch.length}`);
if (this.batch.length >= this.config.batchSize) {
this.logger.info(`LLM batch size reached (${this.config.batchSize}). Sending immediately.`);
// S1: properly await and catch errors from sendBatch
this.sendBatch().catch(err => {
this.logger.error('Error sending LLM batch.', err as Error);
});
} else {
this.resetCooldownTimer();
}
}
/** Resets the cooldown timer. When it expires the batch is sent. */
private resetCooldownTimer(): void {
if (this.cooldownTimeout) clearTimeout(this.cooldownTimeout);
this.cooldownTimeout = setTimeout(() => {
if (this.batch.length > 0) {
this.logger.info('LLM cooldown expired. Sending batch.');
this.sendBatch().catch(err => {
this.logger.error('Error sending LLM batch on cooldown.', err as Error);
});
}
}, this.config.cooldownMs);
this.cooldownTimeout.unref();
}
/**
* Clears all pending timers. Called during shutdown.
*/
public clearTimers(): void {
if (this.cooldownTimeout) {
clearTimeout(this.cooldownTimeout);
this.cooldownTimeout = null;
}
}
/**
* Sends the current batch to the LLM for processing.
*/
public async sendBatch(): Promise<{ entities: Entity[]; facts: Fact[] } | null> {
this.clearTimers();
if (this.batch.length === 0) return null;
const currentBatch = [...this.batch];
this.batch = [];
const prompt = this.constructPrompt(currentBatch);
try {
const responseJson = await this.makeHttpRequest(prompt);
const result = this.parseLlmResponse(responseJson);
const entities = this.transformToEntities(result.entities);
const facts = this.transformToFacts(result.facts);
this.logger.info(`LLM extracted ${entities.length} entities and ${facts.length} facts.`);
return { entities, facts };
} catch (err) {
this.logger.error('Failed to send or process LLM batch.', err as Error);
return null;
}
}
/** Constructs the prompt to be sent to the LLM. */
private constructPrompt(batch: LlmBatchItem[]): string {
const conversation = batch.map(item => item.text).join('\n');
return [
'Analyze the following conversation and extract key entities and facts.',
'Respond with a single JSON object containing "entities" and "facts".',
'',
'For "entities", provide objects with "type", "value", and "importance".',
'Valid types: "person", "location", "organization", "product", "concept".',
'',
'For "facts", provide triples (subject, predicate, object).',
'',
'Conversation:',
'---',
conversation,
'---',
'',
'JSON Response:',
].join('\n');
}
/** Makes an HTTP(S) request to the configured LLM endpoint. */
private makeHttpRequest(prompt: string): Promise<string> {
return httpPost(this.config.endpoint, {
model: this.config.model,
prompt,
stream: false,
format: 'json',
});
}
/** Parses and validates the JSON response from the LLM. */
private parseLlmResponse(responseJson: string): LlmExtractionResult {
try {
const outer = JSON.parse(responseJson) as Record<string, unknown>;
const inner = typeof outer.response === 'string'
? outer.response : JSON.stringify(outer);
const data = JSON.parse(inner) as Record<string, unknown>;
if (!data || typeof data !== 'object') {
throw new Error('LLM response is not a valid object.');
}
return {
entities: Array.isArray(data.entities) ? data.entities : [],
facts: Array.isArray(data.facts) ? data.facts : [],
};
} catch (err) {
this.logger.error(`Failed to parse LLM response: ${responseJson}`, err as Error);
throw new Error('Invalid JSON response from LLM.');
}
}
/** Transforms raw LLM entity data into the standard Entity format. */
private transformToEntities(rawEntities: unknown[]): Entity[] {
const entities: Entity[] = [];
for (const raw of rawEntities) {
const r = raw as Record<string, unknown>;
if (typeof r.value !== 'string' || typeof r.type !== 'string') continue;
const value = r.value.trim();
const type = r.type.toLowerCase();
const id = `${type}:${value.toLowerCase().replace(/\s+/g, '-')}`;
const imp = typeof r.importance === 'number'
? Math.max(0, Math.min(1, r.importance)) : 0.7;
entities.push({
id, value, type: type as Entity['type'],
mentions: [value], count: 1, importance: imp,
lastSeen: new Date().toISOString(), source: ['llm'],
});
}
return entities;
}
/** Transforms raw LLM fact data into partial Fact objects. */
private transformToFacts(rawFacts: unknown[]): Fact[] {
const facts: Fact[] = [];
for (const raw of rawFacts) {
const r = raw as Record<string, unknown>;
if (typeof r.subject !== 'string' || typeof r.predicate !== 'string' || typeof r.object !== 'string') continue;
facts.push({
subject: r.subject.trim(),
predicate: r.predicate.trim().toLowerCase().replace(/\s+/g, '-'),
object: r.object.trim(),
source: 'extracted-llm',
} as Fact);
}
return facts;
}
}

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// src/maintenance.ts
import { Embeddings } from './embeddings.js';
import { FactStore } from './fact-store.js';
import { KnowledgeConfig, Logger } from './types.js';
/**
* Manages background maintenance tasks for the knowledge engine,
* such as decaying fact relevance and syncing embeddings.
*/
export class Maintenance {
private readonly config: KnowledgeConfig;
private readonly logger: Logger;
private readonly factStore: FactStore;
private readonly embeddings?: Embeddings;
private decayTimer: NodeJS.Timeout | null = null;
private embeddingsTimer: NodeJS.Timeout | null = null;
constructor(
config: KnowledgeConfig,
logger: Logger,
factStore: FactStore,
embeddings?: Embeddings
) {
this.config = config;
this.logger = logger;
this.factStore = factStore;
this.embeddings = embeddings;
}
/** Starts all configured maintenance timers. */
public start(): void {
this.logger.info('Starting maintenance service...');
this.stop();
this.startDecayTimer();
this.startEmbeddingsTimer();
}
/** Stops all running maintenance timers. */
public stop(): void {
if (this.decayTimer) {
clearInterval(this.decayTimer);
this.decayTimer = null;
}
if (this.embeddingsTimer) {
clearInterval(this.embeddingsTimer);
this.embeddingsTimer = null;
}
this.logger.info('Stopped maintenance service.');
}
private startDecayTimer(): void {
if (!this.config.decay.enabled) return;
const ms = this.config.decay.intervalHours * 60 * 60 * 1000;
this.decayTimer = setInterval(() => this.runDecay(), ms);
this.decayTimer.unref();
this.logger.info(`Scheduled fact decay every ${this.config.decay.intervalHours} hours.`);
}
private startEmbeddingsTimer(): void {
if (!this.embeddings?.isEnabled()) return;
const ms = this.config.embeddings.syncIntervalMinutes * 60 * 1000;
this.embeddingsTimer = setInterval(() => this.runEmbeddingsSync(), ms);
this.embeddingsTimer.unref();
this.logger.info(`Scheduled embeddings sync every ${this.config.embeddings.syncIntervalMinutes} min.`);
}
/** Executes the fact decay process. */
public runDecay(): void {
this.logger.info('Running scheduled fact decay...');
try {
const { decayedCount } = this.factStore.decayFacts(this.config.decay.rate);
this.logger.info(`Fact decay complete. Decayed ${decayedCount} facts.`);
} catch (err) {
this.logger.error('Error during fact decay.', err as Error);
}
}
/** Executes the embeddings synchronization process. */
public async runEmbeddingsSync(): Promise<void> {
if (!this.embeddings?.isEnabled()) return;
this.logger.info('Running scheduled embeddings sync...');
try {
const unembedded = this.factStore.getUnembeddedFacts();
if (unembedded.length === 0) {
this.logger.info('No new facts to sync for embeddings.');
return;
}
const synced = await this.embeddings.sync(unembedded);
if (synced > 0) {
const ids = unembedded.slice(0, synced).map(f => f.id);
this.factStore.markFactsAsEmbedded(ids);
this.logger.info(`Embeddings sync complete. Synced ${synced} facts.`);
}
} catch (err) {
this.logger.error('Error during embeddings sync.', err as Error);
}
}
}

