🚀 FastAPI Project

This is a FastAPI project setup using uv, a blazing fast Python package manager.

Follow the steps below to get started.

---

📦 Requirements

• Python 3.10 (uv handles virtual environments automatically)
• uv installed

curl -LsSf https://astral.sh/uv/install.sh | sh

• (Optional) Docker & Docker Compose

---

⚙️ Environment Variables

Create a .env file in the project root with the following values:

# API Keys
GEMINI_API_KEY= # for API_VERSION_V1
ANTHROPIC_API_KEY= # for API_VERSION_V2
GROQ_API_KEY=

# Spotify API
SPOTIFY_CLIENT_ID=
SPOTIFY_CLIENT_SECRET=

# Supabase
SUPABASE_API_KEY=
SUPABASE_URL=

# Auth0 - only for testing protected route
AUTH0_DOMAIN=
AUTH0_API_IDENTIFIER=
AUTH0_CLIENT_SECRET=

# Logging
LOG_LEVEL=INFO   # Options: NOTSET, DEBUG, INFO, WARNING, ERROR, CRITICAL

⚠️ Make sure not to commit .env to version control.

---

🎵 Splitter AI Setup (Audio Processing)

Splitter AI saves processed audio files to Supabase Storage.

Before running:

1. Go to your Supabase project dashboard

2. Navigate to Storage → Buckets

3. Create a new bucket with the name:

   Media-Files
   

4. Enable ✅ “Public bucket”

5. Inside this bucket, create a directory:

   splitter_ai
   

Now, Splitter AI will save all audio files under:

Media-Files/splitter_ai/

---

⚙️ Local Setup Instructions

1. Clone the repository

   git clone https://github.com/NafeesMadni/GenZStudio_Backend.git
   cd GenZStudio_Backend

2. Install dependencies

   uv sync

3. Activate the virtual environment (optional if you run via uv run)

   source .venv/bin/activate   # Linux / MacOS
   .venv\Scripts\activate      # Windows

---

▶️ Running the App (Local)

uv run main.py

• App: http://127.0.0.1:8000
• Docs: http://127.0.0.1:8000/docs
• ReDoc: http://127.0.0.1:8000/redoc

---

⚡ Running Celery Worker (Local)

celery -A app.core.celery_app worker --loglevel=INFO

---

🧪 Running Tests

Run all tests:

pytest

Run Generators API tests:

pytest app/tools/testing/test_api.py -v

---

🐳 Running with Docker & Docker Compose

1. Build & Start Services

docker-compose up --build

Services started:

• Redis (broker & backend for Celery)
• Web (FastAPI app) → http://localhost:8000
• Celery Worker (background task processor)

2. Stop Services

docker-compose down

Remove volumes (e.g., Redis data):

docker-compose down -v

3. Logs

docker-compose logs -f        # all services
docker-compose logs -f web    # only FastAPI
docker-compose logs -f celery-worker