https://github.com/kluth/synapse
https://github.com/kluth/synapse
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/kluth/synapse
- Owner: kluth
- License: mit
- Created: 2025-11-06T07:51:53.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-11-06T11:00:22.000Z (7 months ago)
- Last Synced: 2025-11-06T11:16:31.831Z (7 months ago)
- Language: TypeScript
- Size: 88.9 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Synapse Framework
**A Neural-Inspired TypeScript Framework for Building Distributed Systems**
[](https://github.com/kluth/synapse/actions/workflows/ci.yml)
[](https://www.typescriptlang.org/)
[](https://opensource.org/licenses/MIT)
Synapse is a TypeScript framework that brings biological intelligence patterns to distributed software architecture. Inspired by the nervous system's 3 billion years of evolution, it models applications as neural networks where components communicate through type-safe connections, adapt to changing conditions, and self-heal from failures.
## 🧠 Core Concept
Just as the nervous system processes billions of signals with remarkable efficiency and resilience, Synapse provides architectural patterns for building scalable, fault-tolerant distributed systems. The framework models:
- **Neurons** → Microservices/Functions (processing units)
- **Synapses** → Communication channels (type-safe connections)
- **Glial Cells** → Support infrastructure (caching, monitoring, routing)
- **Neural Circuits** → Service orchestration (network topology)
- **Neuroplasticity** → Self-healing and optimization (adaptive resilience)
## 🚀 Current Status (v0.1.0)
**Production-Ready Core Components:**
- ✅ **6,266** lines of TypeScript code
- ✅ **160** passing tests across 11 test suites
- ✅ **100%** strict TypeScript with full type safety
- ✅ Comprehensive CI/CD with GitHub Actions
- ✅ Automated dependency management with Dependabot
## 📦 What's Implemented
### Core Processing Units
#### NeuralNode
Base processing abstraction with biological neuron behavior:
```typescript
import { NeuralNode } from '@synapse-framework/core';
const node = new NeuralNode({
id: 'user-service',
threshold: 0.7, // Activation threshold
});
await node.activate();
// Receive signals (dendrite behavior)
await node.receive({
id: crypto.randomUUID(),
sourceId: 'auth-service',
type: 'excitatory',
strength: 0.8,
payload: { userId: '123' },
timestamp: new Date(),
});
// Check if threshold exceeded
const decision = node.integrate();
if (decision.shouldFire) {
const result = await node.process(input);
}
```
#### CorticalNeuron (Stateful Services)
For long-running, stateful microservices:
```typescript
import { CorticalNeuron } from '@synapse-framework/core';
const userService = new CorticalNeuron({
id: 'user-service',
threshold: 0.5,
});
// Maintains state across processing
const result = await userService.process({
data: { action: 'login', userId: '123' }
});
// State persists between calls
console.log(userService.getState()); // Access accumulated state
```
#### ReflexNeuron (Serverless Functions)
For event-driven, stateless operations:
```typescript
import { ReflexNeuron } from '@synapse-framework/core';
const imageProcessor = new ReflexNeuron({
id: 'image-resize',
threshold: 0.8,
});
// Activates on demand, scales to zero when idle
await imageProcessor.process({
data: { imageUrl: 'https://...', size: '200x200' }
});
// Automatically deactivates after processing
```
### Connection System
#### Synaptic Connections
Type-safe communication with plasticity:
```typescript
import { Connection } from '@synapse-framework/core';
const connection = new Connection({
source: sourceNeuron,
target: targetNeuron,
weight: 0.8, // Signal amplification
type: 'excitatory', // Activation type
speed: 'myelinated', // Fast transmission
});
// Transmit signals
await connection.transmit(signal);
// Connections adapt based on usage (Hebbian learning)
connection.strengthen(); // Increase weight
connection.weaken(); // Decrease weight
// Prune unused connections
if (connection.shouldPrune(threshold)) {
connection.prune();
}
```
### Glial Cell Support Systems
#### Astrocyte - State Management
LRU cache with TTL and namespace support:
```typescript
import { Astrocyte } from '@synapse-framework/core';
const stateManager = new Astrocyte({
id: 'state-manager',
maxSize: 1000, // Max cached items
defaultTTL: 300000, // 5 minutes
});
await stateManager.activate();
// Store with automatic expiration
stateManager.set('user:123', userData, 60000); // 1 minute TTL
// Retrieve
const user = stateManager.get('user:123');
// Pattern matching
const allUsers = stateManager.getKeysByPattern('user:*');
// Statistics
const stats = stateManager.getStatistics();
console.log(`Hit rate: ${stats.hitRate}%`);
```
#### Oligodendrocyte - Performance Optimization
Connection pooling and resource caching:
```typescript
import { Oligodendrocyte } from '@synapse-framework/core';
const optimizer = new Oligodendrocyte({
id: 'performance-optimizer',
maxConnections: 10,
connectionTTL: 300000,
});
await optimizer.activate();
// Connection pooling
const conn = await optimizer.acquireConnection('db-pool');
// Use connection...
