File size: 8,479 Bytes
2aeb649
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f212c91
2aeb649
 
 
 
 
f212c91
 
9c76a63
f212c91
2aeb649
 
f212c91
2aeb649
f212c91
2aeb649
f212c91
2aeb649
f212c91
2aeb649
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f212c91
2aeb649
 
 
 
 
 
f212c91
2aeb649
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b189c01
f212c91
094b5e7
b189c01
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2aeb649
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f212c91
2aeb649
 
 
 
 
 
 
 
f212c91
 
2aeb649
 
f212c91
2aeb649
a3db9b4
f212c91
2aeb649
 
d7d7222
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
import requests
import os
import gradio as gr
from huggingface_hub import HfApi
from slugify import slugify
import gradio as gr
import uuid
from typing import Optional

def get_json_data(url):
    api_url = f"https://civitai.com/api/v1/models/{url.split('/')[4]}"
    try:
        response = requests.get(api_url)
        response.raise_for_status()
        return response.json()
    except requests.exceptions.RequestException as e:
        print(f"Error fetching JSON data: {e}")
        return None

def check_nsfw(json_data):
    if json_data["nsfw"]:
        return False
    for model_version in json_data["modelVersions"]:
        for image in model_version["images"]:
            if image["nsfw"] != "None":
                return False
    return True

def extract_info(json_data):
    if json_data["type"] == "LORA":
        for model_version in json_data["modelVersions"]:
            if model_version["baseModel"] in ["SDXL 1.0", "SDXL 0.9"]:
                for file in model_version["files"]:
                    if file["primary"]:
                        info = {
                            "urls_to_download": [
                                {"url": file["downloadUrl"], "filename": file["name"], "type": "weightName"},
                                {"url": model_version["images"][0]["url"], "filename": os.path.basename(model_version["images"][0]["url"]), "type": "imageName"}
                            ],
                            "id": model_version["id"],
                            "modelId": model_version["modelId"],
                            "name": json_data["name"],
                            "description": json_data["description"],
                            "trainedWords": model_version["trainedWords"],
                            "creator": json_data["creator"]["username"]
                        }
                        return info
    return None

def download_files(info, folder="."):
    downloaded_files = {
        "imageName": [],
        "weightName": []
    }
    for item in info["urls_to_download"]:
        download_file(item["url"], item["filename"], folder)
        downloaded_files[item["type"]].append(item["filename"])
    return downloaded_files

def download_file(url, filename, folder="."):
    try:
        response = requests.get(url)
        response.raise_for_status()
        with open(f"{folder}/{filename}", 'wb') as f:
            f.write(response.content)
        print(f"{filename} downloaded.")
    except requests.exceptions.RequestException as e:
        print(f"Error downloading file: {e}")

def process_url(url, download_files=True, folder="."):
    json_data = get_json_data(url)
    if json_data:
        if check_nsfw(json_data):
            info = extract_info(json_data)
            if info:
                if(download_files):
                    downloaded_files = download_files(info, folder)
                else:
                    downloaded_files = []
                return info, downloaded_files
            else:
                raise gr.Error("Only SDXL LoRAs are supported for now")
        else:
            raise gr.Error("This model has content tagged as unsafe by CivitAI")
    else:
        raise gr.Error("Something went wrong in fetching CivitAI API")

def create_readme(info, downloaded_files, is_author=True, folder="."):
    readme_content = ""
    original_url = f"https://civitai.com/models/{info['id']}"
    non_author_disclaimer = f'This model was originally uploaded on [CivitAI]({original_url}), by [{info["creator"]}](https://civitai.com/user/{info["creator"]}/models). The information below was provided by the author on CivitAI:'
    content = f"""---
license: other
tags:
  - text-to-image
  - stable-diffusion
  - lora
  - diffusers
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: {info["trainedWords"][0]}
widget:
  - text: {info["trainedWords"][0]}
---

# {info["name"]}

{non_author_disclaimer if not is_author else ''}

![Image]({downloaded_files["imageName"][0]})

