from diffusers import StableDiffusionPipeline
import torch
import os
from huggingface_hub import login

# Retrieve the token from the environment variable
token = os.getenv("HF_TOKEN")  # Hugging Face token from the secret
if token:
    login(token=token)  # Log in with the retrieved token
else:
    raise ValueError("Hugging Face token not found. Please set it as a repository secret in the Space settings.")

# Load the Stable Diffusion 3.5 model
model_id = "stabilityai/stable-diffusion-3.5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.to("cuda")

# Define the path to the LoRA model (since it's in the main directory)
lora_model_path = "lora_model.pth"  # Path to the uploaded LoRA model

# Load the LoRA model weights into the pipeline
pipe.load_lora_model(lora_model_path)  # Integrate the LoRA weights

# Function to generate an image from a text prompt
def generate_image(prompt):
    image = pipe(prompt).images[0]
    return image

import gradio as gr
iface = gr.Interface(fn=generate_image, inputs="text", outputs="image")
iface.launch()