Delete LTX2.3

LTX2.3/API issues-API问题办法.bat

@@ -1,37 +0,0 @@
-@echo off
-chcp 65001 >nul
-title LTX Local GPU Fix Tool
-
-echo ========================================
-echo    LTX Local GPU Fix Tool
-echo ========================================
-echo.
-
-net session >nul 2>&1
-if %errorlevel% neq 0 (
-    echo [!] Please run as Administrator
-    pause
-    exit /b 1
-)
-
-echo [1/2] Reading LTX from shortcut...
-
-:: Run PowerShell script to handle everything
-powershell -ExecutionPolicy Bypass -File "%~dp0fix_ltx.ps1"
-
-echo.
-echo [2/2] Clearing API Key...
-set "settings_file=%USERPROFILE%\AppData\Local\LTXDesktop\settings.json"
-
-if exist "%settings_file%" (
-    powershell -Command "(Get-Content '%settings_file%' -Raw) -replace '\"fal_api_key\": \"[^\"]*\"', '\"fal_api_key\": \"\"' | Set-Content '%settings_file%'"
-    echo     ^_^ API Key cleared
-) else (
-    echo     [!] settings.json not found
-)
-
-echo.
-echo ========================================
-echo    Done! Please restart LTX Desktop
-echo ========================================
-pause

LTX2.3/API issues-API问题办法.txt

@@ -1,50 +0,0 @@
-1. 复制LTX桌面版的快捷方式到LTX_Shortcut
-
-2. 运行run.bat
-----
-1. Copy the LTX desktop shortcut to LTX_Shortcut
-
-2. Run run.bat
-----
-
-
-
-【问题描述 / Problem】
-系统强制使用 FAL API 生成图片，即使本地有 GPU 可用。
-System forces FAL API generation even when local GPU is available.
-
-【原因 / Cause】
-LTX 强制要求 GPU 有 31GB VRAM 才会使用本地显卡，低于此值会强制走 API 模式。
-LTX requires 31GB VRAM to use local GPU. Below this, it forces API mode.
-
-================================================================================
-【修复方法 / Fix Method】
-================================================================================
-
-运行: API issues.bat.bat (以管理员身份)
-Run: API issues.bat.bat (as Administrator)
-
-================================================================================
-================================================================================
-
-【或者手动 / Or Manual】
-
-1. 修改 VRAM 阈值 / Modify VRAM Threshold
-   文件路径 / File: C:\Program Files\LTX Desktop\resources\backend\runtime_config\runtime_policy.py
-   第16行 / Line 16:
-   原 / Original: return vram_gb < 31
-   改为 / Change:  return vram_gb < 6
-
-2. 清空 API Key / Clear API Key
-   文件路径 / File: C:\Users\<用户名>\AppData\Local\LTXDesktop\settings.json
-   原 / Original: "fal_api_key": "xxxxx"
-   改为 / Change:  "fal_api_key": ""
-
-【说明 / Note】
-- VRAM 阈值改为 6GB，意味着 6GB 及以上显存都会使用本地显卡
-- VRAM threshold set to 6GB means 6GB+ VRAM will use local GPU
-- 清空 fal_api_key 避免系统误判为已配置 API
-- Clear fal_api_key to avoid system thinking API is configured
-- 修改后重启程序即可生效
-- Restart LTX Desktop after changes
-================================================================================

LTX2.3/UI/index.css

@@ -1,298 +0,0 @@
-:root {
-            --accent:      #2563EB;     /* Refined blue – not too bright, not purple */
-            --accent-hover:#3B82F6;
-            --accent-dim:  rgba(37,99,235,0.14);
-            --accent-ring: rgba(37,99,235,0.35);
-            --bg:          #111113;
-            --panel:       #18181B;
-            --panel-2:     #1F1F23;
-            --item:        rgba(255,255,255,0.035);
-            --border:      rgba(255,255,255,0.08);
-            --border-2:    rgba(255,255,255,0.05);
-            --text-dim:    #71717A;
-            --text-sub:    #A1A1AA;
-            --text:        #FAFAFA;
-        }
-
-        * { box-sizing: border-box; -webkit-font-smoothing: antialiased; min-width: 0; }
-        body {
-            background: var(--bg); margin: 0; color: var(--text);
-            font-family: -apple-system, "SF Pro Display", "Segoe UI", sans-serif;
-            display: flex; height: 100vh; overflow: hidden;
-            font-size: 13px; line-height: 1.5;
-        }
-
-        .sidebar {
-            width: 460px; min-width: 460px;
-            background: var(--panel);
-            border-right: 1px solid var(--border);
-            display: flex; flex-direction: column; z-index: 20;
-            overflow-y: auto; overflow-x: hidden;
-        }
-
-        /* Scrollbar */
-        ::-webkit-scrollbar { width: 5px; height: 5px; }
-        ::-webkit-scrollbar-track { background: transparent; }
-        ::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.08); border-radius: 10px; }
-        ::-webkit-scrollbar-thumb:hover { background: rgba(255,255,255,0.18); }
-
-        .sidebar-header { padding: 24px 24px 4px; }
-        .sidebar-section { padding: 8px 24px 18px; border-bottom: 1px solid var(--border); }
-
-        .setting-group {
-            background: rgba(255,255,255,0.025);
-            border: 1px solid var(--border-2);
-            border-radius: 10px;
-            padding: 14px;
-            margin-bottom: 12px;
-        }
-        .group-title {
-            font-size: 10px; color: var(--text-dim); font-weight: 700;
-            text-transform: uppercase; letter-spacing: 0.7px;
-            margin-bottom: 12px;
-            padding-bottom: 5px;
-            border-bottom: 1px solid var(--border-2);
-        }
-
-        /* Mode Tabs */
-        .tabs {
-            display: flex; gap: 4px; margin-bottom: 14px;
-            background: rgba(255,255,255,0.04);
-            padding: 4px; border-radius: 10px;
-            border: 1px solid var(--border-2);
-        }
-        .tab {
-            flex: 1; padding: 9px 0; text-align: center; border-radius: 7px;
-            cursor: pointer; font-size: 12px; color: var(--text-dim);
-            transition: all 0.2s; font-weight: 600;
-            display: flex; align-items: center; justify-content: center;
-        }
-        .tab.active { background: var(--accent); color: #fff; box-shadow: 0 1px 6px rgba(10,132,255,0.45); }
-        .tab:hover:not(.active) { background: rgba(255,255,255,0.06); color: var(--text); }
-
-        .label-group { display: flex; justify-content: space-between; align-items: center; margin-bottom: 6px; }
-        label { display: block; font-size: 11px; color: var(--text-dim); font-weight: 600; text-transform: uppercase; letter-spacing: 0.5px; margin-bottom: 6px; }
-        .val-badge { font-size: 11px; color: var(--accent); font-family: "SF Mono", ui-monospace, monospace; font-weight: 600; }
-
-        input[type="text"], input[type="number"], select, textarea {
-            width: 100%; background: var(--panel-2);
-            border: 1px solid var(--border);
-            border-radius: 7px; color: var(--text);
-            padding: 8px 11px; font-size: 12.5px; outline: none; margin-bottom: 9px;
-            /* Only transition border/shadow – NOT background-image to prevent arrow flicker */
-            transition: border-color 0.15s, box-shadow 0.15s;
-        }
-        input:focus, select:focus, textarea:focus {
-            border-color: var(--accent);
-            box-shadow: 0 0 0 2px var(--accent-ring);
-        }
-        select {
-            -webkit-appearance: none; -moz-appearance: none; appearance: none;
-            /* Stable grey arrow – no background shorthand so it won't animate */
-            background-color: var(--panel-2);
-            background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='12' height='12' viewBox='0 0 24 24' fill='none' stroke='%2371717A' stroke-width='2.5' stroke-linecap='round' stroke-linejoin='round'%3E%3Cpolyline points='6 9 12 15 18 9'/%3E%3C/svg%3E");
-            background-repeat: no-repeat;
-            background-position: right 10px center;
-            background-size: 12px;
-            padding-right: 28px;
-            cursor: pointer;
-            /* Explicitly do NOT transition background properties */
-            transition: border-color 0.15s, box-shadow 0.15s;
-        }
-        select:focus { background-color: var(--panel-2); }
-        select option { background: #27272A; color: var(--text); }
-        textarea { resize: vertical; min-height: 78px; font-family: inherit; }
-
-        .slider-container { display: flex; align-items: center; gap: 12px; margin-bottom: 14px; }
-        input[type="range"] { flex: 1; accent-color: var(--accent); height: 4px; cursor: pointer; border-radius: 2px; }
-
-        .upload-zone {
-            border: 1px dashed var(--border); border-radius: 10px;
-            padding: 18px 10px; text-align: center; cursor: pointer;
-            background: rgba(255,255,255,0.01); margin-bottom: 10px; position: relative;
-            transition: all 0.2s;
-        }
-        .upload-zone:hover, .upload-zone.dragover { background: var(--accent-dim); border-color: var(--accent); }
-        .upload-icon { font-size: 18px; margin-bottom: 6px; opacity: 0.45; }
-        .upload-text { font-size: 11px; color: var(--text); }
-        .upload-hint { font-size: 10px; color: var(--text-dim); margin-top: 3px; }
-        .preview-thumb { width: 100%; height: auto; max-height: 100px; object-fit: contain; border-radius: 8px; display: none; margin-top: 10px; }
-        .clear-img-overlay {
-            position: absolute; top: 8px; right: 8px; background: rgba(255,59,48,0.85); color: white;
-            width: 20px; height: 20px; border-radius: 10px; display: none; align-items: center; justify-content: center;
-            font-size: 11px; cursor: pointer; z-index: 5;
-        }
-
-        .btn-outline {
-            background: var(--panel-2);
-            border: 1px solid var(--border);
-            color: var(--text-sub); padding: 5px 12px; border-radius: 7px;
-            font-size: 11.5px; font-weight: 600; cursor: pointer;
-            transition: background 0.15s, border-color 0.15s, color 0.15s;
-            display: inline-flex; align-items: center; justify-content: center; gap: 5px;
-            white-space: nowrap;
-        }
-        .btn-outline:hover:not(:disabled) { background: rgba(255,255,255,0.08); color: var(--text); border-color: rgba(255,255,255,0.18); }