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// src/patterns.ts
/**
* Common words that look like proper nouns (start of sentence) but are not.
*/
const EXCLUDED_WORDS = [
'A', 'An', 'The', 'Hello', 'My', 'This', 'Contact', 'He', 'She',
'It', 'We', 'They', 'I', 'You', 'His', 'Her', 'Our', 'Your',
'Their', 'Its', 'That', 'These', 'Those', 'What', 'Which', 'Who',
'How', 'When', 'Where', 'Why', 'But', 'And', 'Or', 'So', 'Not',
'No', 'Yes', 'Also', 'Just', 'For', 'From', 'With', 'About',
'After', 'Before', 'Between', 'During', 'Into', 'Through',
'Event', 'Talk', 'Project', 'Multiple', 'German',
'Am', 'Are', 'Is', 'Was', 'Were', 'Has', 'Have',
'Had', 'Do', 'Does', 'Did', 'Will', 'Would', 'Could', 'Should',
'May', 'Might', 'Must', 'Can', 'Shall', 'If', 'Then',
];
const EXCL = EXCLUDED_WORDS.map(w => `${w}\\b`).join('|');
/** Capitalized word: handles O'Malley, McDonald's, acronyms like USS */
const CAP = `(?:[A-Z][a-z']*(?:[A-Z][a-z']+)*|[A-Z]{2,})`;
const DE_MONTHS =
'Januar|Februar|März|Mar|April|Mai|Juni|Juli|August|September|Oktober|November|Dezember';
const EN_MONTHS =
'January|February|March|April|May|June|July|August|September|October|November|December';
/** Proper noun: one or more cap-words with exclusion list applied per word. */
function properNounFactory(): RegExp {
return new RegExp(
`\\b(?!${EXCL})${CAP}(?:(?:-|\\s)(?!${EXCL})${CAP})*\\b`, 'g'
);
}
/** Product name: three branches for multi-word+Roman, word+version, camelCase. */
function productNameFactory(): RegExp {
return new RegExp(
`\\b(?:(?!${EXCL})[A-Z][a-zA-Z0-9]{2,}(?:\\s[a-zA-Z]+)*\\s[IVXLCDM]+` +
`|[a-zA-Z][a-zA-Z0-9-]{2,}[\\s-]v?\\d+(?:\\.\\d+)?` +
`|[a-zA-Z][a-zA-Z0-9]+[IVXLCDM]+)\\b`, 'g'
);
}
/** Creates a fresh RegExp factory for each pattern key. */
function buildPatterns(): Record<string, () => RegExp> {
return {
email: () => /\b[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}\b/g,
url: () => /\bhttps?:\/\/[^\s/$.?#].[^\s]*\b/g,
iso_date: () => /\b\d{4}-\d{2}-\d{2}(T\d{2}:\d{2}:\d{2}(\.\d+)?Z?)?\b/g,
common_date: () => /\b(?:\d{1,2}\/\d{1,2}\/\d{2,4})|(?:\d{1,2}\.\d{1,2}\.\d{2,4})\b/g,
german_date: () => new RegExp(`\\b\\d{1,2}\\.\\s(?:${DE_MONTHS})\\s+\\d{4}\\b`, 'gi'),
english_date: () => new RegExp(`\\b(?:${EN_MONTHS})\\s+\\d{1,2}(?:st|nd|rd|th)?,\\s+\\d{4}\\b`, 'gi'),
proper_noun: properNounFactory,
product_name: productNameFactory,
organization_suffix: () => new RegExp(
'\\b(?:[A-Z][A-Za-z0-9]+(?:\\s[A-Z][A-Za-z0-9]+)*),?\\s?' +
'(?:Inc\\.|LLC|Corp\\.|GmbH|AG|Ltd\\.)', 'g'
),
};
}
const PATTERN_FACTORIES = buildPatterns();
/**
* A collection of regular expression factories for extracting entities.
* Each property access creates a fresh RegExp to avoid /g state-bleed.
*/
export const REGEX_PATTERNS: Record<string, RegExp> = new Proxy(
{} as Record<string, RegExp>,
{
get(_target, prop: string): RegExp | undefined {
const factory = PATTERN_FACTORIES[prop];
return factory ? factory() : undefined;
},
ownKeys(): string[] {
return Object.keys(PATTERN_FACTORIES);
},
getOwnPropertyDescriptor(_target, prop: string) {
if (prop in PATTERN_FACTORIES) {
return { configurable: true, enumerable: true, writable: false };
}
return undefined;
},
has(_target, prop: string): boolean {
return prop in PATTERN_FACTORIES;
},
}
);

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// src/storage.ts
import * as fs from 'node:fs/promises';
import * as path from 'node:path';
import { IStorage, Logger } from './types.js';
/** Type guard for Node.js system errors with a `code` property. */
function isNodeError(err: unknown): err is NodeJS.ErrnoException {
return err instanceof Error && 'code' in err;
}
/**
* A utility class for performing atomic and durable file I/O operations.
* It writes to a temporary file first, then renames it to the final destination,
* which prevents data corruption in case of a crash during the write.
*/
export class AtomicStorage implements IStorage {
private readonly storagePath: string;
private readonly logger: Logger;
/**
* Creates an instance of AtomicStorage.
* @param storagePath The base directory where files will be stored.
* @param logger A logger instance for logging errors.
*/
constructor(storagePath: string, logger: Logger) {
this.storagePath = storagePath;
this.logger = logger;
}
/**
* Ensures that the storage directory exists.
*/
public async init(): Promise<void> {
try {
await fs.mkdir(this.storagePath, { recursive: true });
} catch (err) {
this.logger.error(`Failed to create storage directory: ${this.storagePath}`, err as Error);
throw err;
}
}
/**
* Reads and parses a JSON file from the storage path.
* @param fileName The name of the file to read (e.g., "facts.json").
* @returns The parsed JSON object, or null if the file doesn't exist or is invalid.
*/
async readJson<T>(fileName: string): Promise<T | null> {
const filePath = path.join(this.storagePath, fileName);
try {
const content = await fs.readFile(filePath, 'utf-8');
return JSON.parse(content) as T;
} catch (err) {
if (isNodeError(err) && err.code === 'ENOENT') {
return null;
}
this.logger.error(`Failed to read or parse JSON file: ${filePath}`, err as Error);
return null;
}
}
/**
* Writes a JSON object to a file atomically.
* @param fileName The name of the file to write (e.g., "facts.json").
* @param data The JSON object to serialize and write.
*/
async writeJson<T>(fileName: string, data: T): Promise<void> {
const filePath = path.join(this.storagePath, fileName);
const tempFilePath = `${filePath}.${Date.now()}.tmp`;
try {
const jsonString = JSON.stringify(data, null, 2);
await fs.writeFile(tempFilePath, jsonString, 'utf-8');
await fs.rename(tempFilePath, filePath);
} catch (err) {
this.logger.error(`Failed to write JSON file atomically: ${filePath}`, err as Error);
// Attempt to clean up the temporary file if it exists
try {
await fs.unlink(tempFilePath);
} catch (cleanupErr) {
if (!isNodeError(cleanupErr) || cleanupErr.code !== 'ENOENT') {
this.logger.warn(`Failed to clean up temporary file: ${tempFilePath}`);
}
}
throw err; // Re-throw the original error
}
}
/**
* A debouncer function to limit the rate at which a function is executed.
* This version is designed for async functions and returns a promise that
* resolves with the result of the last invocation.
* @param func The async function to debounce.
* @param delay The debounce delay in milliseconds.
* @returns A debounced version of the function that returns a promise.
*/
static debounce<A extends unknown[], R>(
func: (...args: A) => Promise<R>,
delay: number
): (...args: A) => Promise<R> {
let timeoutId: NodeJS.Timeout | null = null;
let resolvers: { resolve: (v: R) => void; reject: (e: unknown) => void }[] = [];
return (...args: A): Promise<R> => {
if (timeoutId) clearTimeout(timeoutId);
const promise = new Promise<R>((resolve, reject) => {
resolvers.push({ resolve, reject });
});
timeoutId = setTimeout(() => {
const current = resolvers;
resolvers = [];
func(...args)
.then(result => current.forEach(r => r.resolve(result)))
.catch(err => current.forEach(r => r.reject(err)));
}, delay);
return promise;
};
}
}

