How to Handle Ad-Injection Errors in Vercel AI SDK (Next.js)

Overview

Monetization should never break your Vercel AI SDK (Next.js) app. The Monetzly SDK is built for this: if the ad service connection fails or errors mid-stream, it falls back to yielding your original, un-injected token stream, so the user still gets a complete answer.

You should still wrap the injection loop in your normal error handling so a failure degrades to a plain Vercel AI SDK (Next.js) response rather than a broken request.

Vercel AI SDK (Next.js) apps are usually built for streaming chat UIs, Next.js AI apps, and edge/serverless LLM routes, so handle ad-injection errors typically comes up while a user is mid-conversation, the moment where monetization has to be additive rather than disruptive.

How this works on Vercel AI SDK (Next.js)

Vercel's streamText() exposes a textStream of plain strings. Wrap it in an async generator that yields { content: text } and pass that into sdk.inject(); then stream the injected tokens back in your Route Handler Response. Both APIs are documented, so this is a direct fit.

Because Monetzly's inject() accepts any async token stream, the Vercel AI SDK (Next.js) side of this task is just mapping your output to it, no rewrite of your Vercel AI SDK (Next.js) model call.

Steps

1. Wrap the injection loop in your standard Vercel AI SDK (Next.js) error handling.
2. Rely on the SDK's automatic fallback to the original stream on ad-service failure.
3. Log injection failures so you can monitor fill and uptime separately from your model.

Integration snippet

import { streamText } from "ai";
import { google } from "@ai-sdk/google";
import { MonetzlySDK } from "@monetzly/server-sdk";

const sdk = new MonetzlySDK({
  apiKey: process.env.MONETZLY_API_KEY!,
  serverAddress: process.env.MONETZLY_SERVER_ADDRESS!,
});

export async function POST(req: Request) {
  const { prompt } = await req.json();
  await sdk.connect();
  const { textStream } = streamText({ model: google("gemini-2.0-flash"), prompt });

  // Adapt Vercel's string stream to Monetzly's TokenChunk shape.
  async function* asChunks() {
    for await (const text of textStream) yield { content: text };
  }

  const enc = new TextEncoder();
  const body = new ReadableStream({
    async start(c) {
      for await (const t of sdk.inject(asChunks(), { prompt }))
        c.enqueue(enc.encode(t.content ?? ""));
      await sdk.disconnect();
      c.close();
    },
  });
  return new Response(body, { headers: { "Content-Type": "text/plain; charset=utf-8" } });
}

Frequently asked questions

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