-        .btn-outline:active { opacity: 0.7; }
-        .btn-outline:disabled { opacity: 0.3; cursor: not-allowed; }
-
-        .btn-icon {
-            padding: 5px; background: transparent; border: none; color: var(--text-dim);
-            border-radius: 6px; cursor: pointer; display: flex; align-items: center; justify-content: center;
-            transition: color 0.15s, background 0.15s;
-        }
-        .btn-icon:hover { color: var(--text-sub); background: rgba(255,255,255,0.07); }
-
-        .btn-primary {
-            width: 100%; padding: 13px;
-            background: var(--accent); border: none;
-            border-radius: 9px; color: #fff; font-weight: 700; font-size: 13.5px;
-            letter-spacing: 0.2px; cursor: pointer; margin-top: 14px;
-            transition: background 0.15s;
-        }
-        .btn-primary:hover:not(:disabled) { background: var(--accent-hover); }
-        .btn-primary:active { opacity: 0.82; }
-        .btn-primary:disabled { background: rgba(255,255,255,0.08); color: var(--text-dim); cursor: not-allowed; }
-
-        .btn-danger {
-            width: 100%; padding: 12px; background: #DC2626; border: none;
-            border-radius: 9px; color: #fff; font-weight: 700; font-size: 13.5px;
-            cursor: pointer; margin-top: 8px; display: none; transition: background 0.15s;
-        }
-        .btn-danger:hover { background: #EF4444; }
-
-        /* Workspace */
-        .workspace { flex: 1; display: flex; flex-direction: column; background: #0A0A0A; position: relative; overflow: hidden; }
-        .viewer { flex: 2; display: flex; align-items: center; justify-content: center; padding: 16px; background: #0A0A0A; position: relative; min-height: 40vh; }
-        .monitor {
-            width: 100%; height: 100%; max-width: 1650px; border-radius: 10px; border: 1px solid var(--border);
-            overflow: hidden; position: relative; background: #070707;
-            display: flex; align-items: center; justify-content: center;
-            background-image: radial-gradient(rgba(255,255,255,0.02) 1px, transparent 1px);
-            background-size: 18px 18px;
-        }
-        .monitor img, .monitor video {
-            width: auto; height: auto; max-width: 100%; max-height: 100%;
-            object-fit: contain; display: none; z-index: 2; border-radius: 3px;
-        }
-
-        .progress-container { position: absolute; bottom: 0; left: 0; width: 100%; height: 2px; background: var(--border-2); z-index: 10; }
-        #progress-fill { width: 0%; height: 100%; background: var(--accent); transition: width 0.5s; }
-        #loading-txt { font-size: 12px; color: var(--text-sub); font-weight: 600; z-index: 5; position: absolute; display: none; }
-
-
-
-        .spinner {
-            width: 12px; height: 12px;
-            border: 2px solid rgba(255,255,255,0.2);
-            border-top-color: currentColor;
-            border-radius: 50%;
-            animation: spin 1s linear infinite;
-        }
-        @keyframes spin { to { transform: rotate(360deg); } }
-        
-        .loading-card {
-            display: flex; align-items: center; justify-content: center;
-            flex-direction: column; gap: 6px; color: var(--text-dim); font-size: 10px;
-            background: rgba(37,99,235,0.07) !important;
-            border-color: rgba(37,99,235,0.3) !important;
-        }
-        .loading-card .spinner { width: 28px; height: 28px; border-width: 3px; color: var(--accent); }
-        .loading-card:hover { background: rgba(37,99,235,0.14) !important; border-color: var(--accent) !important; }
-
-        .library { flex: 1.5; border-top: 1px solid var(--border); padding: 14px 20px; display: flex; flex-direction: column; background: #0F0F11; overflow-y: hidden; }
-        #log-container { flex: 1; overflow-y: auto; padding-right: 4px; }
-        #log { font-family: ui-monospace, "SF Mono", monospace; font-size: 10.5px; color: var(--text-dim); line-height: 1.7; }
-
-        /* History wrapper: scrollable area for thumbnails only */
-        #history-wrapper {
-            flex: 1;
-            overflow-y: auto;
-            min-height: 110px;   /* always show at least one row */
-            padding-right: 4px;
-        }
-        #history-container {
-            display: grid;
-            grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));
-            justify-content: start;
-            gap: 10px; align-content: flex-start;
-            padding-bottom: 4px;
-        }
-        /* Pagination row: hidden, using infinite scroll instead */
-        #pagination-bar {
-            display: none;
-        }
-
-        .history-card {
-            width: 100%; max-width: 200px; aspect-ratio: 16 / 9;
-            background: #1A1A1E; border-radius: 7px;
-            overflow: hidden; border: 1px solid var(--border);
-            cursor: pointer; position: relative; transition: border-color 0.15s, transform 0.15s;
-        }
-        .history-card:hover { border-color: var(--accent); transform: translateY(-1px); }
-        .history-card img, .history-card video { width: 100%; height: 100%; object-fit: cover; }
-        .history-type-badge {
-            position: absolute; top: 5px; left: 5px; font-size: 8px; padding: 1px 5px; border-radius: 3px;
-            background: rgba(0,0,0,0.8); color: var(--text-sub); border: 1px solid rgba(255,255,255,0.06);
-            z-index: 2; font-weight: 700; letter-spacing: 0.4px;
-        }
-        .history-delete-btn {
-            position: absolute; top: 5px; right: 5px; width: 20px; height: 20px;
-            border-radius: 50%; border: none; background: rgba(255,50,50,0.8); color: #fff;
-            font-size: 10px; cursor: pointer; z-index: 3; display: flex; align-items: center; justify-content: center;
-            opacity: 0; transition: opacity 0.2s;
-        }
-        .history-card:hover .history-delete-btn { opacity: 1; }
-        .history-delete-btn:hover { background: rgba(255,0,0,0.9); }
-
-        .vram-bar { width: 160px; height: 5px; background: rgba(255,255,255,0.08); border-radius: 999px; overflow: hidden; display: inline-block; vertical-align: middle; }
-        .vram-used { height: 100%; background: var(--accent); width: 0%; transition: width 0.5s; }
-
-        .sub-mode-toggle { display: flex; background: var(--panel-2); border-radius: 7px; padding: 3px; border: 1px solid var(--border); }
-        .sub-mode-btn { flex: 1; padding: 6px 0; border-radius: 5px; border: none; background: transparent; font-size: 11.5px; color: var(--text-dim); font-weight: 600; cursor: pointer; transition: background 0.15s, color 0.15s; }
-        .sub-mode-btn.active { background: var(--accent); color: #fff; }
-        .sub-mode-btn:hover:not(.active) { background: rgba(255,255,255,0.05); color: var(--text-sub); }
-
-        .vid-section { display: none; margin-top: 12px; }
-        .vid-section.active-section { display: block; animation: fadeIn 0.25s ease; }
-        @keyframes fadeIn { from { opacity: 0; transform: translateY(4px); } to { opacity: 1; transform: translateY(0); } }
-
-        /* Status indicator */
-        @keyframes breathe-orange {
-            0%,100% { box-shadow: 0 0 4px #FF9F0A; opacity: 0.7; }
-            50%      { box-shadow: 0 0 10px #FF9F0A; opacity: 1; }
-        }
-        .indicator-busy    { background: #FF9F0A !important; animation: breathe-orange 1.6s infinite ease-in-out !important; box-shadow: none !important; transition: all 0.3s; }
-        .indicator-ready   { background: #30D158 !important; box-shadow: 0 0 8px rgba(48,209,88,0.6) !important; animation: none !important; transition: all 0.3s; }
-        .indicator-offline { background: #636366 !important; box-shadow: none !important; animation: none !important; transition: all 0.3s; }
-
-        .res-preview-tag { font-size: 11px; color: var(--accent); margin-bottom: 10px; font-family: ui-monospace, monospace; }
-        .top-status { display: flex; justify-content: space-between; font-size: 12px; color: var(--text-dim); margin-bottom: 8px; align-items: center; }
-        .checkbox-container { display: flex; align-items: center; gap: 8px; cursor: pointer; background: rgba(255,255,255,0.02); padding: 10px; border-radius: 8px; border: 1px solid var(--border-2); }
-        .checkbox-container input { width: 15px; height: 15px; accent-color: var(--accent); cursor: pointer; margin: 0; }
-        .checkbox-container label { margin-bottom: 0; cursor: pointer; text-transform: none; color: var(--text); }
-        .flex-row { display: flex; gap: 10px; }
-        .flex-1 { flex: 1; min-width: 0; }
-
-        @media (max-width: 1024px) {
-            body { flex-direction: column; overflow-y: auto; }
-            .sidebar { width: 100%; min-width: 100%; border-right: none; border-bottom: 1px solid var(--border); height: auto; overflow: visible; }
-            .workspace { height: auto; min-height: 100vh; overflow: visible; }
-        }
-:root {
-    --plyr-color-main: #3F51B5;
-    --plyr-video-control-background-hover: rgba(255,255,255,0.1);
-    --plyr-control-radius: 6px;
-    --plyr-player-width: 100%;
-}
-.plyr {
-    border-radius: 8px;
-    overflow: hidden;
-    width: 100%;
-    height: 100%;
-}
-.plyr--video .plyr__controls {
-    background: linear-gradient(rgba(0,0,0,0), rgba(0,0,0,0.8));
-    padding: 20px 15px 15px 15px;
-}
-

LTX2.3/UI/index.html

@@ -1,302 +0,0 @@
-<!DOCTYPE html>
-<html lang="zh-CN">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>LTX-2 | Multi-GPU Cinematic Studio</title>
-        <link rel="stylesheet" href="index.css">
-        <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/plyr/3.7.8/plyr.css" />
-</head>
-<body>
-
-<aside class="sidebar">
-    <div class="sidebar-header">
