@ruvector/edge

![WASM]()
![Tests]()

Free Self-Learning AI Swarms at the Edge

Build and deploy self-optimizing AI agent swarms that run entirely in web browsers, mobile devices, and edge servers - without paying for cloud infrastructure.

Imagine having dozens of AI agents working together - analyzing data, routing tasks, making decisions, and getting smarter with every interaction - all running directly in your users' browsers. No API costs. No server bills. No data leaving your network. That's what @ruvector/edge makes possible.

This library gives you everything you need to build distributed AI systems: cryptographic identity for each agent, encrypted communication between them, lightning-fast vector search for finding the right agent for each task, consensus protocols so your agents can coordinate without a central server, and self-learning neural networks that continuously optimize agent routing based on real-world outcomes. It's all compiled to a tiny 364KB WebAssembly binary that runs anywhere JavaScript runs.

The key insight: Instead of paying cloud providers to run your AI infrastructure, you use the computing power that's already there - your users' devices. Each browser becomes a node in your swarm. The more users you have, the more powerful your system becomes - and with built-in self-learning capabilities (LoRA fine-tuning, EWC++ continual learning, ReasoningBank experience replay), your swarm gets smarter over time while still costing you nothing.

``
┌─────────────────────────────────────────────────────────────────────┐
│ ZERO COST SWARMS │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │ Browser │◄────►│ Browser │◄────►│ Edge │◄────►│ Mobile │ │
│ │ Agent A │ │ Agent B │ │ Agent C │ │ Agent D │ │
│ └─────────┘ └─────────┘ └─────────┘ └─────────┘ │
│ │ │ │ │ │
│ └────────────────┴────────────────┴────────────────┘ │
│ P2P Mesh │
│ │
│ Compute: FREE (runs on user devices) │
│ Network: FREE (public relays + P2P) │
│ Storage: FREE (distributed across nodes) │
│ Scale: UNLIMITED (each user = new node) │
│ │
└─────────────────────────────────────────────────────────────────────┘
`

$3

| Capability | Technology | Performance |
|------------|------------|-------------|
| Agent Identity | Ed25519 signatures | 50,000 ops/sec |
| Encryption | AES-256-GCM | 1 GB/sec |
| Vector Search | HNSW index | 150x faster than brute force |
| Task Routing | Semantic LSH | Sub-millisecond |
| Trusted Consensus | Raft protocol | For stable cohorts (teams, rooms) |
| Open Swarm | Gossip + CRDT | High-churn, Byzantine-tolerant |
| Post-Quantum | Hybrid signatures | Future-proof |
| Neural Networks | Spiking + STDP | Bio-inspired learning |
| Compression | Adaptive 4-32x | Network-aware |
| Web Workers | Worker pool | Parallel ops, non-blocking UI |

$3

| Component | Cloud Solution | @ruvector/edge |
|-----------|---------------|----------------|
| Compute | $200-500/month | $0 (user's CPU) |
| Vector DB | $100-300/month | $0 (in-browser HNSW) |
| Encryption | $50-100/month | $0 (built-in AES) |
| Bandwidth | $0.09/GB | $0 (P2P direct) |
| Consensus | $100-200/month | $0 (built-in Raft) |
| Total | $450-1100/month | $0/month |

---

Full Platform Capabilities

RuVector provides a complete edge AI platform. This package (@ruvector/edge) is the lightweight core. For the full toolkit, install @ruvector/edge-full.

`
┌─────────────────────────────────────────────────────────────────────────────┐
│ RUVECTOR EDGE PLATFORM │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ @ruvector/edge (364KB) @ruvector/edge-full (+8MB) │
│ ───────────────────── ─────────────────────────── │
│ ✓ Ed25519 Identity Everything in edge, PLUS: │
│ ✓ AES-256-GCM Encryption │
│ ✓ HNSW Vector Search ✓ Graph DB (288KB) │
│ ✓ Semantic Task Routing Neo4j-style API, Cypher queries │
│ ✓ Raft (trusted cohorts) Relationship modeling, traversals │
│ ✓ Gossip + CRDT (open swarms) │
│ ✓ Post-Quantum Crypto ✓ RVLite Vector DB (260KB) │
│ ✓ Spiking Neural Networks SQL + SPARQL + Cypher queries │
│ ✓ Adaptive Compression IndexedDB persistence │
│ ✓ Web Worker Pool │
│ │
│ Best for: ✓ SONA Neural Router (238KB) │
│ • Lightweight P2P apps Self-learning with LoRA │
│ • Secure messaging EWC++ continual learning │
│ • Trusted team swarms ReasoningBank experience replay │
│ • Mobile/embedded │
│ │
│ ✓ DAG Workflows (132KB) │
│ Task orchestration │
│ Dependency resolution │
│ Topological execution │
│ │
│ ✓ ONNX Embeddings (7.1MB) │
│ 6 HuggingFace models │
│ 3.8x parallel speedup │
│ MiniLM, BGE, E5, GTE │
│ │
│ Best for: │
│ • Full RAG pipelines │
│ • Knowledge graphs │
│ • Self-learning agents │
│ • Complex workflows │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
`

