fastapi-templates

Design FastAPI project templates with async patterns and layered architecture.

2|Updated Apr 23, 2026

Search Tags:#fastapi #python #dependency injection #repository pattern #backend architecture #jwt authentication #async api

Ready to run

npx skills add https://github.com/gajjalaashok75-UI/GakrCLI --skill fastapi-templates-gajjalaashok75-ui

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: fastapi-templates
Source: https://github.com/gajjalaashok75-UI/GakrCLI/tree/main/assets/skills/backend-atlas/fastapi-pro/fastapi-templates
Command: npx skills add https://github.com/gajjalaashok75-UI/GakrCLI --skill fastapi-templates-gajjalaashok75-ui

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

This Skill helps you design production-ready FastAPI backend projects with a clean structure, async-first patterns, and reliable data access layers instead of scattering logic across routes.

Core Features & Use Cases

Project scaffolding: Organize FastAPI apps into routers, dependencies, core config, models, schemas, services, and repositories.
Async architecture: Apply async routes, async database sessions, middleware, and lifespan handling for high-performance APIs.
Testing and authentication: Set up JWT-based auth, dependency injection, CRUD patterns, and integration tests for real-world backend workflows.
Use case: Build a new REST API with PostgreSQL, user authentication, and a maintainable service layer that is easy to extend and test.

Quick Start

Ask for a production-ready FastAPI project structure with async database handling, JWT auth, repository and service layers, and testing guidance.

Frequently Asked Questions about fastapi-templates

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I structure a production-ready FastAPI project with async database sessions?▼

Structure a production-ready FastAPI project by organizing code into routers, dependencies, core config, models, schemas, services, and repositories. This layered backend architecture uses async database sessions and dependency injection to keep data access and business logic cleanly separated from routing.

What is the repository pattern in FastAPI and when should I use it?▼

The repository pattern in FastAPI isolates data access logic into dedicated repository classes, separating it from services and routes. Use it for maintainable Python web services to keep database operations centralized, making complex CRUD patterns easier to test and extend.

How do I set up JWT authentication in a FastAPI backend?▼

Set up JWT authentication in FastAPI by configuring auth dependencies within the core config and applying them to routers. This approach secures endpoints using dependency injection, ensuring maintainable authentication workflows and reliable integration tests for real-world backend APIs.

Does this FastAPI template support async patterns for microservices?▼

Yes, this FastAPI template supports async patterns for microservices by applying async routes, middleware, and lifespan handling. This high-performance async architecture is designed for new REST APIs, microservices, and authentication systems that require reliable concurrent data processing.

What's the best way to add a service layer to a FastAPI REST API?▼

The best way to add a service layer to a FastAPI REST API is using a repository-service separation pattern. This design isolates business logic into services while repositories handle database operations, creating a maintainable structure that is easy to extend and test.

How do I organize FastAPI routing and dependencies for maintainable Python web services?▼

Organize FastAPI routing and dependencies by structuring the application into dedicated modules for routers, dependencies, and core config. This creates maintainable Python web services by applying dependency injection and structured routing to prevent scattered logic across routes.