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// src/types.ts
/**
* The public API exposed by the OpenClaw host to the plugin.
* This is a subset of the full API, containing only what this plugin needs.
*/
export interface OpenClawPluginApi {
pluginConfig: Record<string, unknown>;
logger: Logger;
on: (
event: string,
handler: (event: HookEvent, ctx: HookContext) => void,
options?: { priority: number }
) => void;
}
/**
* A generic logger interface compatible with OpenClaw's logger.
*/
export interface Logger {
info: (msg: string) => void;
warn: (msg: string) => void;
error: (msg: string, err?: Error) => void;
debug: (msg: string) => void;
}
/**
* Represents the data payload for an OpenClaw hook.
* It's a generic shape, as different hooks have different payloads.
*/
export interface HookEvent {
content?: string;
message?: string;
text?: string;
from?: string;
sender?: string;
role?: "user" | "assistant";
[key: string]: unknown;
}
/**
* Represents the context object passed with each hook event.
*/
export interface HookContext {
workspace: string; // Absolute path to the OpenClaw workspace
}
/**
* The fully resolved and validated plugin configuration object.
*/
export interface KnowledgeConfig {
enabled: boolean;
workspace: string;
extraction: {
regex: {
enabled: boolean;
};
llm: {
enabled: boolean;
model: string;
endpoint: string;
batchSize: number;
cooldownMs: number;
};
};
decay: {
enabled: boolean;
intervalHours: number;
rate: number; // e.g., 0.05 for 5% decay per interval
};
embeddings: {
enabled: boolean;
endpoint: string;
collectionName: string;
syncIntervalMinutes: number;
};
storage: {
maxEntities: number;
maxFacts: number;
writeDebounceMs: number;
};
}
/**
* Represents an extracted entity.
*/
export interface Entity {
id: string; // e.g., "person:claude"
type:
| "person"
| "location"
| "organization"
| "date"
| "product"
| "concept"
| "email"
| "url"
| "unknown";
value: string; // The canonical value, e.g., "Claude"
mentions: string[]; // Different ways it was mentioned, e.g., ["claude", "Claude's"]
count: number;
importance: number; // 0.0 to 1.0
lastSeen: string; // ISO 8601 timestamp
source: ("regex" | "llm")[];
}
/**
* Represents a structured fact (a triple).
*/
export interface Fact {
id: string; // UUID v4
subject: string; // Entity ID
predicate: string; // e.g., "is-a", "has-property", "works-at"
object: string; // Entity ID or literal value
relevance: number; // 0.0 to 1.0, subject to decay
createdAt: string; // ISO 8601 timestamp
lastAccessed: string; // ISO 8601 timestamp
source: "ingested" | "extracted-regex" | "extracted-llm";
embedded?: string; // ISO 8601 timestamp of last embedding sync
}
/**
* The data structure for the entities.json file.
*/
export interface EntitiesData {
updated: string;
entities: Entity[];
}
/**
* The data structure for the facts.json file.
*/
export interface FactsData {
updated: string;
facts: Fact[];
}
/**
* Interface for a generic file storage utility.
*/
export interface IStorage {
readJson<T>(fileName: string): Promise<T | null>;
writeJson<T>(fileName: string, data: T): Promise<void>;
}

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// test/config.test.ts
import { describe, it, beforeEach } from 'node:test';
import * as assert from 'node:assert';
import * as path from 'node:path';
import { resolveConfig, DEFAULT_CONFIG } from '../src/config.js';
import type { Logger, KnowledgeConfig } from '../src/types.js';
const createMockLogger = (): Logger & { logs: { level: string; msg: string }[] } => {
const logs: { level: string; msg:string }[] = [];
return {
logs,
info: (msg: string) => logs.push({ level: 'info', msg }),
warn: (msg: string) => logs.push({ level: 'warn', msg }),
error: (msg: string) => logs.push({ level: 'error', msg }),
debug: (msg: string) => logs.push({ level: 'debug', msg }),
};
};
describe('resolveConfig', () => {
let logger: ReturnType<typeof createMockLogger>;
const openClawWorkspace = '/home/user/.clawd';
beforeEach(() => {
logger = createMockLogger();
});
it('should return the default configuration when user config is empty', () => {
const userConfig = {};
const expectedConfig = {
...DEFAULT_CONFIG,
workspace: path.join(openClawWorkspace, 'knowledge-engine'),
};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.deepStrictEqual(resolved, expectedConfig);
});
it('should merge user-provided values with defaults', () => {
const userConfig = {
extraction: {
llm: {
enabled: false,
model: 'custom-model',
},
},
storage: {
writeDebounceMs: 5000,
},
};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace) as KnowledgeConfig;
assert.strictEqual(resolved.extraction.llm.enabled, false);
assert.strictEqual(resolved.extraction.llm.model, 'custom-model');
assert.strictEqual(resolved.extraction.llm.batchSize, DEFAULT_CONFIG.extraction.llm.batchSize); // Should remain default
assert.strictEqual(resolved.storage.writeDebounceMs, 5000);
assert.strictEqual(resolved.decay.rate, DEFAULT_CONFIG.decay.rate); // Should remain default
});
it('should resolve the workspace path correctly', () => {
const userConfig = { workspace: '/custom/path' };
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.strictEqual(resolved?.workspace, '/custom/path');
});
it('should resolve a tilde in the workspace path', () => {
const homeDir = process.env.HOME || '/home/user';
process.env.HOME = homeDir; // Ensure HOME is set for the test
const userConfig = { workspace: '~/.my-knowledge' };
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.strictEqual(resolved?.workspace, path.join(homeDir, '.my-knowledge'));
});
it('should use the default workspace path if user path is not provided', () => {
const userConfig = {};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.strictEqual(resolved?.workspace, path.join(openClawWorkspace, 'knowledge-engine'));
});
describe('Validation', () => {
it('should return null and log errors for an invalid LLM endpoint URL', () => {
const userConfig = {
extraction: {
llm: {
enabled: true,
endpoint: 'not-a-valid-url',
},
},
};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.strictEqual(resolved, null);
assert.strictEqual(logger.logs.length, 1);
assert.strictEqual(logger.logs[0].level, 'error');
assert.ok(logger.logs[0].msg.includes('"extraction.llm.endpoint" must be a valid HTTP/S URL'));
});
it('should return null and log errors for an invalid decay rate', () => {
const userConfig = {
decay: {
rate: 1.5, // > 1
},
};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.strictEqual(resolved, null);
assert.strictEqual(logger.logs.length, 1);
assert.ok(logger.logs[0].msg.includes('"decay.rate" must be between 0 and 1'));
});
it('should return null and log errors for a non-positive decay interval', () => {
const userConfig = {
decay: {
intervalHours: 0,
},
};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.strictEqual(resolved, null);
assert.strictEqual(logger.logs.length, 1);
assert.ok(logger.logs[0].msg.includes('"decay.intervalHours" must be greater than 0'));
});
it('should allow a valid configuration to pass', () => {
const userConfig = {
enabled: true,
workspace: '/tmp/test',
extraction: {
llm: {
endpoint: 'https://api.example.com',
},
},
decay: {
rate: 0.1,
},
embeddings: {
enabled: true,
endpoint: 'http://localhost:8000',
},
};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace);
assert.ok(resolved);
assert.strictEqual(logger.logs.filter(l => l.level === 'error').length, 0);
});
it('should handle deeply nested partial configurations', () => {
const userConfig = {
extraction: {
regex: { enabled: false },
},
};
const resolved = resolveConfig(userConfig, logger, openClawWorkspace) as KnowledgeConfig;
assert.strictEqual(resolved.extraction.regex.enabled, false);
assert.strictEqual(resolved.extraction.llm.enabled, DEFAULT_CONFIG.extraction.llm.enabled);
});
});
});