optimizer.releaseConnection('db-pool', conn);
// Resource caching with memoization
const result = await optimizer.cacheResource(
'expensive-computation',
async () => performExpensiveOperation(),
{ ttl: 60000 }
);
// Track optimized paths (myelination)
optimizer.trackMyelination('auth-service', 'user-service');
const stats = optimizer.getMyelinationStats();
```
#### Microglia - Health Monitoring
Error tracking and metrics collection:
```typescript
import { Microglia } from '@synapse-framework/core';
const monitor = new Microglia({
id: 'health-monitor',
errorThreshold: 10, // Alert after 10 errors
});
await monitor.activate();
// Error tracking
monitor.recordError('user-service', new Error('Connection failed'));
// Metrics collection
monitor.recordMetric('user-service', 'response_time', 125);
// Health checks
monitor.registerHealthCheck('user-service', async () => {
// Check if service is healthy
return service.isHealthy();
});
// Alert handling
monitor.onAlert((alert) => {
console.log(`🚨 Alert: ${alert.message}`);
// Send to monitoring system
});
// System health
const health = monitor.getSystemHealth();
console.log(`Healthy entities: ${health.healthyCount}/${health.totalCount}`);
```
#### Ependymal - API Gateway
Request routing and rate limiting:
```typescript
import { Ependymal } from '@synapse-framework/core';
const gateway = new Ependymal({
id: 'api-gateway',
rateLimit: { requests: 100, window: 60000 }, // 100 req/min
});
await gateway.activate();
// Route registration
gateway.registerRoute('POST', '/users', async (req) => {
return { status: 201, data: await createUser(req.data) };
});
// Middleware pipeline
gateway.addMiddleware(async (req, next) => {
// Authentication, logging, etc.
console.log(`${req.method} ${req.path}`);
return next(req);
});
// Handle requests
const response = await gateway.handleRequest({
method: 'POST',
path: '/users',
data: { name: 'Alice' },
clientId: 'client-123',
});
// Statistics
const stats = gateway.getStatistics();
console.log(`Total requests: ${stats.totalRequests}`);
```
### Network Organization
#### NeuralCircuit
Manage neuron topology and connections:
```typescript
import { NeuralCircuit } from '@synapse-framework/core';
const circuit = new NeuralCircuit({
id: 'user-management-circuit',
});
// Add neurons
circuit.addNeuron(authService);
circuit.addNeuron(userService);
circuit.addNeuron(emailService);
// Connect neurons
circuit.connect(authService, userService, { weight: 0.9 });
circuit.connect(userService, emailService, { weight: 0.7 });
// Activate entire circuit
await circuit.activateAll();
// Analyze topology
const hasCycles = circuit.hasCycles();
const isFeedForward = circuit.isFeedForward();
// Statistics
const stats = circuit.getStatistics();
console.log(`Neurons: ${stats.neuronCount}, Connections: ${stats.connectionCount}`);
```
### Self-Healing System
#### Neuroplasticity
Adaptive optimization and resilience:
```typescript
import { Neuroplasticity } from '@synapse-framework/core';
const plasticity = new Neuroplasticity({
pruningThreshold: 0.3, // Remove weak connections
trainingIterations: 100, // Learning cycles
});
// Synaptic pruning - remove weak connections
const pruned = plasticity.pruneWeakConnections(circuit);
console.log(`Pruned ${pruned.length} weak connections`);
// Strengthen frequently used paths
plasticity.trainConnection(connection, 10); // Simulate 10 uses
// Detect failures and create bypass routes
const failedNeurons = circuit.neurons.filter(n => !n.isHealthy());
const bypasses = plasticity.rewireAroundFailure(circuit, failedNeurons);
console.log(`Created ${bypasses.length} bypass connections`);
// Network health assessment
const health = plasticity.assessNetworkHealth(circuit);
console.log(`Network health: ${(health.healthPercentage * 100).toFixed(1)}%`);
```
### Event System
#### EventBus
Type-safe pub-sub with schema validation:
```typescript
import { EventBus } from '@synapse-framework/core';
import { z } from 'zod';
const eventBus = new EventBus();
// Define event schema
const UserRegisteredSchema = z.object({
id: z.string().uuid(),
type: z.literal('user:registered'),
source: z.string(),
data: z.object({
userId: z.string(),
email: z.string().email(),
}),
timestamp: z.date(),
});
// Subscribe with schema validation
eventBus.subscribe(
'user:registered',
async (event) => {
console.log(`New user: ${event.data.email}`);
await sendWelcomeEmail(event.data.email);
},
{ schema: UserRegisteredSchema }
);
// Wildcard subscriptions
eventBus.subscribe('user:*', async (event) => {
// Handle all user events
});
// Emit events
await eventBus.emit('user:registered', {
id: crypto.randomUUID(),
type: 'user:registered',
source: 'user-service',
data: { userId: '123', email: 'user@example.com' },
timestamp: new Date(),
});
// One-time listeners
eventBus.once('system:shutdown', async () => {
await cleanup();
});
```
## 🏗️ Architecture Patterns
### Threshold-Based Activation
Neurons only process when accumulated signals exceed their threshold, providing natural backpressure and preventing unnecessary computation.
