Christopher Walles

OpenAPI meets OpenAI

What if your OpenAPI spec could write its own backend? Learn a reliable process to generate fully functional code using LLMs, moving beyond simple server stubs.

OpenAPI meets OpenAI
#1about 5 minutes

Using OpenAPI specifications for automated code generation

The OpenAPI specification provides a language-agnostic way to describe REST APIs, which serves as documentation and enables automated generation of client libraries and server stubs.

#2about 5 minutes

Generating functional backend code with LLMs

Large language models can extend OpenAPI's code generation capabilities beyond simple stubs to create functional backend code, particularly for database-centric operations.

#3about 6 minutes

Structuring a Spring backend for code generation

The code generation process targets a specific Spring framework architecture, breaking the problem down into generating controllers, repositories, entities, and schema classes.

#4about 7 minutes

Crafting prompts to generate schemas and entities

A structured four-part prompt including task, rules, input, and context is used to reliably generate schema classes and database entities from the OpenAPI specification.

#5about 4 minutes

Generating controllers and repositories from the spec

By providing the LLM with the operation specification and previously generated classes as context, it can generate complete controller endpoints and database repositories.

#6about 3 minutes

Reviewing the limitations of this AI-driven approach

While the generated code is reliable for database-centric tasks, limitations include placing logic in controllers, lacking authorization, and the inherent incompleteness of the OpenAPI spec.

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