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