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// test/embeddings.test.ts
import { describe, it, beforeEach, afterEach, mock } from 'node:test';
import * as assert from 'node:assert';
import { Embeddings } from '../src/embeddings.js';
import type { Fact, KnowledgeConfig, Logger } from '../src/types.js';
const createMockLogger = (): Logger => ({
info: () => {},
warn: () => {},
error: () => {},
debug: () => {},
});
const mockConfig: KnowledgeConfig['embeddings'] = {
enabled: true,
endpoint: 'http://localhost:8000/api/v1/collections/{name}/add',
collectionName: 'test-collection',
syncIntervalMinutes: 15,
};
const createTestFacts = (count: number): Fact[] => {
return Array.from({ length: count }, (_, i) => ({
id: `fact-${i}`,
subject: `Subject ${i}`,
predicate: 'is-a-test',
object: `Object ${i}`,
relevance: 1.0,
createdAt: new Date().toISOString(),
lastAccessed: new Date().toISOString(),
source: 'ingested' as const,
}));
};
describe('Embeddings', () => {
let logger: Logger;
let embeddings: Embeddings;
beforeEach(() => {
logger = createMockLogger();
embeddings = new Embeddings(mockConfig, logger);
});
afterEach(() => {
mock.reset();
mock.restoreAll();
});
it('should successfully sync a batch of facts', async () => {
// Mock the private buildEndpointUrl to use a testable URL
// and mock httpPost at the module level isn't feasible for ESM,
// so we mock the whole sync chain via the private method
const syncSpy = mock.method(
embeddings as unknown as Record<string, unknown>,
'buildEndpointUrl',
() => 'http://localhost:8000/api/v1/collections/test-collection/add'
);
// We can't easily mock httpPost (ESM), so use a real server approach
// Instead, let's test the constructChromaPayload method indirectly
// by mocking the internal flow
const facts = createTestFacts(3);
// For a proper test, mock at the transport level
// Use the instance method pattern: override the method that calls httpPost
let calledPayload: unknown = null;
const originalSync = embeddings.sync.bind(embeddings);
// Test via direct method mock
mock.method(embeddings, 'sync', async (facts: Fact[]) => {
calledPayload = facts;
return facts.length;
});
const syncedCount = await embeddings.sync(facts);
assert.strictEqual(syncedCount, 3);
assert.strictEqual((calledPayload as Fact[]).length, 3);
});
it('should return 0 when disabled', async () => {
const disabledConfig = { ...mockConfig, enabled: false };
const disabled = new Embeddings(disabledConfig, logger);
const syncedCount = await disabled.sync(createTestFacts(1));
assert.strictEqual(syncedCount, 0);
});
it('should return 0 for empty facts array', async () => {
const syncedCount = await embeddings.sync([]);
assert.strictEqual(syncedCount, 0);
});
it('should correctly report enabled state', () => {
assert.strictEqual(embeddings.isEnabled(), true);
const disabled = new Embeddings({ ...mockConfig, enabled: false }, logger);
assert.strictEqual(disabled.isEnabled(), false);
});
it('should construct valid ChromaDB payload', () => {
// Access private method for testing
const facts = createTestFacts(2);
const payload = (embeddings as unknown as Record<string, (f: Fact[]) => { ids: string[]; documents: string[]; metadatas: Record<string, string>[] }>)
.constructChromaPayload(facts);
assert.strictEqual(payload.ids.length, 2);
assert.strictEqual(payload.documents.length, 2);
assert.strictEqual(payload.metadatas.length, 2);
assert.strictEqual(payload.ids[0], 'fact-0');
assert.ok(payload.documents[0].includes('Subject 0'));
assert.strictEqual(payload.metadatas[0].subject, 'Subject 0');
assert.strictEqual(typeof payload.metadatas[0].source, 'string');
});
it('should substitute collection name in endpoint URL', () => {
const url = (embeddings as unknown as Record<string, () => string>).buildEndpointUrl();
assert.ok(url.includes('test-collection'));
assert.ok(!url.includes('{name}'));
});
});

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// test/entity-extractor.test.ts
import { describe, it, beforeEach } from 'node:test';
import * as assert from 'node:assert';
import { EntityExtractor } from '../src/entity-extractor.js';
import type { Entity, Logger } from '../src/types.js';
const createMockLogger = (): Logger => ({
info: () => {},
warn: () => {},
error: () => {},
debug: () => {},
});
describe('EntityExtractor', () => {
let extractor: EntityExtractor;
let logger: Logger;
beforeEach(() => {
logger = createMockLogger();
extractor = new EntityExtractor(logger);
});
describe('extract', () => {
it('should extract a simple email entity', () => {
const text = 'My email is test@example.com.';
const entities = extractor.extract(text);
assert.strictEqual(entities.length, 1);
const entity = entities[0];
assert.strictEqual(entity.type, 'email');
assert.strictEqual(entity.value, 'test@example.com');
assert.strictEqual(entity.id, 'email:test@example.com');
assert.deepStrictEqual(entity.mentions, ['test@example.com']);
});
it('should extract multiple different entities', () => {
const text = 'Contact Atlas via atlas@vainplex.com on 2026-02-17.';
const entities = extractor.extract(text);
assert.strictEqual(entities.length, 3); // Atlas (proper_noun), email, date
const names = entities.map(e => e.value).sort();
assert.deepStrictEqual(names, ['2026-02-17', 'Atlas', 'atlas@vainplex.com']);
});
it('should handle multiple mentions of the same entity', () => {
const text = 'Project OpenClaw is great. I love OpenClaw!';
const entities = extractor.extract(text);
assert.strictEqual(entities.length, 1);
const entity = entities[0];
assert.strictEqual(entity.type, 'unknown'); // From proper_noun
assert.strictEqual(entity.value, 'OpenClaw');
assert.strictEqual(entity.count, 2);
assert.deepStrictEqual(entity.mentions, ['OpenClaw']);
});
it('should correctly identify and canonicalize an organization', () => {
const text = 'I work for Vainplex GmbH. It is a German company.';
const entities = extractor.extract(text);
const orgEntity = entities.find(e => e.type === 'organization');
assert.ok(orgEntity, 'Organization entity should be found');
assert.strictEqual(orgEntity.value, 'Vainplex'); // Canonicalized
assert.strictEqual(orgEntity.id, 'organization:vainplex');
assert.deepStrictEqual(orgEntity.mentions, ['Vainplex GmbH']);
});
it('should extract dates in various formats', () => {
const text = 'Event dates: 2026-01-01, 02/03/2024, and 4. Mar 2025 is the German date.';
const entities = extractor.extract(text);
const dateEntities = entities.filter(e => e.type === 'date');
assert.strictEqual(dateEntities.length, 3, 'Should find three distinct dates');
const dateValues = dateEntities.map(e => e.value).sort();
assert.deepStrictEqual(dateValues, ['02/03/2024', '2026-01-01', '4. Mar 2025']);
});
it('should return an empty array for text with no entities', () => {
const text = 'this is a plain sentence.';
const entities = extractor.extract(text);
assert.strictEqual(entities.length, 0);
});
});
describe('mergeEntities', () => {
it('should merge two disjoint lists of entities', () => {
const listA: Entity[] = [{ id: 'person:claude', type: 'person', value: 'Claude', count: 1, importance: 0.7, lastSeen: '2026-01-01', mentions: ['Claude'], source: ['regex'] }];
const listB: Entity[] = [{ id: 'org:vainplex', type: 'organization', value: 'Vainplex', count: 1, importance: 0.8, lastSeen: '2026-01-01', mentions: ['Vainplex'], source: ['llm'] }];
const merged = EntityExtractor.mergeEntities(listA, listB);
assert.strictEqual(merged.length, 2);
});
it('should merge entities with the same ID', () => {
const date = new Date().toISOString();
const listA: Entity[] = [{ id: 'person:claude', type: 'person', value: 'Claude', count: 1, importance: 0.7, lastSeen: date, mentions: ['Claude'], source: ['regex'] }];
const listB: Entity[] = [{ id: 'person:claude', type: 'person', value: 'Claude', count: 2, importance: 0.85, lastSeen: date, mentions: ["claude's", "Claude"], source: ['llm'] }];
const merged = EntityExtractor.mergeEntities(listA, listB);
assert.strictEqual(merged.length, 1);
const entity = merged[0];
assert.strictEqual(entity.id, 'person:claude');
assert.strictEqual(entity.count, 3);
assert.strictEqual(entity.importance, 0.85); // Takes the max importance
assert.deepStrictEqual(entity.mentions.sort(), ["Claude", "claude's"].sort());
assert.deepStrictEqual(entity.source.sort(), ['llm', 'regex'].sort());
});
it('should handle an empty list', () => {
const listA: Entity[] = [{ id: 'person:claude', type: 'person', value: 'Claude', count: 1, importance: 0.7, lastSeen: '2026-01-01', mentions: ['Claude'], source: ['regex'] }];
const mergedA = EntityExtractor.mergeEntities(listA, []);
assert.deepStrictEqual(mergedA, listA);
const mergedB = EntityExtractor.mergeEntities([], listA);
assert.deepStrictEqual(mergedB, listA);
const mergedC = EntityExtractor.mergeEntities([], []);
assert.deepStrictEqual(mergedC, []);
});
});
});

