import gradio as gr
from convert_url_to_diffusers_multi_gr import convert_url_to_diffusers_repo, get_dtypes, FLUX_BASE_REPOS, SD35_BASE_REPOS
from presets import (DEFAULT_DTYPE, schedulers, clips, t5s, sdxl_vaes, sdxl_loras, sdxl_preset_dict, sdxl_set_presets,
                     sd15_vaes, sd15_loras, sd15_preset_dict, sd15_set_presets, flux_vaes, flux_loras, flux_preset_dict, flux_set_presets,
                     sd35_vaes, sd35_loras, sd35_preset_dict, sd35_set_presets)
import os


HF_USER = os.getenv("HF_USER", "")
HF_REPO = os.getenv("HF_REPO", "")
HF_URL = os.getenv("HF_URL", "")
HF_OW = os.getenv("HF_OW", False)
HF_PR = os.getenv("HF_PR", False)

css = """
.title { font-size: 3em; align-items: center; text-align: center; }
.info { align-items: center; text-align: center; }
.block.result { margin: 1em 0; padding: 1em; box-shadow: 0 0 3px 3px #664422, 0 0 3px 2px #664422 inset; border-radius: 6px; background: #665544; }
"""

with gr.Blocks(theme="theNeofr/Syne", fill_width=True, css=css, delete_cache=(60, 3600)) as demo:
    gr.Markdown("# Download SDXL / SD 1.5 / SD 3.5 / FLUX.1 safetensors and convert to HF🤗 Diffusers format and create your repo", elem_classes="title")
    gr.Markdown(f"""
### ⚠️IMPORTANT NOTICE⚠️<br>
It's dangerous to expose your access token or key to others.
If you do use it, I recommend that you duplicate this space on your own HF account in advance.
Keys and tokens could be set to **Secrets** (`HF_TOKEN`, `CIVITAI_API_KEY`) if it's placed in your own space.
It saves you the trouble of typing them in.<br>
It barely works in the CPU space, but larger files can be converted if duplicated on the more powerful **Zero GPU** space.
In particular, conversion of FLUX.1 or SD 3.5 is almost impossible in CPU space.
### The steps are the following:
1. Paste a write-access token from [hf.co/settings/tokens](https://huggingface.co/settings/tokens).
1. Input a model download url of the Hugging Face or Civitai or other sites.
1. If you want to download a model from Civitai, paste a Civitai API Key.
1. Input your HF user ID. e.g. 'yourid'.
1. Input your new repo name. If empty, auto-complete. e.g. 'newrepo'.
1. Set the parameters. If not sure, just use the defaults.
1. Click "Submit".
1. Patiently wait until the output changes. It takes approximately 2 to 3 minutes (on SDXL models downloading from HF).
            """)
    with gr.Column():
        dl_url = gr.Textbox(label="URL to download", placeholder="https://huggingface.co/bluepen5805/blue_pencil-XL/blob/main/blue_pencil-XL-v7.0.0.safetensors",
                            value=HF_URL, max_lines=1)
        with gr.Group():
            with gr.Row():
                hf_user = gr.Textbox(label="Your HF user ID", placeholder="username", value=HF_USER, max_lines=1)
                hf_repo = gr.Textbox(label="New repo name", placeholder="reponame", info="If empty, auto-complete", value=HF_REPO, max_lines=1)
            with gr.Row(equal_height=True):
                with gr.Column():
                    hf_token = gr.Textbox(label="Your HF write token", placeholder="hf_...", value="", max_lines=1)
                    gr.Markdown("Your token is available at [hf.co/settings/tokens](https://huggingface.co/settings/tokens).", elem_classes="info")
                with gr.Column():
                    civitai_key = gr.Textbox(label="Your Civitai API Key (Optional)", info="If you download model from Civitai...", placeholder="", value="", max_lines=1)
                    gr.Markdown("Your Civitai API key is available at [https://civitai.com/user/account](https://civitai.com/user/account).", elem_classes="info")
            with gr.Row():
                is_upload_sf = gr.Checkbox(label="Upload single safetensors file into new repo", value=False)
                is_private = gr.Checkbox(label="Create private repo", value=True)
                gated = gr.Radio(label="Create gated repo", info="Gated repo must be public", choices=["auto", "manual", "False"], value="False")
            with gr.Row():
                is_overwrite = gr.Checkbox(label="Overwrite repo", value=HF_OW)
                is_pr = gr.Checkbox(label="Create PR", value=HF_PR)
        with gr.Tab("SDXL"):
            with gr.Group():
                sdxl_presets = gr.Radio(label="Presets", choices=list(sdxl_preset_dict.keys()), value=list(sdxl_preset_dict.keys())[0])
                sdxl_mtype = gr.Textbox(value="SDXL", visible=False)
                sdxl_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value=DEFAULT_DTYPE)
                with gr.Accordion("Advanced settings", open=False):
                    with gr.Row():
                        sdxl_vae = gr.Dropdown(label="VAE", choices=sdxl_vaes, value="", allow_custom_value=True)
                        sdxl_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=schedulers, value="Euler a")
                        sdxl_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
                    with gr.Column():
                        with gr.Row():
                            sdxl_lora1 = gr.Dropdown(label="LoRA1", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sdxl_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
                        with gr.Row():
                            sdxl_lora2 = gr.Dropdown(label="LoRA2", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sdxl_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
                        with gr.Row():
                            sdxl_lora3 = gr.Dropdown(label="LoRA3", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sdxl_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
                        with gr.Row():
                            sdxl_lora4 = gr.Dropdown(label="LoRA4", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sdxl_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
                        with gr.Row():
                            sdxl_lora5 = gr.Dropdown(label="LoRA5", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sdxl_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
            sdxl_run_button = gr.Button(value="Submit", variant="primary")
        with gr.Tab("SD 1.5"):
            with gr.Group():
                sd15_presets = gr.Radio(label="Presets", choices=list(sd15_preset_dict.keys()), value=list(sd15_preset_dict.keys())[0])
                sd15_mtype = gr.Textbox(value="SD 1.5", visible=False)
                sd15_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value=DEFAULT_DTYPE)
                with gr.Row():
                    sd15_ema = gr.Checkbox(label="Extract EMA", value=True, visible=True)
                    sd15_isize = gr.Radio(label="Image size", choices=["768", "512"], value="768")
