@claude-flow/embeddings
Version:
V3 Embedding Service - OpenAI, Transformers.js, Agentic-Flow (ONNX), Mock providers with hyperbolic embeddings, normalization, and chunking
255 lines • 8.4 kB
JavaScript
/**
* Neural Substrate Integration
*
* Integrates agentic-flow's neural embedding features:
* - Semantic drift detection
* - Memory physics (hippocampal dynamics)
* - Embedding state machine
* - Swarm coordination
* - Coherence monitoring
*
* These features treat embeddings as a synthetic nervous system.
*/
/**
* Lazy-loaded Neural Substrate wrapper
*
* Wraps agentic-flow's NeuralSubstrate with graceful fallback
*/
export class NeuralEmbeddingService {
config;
substrate = null;
initialized = false;
available = false;
constructor(config = {}) {
this.config = config;
}
/**
* Initialize neural substrate
*/
async init() {
if (this.initialized)
return this.available;
try {
const { getNeuralSubstrate } = await import('agentic-flow/embeddings');
this.substrate = await getNeuralSubstrate(this.config);
await this.substrate.init();
this.available = true;
}
catch (error) {
console.warn('[neural] Neural substrate not available:', error instanceof Error ? error.message : error);
this.available = false;
}
this.initialized = true;
return this.available;
}
/**
* Check if neural features are available
*/
isAvailable() {
return this.available;
}
/**
* Detect semantic drift from baseline
*/
async detectDrift(input) {
if (!this.available || !this.substrate)
return null;
return this.substrate.drift.detect(input);
}
/**
* Set baseline for drift detection
*/
async setDriftBaseline(context) {
if (!this.available || !this.substrate)
return;
await this.substrate.drift.setBaseline(context);
}
/**
* Store memory with interference detection
*/
async storeMemory(id, content) {
if (!this.available || !this.substrate)
return null;
return this.substrate.memory.store(id, content);
}
/**
* Recall memories by similarity
*/
async recallMemories(query, topK = 5) {
if (!this.available || !this.substrate)
return null;
return this.substrate.memory.recall(query, topK);
}
/**
* Consolidate memories (merge similar, forget weak)
*/
consolidateMemories() {
if (!this.available || !this.substrate)
return null;
return this.substrate.memory.consolidate();
}
/**
* Register agent for state tracking
*/
async registerAgent(id, role) {
if (!this.available || !this.substrate)
return null;
return this.substrate.states.registerAgent(id, role);
}
/**
* Update agent state based on observation
*/
async updateAgentState(agentId, observation) {
if (!this.available || !this.substrate)
return null;
return this.substrate.states.updateState(agentId, observation);
}
/**
* Get agent state
*/
getAgentState(agentId) {
if (!this.available || !this.substrate)
return null;
return this.substrate.states.getAgent(agentId);
}
/**
* Coordinate swarm for task
*/
async coordinateSwarm(task) {
if (!this.available || !this.substrate)
return null;
return this.substrate.swarm.coordinate(task);
}
/**
* Add agent to swarm
*/
async addSwarmAgent(id, role) {
if (!this.available || !this.substrate)
return null;
return this.substrate.swarm.addAgent(id, role);
}
/**
* Calibrate coherence monitor
*/
async calibrateCoherence(goodOutputs) {
if (!this.available || !this.substrate)
return null;
return this.substrate.coherence.calibrate(goodOutputs);
}
/**
* Check output coherence
*/
async checkCoherence(output) {
if (!this.available || !this.substrate)
return null;
return this.substrate.coherence.check(output);
}
/**
* Process input through full neural substrate
*/
async process(input, context) {
if (!this.available || !this.substrate)
return null;
return this.substrate.process(input, context);
}
/**
* Get substrate health
*/
health() {
if (!this.available || !this.substrate)
return null;
return this.substrate.health();
}
/**
* Full consolidation pass
*/
consolidate() {
if (!this.available || !this.substrate)
return null;
return this.substrate.consolidate();
}
}
/**
* Create neural embedding service
*/
export function createNeuralService(config = {}) {
return new NeuralEmbeddingService(config);
}
/**
* Check if neural features are available
*/
export async function isNeuralAvailable() {
try {
await import('agentic-flow/embeddings');
return true;
}
catch {
return false;
}
}
/**
* List available ONNX embedding models
*/
export async function listEmbeddingModels() {
try {
const { listAvailableModels } = await import('agentic-flow/embeddings');
return listAvailableModels();
}
catch {
// Return default models if agentic-flow not available
return [
{ id: 'all-MiniLM-L6-v2', dimension: 384, size: '23MB', quantized: false, downloaded: false },
{ id: 'all-mpnet-base-v2', dimension: 768, size: '110MB', quantized: false, downloaded: false },
];
}
}
/**
* Download embedding model.
*
* #1700 item 2: previously this propagated `Cannot find package 'agentic-flow'`
* when the optional peer wasn't installed, breaking `embeddings init` even
* though the rest of the embedding pipeline (Xenova/transformers ONNX) does
* not need agentic-flow. Now we try the agentic-flow path first and fall
* back to a no-op success when it isn't installed — the model still loads
* lazily on first `embeddings_generate` call via @xenova/transformers.
*/
export async function downloadEmbeddingModel(modelId, targetDir, onProgress) {
try {
const mod = await import('agentic-flow/embeddings').catch((err) => {
throw err;
});
const downloadFn = mod.downloadModel;
if (typeof downloadFn !== 'function') {
// agentic-flow is installed but has no downloadModel export (the
// 2.x line shipped clearEmbeddingCache/computeEmbedding* but not
// downloadModel; the function lives on a different path or version).
// Treat as lazy-fetch path — @xenova/transformers will download on
// first generate(). #1700 item 2 follow-up.
console.warn('[embeddings] agentic-flow installed but does not expose downloadModel — ' +
'falling back to lazy fetch via @xenova/transformers on first generate.');
return targetDir ?? '.models';
}
return await downloadFn(modelId, targetDir ?? '.models', onProgress);
}
catch (err) {
const msg = err instanceof Error ? err.message : String(err);
// Distinguish "package missing" / "subpath unsupported" from real
// download errors so callers can surface the right hint to users.
// #1468: Windows + Node strict-ESM raises
// `Package subpath './embeddings' is not defined by "exports"`
// when the bundled agentic-flow's package.json doesn't declare the
// ./embeddings entry. WSL/Linux is more permissive on the same code,
// so the bug only surfaces on Windows. Treat both shapes as
// "agentic-flow neural extras unavailable, fall back to lazy fetch".
if (/Cannot find package 'agentic-flow'|Cannot find module/.test(msg)
|| /Package subpath ['"]\.\/embeddings['"] is not defined/.test(msg)
|| /ERR_PACKAGE_PATH_NOT_EXPORTED/.test(msg)) {
console.warn('[embeddings] agentic-flow neural extras unavailable — skipping eager model download. ' +
'Models will be fetched lazily by @xenova/transformers on first generate. ' +
`Reason: ${msg}`);
return targetDir ?? '.models';
}
throw err;
}
}
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