流式输出 Streaming

import { ChatOpenAI } from "@langchain/openai";
 
const model = new ChatOpenAI({ model: "gpt-4o-mini", streaming: true });
 
const stream = await model.stream("讲一个关于单元测试的短故事");
for await (const chunk of stream) {
  process.stdout.write(chunk.content as string);
}

const chain = prompt.pipe(model).pipe(new StringOutputParser());
const stream = await chain.stream({ topic: "向量数据库" });
for await (const text of stream) {
  process.stdout.write(text);
}

const stream = chain.streamEvents({ topic: "RAG" }, { version: "v2" });
 
for await (const event of stream) {
  if (event.event === "on_llm_stream") {
    process.stdout.write(event.data.chunk.content as string);
  }
  if (event.event === "on_retriever_end") {
    console.log("检索到:", event.data.output.length, "块");
  }
}

// app/api/chat/route.ts
export const runtime = "nodejs";
 
export async function POST(req: Request) {
  const { topic } = await req.json();
  const stream = await chain.stream({ topic });
 
  const encoder = new TextEncoder();
  const readable = new ReadableStream({
    async start(controller) {
      for await (const chunk of stream) {
        controller.enqueue(encoder.encode(chunk));
      }
      controller.close();
    },
  });
  return new Response(readable, {
    headers: { "Content-Type": "text/plain; charset=utf-8" },
  });
}

// 前端
const res = await fetch("/api/chat", { method: "POST", body: JSON.stringify({ topic }) });
const reader = res.body!.getReader();
const dec = new TextDecoder();
while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  document.body.append(dec.decode(value)); // 逐字追加
}