-        <div style="display: flex; align-items: center; justify-content: space-between; margin-bottom: 12px;">
-            <div style="display: flex; align-items: center; gap: 10px;">
-                <div id="sys-indicator" class="indicator-ready" style="width: 12px; height: 12px; border-radius: 50%;"></div>
-                <span style="font-weight: 800; font-size: 18px;">LTX-2 STUDIO</span>
-            </div>
-            <div style="display: flex; gap: 8px; align-items: center;">
-                <button id="langBtn" onclick="toggleLang()" class="btn-icon" title="切换语言">
-                    <svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="10"></circle><line x1="2" y1="12" x2="22" y2="12"></line><path d="M12 2a15.3 15.3 0 0 1 4 10 15.3 15.3 0 0 1-4 10 15.3 15.3 0 0 1-4-10 15.3 15.3 0 0 1 4-10z"></path></svg>
-                </button>
-                <button id="clearGpuBtn" onclick="clearGpu()" class="btn-outline" data-lang-zh="释放显存" data-lang-en="Clear VRAM">释放显存</button>
-            </div>
-        </div>
-        
-        <div class="top-status" style="margin-bottom: 5px;">
-            <div style="display: flex; align-items: center; gap: 8px;">
-                <span id="sys-status" style="font-weight:bold; color: var(--text-dim); font-size: 12px;" data-lang-zh="正在扫描 GPU..." data-lang-en="Scanning GPU...">正在扫描 GPU...</span>
-            </div>
-            
-            <button onclick="const el = document.getElementById('sys-settings'); el.style.display = el.style.display === 'none' ? 'block' : 'none';" class="btn-icon" title="系统高级设置">
-                <svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><circle cx="12" cy="12" r="3"></circle><path d="M19.4 15a1.65 1.65 0 0 0 .33 1.82l.06.06a2 2 0 0 1 0 2.83 2 2 0 0 1-2.83 0l-.06-.06a1.65 1.65 0 0 0-1.82-.33 1.65 1.65 0 0 0-1 1.51V21a2 2 0 0 1-2 2 2 2 0 0 1-2-2v-.09A1.65 1.65 0 0 0 9 19.4a1.65 1.65 0 0 0-1.82.33l-.06.06a2 2 0 0 1-2.83 0 2 2 0 0 1 0-2.83l.06-.06a1.65 1.65 0 0 0 .33-1.82 1.65 1.65 0 0 0-1.51-1H3a2 2 0 0 1-2-2 2 2 0 0 1 2-2h.09A1.65 1.65 0 0 0 4.6 9a1.65 1.65 0 0 0-.33-1.82l-.06-.06a2 2 0 0 1 0-2.83 2 2 0 0 1 2.83 0l.06.06a1.65 1.65 0 0 0 1.82.33H9a1.65 1.65 0 0 0 1-1.51V3a2 2 0 0 1 2-2 2 2 0 0 1 2 2v.09a1.65 1.65 0 0 0 1 1.51 1.65 1.65 0 0 0 1.82-.33l.06-.06a2 2 0 0 1 2.83 0 2 2 0 0 1 0 2.83l-.06.06a1.65 1.65 0 0 0-.33 1.82V9a1.65 1.65 0 0 0 1.51 1H21a2 2 0 0 1 2 2 2 2 0 0 1-2 2h-.09a1.65 1.65 0 0 0-1.51 1z"></path></svg>
-            </button>
-
-        </div>
-        
-        <div style="font-size: 11px; color: var(--text-dim); margin-bottom: 20px; display: flex; align-items: center; width: 100%;">
-            <div class="vram-bar" style="width: 120px; min-width: 120px; margin-top: 0; margin-right: 12px;"><div class="vram-used" id="vram-fill"></div></div> 
-            <span id="vram-text" style="font-variant-numeric: tabular-nums; flex-shrink: 0; text-align: right;">0/32 GB</span>
-            <span id="gpu-name" style="display: none;"></span>
-        </div>
-        
-        <div id="sys-settings" style="display: none; padding: 14px; background: rgba(0,0,0,0.4) !important; border-radius: 12px; border: 1px solid rgba(255,255,255,0.1); margin-bottom: 15px; box-shadow: 0 4px 15px rgba(0,0,0,0.5); backdrop-filter: blur(10px);">
-            <div style="font-size: 13px; font-weight: bold; margin-bottom: 12px; color: #fff;" data-lang-zh="高级设置" data-lang-en="Advanced Settings">高级设置</div>
-            
-            <label style="font-size: 11px; margin-bottom: 6px;" data-lang-zh="工作设备" data-lang-en="GPU Device">工作设备</label>
-            <select id="gpu-selector" onchange="switchGpu(this.value)" style="margin-bottom: 12px; font-size: 11px; padding: 6px;">
-                <option value="" data-lang-zh="正在检测 GPU..." data-lang-en="Detecting GPU...">正在检测 GPU...</option>
-            </select>
-            
-            <label style="font-size: 11px; margin-bottom: 6px;" data-lang-zh="输出路径" data-lang-en="Output Path">输出路径</label>
-            <div style="display:flex; gap:6px;">
-                <input type="text" id="global-out-dir" onchange="setOutputDir()" placeholder="默认: LTXDesktop/outputs" style="margin-bottom: 0; padding: 6px 8px; font-size: 11px;">
-                <button class="btn-outline" style="padding: 6px;" onclick="browseOutputDir()" title="浏览本地目录">
-                    <svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><path d="M22 19a2 2 0 0 1-2 2H4a2 2 0 0 1-2-2V5a2 2 0 0 1 2-2h5l2 3h9a2 2 0 0 1 2 2z"></path></svg>
-                </button>
-            </div>
-            <div style="font-size: 10px; color: var(--text-dim); margin-top: 8px; line-height: 1.4;" data-lang-zh="系统默认会在 C 盘保留输出文件。您可以浏览更换目录。" data-lang-en="Default output in C drive. Browse to change path.">系统默认会在 C 盘保留输出文件。您可以浏览更换目录。</div>
-        </div>
-    </div>
-
-    <div class="sidebar-section">
-        <div class="tabs">
-            <div id="tab-video" class="tab active" onclick="switchMode('video')">
-                <svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" style="margin-right: 6px;"><rect x="2" y="2" width="20" height="20" rx="2.18" ry="2.18"></rect><line x1="7" y1="2" x2="7" y2="22"></line><line x1="17" y1="2" x2="17" y2="22"></line><line x1="2" y1="12" x2="22" y2="12"></line><line x1="2" y1="7" x2="7" y2="7"></line><line x1="2" y1="17" x2="7" y2="17"></line><line x1="17" y1="17" x2="22" y2="17"></line><line x1="17" y1="7" x2="22" y2="7"></line></svg>
-                <span data-lang-zh="视频生成" data-lang-en="Video">视频生成</span>
-            </div>
-            <div id="tab-upscale" class="tab" onclick="switchMode('upscale')">
-                <svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" style="margin-right: 6px;"><polygon points="13 2 3 14 12 14 11 22 21 10 12 10 13 2"></polygon></svg>
-                <span data-lang-zh="视频增强" data-lang-en="Upscale">视频增强</span>
-            </div>
-            <div id="tab-image" class="tab" onclick="switchMode('image')">
-                <svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" style="margin-right: 6px;"><rect x="3" y="3" width="18" height="18" rx="2" ry="2"></rect><circle cx="8.5" cy="8.5" r="1.5"></circle><polyline points="21 15 16 10 5 21"></polyline></svg>
-                <span data-lang-zh="图像生成" data-lang-en="Image">图像生成</span>
-            </div>
-        </div>
-        
-        <label data-lang-zh="视觉描述词" data-lang-en="Prompt">视觉描述词</label>
-        <textarea id="prompt" placeholder="在此输入视觉描述词..." style="height: 90px; margin-bottom: 0;"></textarea>
-    </div>
-
-    <!-- 视频模式选项 -->
-    <div class="sidebar-section" id="video-opts" style="display:none">
-        <div class="setting-group">
-            <div class="group-title" data-lang-zh="基础设置" data-lang-en="Basic Settings">基础设置</div>
-            <div class="flex-row">
-                <div class="flex-1">
-                    <label data-lang-zh="清晰度" data-lang-en="Quality">清晰度</label>
-                    <select id="vid-quality" onchange="updateResPreview()">
-                        <option value="1080">1080P Full HD</option>
-                        <option value="720" selected>720P Standard</option>
-                        <option value="576">576P Preview</option>
-                    </select>
-                </div>
-                <div class="flex-1">
-                    <label data-lang-zh="画幅比例" data-lang-en="Aspect Ratio">画幅比例</label>
-                    <select id="vid-ratio" onchange="updateResPreview()">
-                        <option value="16:9">16:9</option>
-                        <option value="9:16">9:16</option>
-                    </select>
-                </div>
-            </div>
-            <div id="res-preview" class="res-preview-tag" style="margin-top: -5px; margin-bottom: 12px;">最终发送: 1280x720</div>
-
-            <div class="flex-row">
-                <div class="flex-1">
-                    <label data-lang-zh="帧率" data-lang-en="FPS">帧率</label>
-                    <select id="vid-fps">
-                        <option value="24" selected>24 FPS</option>
-                        <option value="25">25 FPS</option>
-                        <option value="30">30 FPS</option>
-                        <option value="48">48 FPS</option>
-                        <option value="60">60 FPS</option>
-                    </select>
-                </div>
-                <div class="flex-1">
-                    <label data-lang-zh="时长 (秒)" data-lang-en="Duration (sec)">时长 (秒)</label>
-                    <input type="number" id="vid-duration" value="5" min="1" max="30" step="1">
-                </div>
-            </div>
-        </div>
-
-        <div class="setting-group">
-            <div class="group-title" data-lang-zh="镜头与音频" data-lang-en="Camera & Audio">镜头与音频</div>
-            <label data-lang-zh="镜头运动" data-lang-en="Camera Motion">镜头运动</label>
-            <select id="vid-motion">
-                <option value="static" selected>Static (静止机位)</option>
-                <option value="dolly_in">Dolly In (推近)</option>
-                <option value="dolly_out">Dolly Out (拉远)</option>
-                <option value="dolly_left">Dolly Left (向左)</option>
-                <option value="dolly_right">Dolly Right (向右)</option>
-                <option value="jib_up">Jib Up (升臂)</option>
-                <option value="jib_down">Jib Down (降臂)</option>
-                <option value="focus_shift">Focus Shift (焦点)</option>
-            </select>
-            <div class="checkbox-container">
-                <input type="checkbox" id="vid-audio" checked>
-                <label for="vid-audio" data-lang-zh="生成 AI 环境音" data-lang-en="Generate AI Audio">生成 AI 环境音</label>
-            </div>
-        </div>
-
-        <!-- 生成媒介组 -->
-        <div class="setting-group" id="video-source-group">
