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Update utils.py
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utils.py
CHANGED
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@@ -13,10 +13,72 @@ from diffusers import DiffusionPipeline
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from huggingface_hub import model_info as model_info_data
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from diffusers.pipelines.pipeline_loading_utils import variant_compatible_siblings
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from pathlib import PosixPath
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url = url.strip()
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if "drive.google.com" in url:
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original_dir = os.getcwd()
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@@ -29,21 +91,96 @@ def download_things(directory, url, hf_token="", civitai_api_key=""):
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if "/blob/" in url:
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url = url.replace("/blob/", "/resolve/")
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user_header = f'"Authorization: Bearer {hf_token}"'
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if hf_token:
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os.system(f"aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 {url} -d {directory} -o {
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else:
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os.system(f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 {url} -d {directory} -o {
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elif "civitai.com" in url:
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if civitai_api_key:
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url = url + f"?token={civitai_api_key}"
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os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
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else:
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print("\033[91mYou need an API key to download Civitai models.\033[0m")
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else:
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os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
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def get_model_list(directory_path):
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model_list = []
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@@ -102,13 +239,17 @@ def extract_parameters(input_string):
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return parameters
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def get_my_lora(link_url):
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for url in [url.strip() for url in link_url.split(',')]:
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if not os.path.exists(f"./loras/{url.split('/')[-1]}"):
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download_things(DIRECTORY_LORAS, url, HF_TOKEN, CIVITAI_API_KEY)
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new_lora_model_list = get_model_list(DIRECTORY_LORAS)
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new_lora_model_list.insert(0, "None")
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new_lora_model_list = new_lora_model_list + DIFFUSERS_FORMAT_LORAS
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return gr.update(
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choices=new_lora_model_list
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@@ -120,7 +261,9 @@ def get_my_lora(link_url):
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choices=new_lora_model_list
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), gr.update(
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choices=new_lora_model_list
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),
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def info_html(json_data, title, subtitle):
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@@ -148,9 +291,17 @@ def get_model_type(repo_id: str):
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return default
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def restart_space(repo_id: str, factory_reboot: bool
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api = HfApi(token=
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def extract_exif_data(image):
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from huggingface_hub import model_info as model_info_data
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from diffusers.pipelines.pipeline_loading_utils import variant_compatible_siblings
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from pathlib import PosixPath
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from unidecode import unidecode
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import urllib.parse
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import copy
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import requests
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from requests.adapters import HTTPAdapter
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from urllib3.util import Retry
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USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'
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def request_json_data(url):
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model_version_id = url.split('/')[-1]
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if "?modelVersionId=" in model_version_id:
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match = re.search(r'modelVersionId=(\d+)', url)
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model_version_id = match.group(1)
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endpoint_url = f"https://civitai.com/api/v1/model-versions/{model_version_id}"
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params = {}
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headers = {'User-Agent': USER_AGENT, 'content-type': 'application/json'}
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session = requests.Session()
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retries = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
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session.mount("https://", HTTPAdapter(max_retries=retries))
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try:
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result = session.get(endpoint_url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
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result.raise_for_status()
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json_data = result.json()
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return json_data if json_data else None
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except Exception as e:
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print(f"Error: {e}")
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return None
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class ModelInformation:
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def __init__(self, json_data):
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self.model_version_id = json_data.get("id", "")
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self.model_id = json_data.get("modelId", "")
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self.download_url = json_data.get("downloadUrl", "")
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self.model_url = f"https://civitai.com/models/{self.model_id}?modelVersionId={self.model_version_id}"
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self.filename_url = next(
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(v.get("name", "") for v in json_data.get("files", []) if str(self.model_version_id) in v.get("downloadUrl", "")), ""
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)
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self.filename_url = self.filename_url if self.filename_url else ""
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self.description = json_data.get("description", "")
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if self.description is None: self.description = ""
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self.model_name = json_data.get("model", {}).get("name", "")
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self.model_type = json_data.get("model", {}).get("type", "")
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self.nsfw = json_data.get("model", {}).get("nsfw", False)
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self.poi = json_data.get("model", {}).get("poi", False)
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self.images = [img.get("url", "") for img in json_data.get("images", [])]
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self.example_prompt = json_data.get("trainedWords", [""])[0] if json_data.get("trainedWords") else ""
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self.original_json = copy.deepcopy(json_data)
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def retrieve_model_info(url):
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json_data = request_json_data(url)
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if not json_data:
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return None
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model_descriptor = ModelInformation(json_data)
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return model_descriptor
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def download_things(directory, url, hf_token="", civitai_api_key="", romanize=False):
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url = url.strip()
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downloaded_file_path = None
