How to Use an LLM-Powered Boilerplate for Building Your Own Node.js API

This Node.js API boilerplate, enhanced with the new LLM Codegen tool, revolutionizes project creation. Leveraging the power of LLMs, it automates module code generation from simple text descriptions. This significantly streamlines development by including comprehensive features like end-to-end tests, database migrations, seed data, and the core business logic.

This project builds upon a pre-existing, production-ready Node.js API boilerplate, refined over years of development and adhering to best practices. Its core architecture emphasizes vertical slicing, Clean Code principles, and utilizes technologies like ZOD for input validation, InversifyJS for dependency injection, and Supertest for testing. Docker Compose facilitates multi-service setups.

Key Features and Improvements

The LLM Codegen addition offers several key advantages:

• Automated Module Generation: Quickly create new modules based on textual descriptions, integrating seamlessly into the existing API.
• Database Management: Automatically generates database migrations and updates seed scripts with relevant data.
• Comprehensive Testing: Generates and verifies end-to-end tests, ensuring the generated code functions correctly.

The generated code is clean, maintainable, and adheres to the boilerplate's established vertical slicing architecture. It focuses solely on essential CRUD operations, avoiding unnecessary complexity.

Implementation Details

The llm-codegen folder houses all code generation logic, independent of the core boilerplate. This allows for independent use of the boilerplate without modification.

The system uses three micro-agents: Developer, Troubleshooter, and TestsFixer, orchestrated to generate, debug, and test the code. The Developer generates the initial code; the Troubleshooter addresses compilation errors; and the TestsFixer ensures all tests pass. This iterative process results in high-quality, functional code.

Usage Guide

1. Setup: Navigate to the llm-codegen directory and run npm i. Configure your chosen LLM API key (OpenAI, Anthropic Claude, or OpenRouter LLaMA) in the .env file. OpenRouter LLaMA offers a free tier, but its output quality may be less reliable.

2. Execution: Run npm run start. The tool prompts for a module description and name. Detailed descriptions, including entity attributes and operations, yield better results.

3. Iterative Development: Generate code incrementally, adding modules as needed.

Examples of successful code generation and error correction are shown below:

Technical Aspects

Each micro-agent uses a specific prompt (see GitHub link for Developer prompt). Extensive testing with various LLMs, including gpt-4o-mini and claude-3-5-sonnet-20241022, indicates high code quality, though claude-3–5-haiku-20241022 often produces less reliable results. gpt-4o-mini sessions average around 2 cents in cost.

Anthropic usage logs demonstrate token consumption:

The system achieves a 95% success rate in generating compilable and runnable code.

This boilerplate, enhanced with LLM Codegen, offers a powerful and efficient approach to Node.js development. Contributions and feedback are welcome!

UPDATE [February 9, 2025]: DeepSeek API support added. It's cheaper than gpt-4o-mini with comparable output quality, but slower and prone to API request errors.

*Unless otherwise noted, all images are by the author*

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