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Upload extensions using SD-Hub extension
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import requests
import json
import gradio as gr
import urllib.request
import urllib.parse
import urllib.error
import os
import re
import datetime
import platform
from PIL import Image
from io import BytesIO
from collections import defaultdict
from datetime import datetime, timezone
from modules.images import read_info_from_image
from modules.shared import cmd_opts, opts
from modules.paths import models_path, extensions_dir, data_path
from html import escape
from scripts.civitai_global import print, debug_print
import scripts.civitai_global as gl
import scripts.civitai_download as _download
gl.init()
def contenttype_folder(content_type, desc=None, fromCheck=False, custom_folder=None):
use_LORA = getattr(opts, "use_LORA", False)
folder = None
if desc:
desc = desc.upper()
else:
desc = "PLACEHOLDER"
if custom_folder:
main_models = custom_folder
main_data = custom_folder
else:
main_models = models_path
main_data = data_path
if content_type == "modelFolder":
folder = os.path.join(main_models)
if content_type == "Checkpoint":
if cmd_opts.ckpt_dir and not custom_folder:
folder = cmd_opts.ckpt_dir
else:
folder = os.path.join(main_models,"Stable-diffusion")
elif content_type == "Hypernetwork":
if cmd_opts.hypernetwork_dir and not custom_folder:
folder = cmd_opts.hypernetwork_dir
else:
folder = os.path.join(main_models, "hypernetworks")
elif content_type == "TextualInversion":
if cmd_opts.embeddings_dir and not custom_folder:
folder = cmd_opts.embeddings_dir
else:
folder = os.path.join(main_data, "embeddings")
elif content_type == "AestheticGradient":
if not custom_folder:
folder = os.path.join(extensions_dir, "stable-diffusion-webui-aesthetic-gradients", "aesthetic_embeddings")
else:
folder = os.path.join(custom_folder, "aesthetic_embeddings")
elif content_type == "LORA":
if cmd_opts.lora_dir and not custom_folder:
folder = cmd_opts.lora_dir
else:
folder = folder = os.path.join(main_models, "Lora")
elif content_type == "LoCon":
folder = os.path.join(main_models, "LyCORIS")
if use_LORA and not fromCheck:
if cmd_opts.lora_dir and not custom_folder:
folder = cmd_opts.lora_dir
else:
folder = folder = os.path.join(main_models, "Lora")
elif content_type == "DoRA":
if cmd_opts.lora_dir and not custom_folder:
folder = cmd_opts.lora_dir
else:
folder = folder = os.path.join(main_models, "Lora")
elif content_type == "VAE":
if cmd_opts.vae_dir and not custom_folder:
folder = cmd_opts.vae_dir
else:
folder = os.path.join(main_models, "VAE")
elif content_type == "Controlnet":
if hasattr(cmd_opts, 'controlnet_dir') and cmd_opts.controlnet_dir and not custom_folder:
folder = cmd_opts.controlnet_dir
else:
folder = os.path.join(main_models, "ControlNet")
elif content_type == "Poses":
folder = os.path.join(main_models, "Poses")
elif content_type == "Upscaler":
if "SWINIR" in desc:
if cmd_opts.swinir_models_path and not custom_folder:
folder = cmd_opts.swinir_models_path
else:
folder = os.path.join(main_models, "SwinIR")
elif "REALESRGAN" in desc:
if cmd_opts.realesrgan_models_path and not custom_folder:
folder = cmd_opts.realesrgan_models_path
else:
folder = os.path.join(main_models, "RealESRGAN")
elif "GFPGAN" in desc:
if cmd_opts.gfpgan_models_path and not custom_folder:
folder = cmd_opts.gfpgan_models_path
else:
folder = os.path.join(main_models, "GFPGAN")
elif "BSRGAN" in desc:
if cmd_opts.bsrgan_models_path and not custom_folder:
folder = cmd_opts.bsrgan_models_path
else:
folder = os.path.join(main_models, "BSRGAN")
else:
if cmd_opts.esrgan_models_path and not custom_folder:
folder = cmd_opts.esrgan_models_path
else:
folder = os.path.join(main_models, "ESRGAN")
elif content_type == "MotionModule":
folder = os.path.join(extensions_dir, "sd-webui-animatediff", "model")
elif content_type == "Workflows":
folder = os.path.join(main_models, "Workflows")
elif content_type == "Other":
if "ADETAILER" in desc:
folder = os.path.join(main_models, "adetailer")
else:
folder = os.path.join(main_models, "Other")
elif content_type == "Wildcards":
folder = os.path.join(extensions_dir, "UnivAICharGen", "wildcards")
if not os.path.exists(folder):
folder = os.path.join(extensions_dir, "sd-dynamic-prompts", "wildcards")
return folder
def model_list_html(json_data):
video_playback = getattr(opts, "video_playback", True)
playback = ""
if video_playback: playback = "autoplay loop"
hide_early_access = getattr(opts, "hide_early_access", True)
filtered_items = []
current_time = datetime.now(timezone.utc)
for item in json_data['items']:
versions_to_keep = []
for version in item['modelVersions']:
if not version['files']:
continue
if hide_early_access:
early_access_deadline_str = version.get('earlyAccessDeadline')
if early_access_deadline_str:
early_access_deadline = datetime.strptime(early_access_deadline_str, "%Y-%m-%dT%H:%M:%S.%fZ").replace(tzinfo=timezone.utc)
if current_time <= early_access_deadline:
continue
versions_to_keep.append(version)
if versions_to_keep:
item['modelVersions'] = versions_to_keep
filtered_items.append(item)
json_data['items'] = filtered_items
HTML = '<div class="column civmodellist">'
sorted_models = {}
existing_files = set()
existing_files_sha256 = set()
model_folders = set()
for item in json_data['items']:
model_folder = os.path.join(contenttype_folder(item['type'], item['description']))
model_folders.add(model_folder)
for folder in model_folders:
for root, dirs, files in os.walk(folder, followlinks=True):
for file in files:
existing_files.add(file)
if file.endswith('.json'):
json_path = os.path.join(root, file)
with open(json_path, 'r', encoding="utf-8") as f:
try:
json_file = json.load(f)
if isinstance(json_file, dict):
sha256 = json_file.get('sha256')
if sha256:
existing_files_sha256.add(sha256.upper())
else:
print(f"Invalid JSON data in {json_path}. Expected a dictionary.")