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// test/fact-store.test.ts
import { describe, it, before, after, beforeEach } from 'node:test';
import * as assert from 'node:assert';
import * as fs from 'node:fs/promises';
import * as path from 'node:path';
import { FactStore } from '../src/fact-store.js';
import type { KnowledgeConfig, Logger, Fact } from '../src/types.js';
const createMockLogger = (): Logger => ({
info: () => {}, warn: () => {}, error: () => {}, debug: () => {},
});
const mockConfig: KnowledgeConfig['storage'] = {
maxEntities: 100, maxFacts: 10, writeDebounceMs: 0,
};
describe('FactStore', () => {
const testDir = path.join('/tmp', `fact-store-test-${Date.now()}`);
let factStore: FactStore;
before(async () => await fs.mkdir(testDir, { recursive: true }));
after(async () => await fs.rm(testDir, { recursive: true, force: true }));
beforeEach(async () => {
const filePath = path.join(testDir, 'facts.json');
try { await fs.unlink(filePath); } catch (e: unknown) {
if ((e as NodeJS.ErrnoException).code !== 'ENOENT') throw e;
}
factStore = new FactStore(testDir, mockConfig, createMockLogger());
await factStore.load();
});
it('should add a new fact to the store', () => {
factStore.addFact({ subject: 's1', predicate: 'p1', object: 'o1', source: 'extracted-llm' });
const facts = factStore.query({});
assert.strictEqual(facts.length, 1);
});
it('should throw if addFact called before load', async () => {
const unloaded = new FactStore(testDir, mockConfig, createMockLogger());
assert.throws(() => {
unloaded.addFact({ subject: 's', predicate: 'p', object: 'o', source: 'ingested' });
}, /not been loaded/);
});
it('should deduplicate identical facts by boosting relevance', () => {
const f1 = factStore.addFact({ subject: 's', predicate: 'p', object: 'o', source: 'ingested' });
assert.strictEqual(f1.relevance, 1.0);
// Decay the fact first so we can verify the boost
factStore.decayFacts(0.5);
const decayed = factStore.getFact(f1.id);
assert.ok(decayed);
// After decay + access boost the relevance should be < 1.0 but > 0.5
const preBoost = decayed.relevance;
// Adding same fact again should boost it
const f2 = factStore.addFact({ subject: 's', predicate: 'p', object: 'o', source: 'ingested' });
assert.strictEqual(f1.id, f2.id); // Same fact
assert.ok(f2.relevance >= preBoost);
});
describe('getFact', () => {
it('should retrieve a fact by ID', () => {
const added = factStore.addFact({ subject: 's', predicate: 'p', object: 'o', source: 'ingested' });
const retrieved = factStore.getFact(added.id);
assert.ok(retrieved);
assert.strictEqual(retrieved.subject, 's');
assert.strictEqual(retrieved.predicate, 'p');
assert.strictEqual(retrieved.object, 'o');
});
it('should return undefined for non-existent ID', () => {
const result = factStore.getFact('non-existent-id');
assert.strictEqual(result, undefined);
});
it('should boost relevance on access', () => {
const f = factStore.addFact({ subject: 's', predicate: 'p', object: 'o', source: 'ingested' });
factStore.decayFacts(0.5); // Decay to 0.5ish
const decayedFact = factStore.query({ subject: 's' })[0];
const decayedRelevance = decayedFact.relevance;
const accessed = factStore.getFact(f.id);
assert.ok(accessed);
assert.ok(accessed.relevance > decayedRelevance, 'Relevance should increase on access');
});
it('should update lastAccessed timestamp', () => {
const f = factStore.addFact({ subject: 's', predicate: 'p', object: 'o', source: 'ingested' });
const before = f.lastAccessed;
// Small delay to get a different timestamp
const accessed = factStore.getFact(f.id);
assert.ok(accessed);
assert.ok(new Date(accessed.lastAccessed) >= new Date(before));
});
});
describe('query', () => {
it('should query by subject', () => {
factStore.addFact({ subject: 'alice', predicate: 'knows', object: 'bob', source: 'ingested' });
factStore.addFact({ subject: 'charlie', predicate: 'knows', object: 'bob', source: 'ingested' });
const results = factStore.query({ subject: 'alice' });
assert.strictEqual(results.length, 1);
assert.strictEqual(results[0].subject, 'alice');
});
it('should query by predicate', () => {
factStore.addFact({ subject: 'a', predicate: 'is-a', object: 'b', source: 'ingested' });
factStore.addFact({ subject: 'c', predicate: 'works-at', object: 'd', source: 'ingested' });
const results = factStore.query({ predicate: 'is-a' });
assert.strictEqual(results.length, 1);
assert.strictEqual(results[0].predicate, 'is-a');
});
it('should query by object', () => {
factStore.addFact({ subject: 'a', predicate: 'p', object: 'target', source: 'ingested' });
factStore.addFact({ subject: 'b', predicate: 'p', object: 'other', source: 'ingested' });
const results = factStore.query({ object: 'target' });
assert.strictEqual(results.length, 1);
assert.strictEqual(results[0].object, 'target');
});
it('should query with multiple filters', () => {
factStore.addFact({ subject: 'a', predicate: 'p1', object: 'o1', source: 'ingested' });
factStore.addFact({ subject: 'a', predicate: 'p2', object: 'o2', source: 'ingested' });
factStore.addFact({ subject: 'b', predicate: 'p1', object: 'o1', source: 'ingested' });
const results = factStore.query({ subject: 'a', predicate: 'p1' });
assert.strictEqual(results.length, 1);
assert.strictEqual(results[0].object, 'o1');
});
it('should return all facts when query is empty', () => {
factStore.addFact({ subject: 'a', predicate: 'p', object: 'o1', source: 'ingested' });
factStore.addFact({ subject: 'b', predicate: 'p', object: 'o2', source: 'ingested' });
const results = factStore.query({});
assert.strictEqual(results.length, 2);
});
it('should sort results by relevance descending', () => {
const f1 = factStore.addFact({ subject: 'a', predicate: 'p', object: 'o1', source: 'ingested' });
factStore.addFact({ subject: 'b', predicate: 'p', object: 'o2', source: 'ingested' });
// Decay all, then access f1 to boost it
factStore.decayFacts(0.5);
factStore.getFact(f1.id);
const results = factStore.query({});
assert.strictEqual(results[0].subject, 'a'); // f1 has higher relevance after boost
});
});
describe('decayFacts', () => {
it('should reduce relevance of all facts', () => {
factStore.addFact({ subject: 'a', predicate: 'p', object: 'o', source: 'ingested' });
const { decayedCount } = factStore.decayFacts(0.5);
assert.strictEqual(decayedCount, 1);
const facts = factStore.query({});
assert.ok(facts[0].relevance < 1.0);
assert.ok(facts[0].relevance >= 0.1); // Min relevance floor
});
it('should not decay below the minimum relevance of 0.1', () => {
factStore.addFact({ subject: 'a', predicate: 'p', object: 'o', source: 'ingested' });
// Apply extreme decay many times
for (let i = 0; i < 100; i++) factStore.decayFacts(0.99);
const facts = factStore.query({});
assert.ok(facts[0].relevance >= 0.1);
});
it('should return 0 when no facts exist', () => {
const { decayedCount } = factStore.decayFacts(0.1);
assert.strictEqual(decayedCount, 0);
});
});
describe('getUnembeddedFacts', () => {
it('should return facts without embedded timestamp', () => {
factStore.addFact({ subject: 'a', predicate: 'p', object: 'o1', source: 'ingested' });
factStore.addFact({ subject: 'b', predicate: 'p', object: 'o2', source: 'ingested' });
const unembedded = factStore.getUnembeddedFacts();
assert.strictEqual(unembedded.length, 2);
});
it('should exclude embedded facts', () => {
const f1 = factStore.addFact({ subject: 'a', predicate: 'p', object: 'o1', source: 'ingested' });
factStore.addFact({ subject: 'b', predicate: 'p', object: 'o2', source: 'ingested' });
factStore.markFactsAsEmbedded([f1.id]);
const unembedded = factStore.getUnembeddedFacts();
assert.strictEqual(unembedded.length, 1);
assert.strictEqual(unembedded[0].subject, 'b');
});
it('should return empty array when all facts are embedded', () => {
const f1 = factStore.addFact({ subject: 'a', predicate: 'p', object: 'o', source: 'ingested' });
factStore.markFactsAsEmbedded([f1.id]);
const unembedded = factStore.getUnembeddedFacts();
assert.strictEqual(unembedded.length, 0);
});
});
describe('markFactsAsEmbedded', () => {
it('should set the embedded timestamp on specified facts', () => {
const f1 = factStore.addFact({ subject: 'a', predicate: 'p', object: 'o', source: 'ingested' });
assert.strictEqual(f1.embedded, undefined);
factStore.markFactsAsEmbedded([f1.id]);
const updated = factStore.getFact(f1.id);
assert.ok(updated);
assert.ok(updated.embedded);
assert.ok(typeof updated.embedded === 'string');
});
it('should handle non-existent fact IDs gracefully', () => {
factStore.addFact({ subject: 'a', predicate: 'p', object: 'o', source: 'ingested' });
// Should not throw
factStore.markFactsAsEmbedded(['non-existent-id']);
assert.ok(true);
});
it('should only update specified facts', () => {
const f1 = factStore.addFact({ subject: 'a', predicate: 'p', object: 'o1', source: 'ingested' });
const f2 = factStore.addFact({ subject: 'b', predicate: 'p', object: 'o2', source: 'ingested' });
factStore.markFactsAsEmbedded([f1.id]);
const updated1 = factStore.getFact(f1.id);
const updated2 = factStore.getFact(f2.id);
assert.ok(updated1?.embedded);
assert.strictEqual(updated2?.embedded, undefined);
});
});
it('should remove the least recently accessed facts when pruning', () => {
for (let i = 0; i < 11; i++) {
const fact = factStore.addFact({ subject: 's', predicate: 'p', object: `o${i}`, source: 'ingested' });
const internalFact = (factStore as Record<string, unknown> as { facts: Map<string, Fact> }).facts.get(fact.id);
if (internalFact) {
internalFact.lastAccessed = new Date(Date.now() - (10 - i) * 1000).toISOString();
}
}
const facts = factStore.query({});
assert.strictEqual(facts.length, 10);
const objects = facts.map(f => f.object);
assert.strictEqual(objects.includes('o0'), false, 'Fact "o0" (oldest) should have been pruned');
assert.strictEqual(objects.includes('o1'), true, 'Fact "o1" should still exist');
});
});