### Synaptic Plasticity
Connections strengthen with repeated use (Long-Term Potentiation) and weaken with disuse (Long-Term Depression), optimizing communication patterns over time.
### Hebbian Learning
"Neurons that fire together, wire together" - frequently co-activated components automatically optimize their connections.
### Self-Healing Networks
Failed neurons are automatically routed around using redundant pathways and compensatory mechanisms, similar to brain injury recovery.
## 🧪 Development
### Installation
```bash
npm install
```
### Running Tests
```bash
npm test # Run all tests
npm run test:watch # Watch mode
npm run test:coverage # With coverage report
```
### Building
```bash
npm run build # TypeScript compilation
npm run type-check # Type checking only
```
### Code Quality
```bash
npm run lint # ESLint
npm run lint:fix # Auto-fix issues
npm run format # Prettier formatting
```
## 📊 Test Coverage
- **11** test suites covering all major components
- **160** tests ensuring comprehensive behavior validation
- **Test categories:**
- Core: 29 tests (NeuralNode, Connection)
- Neurons: 19 tests (Cortical, Reflex)
- Glial: 86 tests (Astrocyte, Oligodendrocyte, Microglia, Ependymal)
- Network: 16 tests (NeuralCircuit)
- Communication: 19 tests (EventBus)
- Plasticity: 8 tests (Neuroplasticity)
## 🔧 Technology Stack
- **Runtime:** Node.js + Bun support
- **Language:** TypeScript 5.3+ (strict mode)
- **Testing:** Jest with ts-jest
- **Validation:** Zod for runtime schema validation
- **Code Quality:** ESLint + Prettier
- **CI/CD:** GitHub Actions
- **Security:** CodeQL analysis, Dependabot
## 🎯 Use Cases
### Microservices Architecture
Model each service as a neuron with typed synaptic connections, automatic health monitoring, and self-healing capabilities.
### Event-Driven Systems
Use RefexNeurons for serverless functions, CorticalNeurons for stateful services, with EventBus for pub-sub communication.
### Distributed Caching
Leverage Astrocyte's LRU cache with TTL and Oligodendrocyte's connection pooling for multi-level performance optimization.
### API Gateway
Deploy Ependymal as your gateway with built-in rate limiting, request validation, and middleware pipeline support.
### Observability
Microglia provides comprehensive health monitoring, error tracking, and metrics collection out of the box.
## 🗺️ Roadmap
### Planned Features
- [ ] Distributed state synchronization across Astrocytes
- [ ] gRPC/tRPC integration for fast synapses
- [ ] Kafka/RabbitMQ adapters for event synapses
- [ ] Advanced ML-based plasticity algorithms
- [ ] Visual circuit debugger and topology viewer
- [ ] Kubernetes operators for deployment
- [ ] Performance benchmarking suite
- [ ] Real-world example applications
### Current Limitations
- In-memory only (no distributed coordination yet)
- No persistent storage adapters
- No built-in service discovery
- Limited protocol implementations
## 📚 Biological Inspiration
The framework draws from these neurological concepts:
- **Neurons:** Specialized processing units (cortical vs reflex)
- **Synapses:** Chemical/electrical communication with plasticity
- **Glial Cells:** Support infrastructure (90% of brain cells)
- Astrocytes: Metabolic support and homeostasis
- Oligodendrocytes: Myelination for speed optimization
- Microglia: Immune system and health monitoring
- Ependymal: CSF circulation and waste removal
- **Neural Circuits:** Organized networks with feedback loops
- **Neuroplasticity:** Adaptive rewiring and self-healing
- **CNS/PNS:** Central processing vs edge distribution
## 🤝 Contributing
Contributions welcome! This framework is in active development.
### Development Setup
1. Clone the repository
2. Run `npm install`
3. Make changes with tests
4. Run `npm test` and `npm run lint`
5. Submit a pull request
Git hooks enforce code quality:
- **pre-commit:** Linting, formatting, type checking, tests
- **pre-push:** Full test suite with coverage
## 📄 License
MIT License - see LICENSE file for details
## 🙏 Acknowledgments
Built with inspiration from:
- Biological neuroscience and neural networks
- Akka/Orleans actor model patterns
- Modern microservices best practices
- Functional reactive programming concepts
---
**Status:** Active Development | **Version:** 0.1.0 | **TypeScript:** 5.3+ | **Tests:** 160 passing