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@johpaz/hive-sdk

v0.0.18

Published

Hive SDK — The Agent Harness SDK. Build, deploy, and scale AI agent applications with multi-channel support, context engineering, and swarm orchestration.

Downloads

644

Readme

Documentación — Hive SDK

Hive Agent Harness SDK — Build, deploy, and scale AI agent applications with multi-channel support, Bun Workers, and swarm orchestration.

Documentos

| Documento | Descripción | |-----------|-------------| | API-AGENTS.md | createAgent, AgentLoop, Tool/Skill Selector, LLM Providers | | API-DAG-SCHEDULER.md | DAGScheduler, TaskGraph, TaskNode, Estrategias, Presets | | API-WORKERS-EVENTS.md | Bun Workers, createWorker, WorkerPool, AgentBus, EventBus, Canvas | | API-TOOLS-SKILLS-CHANNELS.md | Tools, Skills, MCP, Gateway, Channels, Tool Runtime, Storage | | API-CONTEXT-COMPILER.md | Context Compiler, Message History, Scratchpad, EthicsGuard, ACE | | TEMPLATE-HIVE-APP.md | Template hive-app — estructura, opciones, personalización |

¿Qué es Hive SDK?

Hive SDK es un Agent Harness: un marco de trabajo completo para construir, desplegar y escalar aplicaciones de agentes de IA. A diferencia de un simple wrapper de LLM, un harness provee todo lo necesario para que un agente opere en producción:

  • Agentes: ciclo ReAct, selección dinámica de tools/skills vía FTS5, múltiples providers (OpenAI, Anthropic, Gemini, Ollama).
  • Tools: 70+ tools incluidas — filesystem, web search, browser automation (agent-browser), APIs (api_request), canvas, voz, office, cron.
  • Skills: workflows reutilizables con defineSkill y SkillLoader.
  • Canales: Telegram, Discord, WhatsApp, Slack y WebChat con ChannelManager.
  • Swarm: orquestación multi-agente con DAGScheduler, TaskGraph y WorkerPool.
  • Runtime: ejecución paralela de tools vía Bun Workers.
  • Gateway: servidor HTTP/WebSocket para exponer agentes como API.
  • Memoria y estado: SQLite + FTS5, scratchpad, context compiler.

Con Hive SDK no montas un agente desde cero: enganchas tu lógica de negocio en un harness ya armado.

Instalación

# Instalar globalmente para el CLI
bun install -g @johpaz/hive-sdk

# O en un proyecto
bun add @johpaz/hive-sdk

CLI Commands

hives init <name>         # Inicializar proyecto agente
hives create-app <name>   # Crear aplicación harness completa
hives add-tool <name>     # Añadir tool
hives add-skill <name>    # Añadir skill
hives add-worker <name>   # Añadir Bun Worker
hives run                 # Ejecutar agente
hives test                # Test tools/skills
hives trace               # Ver logs de ejecución

Inicio Rápido

1. Crear una app harness completa

hives create-app my-hive
cd my-hive
bun install
cp .env.example .env
bun run dev

2. Crear un agente simple

import { createAgent, defineTool } from "@johpaz/hive-sdk";

const tool = defineTool({
  name: "saludar",
  description: "Saluda a alguien",
  execute: async (args: { nombre: string }) => `¡Hola ${args.nombre}!`,
});

const agent = await createAgent({
  name: "asistente",
  provider: "openai",
  model: "gpt-4o-mini",
  tools: [tool],
});

const respuesta = await agent.run("Saluda a Juan");
console.log(respuesta);

3. Crear un worker especializado

import { createWorker } from "@johpaz/hive-sdk";

const researcher = createWorker({
  name: "researcher",
  systemPrompt: "You are a research specialist. Provide concise, factual summaries.",
});

const result = await researcher.run("Research quantum computing advances");
console.log(result);
researcher.terminate();

4. Ejecutar workers en paralelo

import { WorkerPool } from "@johpaz/hive-sdk";

const pool = new WorkerPool({ maxWorkers: 4 });

const tasks = [
  { id: "t1", message: "Summarize article A" },
  { id: "t2", message: "Summarize article B" },
  { id: "t3", message: "Summarize article C" },
];

const results = await pool.executeBatch(tasks);
console.log(results);
pool.shutdown();

5. Gateway HTTP/WebSocket

import { startGateway } from "@johpaz/hive-sdk";

const server = await startGateway({
  host: "127.0.0.1",
  port: 18790,
  agentId: "coordinator",
});

console.log(`Gateway at http://127.0.0.1:18790`);

Variables de Entorno

HIVE_DATA_DIR=./data          # Directorio de datos SQLite
HIVE_HOST=127.0.0.1           # Gateway host
HIVE_PORT=18790               # Gateway port
OPENAI_API_KEY=sk-...         # OpenAI
ANTHROPIC_API_KEY=sk-ant-...  # Anthropic
GOOGLE_API_KEY=...            # Gemini
LOG_LEVEL=info                # debug | info | warn | error

Tests

# Todos los tests (paralelo)
bun test

# Tests con timeout extendido
bun test --timeout 60000

Documentación Hive SDK v0.0.18