except Exception as e:
print(f"Error decoding JSON in {json_path}: {e}")
for item in json_data['items']:
model_id = item.get('id')
model_name = item.get('name')
nsfw = ""
installstatus = ""
baseModel = ""
try:
if 'baseModel' in item['modelVersions'][0]:
baseModel = item['modelVersions'][0]['baseModel']
except:
baseModel = "Not Found"
try:
if 'publishedAt' in item['modelVersions'][0]:
date = item['modelVersions'][0]['publishedAt'].split('T')[0]
except:
date = "Not Found"
if item.get("nsfw"):
nsfw = "civcardnsfw"
if gl.sortNewest:
if date not in sorted_models:
sorted_models[date] = []
if any(item['modelVersions']):
if len(item['modelVersions'][0]['images']) > 0:
media_type = item["modelVersions"][0]["images"][0]["type"]
image = item["modelVersions"][0]["images"][0]["url"]
if media_type == "video":
image = image.replace("width=", "transcode=true,width=")
imgtag = f'<video class="video-bg" {playback} muted playsinline><source src="{image}" type="video/mp4"></video>'
else:
imgtag = f'<img src="{image}"></img>'
else:
imgtag = f'<img src="./file=html/card-no-preview.png"></img>'
installstatus = None
for version in reversed(item['modelVersions']):
for file in version.get('files', []):
file_name = file['name']
file_sha256 = file.get('hashes', {}).get('SHA256', "").upper()
name_match = file_name in existing_files
sha256_match = file_sha256 in existing_files_sha256
if name_match or sha256_match:
if version == item['modelVersions'][0]:
installstatus = "civmodelcardinstalled"
else:
installstatus = "civmodelcardoutdated"
model_name_js = model_name.replace("'", "\\'")
model_string = escape(f"{model_name_js} ({model_id})")
model_card = f'<figure class="civmodelcard {nsfw} {installstatus}" base-model="{baseModel}" date="{date}" onclick="select_model(\'{model_string}\', event)">'
if installstatus != "civmodelcardinstalled":
model_card += f'<input type="checkbox" class="model-checkbox" id="checkbox-{model_string}" onchange="multi_model_select(\'{model_string}\', \'{item["type"]}\', this.checked)" style="opacity: 0; position: absolute; top: 10px; right: 10px;">' \
+ f'<label for="checkbox-{model_string}" class="custom-checkbox"></label>'
if len(item["name"]) > 40:
display_name = item["name"][:40] + '...'
else:
display_name = item["name"]
display_name = escape(display_name)
full_name = escape(item['name'])
model_card += imgtag \
+ f'<figcaption title="{full_name}">{display_name}</figcaption></figure>'
if gl.sortNewest:
sorted_models[date].append(model_card)
else:
HTML += model_card
if gl.sortNewest:
for date, cards in sorted(sorted_models.items(), reverse=True):
HTML += f'<div class="date-section"><h4>{date}</h4><hr style="margin-bottom: 5px; margin-top: 5px;">'
HTML += '<div class="card-row">'
for card in cards:
HTML += card
HTML += '</div></div>'
HTML += '</div>'
return HTML
def create_api_url(content_type=None, sort_type=None, period_type=None, use_search_term=None, base_filter=None, only_liked=None, tile_count=None, search_term=None, nsfw=None, isNext=None):
base_url = "https://civitai.com/api/v1/models"
version_url = "https://civitai.com/api/v1/model-versions"
if isNext is not None:
api_url = gl.json_data['metadata']['nextPage' if isNext else 'prevPage']
debug_print(api_url)
return api_url
params = {'limit': tile_count, 'sort': sort_type, 'period': period_type.replace(" ", "") if period_type else None}
if content_type:
params["types"] = content_type
if use_search_term != "None" and search_term:
search_term = search_term.replace("\\", "\\\\").lower()
if "civitai.com" in search_term:
model_number = re.search(r'models/(\d+)', search_term).group(1)
params = {'ids': model_number}
else:
key_map = {"User name": "username", "Tag": "tag"}
search_key = key_map.get(use_search_term, "query")
params[search_key] = search_term
if base_filter:
params["baseModels"] = base_filter
if only_liked:
params["favorites"] = "true"
params["nsfw"] = "true" if nsfw else "false"
query_parts = []
for key, value in params.items():
if isinstance(value, list):
for item in value:
query_parts.append((key, item))
else:
query_parts.append((key, value))
query_string = urllib.parse.urlencode(query_parts, doseq=True, quote_via=urllib.parse.quote)
api_url = f"{base_url}?{query_string}"
debug_print(api_url)
return api_url
def convert_LORA_LoCon(content_type):
use_LORA = getattr(opts, "use_LORA", False)
if content_type:
if use_LORA and 'LORA, LoCon, DoRA' in content_type:
content_type.remove('LORA, LoCon, DoRA')
if 'LORA' not in content_type:
content_type.append('LORA')
if 'LoCon' not in content_type:
content_type.append('LoCon')
if 'DoRA' not in content_type:
content_type.append('DoRA')
return content_type
def initial_model_page(content_type=None, sort_type=None, period_type=None, use_search_term=None, search_term=None, current_page=None, base_filter=None, only_liked=None, nsfw=None, tile_count=None, from_update_tab=False):
content_type = convert_LORA_LoCon(content_type)
