Claude API Message Batches実践ガイド — 300k出力×バッチ処理で大規模コード生成・データ抽出を自動化する

import Anthropic from "@anthropic-ai/sdk";
const client = new Anthropic();

// --- 同期API: 即座にレスポンスが返る ---
const response = await client.messages.create({
  model: "claude-sonnet-4-6",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Hello" }],
});

// --- バッチAPI: ジョブを投入し、後から結果を取得する ---
const batch = await client.messages.batches.create({
  requests: [
    {
      custom_id: "req-001",
      params: {
        model: "claude-sonnet-4-6",
        max_tokens: 1024,
        messages: [{ role: "user", content: "Hello" }],
      },
    },
    // ... 最大100,000リクエストまで投入可能
  ],
});

const batch = await client.messages.batches.create({
  requests: [
    {
      custom_id: "long-output-001",
      params: {
        model: "claude-opus-4-6",
        max_tokens: 300000,
        messages: [
          {
            role: "user",
            content: "リポジトリ全体のコードレビューレポートを生成してください...",
          },
        ],
      },
    },
  ],
  betas: ["output-300k-2026-03-24"],
});

const batch = await client.messages.batches.create({
  requests: [
    {
      custom_id: "thinking-001",
      params: {
        model: "claude-opus-4-6",
        max_tokens: 300000,
        thinking: {
          type: "adaptive",
        },
        // effortはAPIレベルまたはリクエスト単位で指定可能
        messages: [
          {
            role: "user",
            content: "以下のコードのセキュリティ脆弱性を網羅的に分析して...",
          },
        ],
      },
    },
  ],
  betas: ["output-300k-2026-03-24"],
});

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

// --- 1. バッチ投入 ---
const batch = await client.messages.batches.create({
  requests: tasks.map((task) => ({
    custom_id: task.id, // ファイル名やタスクIDを使う
    params: {
      model: "claude-sonnet-4-6",
      max_tokens: 8192,
      system: SHARED_SYSTEM_PROMPT, // 共通化してPrompt Cachingを効かせる
      messages: [{ role: "user", content: task.prompt }],
    },
  })),
});

// --- 2. ポーリングで完了を待つ ---
let status = batch;
while (status.processing_status === "in_progress") {
  await new Promise((r) => setTimeout(r, 60_000)); // 60秒間隔
  status = await client.messages.batches.retrieve(batch.id);
  console.log(
    `進捗: ${status.request_counts.succeeded}/${status.request_counts.processing}`
  );
}

// --- 3. 結果取得 ---
const results: Record<string, string> = {};
const failed: Array<{ custom_id: string; error: unknown }> = [];

for await (const result of client.messages.batches.results(batch.id)) {
  if (result.result.type === "succeeded") {
    const text = result.result.message.content
      .filter((b) => b.type === "text")
      .map((b) => b.text)
      .join("");
    results[result.custom_id] = text;
  } else {
    failed.push({ custom_id: result.custom_id, error: result.result });
  }
}

// --- 4. エラー分のみリトライバッチ投入 ---
if (failed.length > 0) {
  const retryRequests = failed.map((f) => {
    const original = tasks.find((t) => t.id === f.custom_id)!;
    return {
      custom_id: `retry-${original.id}`,
      params: {
        model: "claude-sonnet-4-6",
        max_tokens: 8192,
        system: SHARED_SYSTEM_PROMPT,
        messages: [{ role: "user" as const, content: original.prompt }],
      },
    };
  });
  const retryBatch = await client.messages.batches.create({
    requests: retryRequests,
  });
  console.log(`リトライバッチ作成: ${retryBatch.id} (${failed.length}件)`);
}

// Prompt Caching併用: system promptにcache_controlを設定
const requests = files.map((file) => ({
  custom_id: file.name,
  params: {
    model: "claude-sonnet-4-6",
    max_tokens: 8192,
    system: [
      {
        type: "text" as const,
        text: SHARED_REVIEW_PROMPT, // 全リクエスト共通の長いプロンプト
        cache_control: { type: "ephemeral" as const },
      },
    ],
    messages: [{ role: "user" as const, content: file.content }],
  },
}));

import Anthropic from "@anthropic-ai/sdk";
import { readFileSync, writeFileSync } from "fs";
import { globSync } from "glob";

const client = new Anthropic();
const MAX_BATCH_SIZE = 100_000;

const REVIEW_PROMPT = `あなたはシニアTypeScriptエンジニアです。
以下のコードについて、バグ・セキュリティリスク・パフォーマンス問題・可読性改善を指摘してください。
重要度（Critical/Warning/Info）を付けて箇条書きで出力してください。`;

// 1. ファイル一覧を取得
const files = globSync("src/**/*.ts").map((path) => ({
  name: path,
  content: readFileSync(path, "utf-8"),
}));

// 2. バッチサイズ上限を考慮して分割
const chunks: typeof files[] = [];
for (let i = 0; i < files.length; i += MAX_BATCH_SIZE) {
  chunks.push(files.slice(i, i + MAX_BATCH_SIZE));
}

// 3. 各チャンクをバッチ投入 → 結果取得 → マージ
const allResults: Record<string, string> = {};

for (const chunk of chunks) {
  const batch = await client.messages.batches.create({
    requests: chunk.map((file) => ({
      custom_id: file.name,
      params: {
        model: "claude-sonnet-4-6",
        max_tokens: 4096,
        system: [
          {
            type: "text" as const,
            text: REVIEW_PROMPT,
            cache_control: { type: "ephemeral" as const },
          },
        ],
        messages: [
          {
            role: "user" as const,
            content: `ファイル: ${file.name}\n\n\`\`\`typescript\n${file.content}\n\`\`\``,
          },
        ],
      },
    })),
  });

  // ポーリング（前述のパターンと同様）
  let status = batch;
  while (status.processing_status === "in_progress") {
    await new Promise((r) => setTimeout(r, 60_000));
    status = await client.messages.batches.retrieve(batch.id);
  }

  for await (const result of client.messages.batches.results(batch.id)) {
    if (result.result.type === "succeeded") {
      const text = result.result.message.content
        .filter((b) => b.type === "text")
        .map((b) => b.text)
        .join("");
      allResults[result.custom_id] = text;
    }
  }
}

// 4. Markdownレポートに集約
const report = Object.entries(allResults)
  .map(([file, review]) => `## ${file}\n\n${review}`)
  .join("\n\n---\n\n");

writeFileSync("code-review-report.md", `# コードレビューレポート\n\n${report}`);