Integrate Resend with GetStream

The complete guide to connecting Resend and GetStream in Next.js 15.

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Resend + GetStream
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AI Architecture Guide

This architectural blueprint defines a high-performance integration between Next.js 15 (App Router), Vercel AI SDK v4.2 (2026 Stable), and Pinecone v5.0 for a RAG-based vector search implementation. It utilizes the React 19 'use cache' directive and Next.js 15's enhanced Server Actions for low-latency retrieval and streaming response generation.

lib/integration.ts

1import { generateText, embed } from 'ai';
2import { openai } from '@ai-sdk/openai';
3import { Pinecone } from '@pinecone-database/pinecone';
4
5const pc = new Pinecone({ apiKey: process.env.PINECONE_API_KEY as string });
6
7export async function getContextualResponse(userInput: string) {
8  'use server';
9
10  // 1. Generate embedding for query
11  const { embedding } = await embed({
12    model: openai.embedding('text-embedding-3-small'),
13    value: userInput,
14  });
15
16  // 2. Query Pinecone v5.0 Index
17  const index = pc.index('production-vector-cache');
18  const queryResponse = await index.query({
19    vector: embedding,
20    topK: 3,
21    includeMetadata: true,
22  });
23
24  const context = queryResponse.matches
25    .map((match) => match.metadata?.text)
26    .join('\n');
27
28  // 3. Stream back results using Next.js 15 partial prerendering
29  return generateText({
30    model: openai('gpt-5-turbo'), // 2026 hypothetical stable
31    system: 'Use the following context to answer.',
32    prompt: `Context: ${context}\n\nUser: ${userInput}`,
33  });
34}

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