current_inputs = (content_type, sort_type, period_type, use_search_term, search_term, tile_count, base_filter, nsfw)
if current_inputs != gl.previous_inputs and gl.previous_inputs != None or not current_page:
current_page = 1
gl.previous_inputs = current_inputs
if not from_update_tab:
gl.from_update_tab = False
if current_page == 1:
api_url = create_api_url(content_type, sort_type, period_type, use_search_term, base_filter, only_liked, tile_count, search_term, nsfw)
gl.url_list = {1 : api_url}
else:
api_url = gl.url_list.get(current_page)
else:
api_url = gl.url_list.get(current_page)
gl.from_update_tab = True
gl.json_data = request_civit_api(api_url)
max_page = 1
model_list = []
hasPrev, hasNext = False, False
if not isinstance(gl.json_data, dict):
HTML = api_error_msg(gl.json_data)
else:
gl.json_data = insert_metadata(1)
metadata = gl.json_data['metadata']
hasNext = 'nextPage' in metadata
hasPrev = 'prevPage' in metadata
for item in gl.json_data['items']:
if len(item['modelVersions']) > 0:
model_list.append(f"{item['name']} ({item['id']})")
max_page = max(gl.url_list.keys())
HTML = model_list_html(gl.json_data)
return (
gr.Dropdown.update(choices=model_list, value="", interactive=True), # Model List
gr.Dropdown.update(choices=[], value=""), # Version List
gr.HTML.update(value=HTML), # HTML Tiles
gr.Button.update(interactive=hasPrev), # Prev Page Button
gr.Button.update(interactive=hasNext), # Next Page Button
gr.Slider.update(value=current_page, maximum=max_page), # Page Slider
gr.Button.update(interactive=False), # Save Tags
gr.Button.update(interactive=False), # Save Images
gr.Button.update(interactive=False, visible=False if gl.isDownloading else True), # Download Button
gr.Button.update(interactive=False, visible=False), # Delete Button
gr.Textbox.update(interactive=False, value=None, visible=True), # Install Path
gr.Dropdown.update(choices=[], value="", interactive=False), # Sub Folder List
gr.Dropdown.update(choices=[], value="", interactive=False), # File List
gr.HTML.update(value='<div style="min-height: 0px;"></div>'), # Preview HTML
gr.Textbox.update(value=None), # Trained Tags
gr.Textbox.update(value=None), # Base Model
gr.Textbox.update(value=None) # Model Filename
)
def prev_model_page(content_type, sort_type, period_type, use_search_term, search_term, current_page, base_filter, only_liked, nsfw, tile_count):
return next_model_page(content_type, sort_type, period_type, use_search_term, search_term, current_page, base_filter, only_liked, nsfw, tile_count, isNext=False)
def next_model_page(content_type, sort_type, period_type, use_search_term, search_term, current_page, base_filter, only_liked, nsfw, tile_count, isNext=True):
content_type = convert_LORA_LoCon(content_type)
current_inputs = (content_type, sort_type, period_type, use_search_term, search_term, tile_count, base_filter, nsfw)
if current_inputs != gl.previous_inputs and gl.previous_inputs != None:
return initial_model_page(content_type, sort_type, period_type, use_search_term, search_term, current_page, base_filter, only_liked, nsfw, tile_count)
api_url = create_api_url(isNext=isNext)
gl.json_data = request_civit_api(api_url)
next_page = current_page
model_list = []
max_page = 1
hasPrev, hasNext = False, False
if not isinstance(gl.json_data, dict):
HTML = api_error_msg(gl.json_data)
else:
next_page = current_page + 1 if isNext else current_page - 1
gl.json_data = insert_metadata(next_page, api_url)
metadata = gl.json_data['metadata']
hasNext = 'nextPage' in metadata
hasPrev = 'prevPage' in metadata
for item in gl.json_data['items']:
if len(item['modelVersions']) > 0:
model_list.append(f"{item['name']} ({item['id']})")
max_page = max(gl.url_list.keys())
HTML = model_list_html(gl.json_data)
return (
gr.Dropdown.update(choices=model_list, value="", interactive=True), # Model List
gr.Dropdown.update(choices=[], value=""), # Version List
gr.HTML.update(value=HTML), # HTML Tiles
gr.Button.update(interactive=hasPrev), # Prev Page Button
gr.Button.update(interactive=hasNext), # Next Page Button
gr.Slider.update(value=next_page, maximum=max_page), # Current Page
gr.Button.update(interactive=False), # Save Tags
gr.Button.update(interactive=False), # Save Images
gr.Button.update(interactive=False, visible=False if gl.isDownloading else True), # Download Button
gr.Button.update(interactive=False, visible=False), # Delete Button
gr.Textbox.update(interactive=False, value=None), # Install Path
gr.Dropdown.update(choices=[], value="", interactive=False), # Sub Folder List
gr.Dropdown.update(choices=[], value="", interactive=False), # File List
gr.HTML.update(value='<div style="min-height: 0px;"></div>'), # Preview HTML
gr.Textbox.update(value=None), # Trained Tags
gr.Textbox.update(value=None), # Base Model
gr.Textbox.update(value=None) # Model Filename
)
def insert_metadata(page_nr, api_url=None):
metadata = gl.json_data['metadata']
if not metadata.get('prevPage', None) and page_nr > 1:
metadata['prevPage'] = gl.url_list.get((page_nr - 1))
if gl.from_update_tab:
if gl.url_list.get((page_nr + 1), None):
metadata['nextPage'] = gl.url_list.get((page_nr + 1))
elif page_nr not in gl.url_list:
gl.url_list[page_nr] = api_url
return gl.json_data
def update_model_versions(model_id, json_input=None):
if json_input:
api_json = json_input
else:
api_json = gl.json_data
for item in api_json['items']:
if int(item['id']) == int(model_id):
content_type = item['type']
desc = item.get('description', "None")
versions_dict = defaultdict(list)
installed_versions = set()
model_folder = os.path.join(contenttype_folder(content_type, desc))
gl.main_folder = model_folder
versions = item['modelVersions']
version_files = set()
for version in versions:
versions_dict[version['name']].append(item["name"])
for version_file in version['files']:
file_sha256 = version_file.get('hashes', {}).get('SHA256', "").upper()
version_filename = version_file['name']
version_files.add((version['name'], version_filename, file_sha256))
for root, _, files in os.walk(model_folder, followlinks=True):
for file in files:
if file.endswith('.json'):
try:
json_path = os.path.join(root, file)
with open(json_path, 'r', encoding="utf-8") as f:
json_data = json.load(f)
if isinstance(json_data, dict):
if 'sha256' in json_data and json_data['sha256']:
sha256 = json_data.get('sha256', "").upper()
for version_name, _, file_sha256 in version_files:
if sha256 == file_sha256:
installed_versions.add(version_name)
break
except Exception as e:
print(f"failed to read: \"{file}\": {e}")
for version_name, version_filename, _ in version_files:
if file == version_filename:
installed_versions.add(version_name)
break
version_names = list(versions_dict.keys())
display_version_names = [f"{v} [Installed]" if v in installed_versions else v for v in version_names]
default_installed = next((f"{v} [Installed]" for v in installed_versions), None)
default_value = default_installed or next(iter(version_names), None)
return gr.Dropdown.update(choices=display_version_names, value=default_value, interactive=True) # Version List
return gr.Dropdown.update(choices=[], value=None, interactive=False) # Version List
def cleaned_name(file_name):
if platform.system() == "Windows":
illegal_chars_pattern = r'[\\/:*?"<>|]'
else:
illegal_chars_pattern = r'/'
name, extension = os.path.splitext(file_name)
clean_name = re.sub(illegal_chars_pattern, '', name)
return f"{clean_name}{extension}"
def fetch_and_process_image(image_url):
proxies, ssl = get_proxies()
try:
parsed_url = urllib.parse.urlparse(image_url)
if parsed_url.scheme and parsed_url.netloc:
response = requests.get(image_url, proxies=proxies, verify=ssl)
if response.status_code == 200:
image = Image.open(BytesIO(response.content))
geninfo, _ = read_info_from_image(image)
return geninfo
else:
image = Image.open(image_url)
geninfo, _ = read_info_from_image(image)
return geninfo
except:
return None
def extract_model_info(input_string):
last_open_parenthesis = input_string.rfind("(")
last_close_parenthesis = input_string.rfind(")")
name = input_string[:last_open_parenthesis].strip()
id_number = input_string[last_open_parenthesis + 1:last_close_parenthesis]
return name, int(id_number)
def update_model_info(model_string=None, model_version=None, only_html=False, input_id=None, json_input=None, from_preview=False):
video_playback = getattr(opts, "video_playback", True)
meta_btn = getattr(opts, "individual_meta_btn", True)
playback = ""
if video_playback: playback = "autoplay loop"
if json_input:
api_data = json_input
else:
api_data = gl.json_data
BtnDownInt = True
BtnDel = False
BtnImage = False
model_id = None
if not input_id:
_, model_id = extract_model_info(model_string)
else:
model_id = input_id
if model_version and "[Installed]" in model_version:
model_version = model_version.replace(" [Installed]", "")
if model_id:
output_html = ""
output_training = ""
output_basemodel = ""
img_html = ""
dl_dict = {}
is_LORA = False
file_list = []
file_dict = []
default_file = None
model_filename = None
sha256_value = None
for item in api_data['items']:
if int(item['id']) == int(model_id):
content_type = item['type']
if content_type == "LORA":
is_LORA = True
desc = item['description']
model_name = item['name']
model_folder = os.path.join(contenttype_folder(content_type, desc))
model_uploader = None
uploader_avatar = None
creator = item.get('creator', None)
if creator:
model_uploader = creator.get('username', None)
uploader_avatar = creator.get('image', None)
if not model_uploader:
model_uploader = 'User not found'
uploader_avatar = 'https://rawcdn.githack.com/gist/BlafKing/8d3f7a19e3f72cfddab46ae835037ee6/raw/296e81afbdd268200278beef478f3018b15936de/profile_placeholder.svg'
uploader_avatar = f'<div class="avatar"><img src={uploader_avatar}></div>'
tags = item.get('tags', "")
model_desc = item.get('description', "")
if model_desc:
model_desc = model_desc.replace('<img', '<img style="max-width: -webkit-fill-available;"')