-            <div class="group-title" data-lang-zh="生成媒介" data-lang-en="Source">生成媒介</div>
-            
-            <div class="flex-row" style="margin-bottom: 10px;">
-                <div class="flex-1">
-                    <label data-lang-zh="起始帧" data-lang-en="Start Frame">起始帧</label>
-                    <div class="upload-zone" id="start-frame-drop-zone" onclick="document.getElementById('start-frame-input').click()">
-                        <div class="clear-img-overlay" id="clear-start-frame-overlay" onclick="event.stopPropagation(); clearFrame('start')">×</div>
-                        <div id="start-frame-placeholder">
-                            <div class="upload-icon">🖼️</div>
-                            <div class="upload-text" data-lang-zh="上传首帧" data-lang-en="Upload">上传首帧</div>
-                        </div>
-                        <img id="start-frame-preview" class="preview-thumb">
-                        <input type="file" id="start-frame-input" accept="image/*" style="display:none" onchange="handleFrameUpload(this.files[0], 'start')">
-                    </div>
-                    <input type="hidden" id="start-frame-path">
-                </div>
-                <div class="flex-1">
-                    <label data-lang-zh="结束帧" data-lang-en="End Frame">结束帧</label>
-                    <div class="upload-zone" id="end-frame-drop-zone" onclick="document.getElementById('end-frame-input').click()">
-                        <div class="clear-img-overlay" id="clear-end-frame-overlay" onclick="event.stopPropagation(); clearFrame('end')">×</div>
-                        <div id="end-frame-placeholder">
-                            <div class="upload-icon">🏁</div>
-                            <div class="upload-text" data-lang-zh="上传尾帧" data-lang-en="Upload">上传尾帧</div>
-                        </div>
-                        <img id="end-frame-preview" class="preview-thumb">
-                        <input type="file" id="end-frame-input" accept="image/*" style="display:none" onchange="handleFrameUpload(this.files[0], 'end')">
-                    </div>
-                    <input type="hidden" id="end-frame-path">
-                </div>
-            </div>
-
-            <div class="flex-row">
-                <div class="flex-1">
-                    <label data-lang-zh="参考音频" data-lang-en="Audio">参考音频</label>
-                    <div class="upload-zone" id="audio-drop-zone" onclick="document.getElementById('vid-audio-input').click()">
-                        <div class="clear-img-overlay" id="clear-audio-overlay" onclick="event.stopPropagation(); clearUploadedAudio()">×</div>
-                        <div id="audio-upload-placeholder">
-                            <div class="upload-icon">🎵</div>
-                            <div class="upload-text" data-lang-zh="点击上传音频" data-lang-en="Upload">点击上传音频</div>
-                        </div>
-                        <div id="audio-upload-status" style="display:none;">
-                            <div class="upload-icon" style="color:var(--accent); opacity:1;">✔️</div>
-                            <div id="audio-filename-status" class="upload-text"></div>
-                        </div>
-                        <input type="file" id="vid-audio-input" accept="audio/*" style="display:none" onchange="handleAudioUpload(this.files[0])">
-                    </div>
-                    <input type="hidden" id="uploaded-audio-path">
-                </div>
-            </div>
-            <div style="font-size: 10px; color: var(--text-dim); text-align: center; margin-top: 5px;" data-lang-zh="💡 仅首帧=图生视频，首尾帧=插帧" data-lang-en="💡 Start only=Img2Vid, Both=Interpolation">
-                💡 仅首帧=图生视频，首尾帧=插帧
-            </div>
-        </div>
-    </div>
-
-    <!-- 图像模式选项 -->
-    <div id="image-opts" class="sidebar-section" style="display:none">
-        <label data-lang-zh="分辨率预设" data-lang-en="Resolution">分辨率预设</label>
-        <select id="img-res-preset" onchange="applyImgPreset(this.value)">
-            <option value="1024x1024">1:1 (1024x1024)</option>
-            <option value="1280x720">16:9 (1280x720)</option>
-            <option value="720x1280">9:16 (720x1280)</option>
-            <option value="custom">Custom</option>
-        </select>
-
-        <div id="img-custom-res" class="flex-row" style="margin-top: 10px;">
-            <div class="flex-1"><label data-lang-zh="宽度" data-lang-en="Width">宽度</label><input type="number" id="img-w" value="1024" onchange="updateImgResPreview()"></div>
-            <div class="flex-1"><label data-lang-zh="高度" data-lang-en="Height">高度</label><input type="number" id="img-h" value="1024" onchange="updateImgResPreview()"></div>
-        </div>
-        <div id="img-res-preview" class="res-preview-tag">最终发送: 1024x1024</div>
-        
-        <div class="label-group" style="margin-top: 15px;">
-            <label data-lang-zh="采样步数" data-lang-en="Steps">采样步数</label>
-            <span class="val-badge" id="stepsVal">28</span>
-        </div>
-        <div class="slider-container">
-            <input type="range" id="img-steps" min="1" max="50" value="28" oninput="document.getElementById('stepsVal').innerText=this.value">
-        </div>
-    </div>
-
-    <!-- 超分模式选项 -->
-    <div id="upscale-opts" class="sidebar-section" style="display:none">
-        <div class="setting-group">
-            <label data-lang-zh="待超分视频" data-lang-en="Video">待超分视频</label>
-            <div class="upload-zone" id="upscale-drop-zone" onclick="document.getElementById('upscale-video-input').click()" style="margin-bottom: 0;">
-                <div class="clear-img-overlay" id="clear-upscale-overlay" onclick="event.stopPropagation(); clearUpscaleVideo()">×</div>
-                <div id="upscale-placeholder">
-                    <div class="upload-icon">📹</div>
-                    <div class="upload-text" data-lang-zh="拖入视频" data-lang-en="Drop Video">拖入视频</div>
-                </div>
-                <div id="upscale-status" style="display:none;">
-                    <div class="upload-icon" style="color:var(--accent); opacity:1;">✔️</div>
-                    <div id="upscale-filename" class="upload-text"></div>
-                </div>
-                <input type="file" id="upscale-video-input" accept="video/*" style="display:none" onchange="handleUpscaleVideoUpload(this.files[0])">
-            </div>
-            <input type="hidden" id="upscale-video-path">
-        </div>
-
-        <div class="setting-group">
-            <label data-lang-zh="目标分辨率" data-lang-en="Target">目标分辨率</label>
-            <select id="upscale-res" style="margin-bottom: 0;">
-                <option value="1080p">1080P (2x)</option>
-                <option value="720p">720P</option>
-            </select>
-        </div>
-    </div>
-
-    <div style="padding: 0 30px 30px 30px;">
-        <button class="btn-primary" id="mainBtn" onclick="run()" data-lang-zh="开始渲染" data-lang-en="Generate">开始渲染</button>
-    </div>
-</aside>
-
-<main class="workspace">
-    <section class="viewer" id="viewer-section">
-        <div class="monitor" id="viewer">
-            <div id="loading-txt" data-lang-zh="等待分配渲染任务..." data-lang-en="Waiting for task...">等待分配渲染任务...</div>
-            <img id="res-img" src="">
-            <div id="video-wrapper" style="width:100%; height:100%; display:none; max-height:100%; align-items:center; justify-content:center;">
-                <video id="res-video" autoplay loop playsinline></video>
-            </div>
-            <div class="progress-container"><div id="progress-fill"></div></div>
-        </div>
-    </section>
-
-    <!-- Drag Handle -->
-    <div id="resize-handle" style="
-        height: 5px; background: transparent; cursor: row-resize;
-        flex-shrink: 0; position: relative; z-index: 50;
-        display: flex; align-items: center; justify-content: center;
-    " title="拖动调整面板高度">
-        <div style="width: 40px; height: 3px; background: var(--border); border-radius: 999px; pointer-events: none;"></div>
-    </div>
-
-    <section class="library" id="library-section">
-        <div style="display: flex; justify-content: space-between; margin-bottom: 15px; align-items: center; border-bottom: 1px solid var(--border); padding-bottom: 10px;">
-            <div style="display: flex; gap: 20px;">
-                <span id="tab-history" style="font-size: 11px; font-weight: 800; color: var(--accent); cursor: pointer; border-bottom: 2px solid var(--accent); padding-bottom: 11px; margin-bottom: -11px;" onclick="switchLibTab('history')" data-lang-zh="历史资产" data-lang-en="ASSETS">历史资产</span>
-                <span id="tab-log" style="font-size: 11px; font-weight: 800; color: var(--text-dim); cursor: pointer; border-bottom: 2px solid transparent; padding-bottom: 11px; margin-bottom: -11px;" onclick="switchLibTab('log')" data-lang-zh="系统日志" data-lang-en="LOGS">系统日志</span>
-            </div>
-                <button onclick="fetchHistory(currentHistoryPage)" style="background: var(--item); border: 1px solid var(--border); border-radius: 6px; color: var(--text-dim); font-size: 11px; padding: 4px 10px; cursor: pointer;" data-lang-zh="刷新" data-lang-en="Refresh">刷新</button>
-        </div>
-        
-        <div id="log-container" style="display: none; flex: 1; flex-direction: column;">
-            <div id="log">> LTX-2 Studio Ready. Expecting commands...</div>
-        </div>
-        
-        <div id="history-wrapper">
-            <div id="history-container"></div>
-        </div>
-        <div id="pagination-bar" style="display:none;"></div>
-    </section>
-</main>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/plyr/3.7.8/plyr.min.js"></script>
-<script src="index.js"></script>
-
-</body>
-</html>

LTX2.3/UI/index.js

