import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "prithivMLmods/Canopus-Flux-LoRA-Hoodies"
trigger_word = "Cloth style"  # Leave trigger_word blank if not used.
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

import gradio as gr

gr.load("prithivMLmods/Canopus-Flux-LoRA-Hoodies").launch()

from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import gradio as gr

def image_generator(prompt):
    pass

interface = gr.Interface(fn=image_generator, inputs="text", outputs="image")
app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

app = gr.mount_gradio_app(app, interface, path="/")