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import os
from huggingface_hub import login
import torch
import gradio as gr
from diffusers import StableDiffusion3Pipeline
# Get Hugging Face token from environment variables
hf_token = os.getenv("HF_API_TOKEN")
if hf_token:
login(token=hf_token)
print("Login successful")
else:
raise ValueError("Hugging Face token is missing. Please set it in the environment variables.")
def image_generator(prompt):
device = "cuda" if torch.cuda.is_available() else "cpu"
pipeline = StableDiffusion3Pipeline.from_pretrained(
"stabilityai/stable-diffusion-3-medium-diffusers",
torch_dtype=torch.float16 if device == "cuda" else torch.float32,
text_encoder_3=None,
tokenizer_3=None
)
# Move the pipeline to the appropriate device
pipeline.to(device)
# Generate the image
image = pipeline(
prompt=prompt,
negative_prompt="blurred, ugly, watermark, low, resolution, blurry",
num_inference_steps=40,
height=1024,
width=1024,
guidance_scale=9.0
).images[0]
return image
# Create a Gradio interface
interface = gr.Interface(
fn=image_generator,
inputs=gr.Textbox(lines=2, placeholder="Enter your prompt..."),
outputs=gr.Image(type="pil"),
title="Image Generator App",
description="This is a simple image generator app using HuggingFace's Stable Diffusion 3 model."
)
# Launch the interface
interface.launch()
print(interface)
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