app.py

import os
from huggingface_hub import HfApi, upload_folder
import gradio as gr

from huggingface_hub import whoami, list_models


def error_str(error, title="Error"):
    return f"""#### {title}
            {error}"""  if error else ""

def url_to_model_id(model_id_str):
    return model_id_str.split("/")[-2] + "/" + model_id_str.split("/")[-1] if model_id_str.startswith("https://huggingface.co/") else model_id_str

def has_diffusion_model(model_id, token):
    api = HfApi(token=token)
    return any([f.endswith("diffusion_pytorch_model.bin") for f in api.list_repo_files(repo_id=model_id)])

def get_my_model_names(token):
    
    try:
        author = whoami(token=token)
        model_infos = list_models(author=author["name"], use_auth_token=token)

        
        model_names = []
        for model_info in model_infos:
            model_id = model_info.modelId
            if has_diffusion_model(model_id, token):
                model_names.append(model_id)
        
#        if not model_names:
#            return [], Exception("No diffusion models found in your account.")

        return model_names, None
        
    except Exception as e:
        return [], e

def on_token_change(token):
    model_names, error = get_my_model_names(token)

    return gr.update(visible=not error), gr.update(choices=model_names), gr.update(value=error_str(error))

def on_load_model(user_model_id, other_model_id, token):

    if not user_model_id and not other_model_id:
        return None, None, None, None, gr.update(value=error_str("Please enter a model ID."))

    try:
        model_id = url_to_model_id(other_model_id) if other_model_id else user_model_id
        original_model_id = model_id

        if not has_diffusion_model(model_id, token):
            return None, None, None, None, gr.update(value=error_str("There are no diffusion weights in the model you selected."))

        user = whoami(token=token)
        model_id = user["name"] + "/" + model_id.split("/")[-1]
        title = " ".join([w.capitalize() for w in model_id.split("/")[-1].replace("-", " ").replace("_", " ").split(" ")])
        
        description = f"""Demo for <a href="https://huggingface.co/{original_model_id}">{title}</a> Stable Diffusion model.<br>
        Add the following tokens to your prompts for the model to work properly: <b>$prefix</b>."""

        return gr.update(visible=True), gr.update(value=model_id), gr.update(value=title), gr.update(value=description), None
    
    except Exception as e:
        return None, None, None, None, gr.update(value=error_str(e))

def create_and_push(space_type, other_model_name, radio_model_names, model_id, title, description, prefix, update, token):

    try:

        # 1. Create the new space
        api = HfApi(token=token)
        repo_url = api.create_repo(
            repo_id=model_id,
            exist_ok=update,
            repo_type="space",
            space_sdk="gradio",
        )

        # 2. Replace the name, title, and description in the template
        with open("template/app_simple.py" if space_type == "Simple" else "template/app_advanced.py", "r") as f:
            app = f.read()
        app = app.replace("$model_id", url_to_model_id(other_model_name) if other_model_name else radio_model_names)
        app = app.replace("$title", title)
        app = app.replace("$description", description)
        app = app.replace("$prefix", prefix)

        # 3. save the new app.py file
        with open("app.py", "w") as f:
            f.write(app)

        # 4. Upload the new app.py to the space
        api.upload_file(
            path_or_fileobj="app.py",
            path_in_repo="app.py",
            repo_id=model_id,
            token=token,
            repo_type="space",
        )

        # 5. Upload template/requirements.txt to the space
        if space_type == "Advanced":
            api.upload_file(
                path_or_fileobj="template/requirements.txt",
                path_in_repo="requirements.txt",
                repo_id=model_id,
                token=token,
                repo_type="space",
            )

        # 5. Delete the app.py file
        os.remove("app.py")

        return f"""Successfully created space at: <a href="{repo_url}" target="_blank">{repo_url}</a>"""

    except Exception as e:
        return error_str(e)


DESCRIPTION = """### Create a gradio space for your Diffusers🧨 model
                With this space, you can easily create a gradio demo for your Diffusers model and share it with the community.
            """

with gr.Blocks() as demo:

    gr.Markdown(DESCRIPTION)
    with gr.Row():

        with gr.Column(scale=11):
            with gr.Column():
                gr.Markdown("#### 1. Choose a model")
                input_token = gr.Textbox(
                    max_lines=1,
                    label="Enter your Hugging Face token",
                    placeholder="WRITE permission is required!",
                )
                gr.Markdown("You can get a token [here](https://huggingface.co/settings/tokens)")
                with gr.Group(visible=False) as group_model:
                    radio_model_names = gr.Radio(label="Your models:")
                    other_model_name = gr.Textbox(label="Other model:", placeholder="URL or model id, e.g. username/model_name")
                    btn_load = gr.Button(value="Load model")

        with gr.Column(scale=10):
            with gr.Column(visible=False) as group_create:
                gr.Markdown("#### 2. Enter details and create the space")
                name = gr.Textbox(label="Name", placeholder="e.g. diffusers-demo")
                title = gr.Textbox(label="Title", placeholder="e.g. Diffusers Demo")
                description = gr.Textbox(label="Description", placeholder="e.g. Demo for my awesome Diffusers model", lines=5)
                prefix = gr.Textbox(label="Prefix tokens", placeholder="Tokens that are required to be present in the prompt, e.g. `rick and morty style`")
                gr.Markdown("""#### Choose space type
                - **Simple** - Runs on GPU using Hugging Face inference API, but you cannot control image generation parameters.
                - **Advanced** - Runs on CPU by default, with the option to upgrade to GPU. You can control image generation parameters: guidance, number of steps, image size, etc. Also supports **image-to-image** generation.""")
                space_type =gr.Radio(label="Space type", choices=["Simple", "Advanced"], value="Simple")
                update = gr.Checkbox(label="Update the space if it already exists?")
                

                brn_create = gr.Button("Create the space")

    error_output = gr.Markdown(label="Output")


    input_token.change(
        fn=on_token_change,
        inputs=input_token,
        outputs=[group_model, radio_model_names, error_output],
        queue=False,
        scroll_to_output=True)

    btn_load.click(
        fn=on_load_model,
        inputs=[radio_model_names, other_model_name, input_token],
        outputs=[group_create, name, title, description, error_output],
        queue=False,
        scroll_to_output=True)

    brn_create.click(
        fn=create_and_push,
        inputs=[space_type, other_model_name, radio_model_names, name, title, description, prefix, update, input_token],
        outputs=[error_output],
        scroll_to_output=True
    )

    # gr.Markdown("""<img src="https://raw.githubusercontent.com/huggingface/diffusers/main/docs/source/imgs/diffusers_library.jpg" width="150"/>""")
    gr.HTML("""
    <div style="border-top: 1px solid #303030;">
      <br>
      <p>Space by: <a href="https://twitter.com/hahahahohohe"><img src="https://img.shields.io/twitter/follow/hahahahohohe?label=%40anzorq&style=social" alt="Twitter Follow"></a></p><br>
      <a href="https://www.buymeacoffee.com/anzorq" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 45px !important;width: 162px !important;" ></a><br><br>
      <p><img src="https://visitor-badge.glitch.me/badge?page_id=anzorq.sd-space-creator" alt="visitors"></p>
    </div>
    """)
    
demo.queue()
demo.launch(debug=True)