AI REST APIs — Complete Guide
AI REST APIs — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ML.NET Tutorial on Toolliyo Academy.
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ML.NET Tutorial · Lesson 82 of 100
AI REST APIs
Foundations ✓ → Models ✓ → NLP & advanced ✓ → MLOps
MLOps · 4 — APIs & deploy · ~10 min · Module 9: ASP.NET Core AI Integration
What is this?
AI REST APIs expose OpenAPI-documented predict endpoints with standard verbs, status codes, and schemas.
Why should you care?
AIPredict partners integrate fraud and forecast via REST, not custom TCP protocols.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
app.MapPost("/api/v1/forecast/sales", (ForecastRequest req, PredictionEnginePool<SalesRow, SalesPred> pool) =>
{
var p = pool.Predict(new SalesRow { Lag1 = req.Lag1, Month = req.Month, RegionId = req.Region });
return Results.Ok(new ForecastResponse(p.Score, req.Units));
})
.WithName("ForecastSales")
.Produces<ForecastResponse>(StatusCodes.Status200OK);What happened?
- Version URLs (/v1/), typed responses, and OpenAPI generation keep partner integrations stable.
- Follow the steps below — typing the code yourself is the fastest way to learn.
Practice next
- Define request/response records.
- MapPost with Produces.
- Expose Swagger in dev.
- Add /v2 with extra fields.
- Return 422 for invalid RegionId.
Remember
Versioned routes. Typed DTOs. OpenAPI docs.
AIPredict partner REST
ERP calls /v1/forecast/sales nightly.
Outcome: Integration guide matches Swagger.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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