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from flask import Flask, request, jsonify | |
from gradio_client import Client | |
app = Flask(__name__) | |
# Initialize the Gradio Client | |
client = Client("stabilityai/stable-diffusion-3.5-large") | |
def generate_image(): | |
data = request.json | |
# Extract parameters from the request | |
prompt = data.get("prompt", "Hello!!") | |
negative_prompt = data.get("negative_prompt", "") | |
seed = data.get("seed", 0) | |
randomize_seed = data.get("randomize_seed", True) | |
width = data.get("width", 1024) | |
height = data.get("height", 1024) | |
guidance_scale = data.get("guidance_scale", 4.5) | |
num_inference_steps = data.get("num_inference_steps", 40) | |
try: | |
# Use the Gradio Client to generate an image | |
result = client.predict( | |
prompt=prompt, | |
negative_prompt=negative_prompt, | |
seed=seed, | |
randomize_seed=randomize_seed, | |
width=width, | |
height=height, | |
guidance_scale=guidance_scale, | |
num_inference_steps=num_inference_steps, | |
api_name="/infer" | |
) | |
return jsonify({"image_url": result}), 200 | |
except Exception as e: | |
return jsonify({"error": str(e)}), 500 | |
if __name__ == "__main__": | |
app.run(host="0.0.0.0", port=5000) | |