{info["description"]}
"""
    readme_content += content + "\n"

    with open(f"{folder}/README.md", "w") as file:
        file.write(readme_content)


def upload_civit_to_hf(profile: Optional[gr.OAuthProfile], url, progress=gr.Progress(track_tqdm=True)):
    if not profile.name:
        return gr.Error("Are you sure you are logged in?")
    
    folder = str(uuid.uuid4())
    os.makedirs(folder, exist_ok=False)
    info, downloaded_files = process_url(url, folder)
    create_readme(info, downloaded_files, folder)
    try:
        api = HfApi(token=hf_token)
        username = api.whoami()["name"]
        slug_name = slugify(info["name"])
        repo_id = f"{username}/{slug_name}"
        api.create_repo(repo_id=repo_id, private=True, exist_ok=True)
        api.upload_folder(
            folder_path=folder,
            repo_id=repo_id,
            repo_type="model"
        )
    except:
        raise gr.Error("something went wrong")
    return "Model uploaded!"

def check_civit_link(profile: Optional[gr.OAuthProfile], url):
    info, _ = process_url(url, download_files=False)
    url_creator = f"https://civitai.com/user/{info['creator']}/models" 
    # Open the target URL
    driver.get(url_creator)
    
    # Define the XPath expression
    xpath_expression = "//a[contains(@class, 'mantine-UnstyledButton-root') and contains(@class, 'mantine-ActionIcon-root') and contains(@class, 'mantine-ubxmi3') and starts-with(@href, 'https://huggingface.co/')]"
    
    # Find the element using the XPath expression
    try:
        element = WebDriverWait(driver, 10).until(
            EC.presence_of_element_located((By.XPATH, xpath_expression))
        )
        
        # Extract the href attribute
        href = element.get_attribute("href")
        
        # Extract the part after 'https://huggingface.co/'
        extracted_part = href.replace("https://huggingface.co/", "")
    
    except Exception as e:
        print("Element not found or error occurred:", e)
    
    finally:
        driver.quit()
    
    return extracted_part == profile.name
    
def swap_fill(profile: Optional[gr.OAuthProfile]):
    if profile is None:
        return gr.update(visible=True), gr.update(visible=False)
    else:
        return gr.update(visible=False), gr.update(visible=True)
    
css = '''
#login {
    font-size: 0px;
    width: 100% !important;
    margin: 0 auto;
}
#login:after {
    content: 'Authorize this app before uploading your model';
    visibility: visible;
    display: block;
    font-size: var(--button-large-text-size);
}
#login:disabled{
    font-size: var(--button-large-text-size);
}
#login:disabled:after{
    content:''
}
#disabled_upload{
    opacity: 0.5;
    pointer-events:none;
}
'''

with gr.Blocks(css=css) as demo:
    gr.LoginButton(elem_id="login")
    with gr.Column(elem_id="disabled_upload") as disabled_area:
        with gr.Row():
                        submit_source_civit = gr.Textbox(
                            label="CivitAI model URL",
                            info="URL of the CivitAI model, make sure it is a SDXL LoRA",
                        )
                        #is_author = gr.Checkbox(label="Are you the model author?", info="If you are not the author, a disclaimer with information about the author and the CivitAI source will be added", value=False)
        submit_button_civit = gr.Button("Upload model to Hugging Face and submit")
        output = gr.Textbox(label="Output progress")
    with gr.Column(visible=False) as enabled_area:
        with gr.Row():
                        submit_source_civit = gr.Textbox(
                            label="CivitAI model URL",
                            info="URL of the CivitAI model, make sure it is a SDXL LoRA",
                        )
                        #is_author = gr.Checkbox(label="Are you the model author?", info="If you are not the author, a disclaimer with information about the author and the CivitAI source will be added", value=False)
        instructions = gr.HTML("")
        submit_button_civit = gr.Button("Upload model to Hugging Face")
        output = gr.Textbox(label="Output progress")
   
    demo.load(fn=swap_fill, outputs=[disabled_area, enabled_area])
    submit_source_civit.change(fn=check_civit_link, inputs=[submit_source_civit], outputs=[instructions])
    submit_button_civit.click(fn=upload_civit_to_hf, inputs=[submit_source_civit], outputs=[output])
    
demo.queue()
demo.launch()