python ai saas boilerplate architect

I have generated a modular FastAPI router for your AI image generation service. This implementation includes strict Pydantic validation for generation parameters and a middleware-style check to prevent tenants from exceeding their monthly image credits.

FastAPI AI Image Generation Router

from fastapi import APIRouter, Depends, HTTPException, status
from pydantic import BaseModel, Field, validator
from typing import Optional

# Router initialization with clean tagging
router = APIRouter(prefix="/api/v1/images", tags=["Image Generation"])

class ImageGenerationRequest(BaseModel):
    prompt: str = Field(..., min_length=10, max_length=1000)
    width: int = Field(1024, ge=256, le=2048)
    height: int = Field(1024, ge=256, le=2048)
    num_images: int = Field(1, ge=1, le=4)

    @validator("width", "height")
    def validate_dimensions(cls, v):
        if v % 8 != 0:
            raise ValueError("Dimensions must be multiples of 8")
        return v

@router.post("/generate")
async def create_image_task(
    request: ImageGenerationRequest,
    current_user: dict = Depends(get_current_active_user)
):
    # 1. Multi-tenant quota enforcement
    images_requested = request.num_images
    if current_user['credits_remaining'] < images_requested:
        raise HTTPException(
            status_code=status.HTTP_402_PAYMENT_REQUIRED,
            detail=f"Insufficient credits. You requested {images_requested} but only have {current_user['credits_remaining']} left."
        )

    # 2. Integration with AI Service (Abstraction)
    try:
        # Task would typically be offloaded to Celery/Redis for async processing
        result = await image_ai_client.generate(
            prompt=request.prompt,
            size=f"{request.width}x{request.height}",
            n=request.num_images
        )

        # 3. Log usage for billing/database
        await deduct_user_credits(current_user['id'], images_requested)

        return {
            "status": "queued",
            "task_id": result.id,
            "credits_used": images_requested,
            "remaining_balance": current_user['credits_remaining'] - images_requested
        }

    except Exception as e:
        # Log error for observability
        logger.error(f"Image generation failed for user {current_user['id']}: {str(e)}")
        raise HTTPException(
            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
            detail="The AI generation service is currently unavailable."
        )

Next steps

1. Implement the get_current_active_user dependency in your auth module.
2. Setup a background worker like Celery if the image generation takes longer than 10 seconds.
3. Configure the deduct_user_credits function to update your PostgreSQL or Redis store.