Pydantic V2 Discriminated Unions in FastAPI: Modeling Polymorphic AI Feature Configs Without Schema Sprawl
The article discusses the implementation of Pydantic V2's discriminated unions in FastAPI for managing various AI feature configurations. It highlights the challenges faced with traditional if/elif chains that led to schema mismatches and runtime errors. By adopting discriminated unions, the author improved type safety and validation, streamlining the API development process.
- ▪The author built nine AI features into CitizenApp, each requiring different configurations.
- ▪Previously, the author used if/elif chains for validation, leading to schema mismatches in production.
- ▪Switching to Pydantic V2's discriminated unions allowed for type-safe, one-liner FastAPI routes.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3944682) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Ugur Aslim Posted on Jun 3 • Originally published at uguraslim.com Pydantic V2 Discriminated Unions in FastAPI: Modeling Polymorphic AI Feature Configs Without Schema Sprawl #fastapi #pydantic #python #apidesign Pydantic V2 Discriminated Unions in FastAPI: Modeling Polymorphic AI Feature Configs Without Schema Sprawl I've built nine AI features into CitizenApp, and each one has a wildly different configuration shape. A summarization feature needs max_tokens and style.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
Discussion
0 commentsMore from DEV.to (Top)