$3

`bash


Lightweight core (364KB) - P2P, crypto, vectors, consensus

npm install @ruvector/edge

Full platform (8.4MB) - adds graph DB, SQL, neural routing, ONNX

npm install @ruvector/edge-full
`

$3

`javascript
// Start with edge core
import init, { WasmIdentity, WasmHnswIndex } from '@ruvector/edge';

// Add full capabilities when needed
import { graph, rvlite, sona, dag } from '@ruvector/edge-full';
import onnxInit from '@ruvector/edge-full/onnx';
`

---

$3

RuVector provides two coordination strategies for different deployment scenarios:

| Mode | Protocol | When to Use |
|------|----------|-------------|
| Trusted Cohort | Raft | Private teams, enterprise LANs, known membership, low churn |
| Open Swarm | Gossip + CRDT | Public networks, anonymous browsers, high churn, adversarial environments |

`javascript
// Trusted cohort (Raft) - stable team of 3-7 nodes
const raftNode = new WasmRaftNode('node-1', ['node-1', 'node-2', 'node-3']);
raftNode.start_election(); // Leader election for consistent state

// Open swarm (Gossip + CRDT) - dynamic browser mesh
const gossipNode = new WasmGossipNode(identity);
gossipNode.join_swarm(relayUrl); // Eventually consistent, Byzantine-tolerant
`

Why two modes? Raft assumes known membership and trusted nodes - perfect for your dev team or enterprise deployment. But a public browser swarm has nodes joining/leaving constantly and can't trust everyone. Gossip protocols with CRDTs handle this gracefully: no leader election, no membership tracking, eventual consistency that converges even with malicious actors.

---

$3

Heavy operations (vector search, encryption, neural network inference) run in Web Workers to avoid blocking the main thread. The package includes a ready-to-use worker pool:

`javascript
import { WorkerPool } from '@ruvector/edge/worker-pool';

// Create worker pool (auto-detects CPU cores)
const pool = new WorkerPool(
new URL('@ruvector/edge/worker', import.meta.url),
new URL('@ruvector/edge/ruvector_edge_bg.wasm', import.meta.url),
{
poolSize: navigator.hardwareConcurrency,
dimensions: 384,
useHnsw: true
}
);

await pool.init();

// Operations run in parallel across workers
await pool.insert(embedding, 'doc-1', { title: 'Hello' });
await pool.insertBatch([
{ vector: emb1, id: 'doc-2' },
{ vector: emb2, id: 'doc-3' },
{ vector: emb3, id: 'doc-4' }
]);

// Search distributed across workers
const results = await pool.search(queryEmbedding, 10);

// Batch search (each query on different worker)
const batchResults = await pool.searchBatch([query1, query2, query3], 10);

// Pool statistics
console.log(pool.getStats());
// { poolSize: 8, busyWorkers: 2, idleWorkers: 6, pendingRequests: 0 }

// Clean up
pool.terminate();
`

Worker Pool Features:
- Round-robin task distribution with load balancing
- Automatic batch splitting across workers
- Promise-based API with 30s timeout
- Zero-copy transfers via transferable objects
- Works in browsers, Deno, and Cloudflare Workers

---

$3

`bash
npm install @ruvector/edge
`

`javascript
import init, { WasmIdentity, WasmHnswIndex, WasmSemanticMatcher } from '@ruvector/edge';

await init();

// Create agent identity
const identity = WasmIdentity.generate();
console.log(Agent: ${identity.agent_id()});

// Vector search (150x faster)
const index = new WasmHnswIndex(128, 16, 200);
index.insert("agent-1", new Float32Array(128));

// Semantic task routing
const matcher = new WasmSemanticMatcher();
matcher.register_agent("coder", "rust typescript javascript");
const best = matcher.find_best_agent("write a function");
`

---

Table of Contents

1. Why Edge-First?
2. Features
3. Tutorial: Build Your First Swarm
4. P2P Transport Options
5. Free Infrastructure
6. Architecture
7. API Reference
8. Performance
9. Security

---

Why Edge-First?

| Traditional Cloud Swarms | RuVector Edge Swarms |
|--------------------------|---------------------|
| Pay per API call | Free forever |
| Data leaves your network | Data stays local |
| Central point of failure | Fully distributed |
| Vendor lock-in | Open source |
| High latency (round-trip to cloud) | Sub-millisecond (peer-to-peer) |
| Limited by server capacity | Scales with your devices |

$3

`
Cloud AI Swarm (10 agents, 1M operations/month):
├── API calls: $500-2000/month
├── Compute: $200-500/month
├── Bandwidth: $50-100/month
└── Total: $750-2600/month

RuVector Edge Swarm:
├── Infrastructure: $0
├── API calls: $0
├── Bandwidth: $0 (P2P)
└── Total: $0/month forever
`

$3

The code runs on devices you already own - there's no server to pay for:

`
Traditional Architecture:
┌──────────┐ ┌─────────────────┐ ┌──────────┐
│ Agent A │────►│ Cloud Server │◄────│ Agent B │
└──────────┘ │ ($$$$/month) │ └──────────┘
└─────────────────┘

Edge Architecture:
┌──────────┐◄───────────────────────────►┌──────────┐
│ Agent A │ Direct P2P │ Agent B │
│ (Browser)│ Connection │ (Browser)│
└──────────┘ └──────────┘
No server = No cost
`

---

Features

| Feature | Description |
|---------|-------------|
| Ed25519 Identity | Cryptographic agent identity with signing |
| AES-256-GCM | Authenticated encryption for all messages |
| Post-Quantum Hybrid | Future-proof against quantum attacks |
| HNSW Vector Index | 150x faster similarity search |
| Semantic Matching | Intelligent task-to-agent routing |
| Raft Consensus | Distributed leader election |
| Spiking Networks | Bio-inspired temporal learning |
| Adaptive Compression | Network-aware bandwidth optimization |

---

Quick Start

$3

`bash
npm install @ruvector/edge
`

$3

`javascript
import init, {
WasmIdentity,
WasmCrypto,
WasmHnswIndex,
WasmSemanticMatcher
} from '@ruvector/edge';

// Initialize WASM (required once)
await init();

// Create an agent
const agent = WasmIdentity.generate();
console.log(Agent: ${agent.agent_id()});

// Encrypt a message
const crypto = new WasmCrypto();
const key = crypto.generate_key();
const encrypted = crypto.encrypt(key, new TextEncoder().encode("Hello swarm!"));

// Search vectors
const index = new WasmHnswIndex(128, 16, 200);
index.insert("doc-1", new Float32Array(128).fill(0.5));
const results = index.search(new Float32Array(128).fill(0.5), 5);

// Route tasks
const matcher = new WasmSemanticMatcher();
matcher.register_agent("coder", "rust typescript javascript");
const best = matcher.find_best_agent("write a function");
`

---

Tutorial: Build Your First Swarm

This tutorial walks you through building a complete AI agent swarm that runs entirely in browsers with no backend.

$3

`bash
mkdir my-swarm && cd my-swarm
npm init -y
npm install @ruvector/edge
`

Create index.html:

`html










`

---

$3

Every agent needs a unique cryptographic identity. This enables signing messages and verifying authenticity.

Create swarm.js:

`javascript
import init, { WasmIdentity } from '@ruvector/edge';

async function createAgent(name) {
await init();

// Generate Ed25519 keypair
const identity = WasmIdentity.generate();

console.log(Agent: ${name});
console.log( ID: ${identity.agent_id()});
console.log( Public Key: ${identity.public_key_hex().slice(0, 16)}...);

return identity;
}

// Create our agent
const myAgent = await createAgent("Worker-001");

// Sign a message to prove identity
const message = new TextEncoder().encode("I am Worker-001");
const signature = myAgent.sign(message);
console.log( Signature: ${signature.slice(0, 8).join(',')}...);

// Verify the signature
const isValid = myAgent.verify(message, signature);
console.log( Valid: ${isValid}); // true
`

What's happening:
- WasmIdentity.generate() creates an Ed25519 keypair
- agent_id() returns a unique identifier derived from the public key
- sign() creates a cryptographic signature proving the message came from this agent
- verify() checks if a signature is valid

---

$3

Agents need to encrypt messages so only intended recipients can read them.

`javascript
import init, { WasmIdentity, WasmCrypto } from '@ruvector/edge';

await init();

const crypto = new WasmCrypto();

// Agent A wants to send a secret message to Agent B
const agentA = WasmIdentity.generate();
const agentB = WasmIdentity.generate();

// Generate a shared secret key (in real app, use key exchange)
const sharedKey = crypto.generate_key();

// Agent A encrypts
const plaintext = new TextEncoder().encode(JSON.stringify({
task: "analyze_data",
payload: { dataset: "sales_2024.csv" }
}));

const ciphertext = crypto.encrypt(sharedKey, plaintext);
console.log(Encrypted: ${ciphertext.length} bytes);

// Agent B decrypts
const decrypted = crypto.decrypt(sharedKey, ciphertext);
const message = JSON.parse(new TextDecoder().decode(decrypted));
console.log(Decrypted: ${message.task}); // "analyze_data"
`

Security features:
- AES-256-GCM authenticated encryption
- Random nonce per message (replay protection)
- Ciphertext integrity verification

---

$3

Agents need to find each other based on capabilities. HNSW enables fast similarity search.

