app.py

import gradio as gr
from convert_diffusion_to_gguf import SUPPORTED_ARCHS, qconfig_map, convert
from huggingface_hub import create_repo, upload_file
from argparse import Namespace
from pathlib import Path


def upload(args, outfile):
    url = ""
    if args.host_repo_id and args.hf_token:
        repo_id = create_repo(args.host_repo_id, repo_type="model", exist_ok=True, token=args.hf_token).repo_id
        info = upload_file(repo_id=repo_id, path_in_repo=str(outfile), path_or_fileobj=str(outfile), token=args.token)
        url = info.commit_url
        print(f"Uploaded to {url}")

    return url


def go_gguf(model_repo_id, subfolder, arch, outtype, outfile_name, bigendian, verbose, host_repo_id, hf_token):
    args = Namespace(
        model=model_repo_id,
        subfolder=subfolder,
        arch=arch,
        outtype=outtype,
        outfile=Path(outfile_name),
        bigendian=bigendian,
        verbose=verbose,
        host_repo_id=host_repo_id,
        hf_token=hf_token,
    )
    convert(args)
    upload(args)


with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("<h1><center>GGUF Converter for Diffusers format model checkpoints</center></h1>")
    gr.Markdown(
        "Convert `diffusers` format model checkpoints from the Hub to GGUF format and optionally upload them back. Based on [this repo](https://github.com/ngxson/diffusion-to-gguf)."
    )

    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### 📥 Input Model")
            model_repo_id = gr.Textbox(label="Model Repo ID", placeholder="e.g., Qwen/Qwen-Image")
            subfolder = gr.Textbox(label="Subfolder (Optional)", placeholder="e.g., transformer")

            gr.Markdown("### ⚙️ Conversion Settings")
            arch = gr.Dropdown(choices=SUPPORTED_ARCHS, label="Architecture")
            outtype = gr.Dropdown(choices=list(qconfig_map.keys()), label="Quantization Type", value="F16")
            outfile_name = gr.Textbox(label="Output Filename", value="{ftype}.gguf")

            with gr.Accordion("Advanced Settings", open=False):
                bigendian = gr.Checkbox(label="Use Big Endian")
                verbose = gr.Checkbox(label="Verbose Logging", value=True)

            gr.Markdown("### 📤 Upload to Hub (Optional)")
            host_repo_id = gr.Textbox(label="Your Hub Repo ID", placeholder="e.g., YourUsername/My-GGUFs")
            hf_token = gr.Textbox(label="Hugging Face Token", type="password", placeholder="hf_...")

            convert_btn = gr.Button("Convert & Upload", variant="primary")

        with gr.Column(scale=2):
            gr.Markdown("### 🚀 Result")
            url_output = gr.Markdown()

    gr.Examples(
        examples=[
            [
                "black-forest-labs/FLUX.1-schnell",
                "transformer",
                "flux",
                "Q4_0",
                "flux-schnell-q4.gguf",
                False,
                False,
                "YourUsername/MyGGUFs",
                "hf_...",
            ],
            [
                "Qwen/Qwen-Image",
                "transformer",
                "flux",
                "Q8_0",
                "qwen-q4.gguf",
                False,
                False,
                "YourUsername/MyGGUFs",
                "hf_...",
            ],
        ],
        inputs=[model_repo_id, subfolder, arch, outtype, outfile_name, bigendian, verbose, host_repo_id, hf_token],
    )

    convert_btn.click(
        fn=lambda x: x,
        inputs=[model_repo_id, subfolder, arch, outtype, outfile_name, bigendian, verbose, host_repo_id, hf_token],
        outputs=[url_output],
    )

if __name__ == "__main__":
    demo.launch()