World Congress 2024 Aug 22, 2024 Session details

OpenAPI meets OpenAI

Christopher Walles

Stop manually coding routine CRUD operations. Discover how to strategically prompt GPT-4 with OpenAPI specs to instantly generate functional, compile-ready Kotlin and Spring backend components.

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#1 about 3 min

Generating functioning backend code from OpenAPI specifications

Using generative AI to eliminate repetitive backend engineering tasks.

#2 about 3 min

Understanding the purpose of OpenAPI specifications

Formal API descriptions in YAML enable documentation and automated client or server stub generation.

#3 about 5 min

Deconstructing API backends and the Pet Store schema

Breaking down database-heavy operations using API schemas from the classic open API pet store example.

#4 about 2 min

Breaking large code generation tasks into smaller segments

Slicing the YAML file into individual pieces ensures more reliable generative output from language models.

#5 about 5 min

Modeling backend components with the Spring framework

Mapping generated backend functionality to controllers, repositories, entities, and database schemas using Kotlin and Spring.

#6 about 6 min

Prompt engineering techniques for generating schema classes

Structuring strict rules and supplying limited context chunks prevents models from outputting unnecessary code explanations.

#7 about 3 min

Generating database entities and resolving relationship mapping

Instructing the language model to translate id references into exact foreign key dependencies for relational databases.

#8 about 4 min

Generating dynamic API endpoint controllers and repositories

Supplying previously generated schema context prompts the model to correctly wire database access and explicit HTTP error handling.

#9 about 3 min

Limitations of directly generating implementation strictly to controllers

Placing business logic strictly in controllers bypasses application service layers and exposes fundamental API specification gaps.

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Building agentic workflows using prompt engineering and language models

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Overview of generative AI and the presentation agenda

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Integrating generative AI capabilities via cloud-based API endpoints

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