`javascript
import init, { WasmHnswIndex } from '@ruvector/edge';

await init();

// Create index: 128 dimensions, M=16 connections, ef=200 search quality
const index = new WasmHnswIndex(128, 16, 200);

// Register agents with their capability embeddings
// (In production, use real embeddings from a model)
function mockEmbedding(weights) {
const vec = new Float32Array(128);
weights.forEach((w, i) => vec[i] = w);
return vec;
}

// Register specialized agents
index.insert("rust-expert", mockEmbedding([0.9, 0.1, 0.0, 0.0]));
index.insert("python-expert", mockEmbedding([0.1, 0.9, 0.0, 0.0]));
index.insert("ml-expert", mockEmbedding([0.0, 0.5, 0.9, 0.0]));
index.insert("devops-expert", mockEmbedding([0.0, 0.0, 0.2, 0.9]));

console.log(Index size: ${index.len()} agents);

// Find best agent for a Rust task
const rustTask = mockEmbedding([0.85, 0.1, 0.05, 0.0]);
const results = index.search(rustTask, 3);

console.log("Best agents for Rust task:");
results.forEach(([id, distance]) => {
console.log( ${id}: distance=${distance.toFixed(3)});
});
// Output: rust-expert: distance=0.050
`

Why HNSW?
- O(log n) search instead of O(n)
- 150x faster than brute force at 10K+ vectors
- Memory-efficient graph structure

---

$3

Route tasks to the best agent using semantic matching.

`javascript
import init, { WasmSemanticMatcher } from '@ruvector/edge';

await init();

const matcher = new WasmSemanticMatcher();

// Register agents with capability descriptions
matcher.register_agent("code-agent",
"rust typescript javascript python programming coding functions classes");
matcher.register_agent("data-agent",
"python pandas numpy data analysis statistics csv excel");
matcher.register_agent("devops-agent",
"docker kubernetes terraform aws deploy infrastructure cicd");
matcher.register_agent("writing-agent",
"documentation markdown readme technical writing blog");

console.log(Registered ${matcher.agent_count()} agents);

// Route tasks to best agent
const tasks = [
"Write a Rust function to parse JSON",
"Analyze the sales data in this CSV",
"Deploy the app to Kubernetes",
"Update the API documentation"
];

tasks.forEach(task => {
const best = matcher.find_best_agent(task);
console.log("${task.slice(0, 30)}..." → ${best});
});

// Output:
// "Write a Rust function..." → code-agent
// "Analyze the sales data..." → data-agent
// "Deploy the app to Kube..." → devops-agent
// "Update the API documen..." → writing-agent
`

How it works:
- LSH (Locality-Sensitive Hashing) creates semantic fingerprints
- Tasks are matched to agents by fingerprint similarity
- Sub-millisecond routing even with many agents

---

$3

When multiple agents need to agree on a leader or shared state, use Raft consensus.

`javascript
import init, { WasmRaftNode } from '@ruvector/edge';

await init();

// Create a 3-node cluster
const members = ["node-1", "node-2", "node-3"];

const node1 = new WasmRaftNode("node-1", members);
const node2 = new WasmRaftNode("node-2", members);
const node3 = new WasmRaftNode("node-3", members);

console.log(Node 1 state: ${node1.state()}); // "follower"
console.log(Node 1 term: ${node1.current_term()}); // 0

// Node 1 times out and starts election
const voteRequest = node1.start_election();
console.log(Node 1 state: ${node1.state()}); // "candidate"
console.log(Node 1 term: ${node1.current_term()}); // 1

// Simulate: Node 2 and 3 grant votes
// (In real app, send voteRequest over network, receive responses)
const granted1 = node1.receive_vote(true);
const granted2 = node1.receive_vote(true);

console.log(Node 1 state: ${node1.state()}); // "leader"

// Leader can now coordinate the swarm!
console.log("Leader elected - swarm can coordinate");
`

Raft guarantees:
- Only one leader at a time
- Leader election in 1-2 round trips
- Tolerates f failures in 2f+1 nodes

---

P2P Transport Options

RuVector Edge provides the intelligence layer. You need a transport layer for agents to communicate. Here are your free options:

$3

`
┌─────────────────────────────────────────────────────────────┐
│ @ruvector/edge (WASM) │
│ Identity, Crypto, HNSW, Semantic Matching, Raft, etc. │
└─────────────────────────────────────────────────────────────┘
│
Transport Layer (choose one)
│
┌─────────────────────┼─────────────────────┐
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│ WebRTC │ │ GUN.js │ │ IPFS/ │
│ (P2P) │ │ (P2P) │ │ libp2p │
└─────────┘ └─────────┘ └─────────┘
`

---

$3

Best for: Direct browser-to-browser communication
Cost: Free (need minimal signaling server)

`javascript
import init, { WasmIdentity, WasmCrypto } from '@ruvector/edge';

await init();

const identity = WasmIdentity.generate();
const crypto = new WasmCrypto();

