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Contributing to LLM API Bench

Thanks for your interest in contributing! This guide will help you get started.

Development Setup

Prerequisites

  • Node.js 18+
  • npm 9+
  • Git

Local Development

git clone https://github.com/idemerge/llm-api-bench.git
cd llm-benchmark
cp .env.example .env

# Backend (runs on port 3001)
cd backend && npm install && npm run dev &

# Frontend (runs on port 5173)
cd ../frontend && npm install && npm run dev

Docker

cp .env.example .env
docker compose up -d

Project Structure

├── backend/          # Express + TypeScript API server
│   ├── src/
│   │   ├── routes/       # API route handlers
│   │   ├── services/     # Business logic
│   │   └── database/     # SQLite schema & queries
│   └── package.json
├── frontend/         # React + Vite + TypeScript
│   ├── src/
│   │   ├── components/   # Shared UI components
│   │   ├── pages/        # Page-level components
│   │   └── services/     # API client
│   └── package.json
├── docker-compose.yml
├── Dockerfile
└── start.sh

How to Contribute

Reporting Bugs

  1. Search existing issues first
  2. Use the Bug Report issue template
  3. Include steps to reproduce, expected vs actual behavior, and screenshots if applicable

Suggesting Features

  1. Open an issue using the Feature Request template
  2. Describe the use case and why it would be useful

Submitting Code

  1. Fork the repository
  2. Create a feature branch from main: 
    git checkout -b feat/your-feature
  3. Make your changes — follow the coding conventions below
  4. Test your changes locally
  5. Commit with a descriptive message: 
    git commit -m "feat: add support for X"
  6. Push and open a Pull Request against main

Coding Conventions

  • Language: All code, comments, and commit messages in English
  • Commit style: Conventional Commits — feat:, fix:, docs:, refactor:, chore:, style:, ci:
  • Frontend: React functional components, TypeScript strict mode, Tailwind CSS for styling
  • Backend: Express routes → service layer → database. Raw SQL with better-sqlite3, no ORM
  • Formatting: Follow the existing code style in each file

Adding a New Provider Adapter

LLM API Bench supports adding custom LLM providers. To add one:

  1. Create a new adapter in backend/src/services/ following the existing pattern (see openai-adapter as reference)
  2. Implement the standard interface: chat, chatStream, listModels
  3. Register the adapter in the provider factory
  4. Add the provider option to the frontend settings page

License

By contributing, you agree that your contributions will be licensed under the MIT License.