@@ -1,1055 +0,0 @@
-// ─── Resizable panel drag logic ───────────────────────────────────────────────
-(function() {
-    const handle = document.getElementById('resize-handle');
-    const viewer = document.getElementById('viewer-section');
-    const library = document.getElementById('library-section');
-    const workspace = document.querySelector('.workspace');
-    let dragging = false, startY = 0, startVH = 0;
-
-    handle.addEventListener('mousedown', (e) => {
-        dragging = true;
-        startY = e.clientY;
-        startVH = viewer.getBoundingClientRect().height;
-        document.body.style.cursor = 'row-resize';
-        document.body.style.userSelect = 'none';
-        handle.querySelector('div').style.background = 'var(--accent)';
-        e.preventDefault();
-    });
-    document.addEventListener('mousemove', (e) => {
-        if (!dragging) return;
-        const wsH = workspace.getBoundingClientRect().height;
-        const delta = e.clientY - startY;
-        let newVH = startVH + delta;
-        // Clamp: viewer min 150px, library min 100px
-        newVH = Math.max(150, Math.min(wsH - 100 - 5, newVH));
-        viewer.style.flex = 'none';
-        viewer.style.height = newVH + 'px';
-        library.style.flex = '1';
-    });
-    document.addEventListener('mouseup', () => {
-        if (dragging) {
-            dragging = false;
-            document.body.style.cursor = '';
-            document.body.style.userSelect = '';
-            handle.querySelector('div').style.background = 'var(--border)';
-        }
-    });
-    // Hover highlight
-    handle.addEventListener('mouseenter', () => { handle.querySelector('div').style.background = 'var(--text-dim)'; });
-    handle.addEventListener('mouseleave', () => { if (!dragging) handle.querySelector('div').style.background = 'var(--border)'; });
-})();
-// ──────────────────────────────────────────────────────────────────────────────
-
-
-
-
-
-
-// 动态获取当前访问的域名或 IP，自动对齐 3000 端口
-    const BASE = `http://${window.location.hostname}:3000`;
-    
-    let currentMode = 'image';
-    let pollInterval = null;
-    let isEnglish = false;
-
-    function toggleLang() {
-        isEnglish = !isEnglish;
-        const lang = isEnglish ? 'en' : 'zh';
-        
-        document.querySelectorAll('[data-lang-zh]').forEach(el => {
-            if (el.tagName === 'INPUT' || el.tagName === 'TEXTAREA') {
-                el.placeholder = el.getAttribute('data-lang-' + lang) || el.placeholder;
-            } else {
-                el.textContent = el.getAttribute('data-lang-' + lang) || el.textContent;
-            }
-        });
-        
-        document.getElementById('langBtn').title = isEnglish ? '切换语言' : 'Toggle Language';
-    }
-
-    // 建议增加一个简单的调试日志，方便在控制台确认地址是否正确
-    console.log("Connecting to Backend API at:", BASE);
-
-    // 分辨率自动计算逻辑
-    function updateResPreview() {
-        const q = document.getElementById('vid-quality').value; // "1080", "720", "544"
-        const r = document.getElementById('vid-ratio').value;
-        
-        let resLabel = q === "1080" ? "1080p" : q === "720" ? "720p" : "576p";
-        
-        let resDisplay;
-        if (r === "16:9") {
-            resDisplay = q === "1080" ? "1920x1080" : q === "720" ? "1280x720" : "1024x576";
-        } else {
-            resDisplay = q === "1080" ? "1080x1920" : q === "720" ? "720x1280" : "576x1024";
-        }
-        
-        document.getElementById('res-preview').innerText = `最终发送规格: ${resLabel} (${resDisplay})`;
-        return resLabel;
-    }
-
-    // 图片分辨率预览
-    function updateImgResPreview() {
-        const w = document.getElementById('img-w').value;
-        const h = document.getElementById('img-h').value;
-        document.getElementById('img-res-preview').innerText = `最终发送规格: ${w}x${h}`;
-    }
-
-    // 切换图片预设分辨率
-    function applyImgPreset(val) {
-        if (val === "custom") {
-            document.getElementById('img-custom-res').style.display = 'flex';
-        } else {
-            const [w, h] = val.split('x');
-            document.getElementById('img-w').value = w;
-            document.getElementById('img-h').value = h;
-            updateImgResPreview();
-            // 隐藏自定义区域或保持显示供微调
-            // document.getElementById('img-custom-res').style.display = 'none';
-        }
-    }
-
-
-
-    // 处理帧图片上传
-    async function handleFrameUpload(file, frameType) {
-        if (!file) return;
-
-        const preview = document.getElementById(`${frameType}-frame-preview`);
-        const placeholder = document.getElementById(`${frameType}-frame-placeholder`);
-        const clearOverlay = document.getElementById(`clear-${frameType}-frame-overlay`);
-
-        const previewReader = new FileReader();
-        previewReader.onload = (e) => {
-            preview.src = e.target.result;
-            preview.style.display = 'block';
-            placeholder.style.display = 'none';
-            clearOverlay.style.display = 'flex';
-        };
-        previewReader.readAsDataURL(file);
-
-        const reader = new FileReader();
-        reader.onload = async (e) => {
-            const b64Data = e.target.result;
-            addLog(`正在上传 ${frameType === 'start' ? '起始帧' : '结束帧'}: ${file.name}...`);
-            try {
-                const res = await fetch(`${BASE}/api/system/upload-image`, {
-                    method: 'POST',
-                    headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({ image: b64Data, filename: file.name })
-                });
-                const data = await res.json();
-                if (res.ok && data.path) {
-                    document.getElementById(`${frameType}-frame-path`).value = data.path;
-                    addLog(`✅ ${frameType === 'start' ? '起始帧' : '结束帧'}上传成功`);
-                } else {
-                    throw new Error(data.error || data.detail || "上传失败");
-                }
-            } catch (e) {
-                addLog(`❌ 帧图片上传失败: ${e.message}`);
-            }
-        };
-        reader.readAsDataURL(file);
-    }
-
-    function clearFrame(frameType) {
-        document.getElementById(`${frameType}-frame-input`).value = "";
-        document.getElementById(`${frameType}-frame-path`).value = "";
-        document.getElementById(`${frameType}-frame-preview`).style.display = 'none';
-        document.getElementById(`${frameType}-frame-preview`).src = "";
-        document.getElementById(`${frameType}-frame-placeholder`).style.display = 'block';
-        document.getElementById(`clear-${frameType}-frame-overlay`).style.display = 'none';
-        addLog(`🧹 已清除${frameType === 'start' ? '起始帧' : '结束帧'}`);
-    }
-
-    // 处理图片上传
-    async function handleImageUpload(file) {
-        if (!file) return;
-        
-        // 预览图片
-        const preview = document.getElementById('upload-preview');
-        const placeholder = document.getElementById('upload-placeholder');
-        const clearOverlay = document.getElementById('clear-img-overlay');
-        
-        const previewReader = new FileReader();
-        preview.onload = () => {
-            preview.style.display = 'block';
-            placeholder.style.display = 'none';
-            clearOverlay.style.display = 'flex';
-        };
-        previewReader.onload = (e) => preview.src = e.target.result;
-        previewReader.readAsDataURL(file);
-
-        // 使用 FileReader 转换为 Base64，绕过后端缺失 python-multipart 的问题
-        const reader = new FileReader();
-        reader.onload = async (e) => {
-            const b64Data = e.target.result;
-            addLog(`正在上传参考图: ${file.name}...`);
-            try {
-                const res = await fetch(`${BASE}/api/system/upload-image`, {
-                    method: 'POST',
-                    headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({
-                        image: b64Data,
-                        filename: file.name
-                    })
-                });
-                const data = await res.json();
-                if (res.ok && data.path) {
-                    document.getElementById('uploaded-img-path').value = data.path;
-                    addLog(`✅ 参考图上传成功: ${file.name}`);
-                } else {
-                    const errMsg = data.error || data.detail || "上传失败";
-                    throw new Error(typeof errMsg === 'string' ? errMsg : JSON.stringify(errMsg));
-                }
-            } catch (e) {
-                addLog(`❌ 图片上传失败: ${e.message}`);
-            }
-        };
-        reader.onerror = () => addLog("❌ 读取本地文件失败");
-        reader.readAsDataURL(file);
-    }
-
-    function clearUploadedImage() {
-        document.getElementById('vid-image-input').value = "";
-        document.getElementById('uploaded-img-path').value = "";
-        document.getElementById('upload-preview').style.display = 'none';
-        document.getElementById('upload-preview').src = "";
-        document.getElementById('upload-placeholder').style.display = 'block';
-        document.getElementById('clear-img-overlay').style.display = 'none';
-        addLog("🧹 已清除参考图");
-    }
-
-    // 处理音频上传
-    async function handleAudioUpload(file) {
-        if (!file) return;
-
-        const placeholder = document.getElementById('audio-upload-placeholder');
-        const statusDiv = document.getElementById('audio-upload-status');
-        const filenameStatus = document.getElementById('audio-filename-status');
-        const clearOverlay = document.getElementById('clear-audio-overlay');
-
-        placeholder.style.display = 'none';
-        filenameStatus.innerText = file.name;
-        statusDiv.style.display = 'block';
-        clearOverlay.style.display = 'flex';
-
-        const reader = new FileReader();
-        reader.onload = async (e) => {
-            const b64Data = e.target.result;