                    sd15_sc = gr.Checkbox(label="Safety checker", value=False)
                with gr.Accordion("Advanced settings", open=False):
                    with gr.Row():
                        sd15_vae = gr.Dropdown(label="VAE", choices=sd15_vaes, value="", allow_custom_value=True)
                        sd15_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=schedulers, value="Euler")
                        sd15_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
                    with gr.Column():
                        with gr.Row():
                            sd15_lora1 = gr.Dropdown(label="LoRA1", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd15_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
                        with gr.Row():
                            sd15_lora2 = gr.Dropdown(label="LoRA2", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd15_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
                        with gr.Row():
                            sd15_lora3 = gr.Dropdown(label="LoRA3", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd15_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
                        with gr.Row():
                            sd15_lora4 = gr.Dropdown(label="LoRA4", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd15_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
                        with gr.Row():
                            sd15_lora5 = gr.Dropdown(label="LoRA5", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd15_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
            sd15_run_button = gr.Button(value="Submit", variant="primary")
        with gr.Tab("FLUX.1"):
            with gr.Group():
                flux_presets = gr.Radio(label="Presets", choices=list(flux_preset_dict.keys()), value=list(flux_preset_dict.keys())[0])
                flux_mtype = gr.Textbox(value="FLUX", visible=False)
                flux_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value="bf16")
                flux_base_repo = gr.Dropdown(label="Base repo ID", choices=FLUX_BASE_REPOS, value=FLUX_BASE_REPOS[0], allow_custom_value=True, visible=True)
                with gr.Accordion("Advanced settings", open=False):
                    with gr.Row():
                        flux_vae = gr.Dropdown(label="VAE", choices=flux_vaes, value="", allow_custom_value=True)
                        flux_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=[""], value="", visible=False)
                    with gr.Row():
                        flux_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
                        flux_t5 = gr.Dropdown(label="T5", choices=t5s, value="", allow_custom_value=True)
                    with gr.Column():
                        with gr.Row():
                            flux_lora1 = gr.Dropdown(label="LoRA1", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            flux_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
                        with gr.Row():
                            flux_lora2 = gr.Dropdown(label="LoRA2", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            flux_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
                        with gr.Row():
                            flux_lora3 = gr.Dropdown(label="LoRA3", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            flux_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
                        with gr.Row():
                            flux_lora4 = gr.Dropdown(label="LoRA4", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            flux_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
                        with gr.Row():
                            flux_lora5 = gr.Dropdown(label="LoRA5", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            flux_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
            flux_run_button = gr.Button(value="Submit", variant="primary")
        with gr.Tab("SD 3.5"):
            with gr.Group():
                sd35_presets = gr.Radio(label="Presets", choices=list(sd35_preset_dict.keys()), value=list(sd35_preset_dict.keys())[0])
                sd35_mtype = gr.Textbox(value="SD 3.5", visible=False)
                sd35_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value="bf16")
                sd35_base_repo = gr.Dropdown(label="Base repo ID", choices=SD35_BASE_REPOS, value=SD35_BASE_REPOS[0], allow_custom_value=True, visible=True)
                with gr.Accordion("Advanced settings", open=False):
                    with gr.Row():
                        sd35_vae = gr.Dropdown(label="VAE", choices=sd35_vaes, value="", allow_custom_value=True)
                        sd35_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=[""], value="", visible=False)
                    with gr.Row():
                        sd35_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
                        sd35_t5 = gr.Dropdown(label="T5", choices=t5s, value="", allow_custom_value=True)
                    with gr.Column():
                        with gr.Row():
                            sd35_lora1 = gr.Dropdown(label="LoRA1", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd35_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
                        with gr.Row():
                            sd35_lora2 = gr.Dropdown(label="LoRA2", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd35_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
                        with gr.Row():
                            sd35_lora3 = gr.Dropdown(label="LoRA3", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd35_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
                        with gr.Row():
                            sd35_lora4 = gr.Dropdown(label="LoRA4", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd35_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
                        with gr.Row():
                            sd35_lora5 = gr.Dropdown(label="LoRA5", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2)
                            sd35_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
            sd35_run_button = gr.Button(value="Submit", variant="primary")
        adv_args = gr.Textbox(label="Advanced arguments", value="", visible=False)
        with gr.Group():
            repo_urls = gr.CheckboxGroup(visible=False, choices=[], value=[])
            output_md = gr.Markdown(label="Output", value="<br><br>", elem_classes="result")
            clear_button = gr.Button(value="Clear Output", variant="secondary")
        gr.DuplicateButton(value="Duplicate Space")

