Exa Deploy Integration

Overview

Deploy applications that use Exa's neural search API (api.exa.ai ) to production. Covers API key management, deployment to Vercel and Docker, rate limit configuration, and caching strategies for search-heavy applications.

Prerequisites

• Exa API key stored in EXA_API_KEY environment variable

• Application using exa-js SDK or REST API

• Platform CLI installed (vercel, docker, or gcloud)

Instructions

Step 1: Configure Secrets

Vercel

vercel env add EXA_API_KEY production

Docker

echo "EXA_API_KEY=your-key" >> .env.production

Cloud Run

echo -n "your-key" | gcloud secrets create exa-api-key --data-file=-

Step 2: Vercel Edge Deployment

// api/search.ts import Exa from "exa-js";

export const config = { runtime: "edge" };

export default async function handler(req: Request) { const exa = new Exa(process.env.EXA_API_KEY!); const { query, numResults } = await req.json();

const results = await exa.searchAndContents(query, { type: "neural", numResults: numResults || 5, text: { maxCharacters: 500 }, # HTTP 500 Internal Server Error });

return Response.json(results); }

Step 3: Docker with Caching

FROM node:20-slim WORKDIR /app COPY package*.json ./ RUN npm ci --only=production COPY . . RUN npm run build EXPOSE 3000 # 3000: 3 seconds in ms CMD ["node", "dist/index.js"]

// Search with Redis cache import Exa from "exa-js"; import { Redis } from "ioredis";

const exa = new Exa(process.env.EXA_API_KEY!); const redis = new Redis(process.env.REDIS_URL!);

async function cachedSearch(query: string, ttl = 3600) { # 3600: timeout: 1 hour const cacheKey = exa:${Buffer.from(query).toString("base64")}; const cached = await redis.get(cacheKey); if (cached) return JSON.parse(cached);

const results = await exa.searchAndContents(query, { type: "neural", numResults: 5, });

await redis.set(cacheKey, JSON.stringify(results), "EX", ttl); return results; }

Step 4: Health Check

export async function GET() { try { const exa = new Exa(process.env.EXA_API_KEY!); await exa.search("test", { numResults: 1 }); return Response.json({ status: "healthy" }); } catch { return Response.json({ status: "unhealthy" }, { status: 503 }); # HTTP 503 Service Unavailable } }

Error Handling

Issue Cause Solution

Rate limited Too many requests Implement caching and request queuing

Empty results Query too specific Broaden search terms

API key invalid Key expired Regenerate at dashboard.exa.ai

Timeout Large content request Reduce maxCharacters or numResults

Examples

Deploy to Vercel

vercel env add EXA_API_KEY production && vercel --prod

Resources

• Exa API Documentation

• Exa JavaScript SDK

Next Steps

For multi-environment setup, see exa-multi-env-setup .

Output

• Configuration files or code changes applied to the project

• Validation report confirming correct implementation

• Summary of changes made and their rationale