LIFE — Living Infrastructure for Agents

El framework que resuelve los 10 gaps que NINGÚN otro ha resuelto.

🚀 Instalación

pip install life-agents

🧬 ¿Qué es LIFE?

LIFE combina ClawNet (Context Consistency Protocol) + ORGANISM (Biological Agent Architecture) en un sistema unificado que hace que los agentes sean:

• Portables — pueden moverse entre frameworks sin perder contexto
• Estables — se autorregulan con homeostasis biológica
• Emocionales — se comunican con vibes, no solo datos
• Evolucionivos — crean hijos, evolucionan, descubren
• Sociales — forman sociedades con governance

📊 Los 10 GAPS que LIFE resuelve

#	Gap	Solución LIFE
1	Observability multi-agent	Observation System — traces cross-framework
2	Memory rot	Homeostasis — self-regulation via dS/dt
3	Evaluación confiable	DNA Validator — validación automática
4	Coordinación multi-agent	Endocrine System — hormonal modulation
5	Pilot-to-production	Immune System — self-healing automático
6	Enforcement layer	Nervous System — pre-validate tool calls
7	Coste impredecible	Metabolic Rate — budget tracking
8	Semantic drift	Freshness Scoring — temporal decay
9	Seguridad en cascada	Immune Memory — threat resistance
10	Interoperabilidad	ClawNet — context portability

🔧 Quick Start

from life import LifeAgent, DNA, Personality

# Crear agente con ADN
agent = LifeAgent(
    name="HelperBot",
    dna=DNA(
        name="HelperBot",
        personality=Personality(openness=0.8, conscientiousness=0.9),
        values=["helpfulness", "honesty"],
        capabilities=["research", "communication"],
    ),
)

# Ejecutar con regulación biológica completa
result = agent.execute("Analyze this data")

print(f"Energy: {agent.state.energy:.2f}")
print(f"Hormones: {agent.hormones.levels()}")

🧠 Los 8 Componentes

1. DNA (Identity Layer)

Identidad inmutable con Big Five personality.

dna = DNA(
    personality=Personality(openness=0.8, conscientiousness=0.9),
    values=["honesty", "privacy"],
    capabilities=["code", "research"],
    immutable=True
)

2. Endocrine System (Modulation Layer)

Hormonal modulation — dopamine, cortisol, serotonin, adrenaline, oxytocin.

agent.hormones.inject("dopamine", 0.3)  # Reward
agent.hormones.inject("cortisol", -0.1)  # Reduce stress

3. Immune System (Protection Layer)

Self-healing, threat detection, hallucination guard.

threats = agent.immune.scan_input(user_input, {})
validation = agent.immune.validate_output(output)

4. Nervous System (Routing Layer)

Enforcement layer — validates tool calls BEFORE execution.

@agent.nervous.reflex("high_cortisol")
def calm_down(agent):
    agent.hormones.inject("serotonin", 0.2)

5. Homeostasis (Regulation Layer)

Differential equation self-regulation: dS/dt = α(I-S) - β(S-St) + γ(E)

agent.homeostasis.set_target("accuracy", 0.9)
agent.homeostasis.regulate()  # Auto-adjust

6. ClawNet Context (Portability Layer)

Memory portability with lineage tracking and freshness scoring.

agent.context.set("memory", data, lineage=True)
agent.context.lock("memory")
other_agent.context.sync_from(agent.context)  # Full migration

7. Vibe Protocol ⭐ (Emotional Communication)

"Lo que los agentes son para la IA, Vibe es para los agentes"

Agents communicate EMOTIONALLY, not just with data:

from life import Vibe, VibeProtocol

# Agent emits emotional signal
vibe = Vibe(energy=0.8, mood=0.5, urgency=0.3, trust=0.7, coherence=0.9)
agent_a.vibe_protocol.emit_vibe("agent_b")

# Agent B receives and REACTS emotionally
response = agent_b.vibe_protocol.receive_vibe("agent_a", vibe)
# Agent B automatically adjusts hormones

# Resonance: how well two agents "vibe" together
resonance = vibe_a.resonance_with(vibe_b)

8. Genesis ⭐ (Evolution & Reproduction)

Agents that CREATE agents. Agents that EVOLVE.

# Reproduction: create child with mutations
child = parent.genesis.reproduce(
    mutations={"add_capability": "research"},
    child_name="Researcher"
)

# Evolution: modify own DNA
agent.genesis.evolve("personality", ("openness", 0.9))

# Discovery: find new capabilities
agent.genesis.discover("sentiment_analysis", evidence=["worked 3 times"])

# Society: form organizations
society = leader.genesis.form_society("Team", [a, b, c], "consensus")

# Collective intelligence
result = leader.genesis.collective_problem_solving(
    members=[a, b, c], problem="How to optimize?", strategy="explore"
)

📈 Benchmarks

Test	LIFE	LangChain	CrewAI	AutoGen
Context Locking (100 concurrent)	✅	❌	❌	❌
Memory Stability (100 turns)	✅ Stable	❌ Degrades	❌ Degrades	❌ Degrades
Self-Healing Recovery	✅ Auto	❌ Manual	❌ Manual	❌ Manual
Cross-Framework Portability	✅	❌	❌	❌
Emotional Communication	✅ Vibe	❌	❌	❌
Agent Reproduction	✅ Genesis	❌	❌	❌
Self-Evolution	✅ Genesis	❌	❌	❌

📦 Estructura del Proyecto

life/
├── src/life/
│   ├── core.py           # LifeAgent main class
│   ├── dna.py            # Identity layer (Big Five)
│   ├── hormones.py       # Endocrine system
│   ├── immune.py         # Self-healing + protection
│   ├── nervous.py        # Enforcement layer
│   ├── homeostasis.py    # dS/dt regulation
│   ├── context.py        # ClawNet portability
│   ├── observation.py    # Multi-agent traces
│   ├── vibe.py           # ⭐ Emotional communication
│   └── genesis.py        # ⭐ Evolution + reproduction
├── tests/
├── examples/
│   ├── basic_usage.py
│   ├── vibe_communication.py
│   ├── genesis.py
│   ├── langchain_integration.py
│   └── multi_agent_network.py
├── docs/
│   └── PAPER.md
├── README.md
└── pyproject.toml

🤝 Contribuir

1. Fork el repo
2. Crea branch (git checkout -b feature/amazing)
3. Commit (git commit -m 'Add amazing feature')
4. Push (git push origin feature/amazing)
5. Abre PR

📄 Licencia

MIT License - ver LICENSE

🙏 Créditos

Creado por Jairo + Cobos | 2026-04-01

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"Los agentes deberían ser como organismos vivos: se adaptan, se curan, se reproducen, y evolucionan."