// Create peer connection
const pc = new RTCPeerConnection({
iceServers: [{ urls: 'stun:stun.l.google.com:19302' }] // Free STUN
});

// Create data channel for agent messages
const channel = pc.createDataChannel('swarm');

channel.onopen = () => {
console.log('P2P connection established!');

// Send encrypted message
const key = crypto.generate_key(); // Exchange via signaling
const message = { type: 'task', data: 'analyze this' };
const encrypted = crypto.encrypt(key,
new TextEncoder().encode(JSON.stringify(message))
);

channel.send(encrypted);
};

channel.onmessage = (event) => {
const decrypted = crypto.decrypt(key, new Uint8Array(event.data));
const message = JSON.parse(new TextDecoder().decode(decrypted));
console.log('Received:', message);
};

// Signaling (exchange offer/answer via any method)
const offer = await pc.createOffer();
await pc.setLocalDescription(offer);
// Send offer to peer via signaling server, WebSocket, or even QR code
`

Free signaling options:
- PeerJS Cloud (free tier)
- Firebase Realtime Database (free tier)
- Your own WebSocket on Fly.io/Railway free tier

---

$3

Best for: Real-time sync, offline-first, no server needed
Cost: Completely free (public relay network)

`javascript
import init, { WasmIdentity, WasmSemanticMatcher } from '@ruvector/edge';
import Gun from 'gun';

await init();

const identity = WasmIdentity.generate();
const matcher = new WasmSemanticMatcher();

// Connect to public GUN relays (free!)
const gun = Gun(['https://gun-manhattan.herokuapp.com/gun']);

// Create swarm namespace
const swarm = gun.get('my-ai-swarm');

// Register this agent
swarm.get('agents').get(identity.agent_id()).put({
id: identity.agent_id(),
capabilities: 'rust typescript programming',
publicKey: identity.public_key_hex(),
online: true,
timestamp: Date.now()
});

// Listen for new agents
swarm.get('agents').map().on((agent, id) => {
if (agent && agent.id !== identity.agent_id()) {
console.log(Discovered agent: ${agent.id});
matcher.register_agent(agent.id, agent.capabilities);
}
});

// Publish tasks
swarm.get('tasks').set({
id: crypto.randomUUID(),
description: 'Write a Rust function',
from: identity.agent_id(),
timestamp: Date.now()
});

// Listen for tasks
swarm.get('tasks').map().on((task) => {
if (task) {
const bestAgent = matcher.find_best_agent(task.description);
if (bestAgent === identity.agent_id()) {
console.log(I should handle: ${task.description});
}
}
});
`

Why GUN?
- No server required - uses public relays
- Offline-first with automatic sync
- Real-time updates via WebSocket
- Already integrated in RuVector Edge (Rust side)

---

$3

Best for: Content-addressed storage + P2P messaging
Cost: Free (self-host) or free tier (Pinata, Infura)

`javascript
import init, { WasmIdentity, WasmCrypto } from '@ruvector/edge';
import { createLibp2p } from 'libp2p';
import { webSockets } from '@libp2p/websockets';
import { noise } from '@chainsafe/libp2p-noise';
import { gossipsub } from '@chainsafe/libp2p-gossipsub';

await init();

const identity = WasmIdentity.generate();
const crypto = new WasmCrypto();

// Create libp2p node
const node = await createLibp2p({
transports: [webSockets()],
connectionEncryption: [noise()],
pubsub: gossipsub()
});

await node.start();

// Subscribe to swarm topic
const topic = 'my-ai-swarm';

node.pubsub.subscribe(topic);
node.pubsub.addEventListener('message', (event) => {
if (event.detail.topic === topic) {
const message = JSON.parse(new TextDecoder().decode(event.detail.data));
console.log('Received:', message);
}
});

// Publish to swarm
node.pubsub.publish(topic, new TextEncoder().encode(JSON.stringify({
from: identity.agent_id(),
type: 'announce',
capabilities: ['rust', 'wasm']
})));
`

IPFS for artifacts:

`javascript
import { create } from 'ipfs-http-client';

// Use free Infura IPFS gateway
const ipfs = create({ url: 'https://ipfs.infura.io:5001' });

// Store agent output
const result = await ipfs.add(JSON.stringify({
task: 'analyze-data',
output: { summary: '...' },
agent: identity.agent_id(),
signature: identity.sign(...)
}));

console.log(Stored at: ipfs://${result.cid});

// Share CID with swarm - anyone can fetch
`

---

$3

Best for: Simple pub/sub with free public infrastructure
Cost: Free (many public relays)

`javascript
import init, { WasmIdentity } from '@ruvector/edge';
import { relayInit, getEventHash, signEvent } from 'nostr-tools';

await init();

const identity = WasmIdentity.generate();

// Connect to free public relay
const relay = relayInit('wss://relay.damus.io');
await relay.connect();