model_desc = model_desc.replace('<code>', '<code style="text-wrap: wrap">')
if model_version is None:
selected_version = item['modelVersions'][0]
else:
for model in item['modelVersions']:
if model['name'] == model_version:
selected_version = model
break
if selected_version['trainedWords']:
output_training = ",".join(selected_version['trainedWords'])
output_training = re.sub(r'<[^>]*:[^>]*>', '', output_training)
output_training = re.sub(r', ?', ', ', output_training)
output_training = output_training.strip(', ')
if selected_version['baseModel']:
output_basemodel = selected_version['baseModel']
for file in selected_version['files']:
dl_dict[file['name']] = file['downloadUrl']
if not model_filename:
model_filename = file['name']
dl_url = file['downloadUrl']
gl.json_info = item
sha256_value = file['hashes'].get('SHA256', 'Unknown')
size = file['metadata'].get('size', 'Unknown')
format = file['metadata'].get('format', 'Unknown')
fp = file['metadata'].get('fp', 'Unknown')
sizeKB = file.get('sizeKB', 0) * 1024
filesize = _download.convert_size(sizeKB)
unique_file_name = f"{size} {format} {fp} ({filesize})"
is_primary = file.get('primary', False)
file_list.append(unique_file_name)
file_dict.append({
"format": format,
"sizeKB": sizeKB
})
if is_primary:
default_file = unique_file_name
model_filename = file['name']
dl_url = file['downloadUrl']
gl.json_info = item
sha256_value = file['hashes'].get('SHA256', 'Unknown')
safe_tensor_found = False
pickle_tensor_found = False
if is_LORA and file_dict:
for file_info in file_dict:
file_format = file_info.get("format", "")
if "SafeTensor" in file_format:
safe_tensor_found = True
if "PickleTensor" in file_format:
pickle_tensor_found = True
if safe_tensor_found and pickle_tensor_found:
if "PickleTensor" in file_dict[0].get("format", ""):
if file_dict[0].get("sizeKB", 0) <= 100:
model_folder = os.path.join(contenttype_folder("TextualInversion"))
model_url = selected_version.get('downloadUrl', '')
model_main_url = f"https://civitai.com/models/{item['id']}"
img_html = '<div class="sampleimgs"><input type="radio" name="zoomRadio" id="resetZoom" class="zoom-radio" checked>'
url = f"https://civitai.com/api/v1/model-versions/{selected_version['id']}"
api_version = request_civit_api(url)
for index, pic in enumerate(api_version['images']):
if from_preview:
index = f"preview_{index}"
class_name = 'class="model-block"'
if pic.get('nsfwLevel') >= 4:
class_name = 'class="civnsfw model-block"'
img_html += f'''
<div {class_name} style="display:flex;align-items:flex-start;">
<div class="civitai-image-container">
<input type="radio" name="zoomRadio" id="zoomRadio{index}" class="zoom-radio">
<label for="zoomRadio{index}" class="zoom-img-container">
'''
prompt_dict = pic.get('meta', {})
meta_button = False
if prompt_dict and prompt_dict.get('prompt'):
meta_button = True
BtnImage = True
image_url = re.sub(r'/width=\d+', f'/width={pic["width"]}', pic["url"])
if pic['type'] == "video":
image_url = image_url.replace("width=", "transcode=true,width=")
img_html += f'<video data-sampleimg="true" {playback} muted playsinline><source src="{image_url}" type="video/mp4"></video>'
meta_button = False
prompt_dict = {}
else:
img_html += f'<img data-sampleimg="true" src="{image_url}">'
img_html += '''
</label>
<label for="resetZoom" class="zoom-overlay"></label>
'''
if meta_button:
img_html += f'''
<div class="civitai_txt2img" style="margin-top:30px;margin-bottom:30px;">
<label onclick='sendImgUrl("{escape(image_url)}")' class="civitai-txt2img-btn" style="max-width:fit-content;cursor:pointer;">Send to txt2img</label>
</div></div>
'''
else:
img_html += '</div>'
if prompt_dict:
img_html += '<div style="margin:1em 0em 1em 1em;text-align:left;line-height:1.5em;" id="image_info"><dl style="gap:10px; display:grid;">'
# Define the preferred order of keys
preferred_order = ["prompt", "negativePrompt", "seed", "Size", "Model", "Clip skip", "sampler", "steps", "cfgScale"]
# Loop through the keys in the preferred order and add them to the HTML
for key in preferred_order:
if key in prompt_dict:
value = prompt_dict[key]
key_map = {
"prompt": "Prompt",
"negativePrompt": "Negative prompt",
"seed": "Seed",
"Size": "Size",
"Model": "Model",
"Clip skip": "Clip skip",
"sampler": "Sampler",
"steps": "Steps",
"cfgScale": "CFG scale"
}
key = key_map.get(key, key)
if meta_btn:
img_html += f'<div class="civitai-meta-btn" onclick="metaToTxt2Img(\'{escape(str(key))}\', this)"><dt>{escape(str(key))}</dt><dd>{escape(str(value))}</dd></div>'
else:
img_html += f'<div class="civitai-meta"><dt>{escape(str(key))}</dt><dd>{escape(str(value))}</dd></div>'
# Check if there are remaining keys in meta
remaining_keys = [key for key in prompt_dict if key not in preferred_order]
# Add the rest
if remaining_keys:
img_html += f"""
<div class="tabs">
<div class="tab">
<input type="checkbox" class="accordionCheckbox" id="chck{index}">
