> ## Documentation Index
> Fetch the complete documentation index at: https://officellm.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> A TypeScript framework for building multi-agent AI systems with continuous execution

# OfficeLLM

A TypeScript framework for building multi-agent AI systems where a manager coordinates specialized worker agents that autonomously use tools to complete tasks.

## What is OfficeLLM?

OfficeLLM provides a framework for creating multi-agent systems:

* **Manager Agent** coordinates and delegates tasks to specialized workers
* **Worker Agents** execute specific tasks using their own tools and LLM providers
* **Provider Support** for OpenAI, Anthropic, Gemini, and OpenRouter
* **Type Safety** with Zod schemas for tool parameters
* **Continuous Execution** where agents work until completion

## Key Features

* **Multi-Agent**: Manager orchestrates specialized worker agents
* **Provider Agnostic**: OpenAI, Anthropic, Gemini, and OpenRouter
* **Type Safe**: Zod schemas for all tool parameters
* **User-Defined Tools**: Bring your own tool implementations
* **Extensible**: Add new providers and customize behavior

## Quick Example

```typescript theme={null}
import { OfficeLLM } from 'officellm';
import { z } from 'zod';

// Define a worker agent
const mathWorker = {
  name: 'Math Solver',
  description: 'Specialized in mathematical calculations',
  provider: {
    type: 'openai' as const,
    apiKey: process.env.OPENAI_API_KEY!,
    model: 'gpt-4',
    temperature: 0.1,
  },
  systemPrompt: 'You are a mathematical expert. Solve problems step by step.',
  tools: [
    {
      name: 'calculate',
      description: 'Perform mathematical calculations',
      parameters: z.object({
        expression: z.string().describe('Math expression to evaluate'),
      }),
    },
  ],
};

// Manager configuration
const manager = {
  name: 'Project Manager',
  description: 'Coordinates AI worker agents',
  provider: {
    type: 'anthropic' as const,
    apiKey: process.env.ANTHROPIC_API_KEY!,
    model: 'claude-3-sonnet-20240229',
    temperature: 0.7,
  },
  systemPrompt: 'You coordinate specialized AI agents to complete tasks.',
  tools: [
    {
      name: 'math_solver',
      description: 'Delegate math tasks to the math expert',
      parameters: z.object({
        task: z.string().describe('Math task to solve'),
        priority: z.enum(['low', 'medium', 'high']).default('medium'),
      }),
    },
  ],
};

// Initialize and use
const office = new OfficeLLM({
  manager,
  workers: [mathWorker],
});

const result = await office.executeTask({
  title: 'Calculate compound interest',
  description: 'What is the compound interest on $1000 at 5% for 3 years?',
  priority: 'high',
});

console.log('Result:', result.content);
```

## Why OfficeLLM?

* **Simplified Architecture**: Workers are called like functions
* **Type Safety**: Zod validates all tool parameters
* **Provider Agnostic**: Easy to switch between LLM providers
* **Extensible**: Adding new providers is straightforward

## How It Works

1. **User submits a task** to the manager via `executeTask()`
2. **Manager analyzes the task** and calls appropriate worker agents
3. **Workers execute tasks** using their specialized tools
4. **Manager synthesizes results** and returns to the user

## Next Steps

* [Quick Start](/quick-start) - Get up and running
* [Installation](/installation) - Install OfficeLLM
* [Configuration](/configuration) - Complete configuration reference
* [API Reference](/api/officeLLM) - Full API documentation