    gr.Markdown("This webui was redesigned with ❤ by [theNeofr](https://huggingface.co/theNeofr)")
    gr.on(
        triggers=[sdxl_run_button.click],
        fn=convert_url_to_diffusers_repo,
        inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls,
                sdxl_dtype, sdxl_vae, sdxl_clip, flux_t5, sdxl_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, sdxl_mtype,
                sdxl_lora1, sdxl_lora1s, sdxl_lora2, sdxl_lora2s, sdxl_lora3, sdxl_lora3s, sdxl_lora4, sdxl_lora4s, sdxl_lora5, sdxl_lora5s, adv_args],
        outputs=[repo_urls, output_md],
    )
    sdxl_presets.change(
        fn=sdxl_set_presets,
        inputs=[sdxl_presets],
        outputs=[sdxl_dtype, sdxl_vae, sdxl_scheduler, sdxl_lora1, sdxl_lora1s, sdxl_lora2, sdxl_lora2s, sdxl_lora3, sdxl_lora3s,
                 sdxl_lora4, sdxl_lora4s, sdxl_lora5, sdxl_lora5s],
        queue=False,
    )
    gr.on(
        triggers=[sd15_run_button.click],
        fn=convert_url_to_diffusers_repo,
        inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls,
                sd15_dtype, sd15_vae, sd15_clip, flux_t5, sd15_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, sd15_mtype,
                sd15_lora1, sd15_lora1s, sd15_lora2, sd15_lora2s, sd15_lora3, sd15_lora3s, sd15_lora4, sd15_lora4s, sd15_lora5, sd15_lora5s, adv_args],
        outputs=[repo_urls, output_md],
    )
    sd15_presets.change(
        fn=sd15_set_presets,
        inputs=[sd15_presets],
        outputs=[sd15_dtype, sd15_vae, sd15_scheduler, sd15_lora1, sd15_lora1s, sd15_lora2, sd15_lora2s, sd15_lora3, sd15_lora3s,
                 sd15_lora4, sd15_lora4s, sd15_lora5, sd15_lora5s, sd15_ema],
        queue=False,
    )
    gr.on(
        triggers=[flux_run_button.click],
        fn=convert_url_to_diffusers_repo,
        inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls,
                flux_dtype, flux_vae, flux_clip, flux_t5, flux_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, flux_mtype,
                flux_lora1, flux_lora1s, flux_lora2, flux_lora2s, flux_lora3, flux_lora3s, flux_lora4, flux_lora4s, flux_lora5, flux_lora5s, adv_args],
        outputs=[repo_urls, output_md],
    )
    flux_presets.change(
        fn=flux_set_presets,
        inputs=[flux_presets],
        outputs=[flux_dtype, flux_vae, flux_scheduler, flux_lora1, flux_lora1s, flux_lora2, flux_lora2s, flux_lora3, flux_lora3s,
                 flux_lora4, flux_lora4s, flux_lora5, flux_lora5s, flux_base_repo],
        queue=False,
    )
    gr.on(
        triggers=[sd35_run_button.click],
        fn=convert_url_to_diffusers_repo,
        inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls,
                sd35_dtype, sd35_vae, sd35_clip, sd35_t5, sd35_scheduler, sd15_ema, sd15_isize, sd15_sc, sd35_base_repo, sd35_mtype,
                sd35_lora1, sd35_lora1s, sd35_lora2, sd35_lora2s, sd35_lora3, sd35_lora3s, sd35_lora4, sd35_lora4s, sd35_lora5, sd35_lora5s, adv_args],
        outputs=[repo_urls, output_md],
    )
    sd35_presets.change(
        fn=sd35_set_presets,
        inputs=[sd35_presets],
        outputs=[sd35_dtype, sd35_vae, sd35_scheduler, sd35_lora1, sd35_lora1s, sd35_lora2, sd35_lora2s, sd35_lora3, sd35_lora3s,
                 sd35_lora4, sd35_lora4s, sd35_lora5, sd35_lora5s, sd35_base_repo],
        queue=False,
    )
    clear_button.click(lambda: ([], "<br><br>"), None, [repo_urls, output_md], queue=False, show_api=False)

demo.queue()
demo.launch(ssr_mode=False)