This guide shows how to build reliable AI text features using the ApiNest /api/v1/ai-textendpoint. We focus on prompt design, token budgeting, retries, idempotency, and observability so your feature works at scale.

Why ApiNest for AI text

Predictable costs via points and clear limits
Consistent JSON responses with usage fields
Real-time status page and documented error codes

Quick start (JavaScript)

async function generateText(prompt) {
  const res = await fetch('https://apinest.com/api/v1/ai-text?q=' + encodeURIComponent(prompt), {
    headers: { 'x-api-key': process.env.APINEST_API_KEY }
  })
  if (!res.ok) throw new Error((await res.json()).message)
  return res.json()
}

Retries and backoff

Implement exponential backoff when you see 429s or transient 5xx.

async function withRetries(fn, tries = 3) {
  for (let i = 0; i < tries; i++) {
    try { return await fn() } catch (e) {
      if (i === tries - 1) throw e
      await new Promise(r => setTimeout(r, Math.pow(2, i) * 1000))
    }
  }
}

Prompt patterns that work

Instruction + constraints: “Write a 140‑char headline, JSON only with keys title, tone.”
Few‑shot examples: provide 2–3 formatted samples.
Guardrails: ask for JSON schema and validate.

Observability checklist

Log prompt length and completion length
Capture error code and retryAfter if present
Sample 1% payloads for quality review

FAQ

How do I keep costs predictable?

Set max_tokens and cache frequent prompts. Use the points table in Docs.

What response format should I expect?

Structured JSON with text, model, and usage fields.

How do I handle timeouts?

Set client timeouts to 30–45s for AI calls and implement retries.

Build AI Text Apps on ApiNest: Production Guide with Examples