멀티 에이전트 아키텍처

import { generateText, tool } from 'ai'
import { z } from 'zod'

const researchAgent = tool({
  description: '주어진 주제에 대해 깊이 있는 조사를 수행합니다.',
  inputSchema: z.object({
    topic: z.string(),
    depth: z.enum(['brief', 'detailed']),
  }),
  execute: async ({ topic, depth }) => {
    const result = await generateText({
      model: 'anthropic/claude-sonnet-4.6',
      system: '당신은 리서치 전문가입니다. 제공된 도구로 조사하고 요약합니다.',
      prompt: `${topic}에 대해 ${depth === 'detailed' ? '상세히' : '간략히'} 조사하세요.`,
      tools: { searchDocs, searchWeb },
    })
    return result.text
  },
})

const supervisorResult = await generateText({
  model: 'openai/gpt-5.4',
  system: '당신은 작업 관리자입니다. 필요한 조사를 위임하고 최종 결과를 종합합니다.',
  prompt: userQuery,
  tools: { researchAgent, analyzeData, writeSummary },
})

import { generateText } from 'ai'

export async function multiAgentWorkflow(task: string) {
  'use workflow'

  const plan = await planningStep(task)
  const research = await researchStep(plan.text)

  return synthesisStep(research.text)
}

async function planningStep(task: string) {
  'use step'
  return generateText({
    model: 'anthropic/claude-sonnet-4.6',
    system: 'You are a planning agent.',
    prompt: `Break down this task: ${task}`,
  })
}

async function researchStep(plan: string) {
  'use step'
  return generateText({
    model: 'anthropic/claude-sonnet-4.6',
    system: 'You are a research agent.',
    prompt: plan,
    tools: { searchDocs },
  })
}

async function synthesisStep(research: string) {
  'use step'
  return generateText({
    model: 'openai/gpt-5.4',
    system: 'You are a synthesis agent.',
    prompt: `Based on this research, produce the final output: ${research}`,
  })
}

const classifierAgent = {
  model: 'openai/gpt-5-mini', // fast tier
}
const researchAgent = {
  model: 'anthropic/claude-sonnet-4.6', // quality tier
}
const validatorAgent = {
  model: 'openai/gpt-5-mini', // fast tier
}