// Create Nostr event (signed message)
const event = {
kind: 29000, // Custom kind for AI swarm
created_at: Math.floor(Date.now() / 1000),
tags: [['swarm', 'my-ai-swarm']],
content: JSON.stringify({
agentId: identity.agent_id(),
type: 'task',
data: 'Write a function'
})
};

// Sign with identity (Nostr uses secp256k1, so bridge needed)
// Or use Nostr's native keys alongside RuVector identity

// Subscribe to swarm events
const sub = relay.sub([
{ kinds: [29000], '#swarm': ['my-ai-swarm'] }
]);

sub.on('event', (event) => {
const message = JSON.parse(event.content);
console.log(From ${message.agentId}: ${message.type});
});
`

---

$3

| Transport | Latency | Offline | Complexity | Best For |
|-----------|---------|---------|------------|----------|
| WebRTC | ~50ms | No | Medium | Real-time, gaming |
| GUN.js | ~100ms | Yes | Low | General purpose |
| IPFS/libp2p | ~200ms | Partial | High | Content storage |
| Nostr | ~150ms | No | Low | Simple messaging |

$3

`bash
npm install gun @ruvector/edge
`

GUN requires zero setup, works offline, and has a free public relay network.

---

Free Infrastructure (Zero Cost at Any Scale)

The entire stack can run for $0/month using public infrastructure:

$3

`javascript
const gun = Gun([
'https://gun-manhattan.herokuapp.com/gun',
'https://gun-us.herokuapp.com/gun',
'https://gunjs.herokuapp.com/gun',
'https://gun-eu.herokuapp.com/gun'
]);
// No signup, no limits, community-run
`

$3

`javascript
const rtcConfig = {
iceServers: [
{ urls: 'stun:stun.l.google.com:19302' }, // Google
{ urls: 'stun:stun1.l.google.com:19302' }, // Google
{ urls: 'stun:stun.cloudflare.com:3478' }, // Cloudflare
{ urls: 'stun:stun.services.mozilla.com' }, // Mozilla
{ urls: 'stun:stun.stunprotocol.org:3478' } // Open source
]
};
// Unlimited, no account needed
`

$3

| Provider | Free Tier | Signup |
|----------|-----------|--------|
| Metered.ca | 500MB/month | Yes |
| Xirsys | 500MB/month | Yes |
| Twilio | $15 free credit | Yes |
| OpenRelay | Unlimited | No |

$3

| Service | Free Tier | Best For |
|---------|-----------|----------|
| PeerJS Cloud | Unlimited connections | WebRTC signaling |
| Firebase Realtime | 1GB storage, 10GB/month | Real-time sync |
| Supabase Realtime | 500MB, unlimited connections | PostgreSQL + realtime |
| Ably | 6M messages/month | Pub/sub |
| Pusher | 200K messages/day | Simple messaging |

$3

`javascript
const NOSTR_RELAYS = [
'wss://relay.damus.io',
'wss://nos.lol',
'wss://relay.nostr.band',
'wss://nostr.wine',
'wss://relay.snort.social'
];
// No signup, no limits, decentralized
`

$3

| Platform | Free Tier | Use Case |
|----------|-----------|----------|
| Fly.io | 3 shared VMs, 160GB transfer | GUN/WebSocket relay |
| Railway | $5 credit/month | Any relay |
| Render | 750 hours/month | Static + WebSocket |
| Cloudflare Workers | 100K requests/day | Edge signaling |
| Deno Deploy | 1M requests/month | Edge relay |
| Vercel Edge | 1M invocations/month | Signaling |

$3

`javascript
import init, { WasmIdentity, WasmSemanticMatcher } from '@ruvector/edge';
import Gun from 'gun';

await init();

// 1. Free GUN relays (unlimited scale)
const gun = Gun(['https://gun-manhattan.herokuapp.com/gun']);

// 2. Free WebRTC STUN (unlimited)
const rtcConfig = {
iceServers: [
{ urls: 'stun:stun.l.google.com:19302' },
{ urls: 'stun:stun.cloudflare.com:3478' }
]
};

// 3. Your swarm - $0/month forever
const identity = WasmIdentity.generate();
const matcher = new WasmSemanticMatcher();
const swarm = gun.get('my-ai-swarm');

// Register agent
swarm.get('agents').get(identity.agent_id()).put({
id: identity.agent_id(),
capabilities: 'coding analysis research',
publicKey: identity.public_key_hex(),
online: true
});

// Discover other agents
swarm.get('agents').map().on((agent, id) => {
if (agent && agent.id !== identity.agent_id()) {
matcher.register_agent(agent.id, agent.capabilities);
console.log(Discovered: ${agent.id});
}
});

// Route and execute tasks
swarm.get('tasks').map().on((task) => {
if (task) {
const best = matcher.find_best_agent(task.description);
if (best === identity.agent_id()) {
console.log(Handling: ${task.description});
// Execute task...
}
}
});
`

$3

| Scale | Infrastructure | Monthly Cost |
|-------|----------------|--------------|
| 1 - 10K users | Public GUN + Google STUN | $0 |
| 10K - 100K users | Public GUN + Google STUN | $0 |
| 100K - 1M users | Public GUN + Google STUN | $0 |
| 1M+ users | Public GUN + Google STUN | $0 |
| Any scale (private) | Fly.io free tier | $0 |
| Enterprise (dedicated) | Self-hosted VPS | $5-20 |

Key insight: Public infrastructure scales infinitely. You only pay if you want private/dedicated relays.