-            addLog(`正在上传音频: ${file.name}...`);
-            try {
-                // 复用图片上传接口，后端已支持任意文件类型
-                const res = await fetch(`${BASE}/api/system/upload-image`, {
-                    method: 'POST',
-                    headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({
-                        image: b64Data,
-                        filename: file.name
-                    })
-                });
-                const data = await res.json();
-                if (res.ok && data.path) {
-                    document.getElementById('uploaded-audio-path').value = data.path;
-                    addLog(`✅ 音频上传成功: ${file.name}`);
-                } else {
-                    const errMsg = data.error || data.detail || "上传失败";
-                    throw new Error(typeof errMsg === 'string' ? errMsg : JSON.stringify(errMsg));
-                }
-            } catch (e) {
-                addLog(`❌ 音频上传失败: ${e.message}`);
-            }
-        };
-        reader.onerror = () => addLog("❌ 读取本地音频文件失败");
-        reader.readAsDataURL(file);
-    }
-
-    function clearUploadedAudio() {
-        document.getElementById('vid-audio-input').value = "";
-        document.getElementById('uploaded-audio-path').value = "";
-        document.getElementById('audio-upload-placeholder').style.display = 'block';
-        document.getElementById('audio-upload-status').style.display = 'none';
-        document.getElementById('clear-audio-overlay').style.display = 'none';
-        addLog("🧹 已清除音频文件");
-    }
-
-    // 处理超分视频上传
-    async function handleUpscaleVideoUpload(file) {
-        if (!file) return;
-        const placeholder = document.getElementById('upscale-placeholder');
-        const statusDiv = document.getElementById('upscale-status');
-        const filenameStatus = document.getElementById('upscale-filename');
-        const clearOverlay = document.getElementById('clear-upscale-overlay');
-
-        filenameStatus.innerText = file.name;
-        placeholder.style.display = 'none';
-        statusDiv.style.display = 'block';
-        clearOverlay.style.display = 'flex';
-
-        const reader = new FileReader();
-        reader.onload = async (e) => {
-            const b64Data = e.target.result;
-            addLog(`正在上传待超分视频: ${file.name}...`);
-            try {
-                const res = await fetch(`${BASE}/api/system/upload-image`, {
-                    method: 'POST',
-                    headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({ image: b64Data, filename: file.name })
-                });
-                const data = await res.json();
-                if (res.ok && data.path) {
-                    document.getElementById('upscale-video-path').value = data.path;
-                    addLog(`✅ 视频上传成功`);
-                } else {
-                    throw new Error(data.error || "上传失败");
-                }
-            } catch (e) {
-                addLog(`❌ 视频上传失败: ${e.message}`);
-            }
-        };
-        reader.readAsDataURL(file);
-    }
-
-    function clearUpscaleVideo() {
-        document.getElementById('upscale-video-input').value = "";
-        document.getElementById('upscale-video-path').value = "";
-        document.getElementById('upscale-placeholder').style.display = 'block';
-        document.getElementById('upscale-status').style.display = 'none';
-        document.getElementById('clear-upscale-overlay').style.display = 'none';
-        addLog("🧹 已清除待超分视频");
-    }
-
-    // 初始化拖拽上传逻辑
-    function initDragAndDrop() {
-        const audioDropZone = document.getElementById('audio-drop-zone');
-        const startFrameDropZone = document.getElementById('start-frame-drop-zone');
-        const endFrameDropZone = document.getElementById('end-frame-drop-zone');
-        const upscaleDropZone = document.getElementById('upscale-drop-zone');
-        
-        const zones = [audioDropZone, startFrameDropZone, endFrameDropZone, upscaleDropZone];
-
-        ['dragenter', 'dragover', 'dragleave', 'drop'].forEach(eventName => {
-            zones.forEach(zone => {
-                if (!zone) return;
-                zone.addEventListener(eventName, (e) => {
-                    e.preventDefault();
-                    e.stopPropagation();
-                }, false);
-            });
-        });
-
-        ['dragenter', 'dragover'].forEach(eventName => {
-            zones.forEach(zone => {
-                if (!zone) return;
-                zone.addEventListener(eventName, () => zone.classList.add('dragover'), false);
-            });
-        });
-
-        ['dragleave', 'drop'].forEach(eventName => {
-            zones.forEach(zone => {
-                if (!zone) return;
-                zone.addEventListener(eventName, () => zone.classList.remove('dragover'), false);
-            });
-        });
-
-        audioDropZone.addEventListener('drop', (e) => {
-            const file = e.dataTransfer.files[0];
-            if (file && file.type.startsWith('audio/')) handleAudioUpload(file);
-        }, false);
-
-        startFrameDropZone.addEventListener('drop', (e) => {
-            const file = e.dataTransfer.files[0];
-            if (file && file.type.startsWith('image/')) handleFrameUpload(file, 'start');
-        }, false);
-
-        endFrameDropZone.addEventListener('drop', (e) => {
-            const file = e.dataTransfer.files[0];
-            if (file && file.type.startsWith('image/')) handleFrameUpload(file, 'end');
-        }, false);
-
-        upscaleDropZone.addEventListener('drop', (e) => {
-            const file = e.dataTransfer.files[0];
-            if (file && file.type.startsWith('video/')) handleUpscaleVideoUpload(file);
-        }, false);
-    }
-
-    let _isGeneratingFlag = false;
-
-    // 系统状态轮询
-    async function checkStatus() {
-        try {
-            const h = await fetch(`${BASE}/health`).then(r => r.json()).catch(() => ({status: "error"}));
-            const g = await fetch(`${BASE}/api/gpu-info`).then(r => r.json()).catch(() => ({gpu_info: {}}));
-            const p = await fetch(`${BASE}/api/generation/progress`).then(r => r.json()).catch(() => ({progress: 0}));
-            const sysGpus = await fetch(`${BASE}/api/system/list-gpus`).then(r => r.json()).catch(() => ({gpus: []}));
-            
-            const activeGpu = (sysGpus.gpus || []).find(x => x.active) || (sysGpus.gpus || [])[0] || {};
-            const gpuName = activeGpu.name || g.gpu_info?.name || "GPU";
-            
-            const s = document.getElementById('sys-status');
-            const indicator = document.getElementById('sys-indicator');
-            
-            const isReady = h.status === "ok" || h.status === "ready" || h.models_loaded;
-            const backendActive = (p && p.progress > 0);
-            
-            if (_isGeneratingFlag || backendActive) {
-                s.innerText = `${gpuName}: 运算中...`;
-                if(indicator) indicator.className = 'indicator-busy';
-            } else {
-                s.innerText = isReady ? `${gpuName}: 在线 / 就绪` : `${gpuName}: 启动中...`;
-                if(indicator) indicator.className = isReady ? 'indicator-ready' : 'indicator-offline';
-            }
-            s.style.color = "var(--text-dim)";
-
-            const vUsedMB = g.gpu_info?.vramUsed || 0;
-            const vTotalMB = activeGpu.vram_mb || g.gpu_info?.vram || 32768; 
-            const vUsedGB = vUsedMB / 1024;
-            const vTotalGB = vTotalMB / 1024;
-            
-            document.getElementById('vram-fill').style.width = (vUsedMB / vTotalMB * 100) + "%";
-            document.getElementById('vram-text').innerText = `${vUsedGB.toFixed(1)} / ${vTotalGB.toFixed(0)} GB`;
-        } catch(e) { document.getElementById('sys-status').innerText = "未检测到后端 (Port 3000)"; }
-    }
-    setInterval(checkStatus, 1000); // 提升到 1 秒一次实时监控
-    checkStatus();
-    initDragAndDrop();
-    listGpus(); // 初始化 GPU 列表
-    getOutputDir(); // 获取当前的保存路径
-
-    async function setOutputDir() {
-        const dir = document.getElementById('global-out-dir').value.trim();
-        try {
-            const res = await fetch(`${BASE}/api/system/set-dir`, {
-                method: 'POST',
-                headers: { 'Content-Type': 'application/json' },
-                body: JSON.stringify({ directory: dir })
-            });
-            if (res.ok) {
-                addLog(`✅ 存储路径更新成功! 当前路径: ${dir || '默认路径'}`);
-                if (typeof fetchHistory === 'function') fetchHistory(currentHistoryPage);
-            }
-        } catch (e) {
-            addLog(`❌ 设置路径时连接异常: ${e.message}`);
-        }
-    }
-
-    async function browseOutputDir() {
-        try {
-            const res = await fetch(`${BASE}/api/system/browse-dir`);
-            const data = await res.json();
-            if (data.status === "success" && data.directory) {
-                document.getElementById('global-out-dir').value = data.directory;
-                // auto apply immediately
-                setOutputDir();
-                addLog(`📂 检测到新路径，已自动套用！`);
-            } else if (data.error) {
-                addLog(`❌ 内部系统权限拦截了弹窗: ${data.error}`);
-            }
-        } catch (e) {
-            addLog(`❌ 无法调出文件夹浏览弹窗, 请直接复制粘贴绝对路径。`);
-        }
-    }
-
-    async function getOutputDir() {
-        try {
-            const res = await fetch(`${BASE}/api/system/get-dir`);
-            const data = await res.json();
-            if (data.directory && data.directory.indexOf('LTXDesktop') === -1 && document.getElementById('global-out-dir')) {
-                document.getElementById('global-out-dir').value = data.directory;
-            }
-        } catch (e) {}
-    }
-
-    function switchMode(m) {
-        currentMode = m;
