Initial commit

This commit is contained in:
Will Miao
2025-01-25 19:22:02 +08:00
commit ad6137d355
13 changed files with 1069 additions and 0 deletions

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.gitignore vendored Normal file
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__pycache__/

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__init__.py Normal file
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from .nodes import LorasEndpoint
NODE_CLASS_MAPPINGS = {
"LorasEndpoint": LorasEndpoint
}
WEB_DIRECTORY = "./js"
# Add custom websocket event type
EXTENSION_WEB_SOCKET_MESSAGE_TYPES = ["lora-scan-progress"]
__all__ = ['NODE_CLASS_MAPPINGS']

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manifest.json Normal file
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{
"name": "Loras Endpoint",
"version": "1.0.0",
"author": "Your Name",
"project": "https://github.com/your/repository",
"description": "Adds /loras endpoint to ComfyUI"
}

326
nodes.py Normal file
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# nodes.py 更新后的核心代码
import os
import json
import time
from pathlib import Path
from aiohttp import web
from server import PromptServer
import jinja2
from flask import jsonify, request
from safetensors import safe_open
from .utils.file_utils import get_file_info, save_metadata, load_metadata, update_civitai_metadata
from .utils.lora_metadata import extract_lora_metadata
from typing import Dict, Optional
class LorasEndpoint:
def __init__(self):
self.template_env = jinja2.Environment(
loader=jinja2.FileSystemLoader(
os.path.join(os.path.dirname(__file__), 'templates')
),
autoescape=True
)
# 配置Loras根目录根据实际安装位置调整
self.loras_root = os.path.join(Path(__file__).parents[2], "models", "loras")
@classmethod
def add_routes(cls):
instance = cls()
app = PromptServer.instance.app
static_path = os.path.join(os.path.dirname(__file__), 'static')
app.add_routes([
web.get('/loras', instance.handle_loras_request),
web.static('/loras_static/previews', instance.loras_root),
web.static('/loras_static', static_path),
web.post('/api/delete_model', instance.delete_model)
])
def send_progress(self, current, total, status="Scanning"):
"""Send progress through websocket"""
if self.server and hasattr(self.server, 'send_sync'):
self.server.send_sync("lora-scan-progress", {
"value": current,
"max": total,
"status": status
})
async def scan_loras(self):
"""扫描Loras目录并返回结构化数据"""
loras = []
folders = set()
# 遍历Loras目录包含子目录
for root, _, files in os.walk(self.loras_root):
rel_path = os.path.relpath(root, self.loras_root)
if rel_path == ".":
current_folder = "root"
else:
current_folder = rel_path.replace(os.sep, "/")
folders.add(current_folder)
for file in files:
safetensors_files = [f for f in files if f.endswith('.safetensors')]
total_files = len(safetensors_files)
# 识别模型文件
if file.endswith('.safetensors'):
base_name = os.path.splitext(file)[0]
model_path = os.path.join(root, file)
# Get basic file info and metadata
file_info = await get_file_info(model_path)
base_model_info = await extract_lora_metadata(model_path)
file_info.update(base_model_info)
# Load existing metadata or create new one
metadata = await load_metadata(model_path)
if not metadata:
# First time scanning this file
await save_metadata(model_path, file_info)
metadata = file_info
else:
# Update basic file info in existing metadata
metadata.update(file_info)
await save_metadata(model_path, metadata)
# Add civitai data to return value if exists
if 'civitai' in metadata:
metadata.update(metadata['civitai'])
# 查找预览图
preview_path = os.path.join(root, f"{base_name}.preview.png")
preview_url = await self.get_preview_url(preview_path, root) if os.path.exists(preview_path) else None
loras.append({
"name": base_name,
"folder": current_folder,
"path": model_path,
"preview_url": preview_url,
"metadata": metadata,
"size": os.path.getsize(model_path),
"modified": os.path.getmtime(model_path)
})
self.send_progress(total_files, total_files, "Scan completed")
return {
"loras": sorted(loras, key=lambda x: x["name"].lower()),
"folders": sorted(folders)
}
async def parse_model_metadata(self, file_path):
"""从safetensors文件中提取元数据"""
try:
with safe_open(file_path, framework="pt", device="cpu") as f:
metadata = f.metadata()
if metadata:
return metadata
except Exception as e:
print(f"Error reading metadata from {file_path}: {str(e)}")
return {}
async def parse_metadata(self, meta_file):
"""解析元数据文件"""
try:
if os.path.exists(meta_file):
with open(meta_file, 'r', encoding='utf-8') as f:
meta = json.load(f)
return {
"id": meta.get("id"),
"modelId": meta.get("modelId"),
"model": meta.get("model", {}).get("name"),
"base_model": meta.get("baseModel"),
"trained_words": meta.get("trainedWords", []),
"creator": meta.get("creator", {}).get("username"),
"downloads": meta.get("stats", {}).get("downloadCount", 0),
"images": [img["url"] for img in meta.get("images", [])[:3]],
"description": self.clean_description(
meta.get("model", {}).get("description", "")
)
}
except Exception as e:
print(f"Error parsing metadata {meta_file}: {str(e)}")
return {}
def clean_description(self, desc):
"""清理HTML格式的描述"""
return desc.replace("<p>", "").replace("</p>", "\n").strip()
async def get_preview_url(self, preview_path, root_dir):
"""生成预览图URL"""
if os.path.exists(preview_path):
rel_path = os.path.relpath(preview_path, self.loras_root)
return f"/loras_static/previews/{rel_path.replace(os.sep, '/')}"
return "/loras_static/images/no-preview.png"
async def handle_loras_request(self, request):
"""处理Loras请求并渲染模板"""
try:
scan_start = time.time()
data = await self.scan_loras()
print(f"Scanned {len(data['loras'])} loras in {time.time()-scan_start:.2f}s")
# Format the data for the template
formatted_loras = [self.format_lora(l) for l in data["loras"]]
# Debug logging
if formatted_loras:
print(f"Sample lora data: {formatted_loras[0]}")
else:
print("Warning: No loras found")
context = {
"folders": data.get("folders", []),
"loras": formatted_loras,
# Only set single lora if we're viewing details
"lora": formatted_loras[0] if formatted_loras else {
"name": "",
"folder": "",
"file_name": "",
"preview_url": "",
"modified": "",
"size": "0MB",
"meta": {
"id": "",
"model": "",
"base_model": "",
"trained_words": [],
"creator": "",
"downloads": 0,
"images": [],
"description": ""
}
}
}
template = self.template_env.get_template('loras.html')
rendered = template.render(**context)
return web.Response(
text=rendered,
content_type='text/html'
)
except Exception as e:
print(f"Error handling loras request: {str(e)}")
import traceback
print(traceback.format_exc()) # Print full stack trace
return web.Response(
text="Error loading loras page",
content_type='text/html',
status=500
)
def format_lora(self, lora):
"""格式化前端需要的数据结构"""
try:
metadata = lora.get("metadata", {})
return {
"name": lora["name"],
"folder": lora["folder"],
"preview_url": lora["preview_url"],
"modified": time.strftime("%Y-%m-%d %H:%M",
time.localtime(lora["modified"])),
"size": f"{lora['size']/1024/1024:.1f}MB",
"meta": {
"id": metadata.get("id", ""),
"modelId": metadata.get("modelId", ""),
"model": metadata.get("model", ""),
"base_model": metadata.get("base_model", ""),
"trained_words": metadata.get("trained_words", []),
"creator": metadata.get("creator", ""),
"downloads": metadata.get("downloads", 0),
"images": metadata.get("images", []),
"description": metadata.get("description", "")
}
}
except Exception as e:
print(f"Error formatting lora: {str(e)}")
print(f"Lora data: {lora}")
return {
"name": lora.get("name", "Unknown"),
"folder": lora.get("folder", ""),
"preview_url": lora.get("preview_url", ""),
"modified": "",
"size": "0MB",
"meta": {
"id": "",
"modelId": "",
"model": "",
"base_model": "",
"trained_words": [],
"creator": "",
"downloads": 0,
"images": [],
"description": ""
}
}
async def delete_model(self, request):
try:
data = await request.json()
model_name = data.get('model_name')
folder = data.get('folder') # 从请求中获取folder信息
if not model_name:
return web.Response(text='Model name is required', status=400)
# 构建完整的目录路径
target_dir = self.loras_root
if folder and folder != "root":
target_dir = os.path.join(self.loras_root, folder)
# List of file patterns to delete
required_file = f"{model_name}.safetensors" # 主文件必须存在
optional_files = [ # 这些文件可能不存在
f"{model_name}.civitai.info",
f"{model_name}.preview.png"
]
deleted_files = []
# Try to delete the main safetensors file
main_file_path = os.path.join(target_dir, required_file)
if os.path.exists(main_file_path):
try:
os.remove(main_file_path)
deleted_files.append(required_file)
except Exception as e:
print(f"Error deleting {main_file_path}: {str(e)}")
return web.Response(text=f"Failed to delete main model file: {str(e)}", status=500)
# Only try to delete optional files if main file was deleted
for pattern in optional_files:
file_path = os.path.join(target_dir, pattern)
if os.path.exists(file_path):
try:
os.remove(file_path)
deleted_files.append(pattern)
except Exception as e:
print(f"Error deleting optional file {file_path}: {str(e)}")
else:
return web.Response(text=f"Model file {required_file} not found in {folder}", status=404)
return web.json_response({
'success': True,
'deleted_files': deleted_files
})
except Exception as e:
return web.Response(text=str(e), status=500)
async def update_civitai_info(self, file_path: str, civitai_data: Dict, preview_url: Optional[str] = None):
"""Update Civitai metadata and download preview image"""
# Update metadata file
await update_civitai_metadata(file_path, civitai_data)
# Download and save preview image if URL is provided
if preview_url:
preview_path = f"{os.path.splitext(file_path)[0]}.preview.png"
try:
# Add your image download logic here
# Example:
# await download_image(preview_url, preview_path)
pass
except Exception as e:
print(f"Error downloading preview image: {str(e)}")
# 注册路由
LorasEndpoint.add_routes()

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:root {
--bg-color: #ffffff;
--text-color: #333333;
--card-bg: #ffffff;
--border-color: #e0e0e0;
}
[data-theme="dark"] {
--bg-color: #1a1a1a;
--text-color: #e0e0e0;
--card-bg: #2d2d2d;
--border-color: #404040;
}
body {
margin: 0;
font-family: 'Segoe UI', sans-serif;
background: var(--background-color);
}
.container {
max-width: 1400px;
margin: 20px auto;
padding: 0 15px;
}
/* 文件夹标签样式 */
.folder-tags {
display: flex;
gap: 8px;
overflow-x: auto;
padding: 10px 0;
}
.tag {
padding: 6px 12px;
border-radius: 20px;
background: #e0e0e0;
cursor: pointer;
white-space: nowrap;
transition: all 0.3s;
}
.tag.active {
background: var(--primary-color);
color: white;
}
/* 卡片网格布局 */
.card-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(240px, 1fr));
gap: 12px;
margin-top: 20px;
}
.lora-card {
background: var(--card-bg);
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
overflow: hidden;
transition: transform 0.2s;
aspect-ratio: 896/1152;
max-width: 240px;
margin: 0 auto;
}
.lora-card:hover {
transform: translateY(-5px);
}
/* Card Preview and Footer Overlay */
.card-preview {
position: relative;
width: 100%;
height: 100%;
}
.card-preview img {
width: 100%;
height: 100%;
object-fit: cover;
}
.card-footer {
position: absolute;
bottom: 0;
left: 0;
right: 0;
background: linear-gradient(transparent, rgba(0, 0, 0, 0.85));
color: white;
padding: 15px;
display: flex;
justify-content: space-between;
align-items: flex-end;
min-height: 80px;
}
.model-name {
font-weight: bold;
text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.5);
}
.model-meta {
font-size: 0.9em;
opacity: 0.9;
}
.card-header {
position: absolute;
top: 0;
left: 0;
right: 0;
background: linear-gradient(rgba(0, 0, 0, 0.85), transparent);
color: white;
padding: 15px;
display: flex;
justify-content: space-between;
align-items: center;
z-index: 1;
}
.card-actions i {
margin-left: 10px;
cursor: pointer;
color: white;
transition: opacity 0.2s;
}
.card-actions i:hover {
opacity: 0.8;
}
/* 响应式设计 */
@media (max-width: 768px) {
.card-grid {
grid-template-columns: 1fr;
}
.controls {
flex-direction: column;
gap: 15px;
}
}
/* 新增元数据相关样式 */
.model-info {
flex: 1;
}
.model-meta {
font-size: 0.8em;
color: #666;
margin-top: 4px;
}
.base-model {
display: inline-block;
background: #f0f0f0;
padding: 2px 6px;
border-radius: 4px;
margin-right: 6px;
}
.file-size,
.modified {
display: block;
margin-top: 2px;
}
.tooltip {
position: relative;
cursor: help;
}
.tooltip::after {
content: attr(data-tooltip);
position: absolute;
bottom: 120%;
left: 50%;
transform: translateX(-50%);
background: rgba(0, 0, 0, 0.8);
color: white;
padding: 4px 8px;
border-radius: 4px;
font-size: 0.8em;
white-space: nowrap;
opacity: 0;
transition: opacity 0.2s;
pointer-events: none;
}
.tooltip:hover::after {
opacity: 1;
}
/* 模态窗口样式 */
.modal {
display: none;
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: rgba(0, 0, 0, 0.8);
z-index: 1000;
overflow-y: auto; /* 允许模态窗口内容滚动 */
}
/* 当模态窗口打开时禁止body滚动 */
body.modal-open {
overflow: hidden;
}
.modal-content {
position: relative;
max-width: 800px;
margin: 2rem auto;
background: var(--card-bg);
border-radius: 12px;
padding: 20px;
}
.carousel {
display: grid;
grid-auto-flow: column;
gap: 1rem;
overflow-x: auto;
scroll-snap-type: x mandatory;
}
.carousel img {
scroll-snap-align: start;
max-height: 60vh;
object-fit: contain;
}
/* 主题切换按钮 */
.theme-toggle {
position: fixed;
top: 20px;
right: 20px;
cursor: pointer;
padding: 8px;
border-radius: 50%;
background: var(--card-bg);
}
.base-model-label {
max-width: 120px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
display: inline-block;
color: white;
text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.5);
background: rgba(255, 255, 255, 0.2);
padding: 2px 8px;
border-radius: 4px;
backdrop-filter: blur(2px);
}
.loading-overlay {
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: rgba(0, 0, 0, 0.7);
display: flex;
justify-content: center;
align-items: center;
z-index: 1000;
}
.loading-content {
background: #fff;
padding: 2rem;
border-radius: 8px;
text-align: center;
}
.loading-spinner {
border: 4px solid #f3f3f3;
border-top: 4px solid #3498db;
border-radius: 50%;
width: 40px;
height: 40px;
animation: spin 1s linear infinite;
margin: 0 auto 1rem;
}
.loading-status {
margin-bottom: 1rem;
color: #333;
}
.progress-container {
width: 300px;
background-color: #f0f0f0;
border-radius: 4px;
overflow: hidden;
}
.progress-bar {
width: 0%;
height: 20px;
background-color: #4CAF50;
transition: width 0.3s ease;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}

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<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
<circle cx="12" cy="12" r="5"/>
<path d="M12 1v2"/>
<path d="M12 21v2"/>
<path d="M4.22 4.22l1.42 1.42"/>
<path d="M18.36 18.36l1.42 1.42"/>
<path d="M1 12h2"/>
<path d="M21 12h2"/>
<path d="M4.22 19.78l1.42-1.42"/>
<path d="M18.36 5.64l1.42-1.42"/>
</svg>

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// 排序功能
function sortCards(sortBy) {
const grid = document.getElementById('loraGrid');
const cards = Array.from(grid.children);
cards.sort((a, b) => {
switch(sortBy) {
case 'name':
return a.dataset.name.localeCompare(b.dataset.name);
case 'date':
return new Date(b.dataset.date) - new Date(a.dataset.date);
case 'size':
return parseFloat(b.dataset.size) - parseFloat(a.dataset.size);
}
});
cards.forEach(card => grid.appendChild(card));
}
// 文件夹筛选
document.querySelectorAll('.tag').forEach(tag => {
tag.addEventListener('click', () => {
document.querySelectorAll('.tag').forEach(t => t.classList.remove('active'));
tag.classList.add('active');
const folder = tag.dataset.folder;
filterByFolder(folder);
});
});
function filterByFolder(folder) {
document.querySelectorAll('.lora-card').forEach(card => {
card.style.display = card.dataset.folder === folder ? 'block' : 'none';
});
}
// 刷新功能
async function refreshLoras() {
try {
const response = await fetch('/loras?refresh=true');
if (response.ok) {
location.reload();
}
} catch (error) {
console.error('Refresh failed:', error);
}
}
// 占位功能函数
function openCivitai(loraName) {
// 从卡片的data-meta属性中获取civitai ID
const loraCard = document.querySelector(`.lora-card[data-name="${loraName}"]`);
if (!loraCard) return;
const metaData = JSON.parse(loraCard.dataset.meta);
const civitaiId = metaData.modelId; // 使用modelId作为civitai模型ID
const versionId = metaData.id; // 使用id作为版本ID
// 构建URL
if (civitaiId) {
let url = `https://civitai.com/models/${civitaiId}`;
if (versionId) {
url += `?modelVersionId=${versionId}`;
}
window.open(url, '_blank');
} else {
// 如果没有ID尝试使用名称搜索
window.open(`https://civitai.com/models?query=${encodeURIComponent(loraName)}`, '_blank');
}
}
async function deleteModel(modelName) {
// Prevent event bubbling
event.stopPropagation();
// Get the folder from the card's data attributes
const card = document.querySelector(`.lora-card[data-name="${modelName}"]`);
const folder = card ? card.dataset.folder : null;
// Show confirmation dialog
const confirmed = confirm(`Are you sure you want to delete "${modelName}" and all associated files?`);
if (confirmed) {
try {
const response = await fetch('/api/delete_model', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
model_name: modelName,
folder: folder
})
});
if (response.ok) {
// Remove the card from UI
if (card) {
card.remove();
}
// Show success message
alert('Model deleted successfully');
} else {
const error = await response.text();
alert(`Failed to delete model: ${error}`);
}
} catch (error) {
alert(`Error deleting model: ${error}`);
}
}
}
// 初始化排序
document.getElementById('sortSelect').addEventListener('change', (e) => {
sortCards(e.target.value);
});
// 添加搜索功能
document.getElementById('searchInput')?.addEventListener('input', (e) => {
const term = e.target.value.toLowerCase();
document.querySelectorAll('.lora-card').forEach(card => {
const match = card.dataset.name.toLowerCase().includes(term) ||
card.dataset.folder.toLowerCase().includes(term);
card.style.display = match ? 'block' : 'none';
});
});
// 模态窗口管理
let currentLora = null;
let currentImageIndex = 0;
document.querySelectorAll('.lora-card').forEach(card => {
card.addEventListener('click', () => {
currentLora = JSON.parse(card.dataset.meta);
showModal(currentLora);
});
});
function showModal(lora) {
const modal = document.getElementById('loraModal');
modal.innerHTML = `
<div class="modal-content">
<h2>${lora.name}</h2>
<div class="carousel">
${lora.images.map(img => `<img src="${img}" alt="Preview">`).join('')}
</div>
<div class="description">${lora.description}</div>
<button class="close" onclick="closeModal()">&times;</button>
</div>
`;
modal.style.display = 'block';
document.body.classList.add('modal-open');
// 添加点击事件监听器
modal.onclick = function(event) {
// 如果点击的是模态窗口的背景(不是内容区域),则关闭模态窗口
if (event.target === modal) {
closeModal();
}
};
}
function closeModal() {
const modal = document.getElementById('loraModal');
modal.style.display = 'none';
document.body.classList.remove('modal-open');
// 移除点击事件监听器
modal.onclick = null;
}
// WebSocket handling for progress updates
document.addEventListener('DOMContentLoaded', function() {
const loadingOverlay = document.getElementById('loading-overlay');
const progressBar = document.querySelector('.progress-bar');
const loadingStatus = document.querySelector('.loading-status');
// Show loading overlay initially
loadingOverlay.style.display = 'flex';
// Listen for progress updates
api.addEventListener("lora-scan-progress", (event) => {
const data = event.detail;
const progress = (data.value / data.max) * 100;
progressBar.style.width = `${progress}%`;
progressBar.setAttribute('aria-valuenow', progress);
loadingStatus.textContent = data.status;
if (data.value === data.max) {
// Hide loading overlay when scan is complete
setTimeout(() => {
loadingOverlay.style.display = 'none';
}, 500);
}
});
});
// 主题切换
function toggleTheme() {
const theme = document.body.dataset.theme || 'light';
document.body.dataset.theme = theme === 'light' ? 'dark' : 'light';
localStorage.setItem('theme', document.body.dataset.theme);
}
// 初始化主题
function initTheme() {
const savedTheme = localStorage.getItem('theme') || 'light';
document.body.dataset.theme = savedTheme;
}
// 检测系统主题
window.matchMedia('(prefers-color-scheme: dark)').addListener(e => {
document.body.dataset.theme = e.matches ? 'dark' : 'light';
});
// 键盘导航
document.addEventListener('keydown', (e) => {
if (e.key === 'Escape') closeModal();
if (e.key === 'ArrowLeft') prevImage();
if (e.key === 'ArrowRight') nextImage();
});
// 图片预加载
function preloadImages(urls) {
urls.forEach(url => {
new Image().src = url;
});
}
initTheme();

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templates/loras.html Normal file
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<!DOCTYPE html>
<html>
<head>
<title>LoRA Management</title>
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" href="/loras_static/css/style.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
</head>
<body>
<div class="theme-toggle" onclick="toggleTheme()">
<img src="/loras_static/images/theme-toggle.svg" alt="Theme">
</div>
<!-- 添加模态窗口 -->
<div id="loraModal" class="modal"></div>
<div class="container">
<!-- 控制栏 -->
<div class="controls">
<div class="folder-tags">
{% for folder in folders %}
<div class="tag" data-folder="{{ folder }}">{{ folder }}</div>
{% endfor %}
</div>
<div class="actions">
<select id="sortSelect">
<option value="name">Name</option>
<option value="date">Date</option>
<option value="size">Size</option>
</select>
<button onclick="refreshLoras()"><i class="fas fa-sync"></i> Refresh</button>
<button onclick="fetchCivitai()" class="secondary"><i class="fas fa-download"></i> Fetch</button>
</div>
</div>
<!-- Lora卡片容器 -->
<div class="card-grid" id="loraGrid">
{% for lora in loras %}
<!-- 在卡片部分更新元数据展示 -->
<div class="lora-card" data-folder="{{ lora.folder }}" data-name="{{ lora.name }}" data-date="{{ lora.modified }}"
data-size="{{ lora.size }}" data-meta="{{ lora.meta | default({}) | tojson | forceescape }}">
<div class="card-preview">
<img src="{{ lora.preview_url or '/loras_static/images/no-preview.png' }}" alt="{{ lora.name }}">
<div class="card-header">
<span class="base-model-label" title="{{ lora.meta.base_model if lora.meta else 'Unknown' }}">
{{ lora.meta.base_model if lora.meta and lora.meta.base_model else 'Unknown' }}
</span>
<div class="card-actions">
<i class="fas fa-globe"
title="View on Civitai"
onclick="event.stopPropagation(); openCivitai('{{ lora.name }}')"></i>
<i class="fas fa-copy"
title="Copy Model Name"
onclick="event.stopPropagation(); navigator.clipboard.writeText(this.closest('.lora-card').dataset.name)"></i>
<i class="fas fa-trash"
title="Delete Model"
onclick="event.stopPropagation(); deleteModel('{{ lora.name }}')"></i>
</div>
</div>
<div class="card-footer">
<div class="model-info">
<span class="model-name">{{ lora.name }}</span>
</div>
<div class="card-actions">
<i class="fas fa-image"
title="Replace Preview Image"
onclick="event.stopPropagation(); replacePreview('{{ lora.name }}')"></i>
</div>
</div>
</div>
</div>
{% endfor %}
</div>
</div>
<script src="/loras_static/js/script.js"></script>
</body>
</html>

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# Empty file to mark directory as Python package

48
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import os
import hashlib
import json
from typing import Dict, Optional
async def calculate_sha256(file_path: str) -> str:
"""Calculate SHA256 hash of a file"""
sha256_hash = hashlib.sha256()
with open(file_path, "rb") as f:
for byte_block in iter(lambda: f.read(4096), b""):
sha256_hash.update(byte_block)
return sha256_hash.hexdigest()
async def get_file_info(file_path: str) -> Dict:
"""Get basic file information"""
return {
"name": os.path.splitext(os.path.basename(file_path))[0],
"file_path": file_path,
"size": os.path.getsize(file_path),
"modified": os.path.getmtime(file_path),
"sha256": await calculate_sha256(file_path)
}
async def save_metadata(file_path: str, metadata: Dict) -> None:
"""Save metadata to .metadata.json file"""
metadata_path = f"{os.path.splitext(file_path)[0]}.metadata.json"
try:
with open(metadata_path, 'w', encoding='utf-8') as f:
json.dump(metadata, f, indent=2, ensure_ascii=False)
except Exception as e:
print(f"Error saving metadata to {metadata_path}: {str(e)}")
async def load_metadata(file_path: str) -> Dict:
"""Load metadata from .metadata.json file"""
metadata_path = f"{os.path.splitext(file_path)[0]}.metadata.json"
try:
if os.path.exists(metadata_path):
with open(metadata_path, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
print(f"Error loading metadata from {metadata_path}: {str(e)}")
return {}
async def update_civitai_metadata(file_path: str, civitai_data: Dict) -> None:
"""Update metadata file with Civitai data"""
metadata = await load_metadata(file_path)
metadata['civitai'] = civitai_data
await save_metadata(file_path, metadata)

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from safetensors import safe_open
from typing import Dict
from .model_utils import determine_base_model
async def extract_lora_metadata(file_path: str) -> Dict:
"""Extract essential metadata from safetensors file"""
try:
with safe_open(file_path, framework="pt", device="cpu") as f:
metadata = f.metadata()
if metadata:
# Only extract base_model from ss_base_model_version
base_model = determine_base_model(metadata.get("ss_base_model_version"))
return {"base_model": base_model}
except Exception as e:
print(f"Error reading metadata from {file_path}: {str(e)}")
return {"base_model": "Unknown"}

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from typing import Dict, Optional
# Base model mapping based on version string
BASE_MODEL_MAPPING = {
"sd-v1-5": "SD1.5",
"sd-v2-1": "SD2.1",
"sdxl": "SDXL",
"sd-v2": "SD2.0",
"flux1": "Flux1.D",
}
def determine_base_model(version_string: Optional[str]) -> str:
"""Determine base model from version string in safetensors metadata"""
if not version_string:
return "Unknown"
version_lower = version_string.lower()
for key, value in BASE_MODEL_MAPPING.items():
if key in version_lower:
return value
return "Unknown"