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if "drive.google.com" in url:
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original_dir = os.getcwd()
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if "/blob/" in url:
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url = url.replace("/blob/", "/resolve/")
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user_header = f'"Authorization: Bearer {hf_token}"'
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filename = unidecode(url.split('/')[-1]) if romanize else url.split('/')[-1]
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if hf_token:
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os.system(f"aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 {url} -d {directory} -o {filename}")
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else:
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os.system(f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 {url} -d {directory} -o {filename}")
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downloaded_file_path = os.path.join(directory, filename)
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elif "civitai.com" in url:
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if not civitai_api_key:
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print("\033[91mYou need an API key to download Civitai models.\033[0m")
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model_profile = retrieve_model_info(url)
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if model_profile.download_url and model_profile.filename_url:
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url = model_profile.download_url
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filename = unidecode(model_profile.filename_url) if romanize else model_profile.filename_url
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else:
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if "?" in url:
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url = url.split("?")[0]
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filename = ""
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url_dl = url + f"?token={civitai_api_key}"
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print(f"Filename: {filename}")
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param_filename = ""
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if filename:
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param_filename = f"-o '{filename}'"
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aria2_command = (
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f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
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f'-k 1M -s 16 -d "{directory}" {param_filename} "{url_dl}"'
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)
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os.system(aria2_command)
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if param_filename and os.path.exists(os.path.join(directory, filename)):
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downloaded_file_path = os.path.join(directory, filename)
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# # PLAN B
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# # Follow the redirect to get the actual download URL
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# curl_command = (
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# f'curl -L -sI --connect-timeout 5 --max-time 5 '
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# f'-H "Content-Type: application/json" '
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# f'-H "Authorization: Bearer {civitai_api_key}" "{url}"'
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# )
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# headers = os.popen(curl_command).read()
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# # Look for the redirected "Location" URL
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# location_match = re.search(r'location: (.+)', headers, re.IGNORECASE)
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# if location_match:
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# redirect_url = location_match.group(1).strip()
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# # Extract the filename from the redirect URL's "Content-Disposition"
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# filename_match = re.search(r'filename%3D%22(.+?)%22', redirect_url)
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# if filename_match:
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# encoded_filename = filename_match.group(1)
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# # Decode the URL-encoded filename
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# decoded_filename = urllib.parse.unquote(encoded_filename)
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# filename = unidecode(decoded_filename) if romanize else decoded_filename
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# print(f"Filename: {filename}")
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# aria2_command = (
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# f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
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# f'-k 1M -s 16 -d "{directory}" -o "{filename}" "{redirect_url}"'
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# )
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# return_code = os.system(aria2_command)
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# # if return_code != 0:
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# # raise RuntimeError(f"Failed to download file: {filename}. Error code: {return_code}")
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# downloaded_file_path = os.path.join(directory, filename)
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# if not os.path.exists(downloaded_file_path):
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# downloaded_file_path = None
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# if not downloaded_file_path:
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# # Old method
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# if "?" in url:
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# url = url.split("?")[0]
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# url = url + f"?token={civitai_api_key}"
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# os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
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else:
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os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
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return downloaded_file_path
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def get_model_list(directory_path):
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model_list = []
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return parameters
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def get_my_lora(link_url, romanize):
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for url in [url.strip() for url in link_url.split(',')]:
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if not os.path.exists(f"./loras/{url.split('/')[-1]}"):
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l_name = download_things(DIRECTORY_LORAS, url, HF_TOKEN, CIVITAI_API_KEY, romanize)
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new_lora_model_list = get_model_list(DIRECTORY_LORAS)
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new_lora_model_list.insert(0, "None")
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new_lora_model_list = new_lora_model_list + DIFFUSERS_FORMAT_LORAS
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msg_lora = "Downloaded"
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if l_name:
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msg_lora += f": <b>{l_name}</b>"
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print(msg_lora)
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return gr.update(
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choices=new_lora_model_list
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choices=new_lora_model_list
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), gr.update(
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choices=new_lora_model_list
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), gr.update(
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value=msg_lora
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)
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def info_html(json_data, title, subtitle):
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return default
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def restart_space(repo_id: str, factory_reboot: bool):
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api = HfApi(token=os.environ.get("HF_TOKEN"))
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try:
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runtime = api.get_space_runtime(repo_id=repo_id)
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if runtime.stage == "RUNNING":
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api.restart_space(repo_id=repo_id, factory_reboot=factory_reboot)
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print(f"Restarting space: {repo_id}")
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else:
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print(f"Space {repo_id} is in stage: {runtime.stage}")
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except Exception as e:
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print(e)
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def extract_exif_data(image):
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