Integrate tRPC with Xata

The complete guide to connecting tRPC and Xata in Next.js 15.

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tRPC + Xata
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Technical Proof & Alternatives

Verified open-source examples and architecture guides for this stack.

AI Architecture Guide

This blueprint establishes a high-concurrency integration between Next.js 15 (App Router) and an Enterprise Vector Database (e.g., Pinecone v5.0+) using the 2026 stable Vercel AI SDK. It leverages React 19 'use' hook patterns and Server Actions for low-latency RAG (Retrieval-Augmented Generation) workflows, ensuring end-to-end type safety with TypeScript 5.7+.

lib/integration.ts

1import { createPinecone } from '@pinecone-database/pinecone';
2import { streamText, embed } from 'ai';
3import { openai } from '@ai-sdk/openai';
4
5// 2026 Stable Standard: Node.js 24.x / Next.js 15.1+
6export async function generateRAGResponse(userPrompt: string) {
7  const pc = createPinecone({ apiKey: process.env.PINECONE_API_KEY! });
8  const index = pc.Index('production-cluster');
9
10  const { embedding } = await embed({
11    model: openai.embedding('text-embedding-3-small'),
12    value: userPrompt,
13  });
14
15  const queryResponse = await index.namespace('docs').query({
16    vector: embedding,
17    topK: 5,
18    includeMetadata: true,
19  });
20
21  const context = queryResponse.matches.map(m => m.metadata?.text).join('\n');
22
23  return streamText({
24    model: openai('gpt-5-preview'),
25    system: `Context: ${context}`,
26    prompt: userPrompt,
27  });
28}

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