nodejs-todo-api-boilerplate
π οΈ A production-ready LLM-Powered Node.js & TypeScript REST API template, with a focus on Clean Architecture
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An LLM-powered code generation tool that relies on the built-in Node.js API Typescript Template Project to easily generate clean, well-structured CRUD module code from text description. It orchestrates 3 LLM micro-agents (`Developer`, `Troubleshooter` and `TestsFixer`) to generate code, fix compilation errors, and ensure passing E2E tests. The process includes module code generation, DB migration creation, seeding data, and running tests to validate output. By cycling through these steps, it guarantees consistent and production-ready CRUD code aligned with vertical slicing architecture.
README:
An LLM-powered code generation tool that relies on the built-in Node.js API Typescript Template Project to easily generate clean, well-structured CRUD module code from text description.
Before you proceed, verify that Node.js and npm are installed, and update your .env file with a valid LLM provider API key (e.g., OPENAI_API_KEY). You may choose from providers like OpenAI, Claude, DeepSeek, or OpenRouter/Llama.
It orchestrates 3 LLM micro-agents (Developer, Troubleshooter and TestsFixer) to generate code, fix compilation errors, and ensure passing E2E tests. The process includes module code generation, DB migration creation, seeding data, and running tests to validate output. By cycling through these steps, it guarantees consistent and production-ready CRUD code aligned with vertical slicing architecture. It uses OpenAI/Anthropic/DeepSeek/Llama LLM API to perform code-generation
First, navigate to the root ./llm-codegen folder and run npm install to install dependencies. Then execute npm run start and provide the requested module description when prompted. Finally, after the code generation finishes, review the output, and if the output meets your expectations, begin integrating it into your codebase
This project is a simple Node.js boilerplate using TypeScript and Docker. It demonstrates vertical slicing architecture for a REST API, as detailed here: https://markhneedham.com/blog/2012/02/20/coding-packaging-by-vertical-slice/. Unlike horizontal slicing (layered architecture), vertical slicing reduces the model code gap, making the modeled domain easier to understand. The implementation also follows the principles of Clean Architecture by Uncle Bob: https://blog.cleancoder.com/uncle-bob/2012/08/13/the-clean-architecture.html.
The application provides APIs for users to get, create, update, and delete Todo (CRUD operations)
- Vertical slicing architecture based on DDD & MVC principles
- Services input validation using ZOD
- Decoupling application components through dependency injection using InversifyJS
- Integration and E2E testing with Supertest
- Docker-compose simplifies multi-service setup, running application, DB, and Redis in isolated docker containers easily
- Simple DB transaction management with Knex
- Multi-layer trace ID support for logging with winston
- Support graceful shutdown for the express.js server
- In-memory data storage and caching with ioredis
- Auto-reload on save using ts-node-dev
- Automated documentation generation with TypeDoc
- Scheduled server-side cron jobs using node-cron
- AWS S3 integration for file uploads using aws-sdk
Please make sure that you have docker installed https://docs.docker.com/engine/install/
How to run locally (in dev mode):
- Copy
.env.sampleand rename it to.env, providing the appropriate environment variable values. Some of the variables are defined in the docker-compose file - Install dependencies locally
npm i - Start the app using
npm run docker:run - By default, the API server is available at
http://localhost:8080/
Migrations and seed run automatically
How to run tests in separate docker containers locally:
- Install dependencies locally
npm i - Run API tests in separate docker containers
npm run docker:test
How to run tests locally with a local SQLite DB:
- Install dependencies locally
npm i - Execute API tests using a local SQLite DB that stores data in a file:
npm run local:test
todo-api
ββ package.json
ββ src
β ββmodules (domain components)
β β ββ todos
β β β ββ tests
β β β ββ repository
β β β ββ routes
β β β ββ controllers
β β β ββ *.service (business logic implementation)
β ββ users
β ββ ...
β β
ββ infra (generic cross-component functionality)
β ββ data (migrations, seeds)
β ββ integrations (services responsible for integrations with 3rd party services - belong to repository layer)
β ββ loaders
β ββ middlewaresComprehensive API documentation is created directly from the source code using TypeDoc. To generate the documentation, run:
- Generate documentation:
npm run generate:docs - Serve documentation locally:
npm run serve:docs
After running these commands, the documentation will be accessible at http://127.0.0.1:8081.
Here is Postman collection to work with API locally:
List of available routes:
Auth routes:
POST /api/signup - register
POST /api/signin - login
POST /api/jwt/refresh - refresh auth token
POST /api/signout - logout
User routes:
GET /v1/users - get all users (requires admin access rights)
GET /v1/users/me - get current user
Todo routes:
POST /api/todos - create new todo
PUT /api/todos/:todoId - update todo
GET /api/todos/:todoId - get specific todo
GET /api/todos/my - get all users' todos
DELETE /api/todos/:todoId - delete user
GET /api/todos - get all created todos (requires admin access rights)
The codebase is organized into modules, with each module representing either a use case (business logic) or an integration service (with a third-party service, e.g., AWS). Each module defines its dependencies using dependency injection and validates input parameters with ZOD.
To easily manage dependencies and decouple parts of the application, the InversifyJS package is used. Each class or module can consume one of the registered dependencies via decorators. In the dependency container file located at src/infra/loaders/diContainer.ts, you can find each dependency and its corresponding imported module.
The application uses the winston logger for effective logging and implements cross-layer trace IDs in the winston wrapper output logic. As a result, logs related to the same request but from different layers (service, repository, controller) are outputted with the same trace ID without any extra implementation.
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