status_code=400, Input too large: estimated 1468582 tokens exceeds the maximum a...

🔍 报错分析

1. 🌐 错误翻译

原文：status_code=400, Input too large: estimated 1468582 tokens exceeds the maximum allowed for model claude-opus-4-8 (1000000). (request id: 202607170604395185929038268d9d6UBVc2vyS) (request id: 20260717060440206408136
译文：状态码=400，输入过大：预估1468582个token超出模型claude-opus-4-8允许的最大值（1000000）。

2. 🎯 原因分析

3. 💡 解决方案

``代码语言
// 伪代码示例：文本分块处理逻辑
import { countTokens } from '@anthropic-ai/tokenizer'; // 假设有token计数库

const MAX_TOKENS = 1000000;
const INPUT_TEXT = '你的大段文本内容...';

// 方法一：文本分块处理
function splitTextIntoChunks(text, maxTokens) {
const chunks = [];
const sentences = text.split(/[.!?；。！？]\s+/); // 按句子分割

let currentChunk = '';
let currentTokens = 0;

for (const sentence of sentences) {
const sentenceTokens = countTokens(sentence);
if (currentTokens + sentenceTokens <= maxTokens) {
currentChunk += sentence + '。';
currentTokens += sentenceTokens;
} else {
if (currentChunk) chunks.push(currentChunk);
currentChunk = sentence + '。';
currentTokens = sentenceTokens;
}
}

if (currentChunk) chunks.push(currentChunk);
return chunks;
}

// 使用分块处理
const chunks = splitTextIntoChunks(INPUT_TEXT, MAX_TOKENS);

// 方法二：流式处理（若API支持）
// 通过流式传输，边发送边处理，避免一次性加载全部内容
async function streamRequest(text, model, maxTokens) {
// 按行/段落逐步读取文本并发送
const stream = fs.createReadStream(text, { encoding: 'utf8' });
let accumulatedTokens = 0;

for await (const chunk of stream) {
const chunkTokens = countTokens(chunk);
if (accumulatedTokens + chunkTokens > maxTokens) {
// 超出限制，处理当前累积内容并重置
await processChunk(currentBuffer, model);
accumulatedTokens = 0;
currentBuffer = '';
}
currentBuffer += chunk;
accumulatedTokens += chunkTokens;
}

// 处理剩余内容
if (currentBuffer) await processChunk(currentBuffer, model);
}
`

4. 🛡️ 预防措施