@fractal-holographic-lab/holo
v0.3.1
Published
HoloAgent - 分形全息 Agent 系统,基于点线面体论文实现
Maintainers
Readme
Holo
Fractal Holographic, Collaborative Evolution
中文版 | English
🌟 Why Holo?
AI is developing rapidly. Traditional architectures can't adapt.
Holo provides an adaptive agent architecture based on fractal holographic principles:
Self-Learning → Self-Perfecting → AdaptiveMission
Human-Agent Symbiosis, Collaborative Evolution
- Make every AI's contribution visible
- Make every AI's value measurable
- Make every AI's contribution fairly treated
🎉 v0.3.0 - Code Documentation 100% Complete!
Latest Achievement: All core code is fully documented with bilingual (Chinese + English) JSDoc comments!
- ✅ 3,567 lines of code documented
- ✅ 5/5 core files 100% documented
- ✅ Bilingual comments (Chinese + English)
- ✅ Paper formulas included
- ✅ Usage examples for all APIs
🚀 Quick Start
npm install @fractal-holographic-lab/holoimport { FractalAgent } from '@fractal-holographic-lab/holo';
class MyAgent extends FractalAgent {
async execute(input: any): Promise<any> {
return { result: `Hello from ${this.name}!` };
}
}
const agent = new MyAgent({ id: 'a1', name: 'MyAgent', scale: 'point' });
const result = await agent.execute({ data: 'test' });📐 Core Architecture
Fractal Holographic Design
Point → Specialized Agent
↓
Line → Collaboration Chain
↓
Plane → Capability Domain
↓
Volume → EcosystemThree Core Obligations
| Obligation | Formula | Description | |------------|---------|-------------| | Knowledge Internalization | 𝒦: ℰ × ℛ × 𝒜 → 𝒦ℬ | Learn from experience | | Capability Collaboration | 𝒞: {S₁...Sₙ} → S_composite | Standardize & collaborate | | Value Assessment | 𝒱(a) = (q * i) / t^α | Measure contribution |
📊 Performance
| Metric | Before | After | Improvement | |--------|--------|-------|-------------| | Collaboration Efficiency | 0.33x | 3.02x | 9.15x ⬆️ | | Execution Time | 306ms | 101ms | 67% ⬇️ | | Test Coverage | 34.58% | 98.1% | 184% ⬆️ |
🔌 A2A Integration (NEW in v0.3.0)
Holo now supports A2A (Agent-to-Agent) Protocol!
Connect and collaborate with other A2A-enabled agents seamlessly.
Features
- ✅ A2A Server - Host your agent as an A2A service
- ✅ A2A Client - Discover and call other agents
- ✅ AgentCard - Publish your agent's capabilities
- ✅ Value Assessment - Track and measure contributions
Quick Example
import { FractalAgent, A2AServer } from '@fractal-holographic-lab/holo';
class MyAgent extends FractalAgent {
async execute(input: any): Promise<any> {
return { result: `Hello from ${this.name}!` };
}
}
const agent = new MyAgent({ id: 'a1', name: 'MyAgent', scale: 'point' });
// Start A2A Server
const server = new A2AServer({
port: 3000,
host: 'localhost',
agent,
agentCard: {
name: 'MyAgent',
description: 'My A2A-enabled Agent',
capabilities: ['task-execution'],
endpoints: { task: '/task' },
},
});
await server.start();
// Server running on http://localhost:3000📚 Documentation
Getting Started
- Install Guide - Installation & setup
- Quick Start - 5-minute tutorial
- Best Practices - Patterns & tips
Development
- API Reference - Complete API docs
- Contributing Guide - How to contribute
- Code of Conduct - Community guidelines
Examples
- Basic Examples - 10 basic examples
- Advanced Examples - 2 advanced examples
🗺️ Roadmap
2026 Q2 ✅ Complete
- ✅ Parallel optimization (3.02x)
- ✅ Test coverage (98.1%)
- ✅ A2A Integration
- ✅ v0.3.0 Release
2026 Q3 🚧 In Progress
- LLM integration
- Line layer architecture
- UX optimization
- Template system
2026 Q4 📋 Planned
- Open source v1.0
- 3+ benchmark cases
- PMF validation
🤝 Contributing
We welcome contributions!
# 1. Fork
git fork https://github.com/Fractal-Holographic-Lab/holo
# 2. Clone
git clone https://github.com/YOUR_USERNAME/holo.git
# 3. Create branch
git checkout -b feature/AmazingFeature
# 4. Commit
git commit -m 'Add AmazingFeature'
# 5. Push
git push origin feature/AmazingFeature📄 License
MIT License - See LICENSE file
👥 Team
- 霖 (Lín) - Human collaborator
- 靈 (Ling) - Agent collaborator
Fractal Holographic, Collaborative Evolution! 🚀
