stash-ai-server 0.1.0a7

Stash AI Overhaul Backend Server

AI Overhaul Backend

Minimal FastAPI backend with SQLite + Alembic migrations.

Features

• FastAPI application exposing /api/v1/requests CRUD (create + read/list now)
• SQLite database stored under backend/data/app.db
• SQLAlchemy 2.0 style models
• Alembic migration management
• Docker dev environment with live reload (code mounted as volume)

Directory Layout

backend/
  app/
    api/          # Routers
    core/         # Config
    db/           # Session + base
    models/       # SQLAlchemy models
    schemas/      # Pydantic schemas
    main.py       # FastAPI entry
  alembic/        # Migration scripts
  alembic.ini     # Alembic config
  requirements.txt
  Dockerfile

Run (Docker Compose)

docker compose up --build

Then visit http://localhost:8000/docs for the Swagger UI.

During development, source changes under backend/app auto-reload thanks to --reload and bind mount.

Manual Local Run (Without Docker)

python -m venv .venv
. .venv/Scripts/activate  # Windows PowerShell: .venv\Scripts\Activate.ps1
pip install -r backend/requirements.txt
uvicorn backend.app.main:app --reload

Apply Migrations

The container runs with Base.metadata.create_all() for convenience right now. To use Alembic migration fully:

# Inside container or local env (with PYTHONPATH set to backend):
alembic upgrade head

Example Requests

POST /api/v1/requests
{
  "prompt": "Describe scenic imagery"
}

GET /api/v1/requests
GET /api/v1/requests/1

Next Steps

• Add status update endpoint (PATCH)
• Introduce background processing queue
• Add filtering/pagination on list endpoint
• Add CORS config if frontend fetches directly
• Authentication (API key or session) when needed