Interview Assistant — Coding Challenge Generator

Help beginners and experienced engineers practice for coding interviews. This repository contains a FastAPI backend, a React frontend (Vite), and Celery tasks for background jobs (email notifications).

The app generates coding challenges, tracks a daily quota per user, and stores a user's challenge history so they can review past attempts and explanations.

Key features

• Generate AI-assisted coding challenges (multiple choice + explanation)
• Per-user daily quota with automatic reset
• User authentication (signup, signin, token-based)
• History of generated challenges
• Email verification and password reset via background Celery tasks

Repository layout

• backend/ — FastAPI backend (source in backend/src/)
• frontend/coding-interview/ — React + Vite frontend
• Makefile — development helpers to start backend, frontend and Celery worker
• pyproject.toml — backend Python project configuration

Prerequisites

• Python 3.11+
• Node.js 16+ and npm (for the frontend)
• Redis (for Celery broker and result backend)
• PostgreSQL (or the database configured in DATABASE_URL)

You'll also want a .env file at the repository root (or set environment variables in your environment) with the settings used by the backend (see "Environment variables" below).

Quick start — Development

The Makefile includes convenient targets to run the backend, frontend and Celery worker concurrently. From the repository root, run:

# start backend dev server, celery worker and frontend dev server together
make dev

Notes:

• make dev sets PYTHONPATH=. so backend/src packages import properly.
• If you prefer to run services separately, use the Makefile targets:

# start only the backend dev server (FastAPI CLI)
make run-server

# start only the celery worker (foreground)
make run-celery

# start the frontend dev server (Vite)
make run-frontend

Open the frontend in your browser (Vite will print the dev URL, commonly http://localhost:5173) and the API runs at http://localhost:8000 (FastAPI dev server).

Production deployment (suggested)

The repo doesn't include a production-ready deploy script, but the recommended approach is:

1. Build the frontend:

cd frontend/coding-interview
npm ci
npm run build
# serve the `dist` directory with your preferred static web server (nginx, Caddy, etc.)

2. Run the backend with a production ASGI server (Uvicorn/Gunicorn):

# Example using uvicorn directly
PYTHONPATH=. uvicorn backend.src.__init__:app --host 0.0.0.0 --port 8000 --workers 4

3. Start Celery workers in the production environment (ensure Redis URL is configured):

PYTHONPATH=. celery -A backend.src.celery_tasks.celery_app worker --loglevel=info

4. Use a process manager (systemd, supervisor, docker-compose, Kubernetes) to keep services running.

Environment variables

Create a .env file at the project root or export these vars in your environment. The backend reads settings via pydantic-settings (see backend/src/config.py). Typical variables include:

DATABASE_URL=postgresql+asyncpg://user:pass@localhost:5432/dbname
REDIS_URL=redis://localhost:6379/0
API_PREFIX=/api/v1
ACCESS_TOKEN_EXPIRE_MINUTES=15
REFRESH_TOKEN_EXPIRE_DAYS=7
JWT_SECRETE=your_jwt_secret
JWT_ALGORITHM=HS256
MAIL_USERNAME=...
MAIL_PASSWORD=...
MAIL_SERVER=smtp.example.com
MAIL_PORT=587
MAIL_FROM=you@example.com
MAIL_FROM_NAME="Interview Assistant"
OPENAI_API_KEY=sk-...

Adjust names and values to your environment. Do not commit secrets to source control.

Running locally (step-by-step)

1. Create and activate a virtual environment (recommended):

python -m venv .venv
source .venv/bin/activate

2. Install backend dependencies. This project uses pyproject.toml (Hatch). If you prefer pip, you can create a requirements.txt or use pip to install directly from the project; otherwise install with pip from the project env:

# Example using pip (if you have a requirements file)
pip install -r backend/requirements.txt

# Or install the backend package in editable mode if you have an editable setup
# pip install -e .

3. Install frontend dependencies:

cd frontend/coding-interview
npm ci

4. Start development servers with make dev (recommended) or the individual make targets above.

API (high level)

• POST /api/v1/auth/signup — create account
• POST /api/v1/auth/signin — login (returns tokens)
• POST /api/v1/challenges/generate-challenge — generate a challenge (authenticated)
• GET /api/v1/challenges/quota — get current user's quota
• GET /api/v1/challenges/my-history — user challenge history

Refer to the backend route definitions in backend/src for exact request/response shapes and additional endpoints.

Troubleshooting

• "Module 'logging' has no attribute 'config'" when starting Celery: ensure you don't have a local module named logging.py shadowing the stdlib and that you start Celery with PYTHONPATH=. so imports are resolved correctly (the Makefile sets this).
• If the frontend fails to call API: check CORS and that the frontend dev server origin is allowed by the backend.
• If you see authentication errors, verify tokens are stored in localStorage (frontend) and JWT_SECRETE and other auth env vars are set.

Development notes

• Database migrations: this repo can be wired to Alembic for migrations. If you don't have migrations configured, creating tables via SQLModel's create_all is an option for local development.
• Background tasks: Celery is used to send email (verify/reset). Make sure Redis is running and REDIS_URL is set.

Contributing

Contributions are welcome. Please open issues or pull requests for bugs or improvements. Follow standard Git workflow (feature branch, tests, PR).

License

This project is provided as-is. Add a license file (e.g., LICENSE) if you want to specify terms.