<label class="tab-label" for="chck{index}">More details...</label>
<div class="tab-content" style="gap:10px;display:grid;margin-left:1px;">
"""
for key in remaining_keys:
value = prompt_dict[key]
img_html += f'<div class="civitai-meta"><dt>{escape(str(key).capitalize())}</dt><dd>{escape(str(value))}</dd></div>'
img_html = img_html + '</div></div></div>'
img_html += '</dl></div>'
img_html = img_html + '</div>'
img_html = img_html + '</div>'
tags_html = ''.join([f'<span class="civitai-tag">{escape(str(tag))}</span>' for tag in tags])
def perms_svg(color):
return f'<span style="display:inline-block;vertical-align:middle;">'\
f'<svg width="15" height="15" viewBox="0 1.5 24 24" stroke-width="4" stroke-linecap="round" stroke="{color}">'
allow_svg = f'{perms_svg("lime")}<path d="M5 12l5 5l10 -10"></path></svg></span>'
deny_svg = f'{perms_svg("red")}<path d="M18 6l-12 12"></path><path d="M6 6l12 12"></path></svg></span>'
allowCommercialUse = item.get("allowCommercialUse", [])
perms_html= '<p style="line-height: 2; font-weight: bold;">'\
f'{allow_svg if item.get("allowNoCredit") else deny_svg} Use the model without crediting the creator<br/>'\
f'{allow_svg if "Image" in allowCommercialUse else deny_svg} Sell images they generate<br/>'\
f'{allow_svg if "Rent" in allowCommercialUse else deny_svg} Run on services that generate images for money<br/>'\
f'{allow_svg if "RentCivit" in allowCommercialUse else deny_svg} Run on Civitai<br/>'\
f'{allow_svg if item.get("allowDerivatives") else deny_svg} Share merges using this model<br/>'\
f'{allow_svg if "Sell" in allowCommercialUse else deny_svg} Sell this model or merges using this model<br/>'\
f'{allow_svg if item.get("allowDifferentLicense") else deny_svg} Have different permissions when sharing merges'\
'</p>'
if not creator or model_uploader == 'User not found':
uploader = f'<h3 class="model-uploader"><span>{escape(str(model_uploader))}</span>{uploader_avatar}</h3>'
else:
uploader = f'<h3 class="model-uploader">Uploaded by <a href="https://civitai.com/user/{escape(str(model_uploader))}" target="_blank">{escape(str(model_uploader))}</a>{uploader_avatar}</h3>'
output_html = f'''
<div class="model-block">
<h2><a href={model_main_url} target="_blank" id="model_header">{escape(str(model_name))}</a></h2>
{uploader}
<div class="civitai-version-info" style="display:flex; flex-wrap:wrap; justify-content:space-between;">
<dl id="info_block">
<dt>Version</dt>
<dd>{escape(str(model_version))}</dd>
<dt>Base Model</dt>
<dd>{escape(str(output_basemodel))}</dd>
<dt>CivitAI Tags</dt>
<dd>
<div class="civitai-tags-container">
{tags_html}
</div>
</dd>
{"<dt>Download Link</dt>" if model_url else ''}
{f'<dd><a href={model_url} target="_blank">{model_url}</a></dd>' if model_url else ''}
</dl>
<div style="align-self:center; min-width:320px;">
<div>
{perms_html}
</div>
</div>
</div>
<input type="checkbox" id="{'preview-' if from_preview else ''}civitai-description" class="description-toggle-checkbox">
<div class="model-description">
<h2>Description</h2>
{model_desc}
</div>
<label for="{'preview-' if from_preview else ''}civitai-description" class="description-toggle-label"></label>
</div>
<div align=center>{img_html}</div>
'''
if only_html:
return output_html
folder_location = "None"
default_subfolder = "None"
sub_folders = ["None"]
for root, dirs, files in os.walk(model_folder, followlinks=True):
for filename in files:
if filename.endswith('.json'):
json_file_path = os.path.join(root, filename)
with open(json_file_path, 'r', encoding="utf-8") as f:
try:
data = json.load(f)
sha256 = data.get('sha256')
if sha256:
sha256 = sha256.upper()
if sha256 == sha256_value:
folder_location = root
BtnDownInt = False
BtnDel = True
break
except Exception as e:
print(f"Error decoding JSON: {str(e)}")
else:
for filename in files:
if filename == model_filename or filename == cleaned_name(model_filename):
folder_location = root
BtnDownInt = False
BtnDel = True
break
if folder_location != "None":
break
insert_sub_1 = getattr(opts, "insert_sub_1", False)
insert_sub_2 = getattr(opts, "insert_sub_2", False)
insert_sub_3 = getattr(opts, "insert_sub_3", False)
insert_sub_4 = getattr(opts, "insert_sub_4", False)
insert_sub_5 = getattr(opts, "insert_sub_5", False)
insert_sub_6 = getattr(opts, "insert_sub_6", False)
insert_sub_7 = getattr(opts, "insert_sub_7", False)
insert_sub_8 = getattr(opts, "insert_sub_8", False)
insert_sub_9 = getattr(opts, "insert_sub_9", False)
insert_sub_10 = getattr(opts, "insert_sub_10", False)
insert_sub_11 = getattr(opts, "insert_sub_11", False)
insert_sub_12 = getattr(opts, "insert_sub_12", False)
insert_sub_13 = getattr(opts, "insert_sub_13", False)
insert_sub_14 = getattr(opts, "insert_sub_14", False)
dot_subfolders = getattr(opts, "dot_subfolders", True)
try:
sub_folders = ["None"]
for root, dirs, _ in os.walk(model_folder, followlinks=True):
if dot_subfolders:
dirs = [d for d in dirs if not d.startswith('.')]