-        document.getElementById('tab-image').classList.toggle('active', m === 'image');
-        document.getElementById('tab-video').classList.toggle('active', m === 'video');
-        document.getElementById('tab-upscale').classList.toggle('active', m === 'upscale');
-        
-        document.getElementById('image-opts').style.display = m === 'image' ? 'block' : 'none';
-        document.getElementById('video-opts').style.display = m === 'video' ? 'block' : 'none';
-        document.getElementById('upscale-opts').style.display = m === 'upscale' ? 'block' : 'none';
-        
-        // 如果切到图像模式，隐藏提示词框外的其他东西
-        document.getElementById('prompt').placeholder = m === 'upscale' ? "输入画面增强引导词 (可选)..." : "在此输入视觉描述词 (Prompt)...";
-    }
-
-    function showGeneratingView() {
-        if (!_isGeneratingFlag) return;
-        const resImg = document.getElementById('res-img');
-        const videoWrapper = document.getElementById('video-wrapper');
-        if (resImg) resImg.style.display = "none";
-        if (videoWrapper) videoWrapper.style.display = "none";
-        if (player) {
-            try { player.stop(); } catch(_) {}
-        } else {
-            const vid = document.getElementById('res-video');
-            if (vid) { vid.pause(); vid.removeAttribute('src'); vid.load(); }
-        }
-        const loadingTxt = document.getElementById('loading-txt');
-        if (loadingTxt) loadingTxt.style.display = "flex";
-    }
-
-    async function run() {
-        // 防止重复点击（_isGeneratingFlag 比 btn.disabled 更可靠）
-        if (_isGeneratingFlag) {
-            addLog("⚠️ 当前正在生成中，请等待完成");
-            return;
-        }
-
-        const btn = document.getElementById('mainBtn');
-        const prompt = document.getElementById('prompt').value.trim();
-
-        if (currentMode !== 'upscale' && !prompt) {
-            addLog("⚠️ 请输入提示词后再开始渲染");
-            return;
-        }
-
-        // 先设置标志 + 禁用按钮，然后用顶层 try/finally 保证一定能解锁
-        _isGeneratingFlag = true;
-        btn.disabled = true;
-
-        try {
-            // 安全地操作 UI 元素（改用 if 判空，防止 Plyr 接管后 getElementById 返回 null）
-            const loader = document.getElementById('loading-txt');
-            const resImg = document.getElementById('res-img');
-            const resVideo = document.getElementById('res-video');
-
-            if (loader) {
-                loader.style.display = "flex";
-                loader.style.flexDirection = "column";
-                loader.style.alignItems = "center";
-                loader.style.gap = "12px";
-                loader.innerHTML = `
-                    <div class="spinner" style="width:48px;height:48px;border-width:4px;color:var(--accent);"></div>
-                    <div id="loader-step-text" style="font-size:13px;font-weight:700;color:var(--text-sub);">GPU 正在分配资源...</div>
-                `;
-            }
-            if (resImg) resImg.style.display = "none";
-            // 必须隐藏整个 video-wrapper（Plyr 外层容器），否则第二次生成时视频会与 spinner 叠加
-            const videoWrapper = document.getElementById('video-wrapper');
-            if (videoWrapper) videoWrapper.style.display = "none";
-            if (player) { try { player.stop(); } catch(_) {} }
-            else if (resVideo) { resVideo.pause?.(); resVideo.removeAttribute?.('src'); }
-
-        checkStatus();
-
-            // 重置后端状态锁（非关键，失败不影响主流程）
-            try { await fetch(`${BASE}/api/system/reset-state`, { method: 'POST' }); } catch(_) {}
-
-            startProgressPolling();
-
-            // ---- 新增：在历史记录区插入「正在渲染」缩略图卡片 ----
-            const historyContainer = document.getElementById('history-container');
-            if (historyContainer) {
-                const old = document.getElementById('current-loading-card');
-                if (old) old.remove();
-                const loadingCard = document.createElement('div');
-                loadingCard.className = 'history-card loading-card';
-                loadingCard.id = 'current-loading-card';
-                loadingCard.onclick = showGeneratingView;
-                loadingCard.innerHTML = `
-                    <div class="spinner"></div>
-                    <div id="loading-card-step" style="font-size:10px;color:var(--text-dim);margin-top:4px;">等待中...</div>
-                `;
-                historyContainer.prepend(loadingCard);
-            }
-
-            // ---- 构建请求 ----
-            let endpoint, payload;
-            if (currentMode === 'image') {
-                const w = parseInt(document.getElementById('img-w').value);
-                const h = parseInt(document.getElementById('img-h').value);
-                endpoint = '/api/generate-image';
-                payload = {
-                    prompt, width: w, height: h,
-                    numSteps: parseInt(document.getElementById('img-steps').value),
-                    numImages: 1
-                };
-                addLog(`正在发起图像渲染: ${w}x${h}, Steps: ${payload.numSteps}`);
-
-            } else if (currentMode === 'video') {
-                const res = updateResPreview();
-                const dur = parseFloat(document.getElementById('vid-duration').value);
-                const fps = document.getElementById('vid-fps').value;
-                if (dur > 20) addLog(`⚠️ 时长设定为 ${dur}s 极长，可能导致显存溢出或耗时较久。`);
-
-                const audio = document.getElementById('vid-audio').checked ? "true" : "false";
-                const audioPath = document.getElementById('uploaded-audio-path').value;
-                const startFramePathValue = document.getElementById('start-frame-path').value;
-                const endFramePathValue = document.getElementById('end-frame-path').value;
-
-                let finalImagePath = null, finalStartFramePath = null, finalEndFramePath = null;
-                if (startFramePathValue && endFramePathValue) {
-                    finalStartFramePath = startFramePathValue;
-                    finalEndFramePath = endFramePathValue;
-                } else if (startFramePathValue) {
-                    finalImagePath = startFramePathValue;
-                }
-
-                endpoint = '/api/generate';
-                payload = {
-                    prompt, resolution: res, model: "ltx-2",
-                    cameraMotion: document.getElementById('vid-motion').value,
-                    negativePrompt: "low quality, blurry, noisy, static noise, distorted",
-                    duration: String(dur), fps, audio,
-                    imagePath: finalImagePath,
-                    audioPath: audioPath || null,
-                    startFramePath: finalStartFramePath,
-                    endFramePath: finalEndFramePath,
-                    aspectRatio: document.getElementById('vid-ratio').value
-                };
-                addLog(`正在发起视频渲染: ${res}, 时长: ${dur}s, FPS: ${fps}, 音频: ${audio}, 参考图: ${finalImagePath ? '已加载' : '无'}, 参考音频: ${audioPath ? '已加载' : '无'}, 插帧: ${finalStartFramePath && finalEndFramePath ? '已加载' : '无'}, 镜头: ${payload.cameraMotion}`);
-
-            } else if (currentMode === 'upscale') {
-                const videoPath = document.getElementById('upscale-video-path').value;
-                const targetRes = document.getElementById('upscale-res').value;
-                if (!videoPath) throw new Error("请先上传待超分的视频");
-                endpoint = '/api/system/upscale-video';
-                payload = { video_path: videoPath, resolution: targetRes, prompt: "high quality, detailed, 4k", strength: 0.7 };
-                addLog(`正在发起视频超分: 目标 ${targetRes}`);
-            }
-
-            // ---- 发送请求 ----
-            const res = await fetch(BASE + endpoint, {
-                method: 'POST',
-                headers: { 'Content-Type': 'application/json' },
-                body: JSON.stringify(payload)
-            });
-            const data = await res.json();
-            if (!res.ok) {
-                const errMsg = data.error || data.detail || "API 拒绝了请求";
-                throw new Error(typeof errMsg === 'string' ? errMsg : JSON.stringify(errMsg));
-            }
-
-            // ---- 显示结果 ----
-            const rawPath = data.image_paths ? data.image_paths[0] : data.video_path;
-            if (rawPath) {
-                try { displayOutput(rawPath); } catch (dispErr) { addLog(`⚠️ 播放器显示异常: ${dispErr.message}`); }
-            }
-
-            // 强制刷新历史记录（不依赖 isLoadingHistory 标志，确保新生成的视频立即显示）
-            setTimeout(() => {
-                isLoadingHistory = false; // 强制重置状态
-                if (typeof fetchHistory === 'function') fetchHistory(1);
-            }, 500);
-
-        } catch (e) {
-            addLog(`❌ 渲染中断: ${e.message}`);
-            const loader = document.getElementById('loading-txt');
-            if (loader) loader.innerText = "渲染失败，请检查显存或参数";
-
-        } finally {
-            // ✅ 无论发生什么，这里一定执行，确保按钮永远可以再次点击
-            _isGeneratingFlag = false;
-            btn.disabled = false;
-            stopProgressPolling();
-            checkStatus();
-            // 生成完毕后自动释放显存，降低 VRAM 压力（不 await 避免阻塞 UI 解锁）
-            setTimeout(() => clearGpu(), 500);
-        }
-    }
-
-    async function clearGpu() {
-        const btn = document.getElementById('clearGpuBtn');
-        btn.disabled = true;
-        btn.innerText = "清理中...";
-        try {
-            const res = await fetch(`${BASE}/api/system/clear-gpu`, {
-                method: 'POST',
-                headers: { 'Content-Type': 'application/json' }
-            });
-            const data = await res.json();
-            if (res.ok) {
-                addLog(`🧹 显存清理成功: ${data.message}`);
-                // 立即触发状态刷新
-                checkStatus();
-                setTimeout(checkStatus, 1000); 
-            } else {
-                const errMsg = data.error || data.detail || "后端未实现此接口 (404)";
-                throw new Error(errMsg);