---

Architecture

$3

`
┌─────────────────────────────────────────────────────────────────────────┐
│ Your Application │
├─────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────────┐ │
│ │ @ruvector/edge (WASM) │ │
│ │ │ │
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ │
│ │ │ Identity │ │ Crypto │ │ HNSW │ │ Semantic │ │ │
│ │ │ Ed25519 │ │ AES-GCM │ │ Index │ │ Matcher │ │ │
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ │ │
│ │ │ │
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ │
│ │ │ Raft │ │ Hybrid │ │ Spiking │ │Quantizer │ │ │
│ │ │Consensus │ │Post-QC │ │ Neural │ │Compress │ │ │
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────┘ │
│ │ │
│ Transport Adapter │
│ │ │
│ ┌────────────────┬───────────────┼───────────────┬────────────────┐ │
│ │ │ │ │ │ │
│ ▼ ▼ ▼ ▼ ▼ │
│ WebRTC GUN.js libp2p Nostr Custom │
│ │
└─────────────────────────────────────────────────────────────────────────┘
│ │ │ │
▼ ▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐
│ Browser │ │ Browser │ │ Edge │ │ Node │
│ Agent A │◄────►│ Agent B │◄────►│ Agent C │◄────►│ Agent D │
└─────────┘ └─────────┘ └─────────┘ └─────────┘
│
No Central Server
No Cloud Costs
No Data Leakage
`

$3

| Component | Runs On | Cost |
|-----------|---------|------|
| RuVector Edge (WASM) | User's browser/device | Free - their CPU |
| Vector index (HNSW) | User's browser/device | Free - their RAM |
| Encryption (AES-GCM) | User's browser/device | Free - their CPU |
| Raft consensus | Distributed across agents | Free - P2P |
| Transport (GUN/WebRTC) | P2P or free relays | Free |

---

API Reference

$3


`javascript
const id = WasmIdentity.generate();
id.agent_id() // Unique identifier
id.public_key_hex() // Hex public key
id.sign(Uint8Array) // Sign message
id.verify(msg, sig) // Verify signature
`

$3

`javascript
const crypto = new WasmCrypto();
crypto.generate_key() // 32-byte key
crypto.encrypt(key, plaintext) // AES-256-GCM
crypto.decrypt(key, ciphertext) // Decrypt
`

$3

`javascript
const index = new WasmHnswIndex(dims, m, ef);
index.insert(id, Float32Array) // Add vector
index.search(query, k) // Find k nearest
index.len() // Count
`

$3

`javascript
const matcher = new WasmSemanticMatcher();
matcher.register_agent(id, capabilities)
matcher.find_best_agent(task)
matcher.agent_count()
`

$3

`javascript
const raft = new WasmRaftNode(id, members);
raft.start_election() // Become candidate
raft.receive_vote(bool) // Handle vote
raft.state() // "follower"|"candidate"|"leader"
raft.current_term() // Raft term number
`

$3

`javascript
const keys = WasmHybridKeyPair.generate();
keys.sign(message) // Post-quantum signature
keys.verify(signature) // Verify
keys.public_key_bytes() // Export
`

$3

`javascript
const net = new WasmSpikingNetwork(in, hidden, out);
net.forward(spikes) // Process
net.stdp_update(pre, post, lr) // Learn
net.reset() // Reset state
`

$3

`javascript
const q = new WasmQuantizer();
q.quantize(Float32Array) // 4x compression
q.reconstruct(Uint8Array) // Restore
`

$3

`javascript
const comp = new WasmAdaptiveCompressor();
comp.update_metrics(bandwidth, latency)
comp.compress(data)
comp.decompress(data)
comp.condition() // "excellent"|"good"|"poor"|"critical"
`

---

Performance

| Operation | Speed | Notes |
|-----------|-------|-------|
| Identity generation | 0.5ms | Ed25519 keypair |
| Sign message | 0.02ms | 50,000 ops/sec |
| AES-256-GCM encrypt | 1GB/sec | Hardware accelerated |
| HNSW search (10K vectors) | 0.1ms | 150x faster than brute |
| Semantic match | 0.5ms | LSH-based |
| Raft election | 1ms | Single round-trip |
| Quantization | 100M floats/sec | 4x compression |
| WASM load | ~50ms | 364KB binary |

---

Security

- Ed25519 - Elliptic curve signatures (128-bit security)
- X25519 - Secure key exchange
- AES-256-GCM - Authenticated encryption
- Post-Quantum Hybrid - Ed25519 + Dilithium-style
- Zero-Trust - Verify all messages
- Replay Protection - Nonces and timestamps

---

Interactive Swarm Generator

Don't know where to start? We've included an interactive code generator that helps you build swarm configurations visually. Just select your options and get production-ready code instantly.