dirs = [d for d in dirs if not any(part.startswith('.') for part in os.path.join(root, d).split(os.sep))]
for d in dirs:
sub_folder = os.path.relpath(os.path.join(root, d), model_folder)
if sub_folder:
sub_folders.append(f'{os.sep}{sub_folder}')
sub_folders.remove("None")
sub_folders = sorted(sub_folders, key=lambda x: (x.lower(), x))
sub_folders.insert(0, "None")
base = cleaned_name(output_basemodel)
author = cleaned_name(model_uploader)
name = cleaned_name(model_name)
ver = cleaned_name(model_version)
if insert_sub_1:
sub_folders.insert(1, os.path.join(os.sep, base))
if insert_sub_2:
sub_folders.insert(2, os.path.join(os.sep, base, author))
if insert_sub_3:
sub_folders.insert(3, os.path.join(os.sep, base, author, name))
if insert_sub_4:
sub_folders.insert(4, os.path.join(os.sep, base, author, name, ver))
if insert_sub_5:
sub_folders.insert(5, os.path.join(os.sep, base, name))
if insert_sub_6:
sub_folders.insert(6, os.path.join(os.sep, base, name, ver))
if insert_sub_7:
sub_folders.insert(7, os.path.join(os.sep, author))
if insert_sub_8:
sub_folders.insert(8, os.path.join(os.sep, author, base))
if insert_sub_9:
sub_folders.insert(9, os.path.join(os.sep, author, base, name))
if insert_sub_10:
sub_folders.insert(10, os.path.join(os.sep, author, base, name, ver))
if insert_sub_11:
sub_folders.insert(11, os.path.join(os.sep, author, name))
if insert_sub_12:
sub_folders.insert(12, os.path.join(os.sep, author, name, ver))
if insert_sub_13:
sub_folders.insert(13, os.path.join(os.sep, name))
if insert_sub_14:
sub_folders.insert(14, os.path.join(os.sep, name, ver))
list = set()
sub_folders = [x for x in sub_folders if not (x in list or list.add(x))]
except Exception as e:
print(e)
sub_folders = ["None"]
default_sub = sub_folder_value(content_type, desc)
variable_mapping = {
"Base model": base,
"Author name": author,
"Model name": name,
"Model version": ver
}
if any(key in default_sub for key in variable_mapping.keys()):
path_components = [variable_mapping.get(component.strip(os.sep), component.strip(os.sep)) for component in default_sub.split(os.sep)]
default_sub = os.path.join(os.sep, *path_components)
if folder_location == "None":
folder_location = model_folder
if default_sub != "None":
folder_path = folder_location + default_sub
else:
folder_path = folder_location
else:
folder_path = folder_location
relative_path = os.path.relpath(folder_location, model_folder)
default_subfolder = f'{os.sep}{relative_path}' if relative_path != "." else default_sub if BtnDel == False else "None"
if gl.isDownloading:
item = gl.download_queue[0]
if int(model_id) == int(item['model_id']):
BtnDel = False
BtnDownTxt = "Download model"
if len(gl.download_queue) > 0:
BtnDownTxt = "Add to queue"
for item in gl.download_queue:
if item['version_name'] == model_version and int(item['model_id']) == int(model_id):
BtnDownInt = False
break
return (
gr.HTML.update(value=output_html), # Preview HTML
gr.Textbox.update(value=output_training, interactive=True), # Trained Tags
gr.Textbox.update(value=output_basemodel), # Base Model Number
gr.Button.update(visible=False if BtnDel else True, interactive=BtnDownInt, value=BtnDownTxt), # Download Button
gr.Button.update(interactive=BtnImage), # Images Button
gr.Button.update(visible=BtnDel, interactive=BtnDel), # Delete Button
gr.Dropdown.update(choices=file_list, value=default_file, interactive=True), # File List
gr.Textbox.update(value=cleaned_name(model_filename), interactive=True), # Model File Name
gr.Textbox.update(value=dl_url), # Download URL
gr.Textbox.update(value=model_id), # Model ID
gr.Textbox.update(value=sha256_value), # SHA256
gr.Textbox.update(interactive=True, value=folder_path if model_name else None), # Install Path
gr.Dropdown.update(choices=sub_folders, value=default_subfolder, interactive=True) # Sub Folder List
)
else:
return (
gr.HTML.update(value=None), # Preview HTML
gr.Textbox.update(value=None, interactive=False), # Trained Tags
gr.Textbox.update(value=''), # Base Model Number
gr.Button.update(visible=False if BtnDel else True, value="Download model"), # Download Button
gr.Button.update(interactive=False), # Images Button
gr.Button.update(visible=BtnDel, interactive=BtnDel), # Delete Button
gr.Dropdown.update(choices=None, value=None, interactive=False), # File List
gr.Textbox.update(value=None, interactive=False), # Model File Name
gr.Textbox.update(value=None), # Download URL
gr.Textbox.update(value=None), # Model ID
gr.Textbox.update(value=None), # SHA256
gr.Textbox.update(interactive=False, value=None), # Install Path
gr.Dropdown.update(choices=None, value=None, interactive=False) # Sub Folder List
)
def sub_folder_value(content_type, desc=None):
use_LORA = getattr(opts, "use_LORA", False)
if content_type in ["LORA", "LoCon"] and use_LORA:
folder = getattr(opts, "LORA_LoCon_subfolder", "None")
elif content_type == "Upscaler":
for upscale_type in ["SWINIR", "REALESRGAN", "GFPGAN", "BSRGAN"]:
if upscale_type in desc:
folder = getattr(opts, f"{upscale_type}_subfolder", "None")
folder = getattr(opts, "ESRGAN_subfolder", "None")
else:
folder = getattr(opts, f"{content_type}_subfolder", "None")
if folder == None:
return "None"
return folder
def update_file_info(model_string, model_version, file_metadata):
file_list = []
is_LORA = False
embed_check = False
model_name = None
model_id = None
model_name, model_id = extract_model_info(model_string)
if model_version and "[Installed]" in model_version:
model_version = model_version.replace(" [Installed]", "")
if model_id and model_version:
for item in gl.json_data['items']:
if int(item['id']) == int(model_id):
content_type = item['type']
if content_type == "LORA":
is_LORA = True
desc = item['description']
for model in item['modelVersions']:
if model['name'] == model_version:
for file in model['files']:
size = file['metadata'].get('size', 'Unknown')
format = file['metadata'].get('format', 'Unknown')
