Tutorials Prompt Engineering Tutorial
Structured AI APIs — Complete Guide
Structured AI APIs — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of Prompt Engineering Tutorial on Toolliyo Academy.
On this page
Prompt Engineering Tutorial · Lesson 38 of 100
Structured AI APIs
Prompts → Apps
Prompts · 1 — Basics · ~6 min · Module 4: Structured Outputs
What is this?
Structured AI APIs expose HTTP endpoints that always return schema-valid JSON — wrapping LLM, validation, and errors consistently.
Why should you care?
PromptVerse Public API POST /v1/classify returns { data, meta, errors } with OpenAPI spec.
See it live — copy this example
Copy the prompt into ChatGPT, Claude, or your LLM API playground and compare outputs.
POST /v1/classify
Body: { "text": "...", "locale": "en" }
Response 200:
{ "data": { "intent": "billing", "confidence": 0.91 }, "meta": { "model": "gpt-4o-mini", "prompt_version": "1.2" } }What happened?
- Clients depend on stable shapes.
- meta carries model and prompt version for debugging without parsing prose.
Practice next
- Define OpenAPI schema for one route.
- build validate → LLM → validate.
- Return 422 on schema fail.
- Add request_id in meta.
- 429 with Retry-After on rate limit.
Remember
Stable JSON contract. meta for observability. Version API and prompts.
Partner integration
ISV calls classify API.
Outcome: OpenAPI doc lets them integrate in one day.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
Sign in to ask a question or upvote helpful answers.
No questions yet — be the first to ask!
