LLM Pass-Through

A full-stack application for passing user prompts through to LLM services.

Project Overview

LLM Pass-Through provides a simple interface for users to submit prompts to language model services. The application handles authentication, request formatting, and response processing through a modern web interface.

Setup Instructions

Prerequisites

• Docker and Docker Compose
• Node.js (v16+) for local frontend development
• Python (v3.10+) for local backend development

Development Setup

1. Clone the repository:

   git clone https://github.com/yourusername/llm-pass-through.git
   cd llm-pass-through

2. Start the application with Docker Compose:

   docker-compose up

3. Access the application at http://localhost:3000

Running Tests

Frontend Tests

cd frontend
npm test

Backend Tests

cd backend
pytest

Project Structure

Project Directory Structure

llm-pass-through/
├── frontend/                 # React/TypeScript frontend application
│   ├── src/                  # Source code
│   │   ├── components/       # Reusable UI components
│   │   ├── pages/            # Page-level components
│   │   └── services/         # API client services
│   ├── tests/                # Frontend test configuration
│   ├── package.json          # Frontend dependencies and scripts
│   ├── tsconfig.json         # TypeScript configuration
│   └── vite.config.ts        # Vite build configuration
│
├── backend/                  # Python FastAPI backend
│   ├── app/                  # Application code
│   │   ├── api/              # API routes and controllers
│   │   ├── core/             # Core business logic
│   │   └── models/           # Data models and schemas
│   ├── tests/                # Backend tests
│   └── pyproject.toml        # Python dependencies and configuration
│
├── docker-compose.yml        # Docker compose configuration
├── testing-guidance.md       # Testing practices documentation
└── planning.md               # Project planning documents

Tech Stack

• Frontend: React with TypeScript, Vite
• Backend: Python with FastAPI and Pydantic
• Containerization: Docker and Docker Compose
• Testing: Jest (frontend), Pytest (backend)

Development Principles

This project follows Test-Driven Development (TDD) principles and Extreme Programming (XP) practices. For detailed testing guidance, see testing-guidance.md.