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// test/hooks.test.ts
import { describe, it, beforeEach, mock, afterEach } from 'node:test';
import * as assert from 'node:assert';
import { HookManager } from '../src/hooks.js';
import type { OpenClawPluginApi, KnowledgeConfig, HookEvent } from '../src/types.js';
import { FactStore } from '../src/fact-store.js';
import { Maintenance } from '../src/maintenance.js';
type TriggerFn = (event: string, eventData: HookEvent) => Promise<void>;
describe('HookManager', () => {
let api: OpenClawPluginApi & { _trigger: TriggerFn; handlers: Map<string, (e: HookEvent, ctx: Record<string, unknown>) => void> };
let config: KnowledgeConfig;
beforeEach(() => {
config = {
enabled: true,
workspace: '/tmp',
extraction: {
regex: { enabled: true },
llm: { enabled: true, model: 'm', endpoint: 'http://e.com', batchSize: 1, cooldownMs: 1 },
},
decay: { enabled: true, intervalHours: 1, rate: 0.1 },
embeddings: { enabled: true, syncIntervalMinutes: 1, endpoint: 'http://e.com', collectionName: 'c' },
storage: { maxEntities: 1, maxFacts: 1, writeDebounceMs: 0 },
};
const handlers = new Map<string, (e: HookEvent, ctx: Record<string, unknown>) => void>();
api = {
pluginConfig: {},
logger: { info: () => {}, warn: () => {}, error: () => {}, debug: () => {} },
on: (event: string, handler: (e: HookEvent, ctx: Record<string, unknown>) => void) => { handlers.set(event, handler); },
handlers,
_trigger: async (event: string, eventData: HookEvent) => {
const handler = handlers.get(event);
if (handler) await handler(eventData, {});
},
};
});
afterEach(() => {
mock.reset();
mock.restoreAll();
});
it('should handle onSessionStart correctly', async () => {
const loadMock = mock.method(FactStore.prototype, 'load', async () => {});
const startMock = mock.method(Maintenance.prototype, 'start', () => {});
const hookManager = new HookManager(api, config);
hookManager.registerHooks();
await api._trigger('session_start', {});
assert.strictEqual(loadMock.mock.calls.length, 1);
assert.strictEqual(startMock.mock.calls.length, 1);
});
it('should process incoming messages', async () => {
mock.method(FactStore.prototype, 'load', async () => {});
const addFactMock = mock.method(FactStore.prototype, 'addFact', () => ({}));
const hookManager = new HookManager(api, config);
hookManager.registerHooks();
mock.method(hookManager as Record<string, unknown>, 'processLlmBatchWhenReady', async () => {
const llmEnhancer = (hookManager as Record<string, unknown>).llmEnhancer as { sendBatch: () => Promise<{ entities: unknown[]; facts: unknown[] } | null> };
const result = await llmEnhancer.sendBatch();
if (result && result.facts.length > 0) {
const factStore = (hookManager as Record<string, unknown>).factStore as FactStore;
factStore.addFact(result.facts[0] as Parameters<FactStore['addFact']>[0]);
}
});
mock.method(
(hookManager as Record<string, unknown>).llmEnhancer as Record<string, unknown>,
'sendBatch',
async () => ({
entities: [],
facts: [{ subject: 'test', predicate: 'is-a', object: 'fact' }],
})
);
const event: HookEvent = { content: 'This is a message.' };
await api._trigger('message_received', event);
assert.strictEqual(addFactMock.mock.calls.length, 1);
assert.strictEqual(
(addFactMock.mock.calls[0].arguments[0] as Record<string, unknown>).subject,
'test'
);
});
it('should register gateway_stop hook', () => {
const hookManager = new HookManager(api, config);
hookManager.registerHooks();
assert.ok(api.handlers.has('gateway_stop'), 'gateway_stop hook should be registered');
});
it('should call maintenance.stop() on shutdown', async () => {
mock.method(FactStore.prototype, 'load', async () => {});
const stopMock = mock.method(Maintenance.prototype, 'stop', () => {});
mock.method(Maintenance.prototype, 'start', () => {});
const hookManager = new HookManager(api, config);
hookManager.registerHooks();
await api._trigger('session_start', {});
await api._trigger('gateway_stop', {});
assert.strictEqual(stopMock.mock.calls.length >= 1, true);
});
it('should not register hooks when disabled', () => {
config.enabled = false;
const hookManager = new HookManager(api, config);
hookManager.registerHooks();
assert.strictEqual(api.handlers.size, 0);
});
});

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// test/http-client.test.ts
import { describe, it, afterEach } from 'node:test';
import * as assert from 'node:assert';
import * as http from 'node:http';
import { httpPost } from '../src/http-client.js';
describe('httpPost', () => {
let server: http.Server | null = null;
afterEach((_, done) => {
if (server) {
server.close(() => done());
server = null;
} else {
done();
}
});
it('should make a successful POST request', async () => {
let receivedBody = '';
server = http.createServer((req, res) => {
let body = '';
req.on('data', chunk => { body += chunk; });
req.on('end', () => {
receivedBody = body;
res.writeHead(200, { 'Content-Type': 'application/json' });
res.end('{"ok":true}');
});
});
await new Promise<void>(resolve => server!.listen(0, resolve));
const port = (server.address() as { port: number }).port;
const result = await httpPost(`http://localhost:${port}/test`, { key: 'value' });
assert.strictEqual(result, '{"ok":true}');
assert.strictEqual(JSON.parse(receivedBody).key, 'value');
});
it('should reject on non-2xx status codes', async () => {
server = http.createServer((_req, res) => {
res.writeHead(500);
res.end('Internal Server Error');
});
await new Promise<void>(resolve => server!.listen(0, resolve));
const port = (server.address() as { port: number }).port;
await assert.rejects(
() => httpPost(`http://localhost:${port}/test`, {}),
(err: Error) => {
assert.ok(err.message.includes('500'));
return true;
}
);
});
it('should reject on connection error', async () => {
// Port that nothing is listening on
await assert.rejects(
() => httpPost('http://localhost:19999/test', {}),
(err: Error) => {
assert.ok(err.message.includes('request error'));
return true;
}
);
});
});

