DeepClaude 性能深度评测：在智能体循环中结合 DeepSeek V4 Pro 与 Claude 的实战数据

// deepclaude-client.ts
// 混合客户端：DeepSeek 负责推理，Claude 负责综合

import Anthropic from '@anthropic-ai/sdk'
import OpenAI from 'openai'

// 建议使用 n1n.ai 统一管理各模型 API 密钥
const deepseek = new OpenAI({
  apiKey: process.env.DEEPSEEK_API_KEY,
  baseURL: 'https://api.deepseek.com/v1',
})

const claude = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY,
})

interface DeepClaudeResult {
  deepseekThinking: string // 原始推理链
  claudeOutput: string // 最终输出
  latencyMs: number // 总延迟
  tokensDeepseek: number
  tokensClaude: number
}

async function deepClaudeComplete(prompt: string, systemContext: string): Promise & lt
DeepClaudeResult & gt
{
  const start = Date.now()

  // 第一步：DeepSeek 生成深度推理
  const dsResponse = await deepseek.chat.completions.create({
    model: 'deepseek-reasoner',
    messages: [
      {
        role: 'system',
        content: '深入思考问题，不要直接生成最终答案。',
      },
      { role: 'user', content: prompt },
    ],
    max_tokens: 8000,
  })

  const thinking = dsResponse.choices[0]?.message?.content ?? ''
  const tokensDS = dsResponse.usage?.total_tokens ?? 0

  // 第二步：Claude 结合推理内容进行综合
  const claudeResponse = await claude.messages.create({
    model: 'claude-3-5-sonnet-20241022',
    max_tokens: 4096,
    system: systemContext,
    messages: [
      {
        role: 'user',
        content: `参考推理过程：\n<thinking>\n${thinking}\n</thinking>\n\n任务：${prompt}`,
      },
    ],
  })

  const claudeOutput =
    claudeResponse.content[0].type === 'text' ? claudeResponse.content[0].text : ''

  return {
    deepseekThinking: thinking,
    claudeOutput,
    latencyMs: Date.now() - start,
    tokensDeepseek: tokensDS,
    tokensClaude: claudeResponse.usage.input_tokens + claudeResponse.usage.output_tokens,
  }
}

async function compressThinking(thinking: string): Promise & lt
string & gt
{
  const lines = thinking.split('\n')
  const relevant = lines.filter(
    (l) =>
      l.includes('因此') ||
      l.includes('核心问题是') ||
      l.includes('解决方案') ||
      l.startsWith('→') ||
      l.startsWith('**')
  )

  const compressed = relevant.join('\n')
  // 如果压缩后太短，则保留最后 2000 字符
  return compressed.length & gt
  500 ? compressed : thinking.slice(-2000)
}