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hackoak/
Stable_diffusion_3.5_custom_endpoint_handler

stable-diffusion-xl

endpoints_compatible

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Stable Diffusion 3.5 Custom Handler

This is a custom handler for deploying the stabilityai/stable-diffusion-3.5-large-turbo model on Hugging Face Inference Endpoints.

Files

handler.py: The main custom handler implementation
requirements.txt: Required dependencies
test_handler.py: Test script to verify the handler works
README.md: This file

Handler Features

The custom handler supports:

Text-to-image generation using Stable Diffusion 3.5 Large Turbo
Configurable parameters:
- num_inference_steps: Number of inference steps (default: 1)
- guidance_scale: Guidance scale (default: 0.0)
- width: Image width (default: 1024)
- height: Image height (default: 1024)
- seed: Random seed for reproducible results

Deployment Steps

1. Create a Hugging Face Repository

Go to Hugging Face and create a new repository
Name it something like your-username/stable-diffusion-3.5-handler

2. Upload the Handler Files

Upload these files to your repository:

handler.py
requirements.txt

3. Deploy as Inference Endpoint

Go to Hugging Face Inference Endpoints
Click "New Endpoint"
Select your repository
Choose your cloud provider and region
Select an appropriate instance type (GPU recommended)
Set the task to "Custom"
Deploy the endpoint

API Usage

Once deployed, you can call the endpoint with:

python

import requests

url = "https://your-endpoint-url"
headers = {"Authorization": "Bearer YOUR_TOKEN"}

payload = {
    "inputs": "A beautiful sunset over mountains, digital art",
    "num_inference_steps": 1,
    "guidance_scale": 0.0,
    "width": 1024,
    "height": 1024,
    "seed": 42
}

response = requests.post(url, headers=headers, json=payload)
result = response.json()

# The result contains a base64-encoded image
image_data = result["image"]

Response Format

The handler returns a JSON object with:

json

{
    "image": "base64_encoded_image_string",
    "prompt": "original_prompt",
    "parameters": {
        "num_inference_steps": 1,
        "guidance_scale": 0.0,
        "width": 1024,
        "height": 1024,
        "seed": 42
    }
}

Error Handling

If an error occurs, the response will contain: