410 lines
19 KiB
Python
410 lines
19 KiB
Python
import os
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import sys
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try:
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sys.stdout.reconfigure(encoding="utf-8")
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except:
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pass
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try:
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sys.stderr.reconfigure(encoding="utf-8")
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except:
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pass
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import time
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import json
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import hashlib
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import re
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import requests
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import argparse
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import shutil
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from typing import Dict, Optional
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# ==============================================================================
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# CIVITAI API 配置读取
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# 请在插件目录 (Anomalous_Model_Browser) 下新建 config.json 文件：
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# { "CIVITAI_API_KEY": "你的KEY" }
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# ==============================================================================
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CIVITAI_API_KEY = None
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config_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "config.json")
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if os.path.exists(config_path):
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try:
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with open(config_path, 'r', encoding='utf-8') as f:
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cfg = json.load(f)
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CIVITAI_API_KEY = cfg.get("CIVITAI_API_KEY", "").strip()
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except Exception as e:
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print(f"[-] 读取 config.json 失败: {e}")
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else:
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print("[!] 未找到 config.json，本次请求将不使用 API Key。部分限制级模型或将无法获取图片。")
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def calculate_sha256(file_path: str) -> str:
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"""计算文件的 SHA256 哈希值 (用于 Civitai 匹配)"""
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sha256_hash = hashlib.sha256()
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print(f"[*] 正在计算 Hash (大文件可能需要几分钟): {os.path.basename(file_path)}")
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with open(file_path, "rb") as f:
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for byte_block in iter(lambda: f.read(4096 * 1024), b""):
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sha256_hash.update(byte_block)
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return sha256_hash.hexdigest()
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import struct
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def extract_safetensors_hash(file_path: str) -> Optional[str]:
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"""尝试从 safetensors 头文件中以 O(1) 速度提取内置的 Hash，跳过全量计算"""
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try:
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with open(file_path, "rb") as f:
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header_size_bytes = f.read(8)
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if len(header_size_bytes) < 8:
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return None
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header_size = struct.unpack('<Q', header_size_bytes)[0]
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if header_size > 100 * 1024 * 1024: # 异常大小保护 (头文件大于100MB)
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return None
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header_json_bytes = f.read(header_size)
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header_str = header_json_bytes.decode('utf-8')
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header_json = json.loads(header_str)
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metadata = header_json.get('__metadata__', {})
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if not metadata:
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return None
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# 优先级1: 标准 modelspec
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if 'modelspec.hash.sha256' in metadata:
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return metadata['modelspec.hash.sha256']
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if 'modelspec.hash.blake3' in metadata:
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return metadata['modelspec.hash.blake3']
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# 优先级2: 其他带 hash 的键
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for k, v in metadata.items():
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if ('hash' in k.lower() or 'civitai' in k.lower()) and isinstance(v, str):
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if len(v) == 64 and all(c in '0123456789abcdefABCDEF' for c in v):
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return v
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except Exception as e:
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pass
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return None
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def infer_base_model_from_header(file_path: str) -> str:
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"""从 safetensors 头文件的张量键名推断底层 Base Model (用于脱机/HuggingFace 兼容)"""
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try:
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with open(file_path, "rb") as f:
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header_size_bytes = f.read(8)
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if len(header_size_bytes) < 8: return 'Unknown'
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header_size = struct.unpack('<Q', header_size_bytes)[0]
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if header_size > 100 * 1024 * 1024: return 'Unknown'
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header_json = json.loads(f.read(header_size).decode('utf-8'))
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# 1. 尝试从 __metadata__ 提取
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metadata = header_json.get('__metadata__', {})
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arch = metadata.get('modelspec.architecture', '')
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if 'stable-diffusion-xl' in arch.lower(): return 'SDXL'
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if 'stable-diffusion-v1' in arch.lower() or 'runwayml/stable-diffusion-v1-5' in arch.lower(): return 'SD 1.5'
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if 'flux' in arch.lower(): return 'Flux.1 D'
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if 'sd3' in arch.lower(): return 'SD3'
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# 2. 暴力张量键名指纹匹配 (Tensor Fingerprinting)
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# 把前 500 个键拼接成字符串以提高检索效率，大部分核心键都在前面
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keys_str = " ".join(list(header_json.keys())[:500])
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# Flux 指纹
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if 'double_blocks.0.img_attn' in keys_str or 'img_in.weight' in keys_str: return 'Flux.1 D'
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# SD3 指纹
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if 'joint_blocks.0.x_block' in keys_str: return 'SD3'
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# SDXL 指纹 (包含两套 text encoder)
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if 'conditioner.embedders.1.model' in keys_str or 'label_emb.0.0.weight' in keys_str: return 'SDXL'
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# SD 1.5 指纹
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if 'cond_stage_model.transformer.text_model' in keys_str or 'model.diffusion_model.input_blocks.0.0.weight' in keys_str: return 'SD 1.5'
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return 'Unknown'
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except Exception as e:
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print(f"[-] 离线底模推断失败: {e}")
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return 'Unknown'
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def sanitize_filename(name: str) -> str:
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"""清理文件名中的非法字符"""
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name = re.sub(r'[\r\n\t]+', ' ', name)
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name = re.sub(r'[\\/*?:"<>|#]', "", name)
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return name.strip(' .')
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def fetch_civitai_info(file_hash: str, max_retries: int = 3) -> Optional[Dict]:
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"""向 Civitai API 获取模型信息，支持重试机制"""
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url = f"https://civitai.com/api/v1/model-versions/by-hash/{file_hash}"
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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if CIVITAI_API_KEY:
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headers["Authorization"] = f"Bearer {CIVITAI_API_KEY}"
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for attempt in range(max_retries):
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try:
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response = requests.get(url, headers=headers, timeout=15)
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if response.status_code == 200:
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return response.json()
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elif response.status_code == 404:
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print(f"\033[93m[Skip] 模型 Hash {file_hash} 未在 Civitai 找到 (404)，已跳过。\033[0m")
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return None
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else:
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print(f"[-] 请求异常，状态码: {response.status_code} (尝试 {attempt+1}/{max_retries})")
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except requests.exceptions.RequestException as e:
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print(f"[-] 网络请求超时或异常: {e} (尝试 {attempt+1}/{max_retries})")
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if attempt < max_retries - 1:
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time.sleep(2)
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print(f"\033[93m[Skip] 模型 Hash {file_hash} 网络重试失败，已跳过该文件。\033[0m")
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return None
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def download_media(url: str, base_path: str, max_retries: int = 3):
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"""下载图片或视频并自动识别扩展名"""
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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if CIVITAI_API_KEY:
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headers["Authorization"] = f"Bearer {CIVITAI_API_KEY}"
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for attempt in range(max_retries):
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try:
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response = requests.get(url, stream=True, headers=headers, timeout=15)
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if response.status_code == 200:
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content_type = response.headers.get("Content-Type", "").lower()
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ext = ".png" # default
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if "video/mp4" in content_type: ext = ".mp4"
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elif "video/webm" in content_type: ext = ".webm"
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elif "image/jpeg" in content_type: ext = ".jpg"
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elif "image/webp" in content_type: ext = ".webp"
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elif url.endswith(".mp4"): ext = ".mp4"
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final_path = base_path + ext
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with open(final_path, 'wb') as f:
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for chunk in response.iter_content(8192):
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f.write(chunk)
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return final_path
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else:
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print(f"[-] 媒体下载失败，状态码: {response.status_code} (尝试 {attempt+1}/{max_retries})")
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except requests.exceptions.RequestException as e:
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print(f"[-] 媒体下载网络异常: {e} (尝试 {attempt+1}/{max_retries})")
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return None
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def main():
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parser = argparse.ArgumentParser(description="ComfyUI 模型 Civitai 嗅探与重命名工具")
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parser.add_argument("folder", help="要扫描的文件夹路径 (例如: models/checkpoints)")
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parser.add_argument("--dry-run", action="store_true", help="空跑模式，仅打印将要执行的操作，不修改任何文件")
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parser.add_argument("--undo", action="store_true", help="根据 backup_rename_log.json 恢复文件名")
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parser.add_argument("--skip-rename", action="store_true", help="只下载信息文件，不重命名主文件")
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parser.add_argument("--skip-media", action="store_true", help="不下载预览图或视频")
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args = parser.parse_args()
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target_folder = args.folder
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if not os.path.isdir(target_folder):
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print(f"[-] 错误: 文件夹不存在 -> {target_folder}")
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sys.exit(1)
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backup_log_path = os.path.join(target_folder, "backup_rename_log.json")
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# ==========================
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# 模式一：Undo 回滚模式
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# ==========================
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if args.undo:
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if not os.path.exists(backup_log_path):
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print("[-] 未找到备份日志 backup_rename_log.json，无法撤销。")
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sys.exit(1)
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with open(backup_log_path, 'r', encoding='utf-8') as f:
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log_data = json.load(f)
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print("[*] 开始回滚文件名...")
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for old_path, new_path in log_data.items():
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if os.path.exists(new_path):
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print(f"[*] 恢复主文件: {os.path.basename(new_path)} -> {os.path.basename(old_path)}")
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if not args.dry_run:
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os.replace(new_path, old_path)
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else:
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print(f"[-] 找不到被重命名的文件: {new_path}")
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old_base = os.path.splitext(old_path)[0]
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new_base = os.path.splitext(new_path)[0]
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for ext in [".info", ".civitai.info", ".png", ".jpg", ".webp", ".mp4", ".webm", ".json", ".txt", ".yaml"]:
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new_ext_path = new_base + ext
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old_ext_path = old_base + ext
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if os.path.exists(new_ext_path):
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print(f"[*] 恢复配套文件: {os.path.basename(new_ext_path)} -> {os.path.basename(old_ext_path)}")
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if not args.dry_run:
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os.replace(new_ext_path, old_ext_path)
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print("[+] 回滚完成！")
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sys.exit(0)
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# ==========================
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# 模式二：正常嗅探与重命名
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# ==========================
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rename_log = {}
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success_count = 0
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fail_count = 0
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if os.path.exists(backup_log_path):
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with open(backup_log_path, 'r', encoding='utf-8') as f:
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rename_log = json.load(f)
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print(f"[*] 开始扫描文件夹: {target_folder}")
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if args.dry_run:
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print("==================================================")
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print("[警告]: 当前处于 Dry-Run (空跑) 模式，不会修改系统中的任何文件！")
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print("==================================================")
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for root, _, files in os.walk(target_folder):
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for filename in files:
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if not filename.endswith(".safetensors"):
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continue
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file_path = os.path.join(root, filename)
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old_base = os.path.splitext(file_path)[0]
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info_exists = os.path.exists(old_base + ".info") or os.path.exists(old_base + ".civitai.info")
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preview_exists = args.skip_media
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if not preview_exists:
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for ext in [".png", ".preview.png", ".jpg", ".jpeg", ".webp", ".mp4", ".webm"]:
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if os.path.exists(old_base + ext):
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preview_exists = True
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break
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if info_exists and preview_exists:
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print(f"[*] 已跳过 (信息满足要求): {filename}")
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continue
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print(f"\n---> 处理文件: {filename} (位于 {root})")
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file_hash = extract_safetensors_hash(file_path)
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if file_hash:
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print(f"[*] 成功从头文件极速提取 Hash: {file_hash}")
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else:
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file_hash = calculate_sha256(file_path)
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print(f"[*] 全量物理 SHA256: {file_hash}")
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civitai_data = fetch_civitai_info(file_hash)
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if not civitai_data:
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# 尝试离线推断底模
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inferred_base = infer_base_model_from_header(file_path)
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if inferred_base != 'Unknown':
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print(f"[*] 离线推断底模成功 ({filename}): {inferred_base}")
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civitai_data = {
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"id": -1,
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"modelId": -1,
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"name": os.path.splitext(filename)[0],
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"baseModel": inferred_base,
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"description": "<p>Automatically inferred by Anomalous Local Engine.</p>",
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"model": {
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"name": os.path.splitext(filename)[0],
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"type": "LORA" if "lora" in root.lower() else "Checkpoint"
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}
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}
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else:
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fail_count += 1
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continue
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# --- 额外获取模型主页的说明文字 ---
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model_id = civitai_data.get("modelId")
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if model_id and model_id != -1:
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try:
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
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}
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if CIVITAI_API_KEY:
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headers["Authorization"] = f"Bearer {CIVITAI_API_KEY}"
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m_resp = requests.get(f"https://civitai.com/api/v1/models/{model_id}", headers=headers, timeout=10)
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if m_resp.status_code == 200:
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m_data = m_resp.json()
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main_desc = m_data.get("description")
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if main_desc:
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if "model" not in civitai_data or not isinstance(civitai_data["model"], dict):
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civitai_data["model"] = {}
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civitai_data["model"]["description"] = main_desc
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except Exception as e:
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print(f"[-] 获取模型主页详细说明失败: {e}")
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# ----------------------------------
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model_name = sanitize_filename(civitai_data.get("model", {}).get("name", "UnknownModel"))
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version_name = sanitize_filename(civitai_data.get("name", "UnknownVersion"))
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new_filename = f"{model_name}_{version_name}.safetensors"
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new_file_path = os.path.join(root, new_filename)
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new_base = os.path.splitext(new_file_path)[0]
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# ==========================================
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# 兼容性大刀阔斧改革：直接保存全宇宙最原汁原味的格式
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# ==========================================
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info_data = civitai_data
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if not args.dry_run:
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info_path = old_base + ".info"
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with open(info_path, 'w', encoding='utf-8') as f:
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json.dump(info_data, f, ensure_ascii=True, indent=4)
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print(f"[+] 写入纯净版 Civitai 描述 -> .info")
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else:
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print(f"[Dry-Run] 拟生成标准描述信息 -> .info")
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images = civitai_data.get("images", [])
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if images and len(images) > 0:
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media_url = None
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for img_obj in images:
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if not args.skip_media:
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if img_obj.get("url"):
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media_url = img_obj.get("url")
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break
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if media_url and not args.skip_media:
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if not args.dry_run:
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print(f"[*] 正在下载预览媒体...")
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saved_path = download_media(media_url, old_base)
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if saved_path:
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print(f"[+] 媒体下载成功 -> {os.path.basename(saved_path)}")
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else:
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print(f"[Dry-Run] 拟下载预览媒体...")
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if args.skip_rename:
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print(f"[*] --skip-rename 开启，跳过主文件重命名。仅保存 .info。")
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success_count += 1
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elif file_path != new_file_path and new_filename != filename:
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if os.path.exists(new_file_path):
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print(f"\033[91m[-] 目标版本已存在 (重复模型)，执行永久删除多余副本: {filename}\033[0m")
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if not args.dry_run:
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try:
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os.remove(file_path)
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for ext in [".info", ".civitai.info", ".png", ".jpg", ".webp", ".mp4", ".webm", ".json", ".txt", ".yaml"]:
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old_ext = old_base + ext
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if os.path.exists(old_ext):
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os.remove(old_ext)
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except Exception as e:
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print(f"[-] 删除多余副本失败 (可能文件被占用): {e}")
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else:
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print(f"[Dry-Run] 拟永久删除多余副本及其附属文件: {filename}")
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else:
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if not args.dry_run:
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os.rename(file_path, new_file_path)
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rename_log[file_path] = new_file_path
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for ext in [".info", ".civitai.info", ".png", ".jpg", ".webp", ".mp4", ".webm", ".json", ".txt", ".yaml"]:
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old_ext = old_base + ext
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new_ext = new_base + ext
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if os.path.exists(old_ext):
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os.replace(old_ext, new_ext) # Safety: replace overwrites existing files on Windows
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print(f"[+] 重命名完成: {filename} ==> {new_filename}")
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else:
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print(f"[Dry-Run] 拟重命名文件: {filename} ==> {new_filename}")
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print(f"[Dry-Run] 拟连带重命名附属文件 (.info / .png 等)")
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else:
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print("[*] 文件名已符合规范，无需重命名。")
|
|
success_count += 1
|
|
|
|
|
|
# Save scan results
|
|
if not args.dry_run:
|
|
result_path = os.path.join(target_folder, ".scan_result.json")
|
|
try:
|
|
with open(result_path, 'w', encoding='utf-8') as f:
|
|
json.dump({"success": success_count, "fail": fail_count}, f)
|
|
except Exception as e:
|
|
print(f"[-] 保存统计结果失败: {e}")
|
|
|
|
if not args.dry_run and rename_log:
|
|
with open(backup_log_path, 'w', encoding='utf-8') as f:
|
|
json.dump(rename_log, f, ensure_ascii=True, indent=4)
|
|
print(f"\n[+] 重命名映射日志已保存至: {backup_log_path}")
|
|
|
|
if __name__ == "__main__":
|
|
main() |