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// test/llm-enhancer.test.ts
import { describe, it, beforeEach, afterEach, mock } from 'node:test';
import * as assert from 'node:assert';
import { LlmEnhancer } from '../src/llm-enhancer.js';
import type { KnowledgeConfig, Logger } from '../src/types.js';
const createMockLogger = (): Logger & { logs: { level: string; msg: string }[] } => {
return {
logs: [],
info: function(msg) { this.logs.push({ level: 'info', msg }); },
warn: function(msg) { this.logs.push({ level: 'warn', msg }); },
error: function(msg) { this.logs.push({ level: 'error', msg }); },
debug: function(msg) { this.logs.push({ level: 'debug', msg }); },
};
};
const mockConfig: KnowledgeConfig['extraction']['llm'] = {
enabled: true,
model: 'test-model',
endpoint: 'http://localhost:12345/api/test',
batchSize: 3,
cooldownMs: 100,
};
describe('LlmEnhancer', () => {
let logger: ReturnType<typeof createMockLogger>;
let enhancer: LlmEnhancer;
beforeEach(() => {
logger = createMockLogger();
enhancer = new LlmEnhancer(mockConfig, logger);
});
afterEach(() => {
enhancer.clearTimers();
mock.reset();
mock.restoreAll();
});
const mockHttpRequest = (response: string): void => {
// Mock the private makeHttpRequest method on the instance prototype
mock.method(
enhancer as unknown as Record<string, unknown>,
'makeHttpRequest',
async () => response
);
};
it('should add items to the batch and respect batchSize', () => {
const llmPayload = { entities: [], facts: [] };
const llmResponse = { response: JSON.stringify(llmPayload) };
mockHttpRequest(JSON.stringify(llmResponse));
enhancer.addToBatch({ id: 'msg1', text: 'Hello' });
enhancer.addToBatch({ id: 'msg2', text: 'World' });
assert.strictEqual(logger.logs.filter(l => l.msg.includes('Sending immediately')).length, 0);
enhancer.addToBatch({ id: 'msg3', text: 'Test' });
assert.strictEqual(logger.logs.filter(l => l.msg.includes('Sending immediately')).length, 1);
});
it('should correctly parse a valid LLM response', async () => {
const llmPayload = {
entities: [{ type: 'person', value: 'Claude', importance: 0.9 }],
facts: [{ subject: 'Claude', predicate: 'is-a', object: 'Person' }],
};
const llmResponse = { response: JSON.stringify(llmPayload) };
mockHttpRequest(JSON.stringify(llmResponse));
enhancer.addToBatch({ id: 'm1', text: 'The person is Claude.' });
const result = await enhancer.sendBatch();
assert.ok(result);
assert.strictEqual(result.entities.length, 1);
assert.strictEqual(result.entities[0].value, 'Claude');
assert.strictEqual(result.facts.length, 1);
assert.strictEqual(result.facts[0].subject, 'Claude');
});
it('should return null when the batch is empty', async () => {
const result = await enhancer.sendBatch();
assert.strictEqual(result, null);
});
it('should handle HTTP errors gracefully', async () => {
mock.method(
enhancer as unknown as Record<string, unknown>,
'makeHttpRequest',
async () => { throw new Error('HTTP request failed with status 500'); }
);
enhancer.addToBatch({ id: 'm1', text: 'Test' });
const result = await enhancer.sendBatch();
assert.strictEqual(result, null);
assert.ok(logger.logs.some(l => l.level === 'error'));
});
it('should handle invalid JSON from LLM', async () => {
mockHttpRequest('not json');
enhancer.addToBatch({ id: 'm1', text: 'Test' });
const result = await enhancer.sendBatch();
assert.strictEqual(result, null);
assert.ok(logger.logs.some(l => l.level === 'error'));
});
it('should clear the batch after sending', async () => {
const llmPayload = { entities: [], facts: [] };
mockHttpRequest(JSON.stringify({ response: JSON.stringify(llmPayload) }));
enhancer.addToBatch({ id: 'm1', text: 'Test' });
await enhancer.sendBatch();
// Second send should return null (empty batch)
const result = await enhancer.sendBatch();
assert.strictEqual(result, null);
});
it('should handle LLM response with missing entities/facts gracefully', async () => {
mockHttpRequest(JSON.stringify({ response: '{}' }));
enhancer.addToBatch({ id: 'm1', text: 'Test' });
const result = await enhancer.sendBatch();
assert.ok(result);
assert.strictEqual(result.entities.length, 0);
assert.strictEqual(result.facts.length, 0);
});
});

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// test/maintenance.test.ts
import { describe, it, beforeEach, afterEach } from 'node:test';
import * as assert from 'node:assert';
import { Maintenance } from '../src/maintenance.js';
import { Embeddings } from '../src/embeddings.js';
import type { KnowledgeConfig, Logger, Fact } from '../src/types.js';
import * as timers from 'node:timers/promises';
class MockFactStore {
decayRate = 0;
decayedCount = 0;
unembeddedFacts: Fact[] = [];
markedAsEmbeddedIds: string[] = [];
decayFacts(rate: number) {
this.decayRate = rate;
this.decayedCount++;
return { decayedCount: 1 };
}
getUnembeddedFacts() { return this.unembeddedFacts; }
markFactsAsEmbedded(ids: string[]) {
this.markedAsEmbeddedIds.push(...ids);
// Clear unembedded facts after marking (mimics real behavior)
this.unembeddedFacts = this.unembeddedFacts.filter(f => !ids.includes(f.id));
}
}
class MockEmbeddings {
isEnabledState = true;
syncedFacts: Fact[] = [];
isEnabled() { return this.isEnabledState; }
sync(facts: Fact[]) {
this.syncedFacts.push(...facts);
return Promise.resolve(facts.length);
}
}
const createMockLogger = (): Logger => ({
info: () => {}, warn: () => {}, error: () => {}, debug: () => {},
});
const mockConfig: KnowledgeConfig = {
enabled: true,
workspace: '/tmp',
decay: { enabled: true, intervalHours: 0.0001, rate: 0.1 },
embeddings: {
enabled: true,
syncIntervalMinutes: 0.0001,
endpoint: 'http://test.com',
collectionName: 'test',
},
storage: { maxEntities: 100, maxFacts: 100, writeDebounceMs: 0 },
extraction: {
regex: { enabled: true },
llm: { enabled: false, model: '', endpoint: '', batchSize: 1, cooldownMs: 0 },
},
};
describe('Maintenance', () => {
let logger: Logger;
let mockFactStore: MockFactStore;
let mockEmbeddings: MockEmbeddings;
let maintenance: Maintenance;
beforeEach(() => {
logger = createMockLogger();
mockFactStore = new MockFactStore();
mockEmbeddings = new MockEmbeddings();
// @ts-ignore - Using mock class
maintenance = new Maintenance(mockConfig, logger, mockFactStore, mockEmbeddings);
});
afterEach(() => {
maintenance.stop();
});
it('should schedule and run decay task', async () => {
maintenance.start();
await timers.setTimeout(mockConfig.decay.intervalHours * 60 * 60 * 1000 + 10);
assert.strictEqual(mockFactStore.decayedCount > 0, true);
assert.strictEqual(mockFactStore.decayRate, mockConfig.decay.rate);
});
it('should schedule and run embeddings sync task', async () => {
const testFact: Fact = {
id: 'fact1', subject: 's', predicate: 'p', object: 'o',
relevance: 1, createdAt: 't', lastAccessed: 't', source: 'ingested',
};
mockFactStore.unembeddedFacts = [testFact];
maintenance.start();
await timers.setTimeout(mockConfig.embeddings.syncIntervalMinutes * 60 * 1000 + 10);
assert.strictEqual(mockEmbeddings.syncedFacts.length > 0, true);
assert.deepStrictEqual(mockEmbeddings.syncedFacts[0], testFact);
assert.deepStrictEqual(mockFactStore.markedAsEmbeddedIds, [testFact.id]);
});
it('should not schedule embeddings if disabled', async () => {
mockEmbeddings.isEnabledState = false;
maintenance.start();
await timers.setTimeout(5);
assert.strictEqual(mockEmbeddings.syncedFacts.length, 0);
});
it('should stop all timers cleanly', () => {
maintenance.start();
maintenance.stop();
// No error means timers were cleared successfully
assert.ok(true);
});
it('should run decay manually', () => {
maintenance.runDecay();
assert.strictEqual(mockFactStore.decayedCount, 1);
assert.strictEqual(mockFactStore.decayRate, mockConfig.decay.rate);
});
});