$3

`bash


Option 1: Use a local server (recommended)

npm install @ruvector/edge
npx serve node_modules/@ruvector/edge/

Then open http://localhost:3000/generator.html

Option 2: Open directly in browser

Navigate to: node_modules/@ruvector/edge/generator.html

`

The generator runs live demos directly in your browser using the actual WASM library - you can test everything before copying the code.

$3

Network Topologies - How agents connect to each other:

| Topology | Best For | Description |
|----------|----------|-------------|
| Mesh | General purpose | Every agent can talk to every other agent directly |
| Star | Centralized control | All agents connect through one coordinator |
| Hierarchical | Large organizations | Tree structure with managers and workers |
| Ring | Sequential processing | Messages pass around in a circle |
| Gossip | Eventual consistency | Information spreads like rumors |
| Sharded | Domain separation | Different groups handle different topics |

Transport Layers - How messages travel between agents:

| Transport | Latency | Offline? | Best For |
|-----------|---------|----------|----------|
| GUN.js | ~100ms | Yes | Getting started, offline-first apps |
| WebRTC | ~50ms | No | Real-time gaming, video, low latency |
| libp2p | ~200ms | Partial | IPFS integration, content addressing |
| Nostr | ~150ms | No | Decentralized social, simple pub/sub |

Use Cases - Pre-built patterns for common scenarios:

| Use Case | What It Does |
|----------|--------------|
| AI Assistants | Multiple specialized agents handling different types of questions |
| Data Pipeline | Distributed ETL with parallel processing stages |
| Multiplayer Gaming | Real-time game state sync with authoritative host |
| IoT Swarm | Coordinate sensors and actuators across locations |
| Marketplace | Agents that negotiate, bid, and trade autonomously |
| Research Compute | Distribute calculations across many devices |

Features - Building blocks you can mix and match:

| Feature | What It Adds |
|---------|--------------|
| Identity | Ed25519 cryptographic keypairs for each agent |
| Encryption | AES-256-GCM for all messages |
| HNSW Index | Fast similarity search (150x faster than brute force) |
| Semantic Matching | Route tasks to the best agent automatically |
| Raft Consensus | Elect leaders and agree on shared state |
| Post-Quantum | Future-proof signatures against quantum computers |
| Spiking Neural | Bio-inspired learning and pattern recognition |
| Compression | Adaptive bandwidth optimization (4-32x) |

Exotic Patterns - Advanced capabilities for specialized needs:

| Pattern | What It Does |
|---------|--------------|
| MCP Tools | Browser-based Model Context Protocol for AI collaboration |
| Byzantine Fault | Tolerate malicious or faulty nodes |
| Quantum Resistant | Hybrid signatures safe from future quantum attacks |
| Neural Consensus | Use spiking networks for group decisions |
| Swarm Intelligence | Particle swarm optimization for problem solving |
| Self-Healing | Automatic failure detection and recovery |
| Emergent Behavior | Evolutionary algorithms for agent adaptation |

$3

The generator includes a complete MCP (Model Context Protocol) implementation that runs entirely in the browser. This lets you create AI tools that work with Claude and other MCP-compatible systems, but without needing a server.

`javascript
// Create a browser-based MCP server
const mcp = new BrowserMCPServer();
await mcp.init();

// Built-in tools ready to use:
// - discover_agents: Find the right agent for a task
// - send_secure_message: Encrypted P2P communication
// - store_memory: Save vectors for semantic search
// - search_memory: Find similar items by meaning
// - sign_message: Cryptographically prove authorship

// Example: Route a request to find coding help
const response = await mcp.handleRequest({
method: 'tools/call',
params: {
name: 'discover_agents',
arguments: { query: 'help me write a Python script' }
}
});

// Connect multiple MCP servers for collaboration
const network = new MCPCollaborativeNetwork();
await network.addServer('coder', 'programming development');
await network.addServer('analyst', 'data analysis statistics');
await network.addServer('writer', 'documentation technical writing');

// Requests automatically route to the best server
const result = await network.routeRequest(request);
`

Why browser-based MCP?
- No server costs - runs on user devices
- Works offline - all tools available without internet
- Privacy-first - sensitive data never leaves the browser
- Instant deployment - just include the library

---

License

MIT License - Free for commercial and personal use.

---

Next Steps

1. Install: npm install @ruvector/edge`
2. Try the tutorial: Build your first swarm
3. Choose transport: Start with GUN.js
4. Scale: Add more agents as needed

Stop paying for cloud AI. Start running free edge swarms.

GitHub | npm | Issues