unique_file_name = f"{size} {format}"
file_list.append(unique_file_name)
pass
if is_LORA and file_list:
extracted_formats = [file.split(' ')[1] for file in file_list]
if "SafeTensor" in extracted_formats and "PickleTensor" in extracted_formats:
embed_check = True
for file in model['files']:
model_id = item['id']
file_name = file.get('name', 'Unknown')
sha256 = file['hashes'].get('SHA256', 'Unknown')
metadata = file.get('metadata', {})
file_size = metadata.get('size', 'Unknown')
file_format = metadata.get('format', 'Unknown')
file_fp = metadata.get('fp', 'Unknown')
sizeKB = file.get('sizeKB', 0)
sizeB = sizeKB * 1024
filesize = _download.convert_size(sizeB)
if f"{file_size} {file_format} {file_fp} ({filesize})" == file_metadata:
installed = False
folder_location = "None"
model_folder = os.path.join(contenttype_folder(content_type, desc))
if embed_check and file_format == "PickleTensor":
if sizeKB <= 100:
model_folder = os.path.join(contenttype_folder("TextualInversion"))
dl_url = file['downloadUrl']
gl.json_info = item
for root, _, files in os.walk(model_folder, followlinks=True):
if file_name in files:
installed = True
folder_location = root
break
if not installed:
for root, _, files in os.walk(model_folder, followlinks=True):
for filename in files:
if filename.endswith('.json'):
with open(os.path.join(root, filename), 'r', encoding="utf-8") as f:
try:
data = json.load(f)
sha256_value = data.get('sha256')
if sha256_value != None and sha256_value.upper() == sha256:
folder_location = root
installed = True
break
except Exception as e:
print(f"Error decoding JSON: {str(e)}")
default_sub = sub_folder_value(content_type, desc)
if folder_location == "None":
folder_location = model_folder
if default_sub != "None":
folder_path = folder_location + default_sub
else:
folder_path = folder_location
else:
folder_path = folder_location
relative_path = os.path.relpath(folder_location, model_folder)
default_subfolder = f'{os.sep}{relative_path}' if relative_path != "." else default_sub if installed == False else "None"
BtnDownInt = not installed
BtnDownTxt = "Download model"
if len(gl.download_queue) > 0:
BtnDownTxt = "Add to queue"
for item in gl.download_queue:
if item['version_name'] == model_version:
BtnDownInt = False
break
return (
gr.Textbox.update(value=cleaned_name(file['name']), interactive=True), # Model File Name Textbox
gr.Textbox.update(value=dl_url), # Download URL Textbox
gr.Textbox.update(value=model_id), # Model ID Textbox
gr.Textbox.update(value=sha256), # sha256 textbox
gr.Button.update(interactive=BtnDownInt, visible=False if installed else True, value=BtnDownTxt), # Download Button
gr.Button.update(interactive=True if installed else False, visible=True if installed else False), # Delete Button
gr.Textbox.update(interactive=True, value=folder_path if model_name else None), # Install Path
gr.Dropdown.update(value=default_subfolder, interactive=True) # Sub Folder List
)
return (
gr.Textbox.update(value=None, interactive=False), # Model File Name Textbox
gr.Textbox.update(value=None), # Download URL Textbox
gr.Textbox.update(value=None), # Model ID Textbox
gr.Textbox.update(value=None), # sha256 textbox
gr.Button.update(interactive=False, visible=True), # Download Button
gr.Button.update(interactive=False, visible=False), # Delete Button
gr.Textbox.update(interactive=False, value=None), # Install Path
gr.Dropdown.update(choices=None, value=None, interactive=False) # Sub Folder List
)
def get_proxies():
custom_proxy = getattr(opts, "custom_civitai_proxy", "")
disable_ssl = getattr(opts, "disable_sll_proxy", False)
cabundle_path = getattr(opts, "cabundle_path_proxy", "")
ssl = True
proxies = {}
if custom_proxy:
if not disable_ssl:
if cabundle_path:
ssl = os.path(cabundle_path)
else:
ssl = False
proxies = {
'http': custom_proxy,
'https': custom_proxy,
}
return proxies, ssl
def get_headers(referer=None, no_api=None):
api_key = getattr(opts, "custom_api_key", "")
headers = {
"Connection": "keep-alive",
"Sec-Ch-Ua-Platform": "Windows",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36",
"Content-Type": "application/json"
}
if referer:
headers['Referer'] = f"https://civitai.com/models/{referer}"
if api_key and not no_api:
headers['Authorization'] = f'Bearer {api_key}'
return headers
def request_civit_api(api_url=None):
headers = get_headers()
proxies, ssl = get_proxies()
try:
response = requests.get(api_url, headers=headers, timeout=(60,30), proxies=proxies, verify=ssl)
response.raise_for_status()
except requests.exceptions.Timeout as e:
print("The request timed out. Please try again later.")
return "timeout"
except requests.exceptions.RequestException as e:
print(f"Error: {e}")
return "error"
else:
response.encoding = "utf-8"
try:
data = json.loads(response.text)
except json.JSONDecodeError:
print(response.text)
print("The CivitAI servers are currently offline. Please try again later.")
return "offline"
return data
def api_error_msg(input_string):
div = '<div style="color: white; font-family: var(--font); font-size: 24px; text-align: center; margin: 50px !important;">'
if input_string == "not_found":
return div + "Model ID not found on CivitAI.<br>Maybe the model doesn\'t exist on CivitAI?</div>"
elif input_string == "path_not_found":
return div + "Local model not found.<br>Could not locate the model path.</div>"
elif input_string == "timeout":
return div + "The CivitAI-API has timed out, please try again.<br>The servers might be too busy or down if the issue persists."
elif input_string == "offline":
return div + "The CivitAI servers are currently offline.<br>Please try again later."
elif input_string == "no_items":
return div + "Failed to retrieve any models from CivitAI<br>The servers might be too busy or down if the issue persists."
else:
return div + "The CivitAI-API failed to respond due to an error.<br>Check the logs for more details."