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

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

exa-deploy-integration