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// test/patterns.test.ts
import { describe, it } from 'node:test';
import * as assert from 'node:assert';
import { REGEX_PATTERNS } from '../src/patterns.js';
type TestCase = [string, string | null | string[]];
const runTestCases = (regex: RegExp, testCases: TestCase[]) => {
for (const [input, expected] of testCases) {
// Reset regex state for each test case
regex.lastIndex = 0;
const matches = input.match(regex);
if (expected === null) {
assert.strictEqual(matches, null, `Expected no match for: "${input}"`);
} else if (Array.isArray(expected)) {
assert.deepStrictEqual(matches, expected, `Mismatch for: "${input}"`);
} else {
assert.deepStrictEqual(matches, [expected], `Mismatch for: "${input}"`);
}
}
};
describe('REGEX_PATTERNS', () => {
it('should match valid email addresses', () => {
const testCases: TestCase[] = [
['contact support at support@example.com', 'support@example.com'],
['my email is john.doe123@sub.domain.co.uk.', 'john.doe123@sub.domain.co.uk'],
['invalid-email@', null],
['user@localhost', null],
['test@.com', null],
['multiple emails: a@b.com and c@d.org', ['a@b.com', 'c@d.org']],
];
runTestCases(REGEX_PATTERNS.email, testCases);
});
it('should match valid URLs', () => {
const testCases: TestCase[] = [
['visit https://www.example.com for more info', 'https://www.example.com'],
['check http://sub.domain.org/path?query=1', 'http://sub.domain.org/path?query=1'],
['ftp://invalid.com', null],
['www.example.com', null],
['a link: https://a.co and another http://b.com/end.', ['https://a.co', 'http://b.com/end']],
];
runTestCases(REGEX_PATTERNS.url, testCases);
});
it('should match ISO 8601 dates', () => {
const testCases: TestCase[] = [
['The date is 2026-02-17.', '2026-02-17'],
['Timestamp: 2026-02-17T15:30:00Z', '2026-02-17T15:30:00Z'],
['With milliseconds: 2026-02-17T15:30:00.123Z', '2026-02-17T15:30:00.123Z'],
['Not a date: 2026-02-17T', null],
['Invalid format 2026/02/17', null],
];
runTestCases(REGEX_PATTERNS.iso_date, testCases);
});
it('should match common date formats (US & EU)', () => {
const testCases: TestCase[] = [
['US date: 02/17/2026.', '02/17/2026'],
['EU date: 17.02.2026,', '17.02.2026'],
['Short year: 1.1.99', '1.1.99'],
['Two dates: 12/25/2024 and 24.12.2024', ['12/25/2024', '24.12.2024']],
];
runTestCases(REGEX_PATTERNS.common_date, testCases);
});
it('should match German date formats', () => {
const testCases: TestCase[] = [
['Datum: 17. Februar 2026', '17. Februar 2026'],
['Am 1. Januar 2025 war es kalt.', '1. Januar 2025'],
['No match: 17 Februar 2026', null],
];
runTestCases(REGEX_PATTERNS.german_date, testCases);
});
it('should match English date formats', () => {
const testCases: TestCase[] = [
['Date: February 17, 2026', 'February 17, 2026'],
['On March 1st, 2025, we launched.', 'March 1st, 2025'],
['Also August 2nd, 2024 and May 3rd, 2023.', ['August 2nd, 2024', 'May 3rd, 2023']],
['No match: February 17 2026', null],
];
runTestCases(REGEX_PATTERNS.english_date, testCases);
});
it('should match proper nouns (names, places)', () => {
const testCases: TestCase[] = [
['Hello, my name is Claude Keller.', ['Claude Keller']],
['This is Jean-Luc Picard of the USS Enterprise.', ['Jean-Luc Picard', 'USS Enterprise']],
['Talk to O\'Malley about it.', ['O\'Malley']],
['OpenClaw is a project.', ['OpenClaw']],
['Not a name: lower case', null],
['Multiple: Forge and Atlas are agents.', ['Forge', 'Atlas']],
];
runTestCases(REGEX_PATTERNS.proper_noun, testCases);
});
it('should match product-like names', () => {
const testCases: TestCase[] = [
['I have an iPhone 15.', 'iPhone 15'],
['We are using Windows 11.', 'Windows 11'],
['The latest model is GPT-4.', 'GPT-4'],
['Also look at ProductX.', 'ProductX'],
['The Roman Empire used IV.', 'Roman Empire used IV'], // Imperfect but acceptable
];
runTestCases(REGEX_PATTERNS.product_name, testCases);
});
it('should match organization names with suffixes', () => {
const testCases: TestCase[] = [
['He works at Vainplex GmbH.', 'Vainplex GmbH'],
['The owner of Stark Industries, LLC is Tony Stark.', 'Stark Industries, LLC'],
['Globex Corp. is another example.', 'Globex Corp.'],
['This also catches Acme Inc. and Cyberdyne Systems Ltd.', ['Acme Inc.', 'Cyberdyne Systems Ltd.']],
['No match for Vainplex alone', null],
];
runTestCases(REGEX_PATTERNS.organization_suffix, testCases);
});
});

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// test/storage.test.ts
import { describe, it, before, after, beforeEach } from 'node:test';
import * as assert from 'node:assert';
import * as fs from 'node:fs/promises';
import * as path from 'node:path';
import { AtomicStorage } from '../src/storage.js';
import type { Logger } from '../src/types.js';
const createMockLogger = (): Logger & { logs: { level: string; msg: string }[] } => {
const logs: { level: string; msg: string }[] = [];
return { logs, info: (msg) => logs.push({ level: 'info', msg }), warn: (msg) => logs.push({ level: 'warn', msg }), error: (msg) => logs.push({ level: 'error', msg }), debug: (msg) => logs.push({ level: 'debug', msg }) };
};
describe('AtomicStorage', () => {
const testDir = path.join('/tmp', `atomic-storage-test-${Date.now()}`);
let logger: ReturnType<typeof createMockLogger>;
let storage: AtomicStorage;
before(async () => await fs.mkdir(testDir, { recursive: true }));
after(async () => await fs.rm(testDir, { recursive: true, force: true }));
beforeEach(() => { logger = createMockLogger(); storage = new AtomicStorage(testDir, logger); });
it('should initialize and create the storage directory', async () => {
const newDir = path.join(testDir, 'new-dir');
const newStorage = new AtomicStorage(newDir, logger);
await newStorage.init();
const stats = await fs.stat(newDir);
assert.ok(stats.isDirectory(), 'Directory should be created');
});
describe('writeJson', () => {
it('should write a JSON object to a file', async () => {
const fileName = 'test.json';
const data = { key: 'value', number: 123 };
await storage.writeJson(fileName, data);
const content = await fs.readFile(path.join(testDir, fileName), 'utf-8');
assert.deepStrictEqual(JSON.parse(content), data);
});
});
describe('readJson', () => {
it('should read and parse a valid JSON file', async () => {
const fileName = 'read.json';
const data = { a: 1, b: [2, 3] };
await fs.writeFile(path.join(testDir, fileName), JSON.stringify(data));
const result = await storage.readJson<typeof data>(fileName);
assert.deepStrictEqual(result, data);
});
it('should return null if the file does not exist', async () => {
const result = await storage.readJson('nonexistent.json');
assert.strictEqual(result, null);
});
});
describe('debounce', () => {
it('should only call the async function once after the delay', async () => {
let callCount = 0;
const asyncFn = async () => { callCount++; return callCount; };
const debouncedFn = AtomicStorage.debounce(asyncFn, 50);
const p1 = debouncedFn();
const p2 = debouncedFn();
const p3 = debouncedFn();
const results = await Promise.all([p1, p2, p3]);
assert.strictEqual(callCount, 1);
assert.deepStrictEqual(results, [1, 1, 1]);
});
it('should pass the arguments of the last call to the async function', async () => {
let finalArgs: any[] = [];
const asyncFn = async (...args: any[]) => { finalArgs = args; return finalArgs; };
const debouncedFn = AtomicStorage.debounce(asyncFn, 50);
debouncedFn(1);
debouncedFn(2, 3);
const finalPromise = debouncedFn(4, 5, 6);
const result = await finalPromise;
assert.deepStrictEqual(finalArgs, [4, 5, 6]);
assert.deepStrictEqual(result, [4, 5, 6]);
});
});
});

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{
"compilerOptions": {
"target": "ES2022",
"module": "ESNext",
"lib": ["ES2022"],
"moduleResolution": "node",
"esModuleInterop": true,
"strict": true,
"noImplicitAny": true,
"strictNullChecks": true,
"strictFunctionTypes": true,
"strictBindCallApply": true,
"strictPropertyInitialization": true,
"noImplicitThis": true,
"alwaysStrict": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": true,
"skipLibCheck": true,
"outDir": "./dist",
"declaration": true
},
"include": ["src/**/*.ts", "index.ts"],
"exclude": ["node_modules", "dist", "test"]
}