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import gradio as gr
from huggingface_hub import HfApi, HfFolder, hf_hub_download, snapshot_download
import os
from pathlib import Path
import shutil
import gc
import re
import urllib.parse
import subprocess
import time
from typing import Any
def get_token():
try:
token = HfFolder.get_token()
except Exception:
token = ""
return token
def set_token(token):
try:
HfFolder.save_token(token)
except Exception:
print(f"Error: Failed to save token.")
def get_state(state: dict, key: str):
if key in state.keys(): return state[key]
else:
print(f"State '{key}' not found.")
return None
def set_state(state: dict, key: str, value: Any):
state[key] = value
def get_user_agent():
return 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'
def is_repo_exists(repo_id: str, repo_type: str="model"):
hf_token = get_token()
api = HfApi(token=hf_token)
try:
if api.repo_exists(repo_id=repo_id, repo_type=repo_type, token=hf_token): return True
else: return False
except Exception as e:
print(f"Error: Failed to connect {repo_id} ({repo_type}). {e}")
return True # for safe
MODEL_TYPE_CLASS = {
"diffusers:StableDiffusionPipeline": "SD 1.5",
"diffusers:StableDiffusionXLPipeline": "SDXL",
"diffusers:FluxPipeline": "FLUX",
}
def get_model_type(repo_id: str):
hf_token = get_token()
api = HfApi(token=hf_token)
lora_filename = "pytorch_lora_weights.safetensors"
diffusers_filename = "model_index.json"
default = "SDXL"
try:
if api.file_exists(repo_id=repo_id, filename=lora_filename, token=hf_token): return "LoRA"
if not api.file_exists(repo_id=repo_id, filename=diffusers_filename, token=hf_token): return "None"
model = api.model_info(repo_id=repo_id, token=hf_token)
tags = model.tags
for tag in tags:
if tag in MODEL_TYPE_CLASS.keys(): return MODEL_TYPE_CLASS.get(tag, default)
except Exception:
return default
return default
def list_uniq(l):
return sorted(set(l), key=l.index)
def list_sub(a, b):
return [e for e in a if e not in b]
def is_repo_name(s):
return re.fullmatch(r'^[\w_\-\.]+/[\w_\-\.]+$', s)
def get_hf_url(repo_id: str, repo_type: str="model"):
if repo_type == "dataset": url = f"https://huggingface.co/datasets/{repo_id}"
elif repo_type == "space": url = f"https://huggingface.co/spaces/{repo_id}"
else: url = f"https://huggingface.co/{repo_id}"
return url
def split_hf_url(url: str):
try:
s = list(re.findall(r'^(?:https?://huggingface.co/)(?:(datasets|spaces)/)?(.+?/.+?)/\w+?/.+?/(?:(.+)/)?(.+?.\w+)(?:\?download=true)?$', url)[0])
if len(s) < 4: return "", "", "", ""
repo_id = s[1]
if s[0] == "datasets": repo_type = "dataset"
elif s[0] == "spaces": repo_type = "space"
else: repo_type = "model"
subfolder = urllib.parse.unquote(s[2]) if s[2] else None
filename = urllib.parse.unquote(s[3])
return repo_id, filename, subfolder, repo_type
except Exception as e:
print(e)
def download_hf_file(directory, url, progress=gr.Progress(track_tqdm=True)):
hf_token = get_token()
repo_id, filename, subfolder, repo_type = split_hf_url(url)
try:
print(f"Downloading {url} to {directory}")
if subfolder is not None: path = hf_hub_download(repo_id=repo_id, filename=filename, subfolder=subfolder, repo_type=repo_type, local_dir=directory, token=hf_token)
else: path = hf_hub_download(repo_id=repo_id, filename=filename, repo_type=repo_type, local_dir=directory, token=hf_token)
return path
except Exception as e:
print(f"Failed to download: {e}")
return None
def download_thing(directory, url, civitai_api_key="", progress=gr.Progress(track_tqdm=True)): # requires aria2, gdown
try:
url = url.strip()
if "drive.google.com" in url:
original_dir = os.getcwd()
os.chdir(directory)
subprocess.run(f"gdown --fuzzy {url}", shell=True)
os.chdir(original_dir)
elif "huggingface.co" in url:
url = url.replace("?download=true", "")
if "/blob/" in url: url = url.replace("/blob/", "/resolve/")
download_hf_file(directory, url)
elif "civitai.com" in url:
if civitai_api_key:
url = f"'{url}&token={civitai_api_key}'" if "?" in url else f"{url}?token={civitai_api_key}"
print(f"Downloading {url}")
subprocess.run(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}", shell=True)
else:
print("You need an API key to download Civitai models.")
else:
os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
except Exception as e:
print(f"Failed to download: {e}")
def get_local_file_list(dir_path):
file_list = []
for file in Path(dir_path).glob("**/*.*"):
if file.is_file():
file_path = str(file)
file_list.append(file_path)
return file_list
def get_download_file(temp_dir, url, civitai_key, progress=gr.Progress(track_tqdm=True)):
try:
if not "http" in url and is_repo_name(url) and not Path(url).exists():
print(f"Use HF Repo: {url}")
new_file = url
elif not "http" in url and Path(url).exists():
print(f"Use local file: {url}")
new_file = url
elif Path(f"{temp_dir}/{url.split('/')[-1]}").exists():
print(f"File to download alreday exists: {url}")
new_file = f"{temp_dir}/{url.split('/')[-1]}"
else:
print(f"Start downloading: {url}")
before = get_local_file_list(temp_dir)
download_thing(temp_dir, url.strip(), civitai_key)
after = get_local_file_list(temp_dir)
new_file = list_sub(after, before)[0] if list_sub(after, before) else ""
if not new_file:
print(f"Download failed: {url}")
return ""
print(f"Download completed: {url}")
return new_file
except Exception as e:
print(f"Download failed: {url} {e}")
return ""
def download_repo(repo_id: str, dir_path: str, progress=gr.Progress(track_tqdm=True)): # for diffusers repo
hf_token = get_token()
try:
snapshot_download(repo_id=repo_id, local_dir=dir_path, token=hf_token, allow_patterns=["*.safetensors", "*.bin"],
ignore_patterns=["*.fp16.*", "/*.safetensors", "/*.bin"], force_download=True)
return True
except Exception as e:
print(f"Error: Failed to download {repo_id}. {e}")
gr.Warning(f"Error: Failed to download {repo_id}. {e}")
return False
def upload_repo(repo_id: str, dir_path: str, is_private: bool, is_pr: bool=False, progress=gr.Progress(track_tqdm=True)): # for diffusers repo
hf_token = get_token()
api = HfApi(token=hf_token)
try:
progress(0, desc="Start uploading...")
api.create_repo(repo_id=repo_id, token=hf_token, private=is_private, exist_ok=True)
api.upload_folder(repo_id=repo_id, folder_path=dir_path, path_in_repo="", create_pr=is_pr, token=hf_token)
progress(1, desc="Uploaded.")
return get_hf_url(repo_id, "model")
except Exception as e:
print(f"Error: Failed to upload to {repo_id}. {e}")
return ""
def gate_repo(repo_id: str, gated_str: str, repo_type: str="model"):
hf_token = get_token()
api = HfApi(token=hf_token)
try:
if gated_str == "auto": gated = "auto"
elif gated_str == "manual": gated = "manual"
else: gated = False
api.update_repo_settings(repo_id=repo_id, gated=gated, repo_type=repo_type, token=hf_token)
except Exception as e:
print(f"Error: Failed to update settings {repo_id}. {e}")
HF_SUBFOLDER_NAME = ["None", "user_repo"]
def duplicate_hf_repo(src_repo: str, dst_repo: str, src_repo_type: str, dst_repo_type: str,
is_private: bool, subfolder_type: str=HF_SUBFOLDER_NAME[1], progress=gr.Progress(track_tqdm=True)):
hf_token = get_token()
api = HfApi(token=hf_token)
try:
if subfolder_type == "user_repo": subfolder = src_repo.replace("/", "_")
else: subfolder = ""
progress(0, desc="Start duplicating...")
api.create_repo(repo_id=dst_repo, repo_type=dst_repo_type, private=is_private, exist_ok=True, token=hf_token)
for path in api.list_repo_files(repo_id=src_repo, repo_type=src_repo_type, token=hf_token):
file = hf_hub_download(repo_id=src_repo, filename=path, repo_type=src_repo_type, token=hf_token)
if not Path(file).exists(): continue
if Path(file).is_dir(): # unused for now
api.upload_folder(repo_id=dst_repo, folder_path=file, path_in_repo=f"{subfolder}/{path}" if subfolder else path,
repo_type=dst_repo_type, token=hf_token)
elif Path(file).is_file():
api.upload_file(repo_id=dst_repo, path_or_fileobj=file, path_in_repo=f"{subfolder}/{path}" if subfolder else path,
repo_type=dst_repo_type, token=hf_token)
if Path(file).exists(): Path(file).unlink()
progress(1, desc="Duplicated.")
return f"{get_hf_url(dst_repo, dst_repo_type)}/tree/main/{subfolder}" if subfolder else get_hf_url(dst_repo, dst_repo_type)
except Exception as e:
print(f"Error: Failed to duplicate repo {src_repo} to {dst_repo}. {e}")
return ""
BASE_DIR = str(Path(__file__).resolve().parent.resolve())
CIVITAI_API_KEY = os.environ.get("CIVITAI_API_KEY")
def get_file(url: str, path: str): # requires aria2, gdown
print(f"Downloading {url} to {path}...")
get_download_file(path, url, CIVITAI_API_KEY)
def git_clone(url: str, path: str, pip: bool=False, addcmd: str=""): # requires git
os.makedirs(str(Path(BASE_DIR, path)), exist_ok=True)
os.chdir(Path(BASE_DIR, path))
print(f"Cloning {url} to {path}...")
cmd = f'git clone {url}'
print(f'Running {cmd} at {Path.cwd()}')
i = subprocess.run(cmd, shell=True).returncode
if i != 0: print(f'Error occured at running {cmd}')
p = url.split("/")[-1]
if not Path(p).exists: return
if pip:
os.chdir(Path(BASE_DIR, path, p))
cmd = f'pip install -r requirements.txt'
print(f'Running {cmd} at {Path.cwd()}')
i = subprocess.run(cmd, shell=True).returncode
if i != 0: print(f'Error occured at running {cmd}')
if addcmd:
os.chdir(Path(BASE_DIR, path, p))
cmd = addcmd
print(f'Running {cmd} at {Path.cwd()}')
i = subprocess.run(cmd, shell=True).returncode
if i != 0: print(f'Error occured at running {cmd}')
def run(cmd: str, timeout: float=0):
print(f'Running {cmd} at {Path.cwd()}')
if timeout == 0:
i = subprocess.run(cmd, shell=True).returncode
if i != 0: print(f'Error occured at running {cmd}')
else:
p = subprocess.Popen(cmd, shell=True)
time.sleep(timeout)
p.terminate()
print(f'Terminated in {timeout} seconds')