exa-deploy-integration

# Exa Deploy Integration ## Overview Deploy applications using Exa's neural search API to production. Covers API endpoint creation, secret management per platform, caching for production traffic, and health check endpoints. ## Prerequisites - Exa API key stored in `EXA_API_KEY` environment variable - Application using `exa-js` SDK - Platform CLI installed (vercel, docker, or gcloud) ## Instructions ### Step 1: Vercel Edge Function ```typescript // api/search.ts — Vercel API route import Exa from "exa-js"; export const config = { runtime: "edge" }; export default async function handler(req: Request) { if (req.method !== "POST") { return new Response("Method not allowed", { status: 405 }); } const exa = new Exa(process.env.EXA_API_KEY!); const { query, numResults = 5 } = await req.json(); if (!query || typeof query !== "string") { return Response.json({ error: "query is required" }, { status: 400 }); } try { const results = await exa.searchAndContents(query, { type: "auto", numResults: Math.min(numResults, 20), text: { maxCharacters: 1000 }, highlights: { maxCharacters: 300, query }, }); return Response.json({ results: results.results.map(r => ({ title: r.title, url: r.url, score: r.score, snippet: r.text?.substring(0, 300), highlights: r.highlights, })), }); } catch (err: any) { const status = err.status || 500; return Response.json( { err...