-            }
-        } catch(e) {
-            addLog(`❌ 清理显存失败: ${e.message}`);
-        } finally {
-            btn.disabled = false;
-            btn.innerText = "释放显存";
-        }
-    }
-
-    async function listGpus() {
-        try {
-            const res = await fetch(`${BASE}/api/system/list-gpus`);
-            const data = await res.json();
-            if (res.ok && data.gpus) {
-                const selector = document.getElementById('gpu-selector');
-                selector.innerHTML = data.gpus.map(g => 
-                    `<option value="${g.id}" ${g.active ? 'selected' : ''}>GPU ${g.id}: ${g.name} (${g.vram})</option>`
-                ).join('');
-                
-                // 更新当前显示的 GPU 名称
-                const activeGpu = data.gpus.find(g => g.active);
-                if (activeGpu) document.getElementById('gpu-name').innerText = activeGpu.name;
-            }
-        } catch (e) {
-            console.error("Failed to list GPUs", e);
-        }
-    }
-
-    async function switchGpu(id) {
-        if (!id) return;
-        addLog(`🔄 正在切换到 GPU ${id}...`);
-        try {
-            const res = await fetch(`${BASE}/api/system/switch-gpu`, {
-                method: 'POST',
-                headers: { 'Content-Type': 'application/json' },
-                body: JSON.stringify({ gpu_id: parseInt(id) })
-            });
-            const data = await res.json();
-            if (res.ok) {
-                addLog(`✅ 已成功切换到 GPU ${id}，模型将重新加载。`);
-                listGpus(); // 重新获取列表以同步状态
-                setTimeout(checkStatus, 1000);
-            } else {
-                throw new Error(data.error || "切换失败");
-            }
-        } catch (e) {
-            addLog(`❌ GPU 切换失败: ${e.message}`);
-        }
-    }
-
-    function startProgressPolling() {
-        if (pollInterval) clearInterval(pollInterval);
-        pollInterval = setInterval(async () => {
-            try {
-                const res = await fetch(`${BASE}/api/generation/progress`);
-                const d = await res.json();
-                if (d.progress > 0) {
-                    const phaseMap = {
-                        'loading_model': '加载权重',
-                        'encoding_text': 'T5 编码',
-                        'validating_request': '校验请求',
-                        'uploading_audio': '上传音频',
-                        'uploading_image': '上传图像',
-                        'inference': 'AI 推理',
-                        'downloading_output': '下载结果',
-                        'complete': '完成'
-                    };
-                    const phaseStr = phaseMap[d.phase] || d.phase || '推理';
-
-                    // 步骤格式：优先显示 current_step/total_steps，降级用百分比
-                    let stepLabel;
-                    if (d.current_step !== undefined && d.current_step !== null && d.total_steps) {
-                        stepLabel = `${d.current_step}/${d.total_steps} 步`;
-                    } else {
-                        stepLabel = `${d.progress}%`;
-                    }
-
-                    document.getElementById('progress-fill').style.width = d.progress + "%";
-                    // 更��主预览区的进度文字（内嵌子元素）
-                    const loaderStep = document.getElementById('loader-step-text');
-                    if (loaderStep) loaderStep.innerText = `GPU 运算中: ${stepLabel}  [ ${phaseStr} ]`;
-                    else {
-                        const loadingTxt = document.getElementById('loading-txt');
-                        if (loadingTxt) loadingTxt.innerText = `GPU 运算中: ${stepLabel} [${phaseStr}]`;
-                    }
-
-                    // 同步更新历史缩略图卡片上的进度文字
-                    const cardStep = document.getElementById('loading-card-step');
-                    if (cardStep) cardStep.innerText = stepLabel;
-                }
-            } catch(e) {}
-        }, 1000);
-    }
-
-    function stopProgressPolling() {
-        clearInterval(pollInterval);
-        pollInterval = null;
-        document.getElementById('progress-fill').style.width = "0%";
-        // 移除渲染中的卡片（生成已结束）
-        const lc = document.getElementById('current-loading-card');
-        if (lc) lc.remove();
-    }
-
-    function displayOutput(fileOrPath) {
-        const img = document.getElementById('res-img');
-        const vid = document.getElementById('res-video');
-        const loader = document.getElementById('loading-txt');
-        
-        // 关键BUG修复：切换前强制清除并停止现有视频和声音，避免后台继续播放
-        if(player) {
-            player.stop();
-        } else {
-            vid.pause();
-            vid.removeAttribute('src');
-            vid.load();
-        }
-        
-        let url = "";
-        let fileName = fileOrPath;
-        if (fileOrPath.indexOf('\\') !== -1 || fileOrPath.indexOf('/') !== -1) {
-            url = `${BASE}/api/system/file?path=${encodeURIComponent(fileOrPath)}&t=${Date.now()}`;
-            fileName = fileOrPath.split(/[\\/]/).pop();
-        } else {
-            const outInput = document.getElementById('global-out-dir');
-            const globalDir = outInput ? outInput.value.replace(/\\/g, '/').replace(/\/$/, '') : "";
-            if (globalDir && globalDir !== "") {
-                url = `${BASE}/api/system/file?path=${encodeURIComponent(globalDir + '/' + fileOrPath)}&t=${Date.now()}`;
-            } else {
-                url = `${BASE}/outputs/${fileOrPath}?t=${Date.now()}`;
-            }
-        }
-
-        loader.style.display = "none";
-        if (currentMode === 'image') {
-            img.src = url;
-            img.style.display = "block";
-            addLog(`✅ 图像渲染成功: ${fileName}`);
-        } else {
-            document.getElementById('video-wrapper').style.display = "flex";
-            
-            if(player) {
-                player.source = {
-                    type: 'video',
-                    sources: [{ src: url, type: 'video/mp4' }]
-                };
-                player.play();
-            } else {
-                vid.src = url;
-            }
-            addLog(`✅ 视频渲染成功: ${fileName}`);
-        }
-    }
-
-
-
-    function addLog(msg) {
-        const log = document.getElementById('log');
-        const time = new Date().toLocaleTimeString();
-        log.innerHTML += `<div style="margin-bottom:5px"> <span style="color:var(--text-dim)">[${time}]</span> ${msg}</div>`;
-        log.scrollTop = log.scrollHeight;
-    }
-
-
-// Force switch to video mode on load
-window.addEventListener('DOMContentLoaded', () => switchMode('video'));
-
-
-    
-    
-    
-    
-    
-    
-    
-    
-    
-    
-    let isLoadingHistory = false;
-
-    function switchLibTab(tab) {
-        document.getElementById('log-container').style.display = tab === 'log' ? 'flex' : 'none';
-        const hw = document.getElementById('history-wrapper');
-        if (hw) hw.style.display = tab === 'history' ? 'block' : 'none';
-        
-        document.getElementById('tab-log').style.color = tab === 'log' ? 'var(--accent)' : 'var(--text-dim)';
-        document.getElementById('tab-log').style.borderColor = tab === 'log' ? 'var(--accent)' : 'transparent';
-        
-        document.getElementById('tab-history').style.color = tab === 'history' ? 'var(--accent)' : 'var(--text-dim)';
-        document.getElementById('tab-history').style.borderColor = tab === 'history' ? 'var(--accent)' : 'transparent';
-        
-        if (tab === 'history') {
-            fetchHistory();
-        }
-    }
-
-    async function fetchHistory(isFirstLoad = false, silent = false) {
-        if (isLoadingHistory) return;
-        isLoadingHistory = true;
-        
-        try {
-            // 加载所有历史，不分页
-            const res = await fetch(`${BASE}/api/system/history?page=1&limit=10000`);
-            if (!res.ok) {
-                isLoadingHistory = false;
-                return;
-            }
-            const data = await res.json();
-            
-            if (data.history && data.history.length > 0) {
-                const container = document.getElementById('history-container');
-                
-                // 清空容器
-                let loadingCardHtml = "";
-                const lc = document.getElementById('current-loading-card');
-                if (lc && _isGeneratingFlag) {
-                    loadingCardHtml = lc.outerHTML;
-                }
-                container.innerHTML = loadingCardHtml;
-
-                const outInput = document.getElementById('global-out-dir');
-                const globalDir = outInput ? outInput.value.replace(/\\/g, '/').replace(/\/$/, '') : "";
-                
-                // 过滤无效数据
-                const validHistory = data.history.filter(item => item && item.filename);
-                
-                const cardsHtml = validHistory.map((item, index) => {
-                    const url = (globalDir && globalDir !== "") 
-                        ? `${BASE}/api/system/file?path=${encodeURIComponent(globalDir + '/' + item.filename)}` 
-                        : `${BASE}/outputs/${item.filename}`;
-                        
-                    const safeFilename = item.filename.replace(/'/g, "\\'").replace(/"/g, '\\"');
-                    const media = item.type === 'video' 
-                        ? `<video data-src="${url}#t=0.001" class="lazy-load" muted loop preload="none" onmouseover="if(this.readyState >= 2) this.play()" onmouseout="this.pause()" style="pointer-events: none; object-fit: cover; width: 100%; height: 100%;"></video>` 
-                        : `<img data-src="${url}" class="lazy-load" style="object-fit: cover; width: 100%; height: 100%;">`;
-                    return `<div class="history-card" onclick="displayHistoryOutput('${safeFilename}', '${item.type}')">
-                                <div class="history-type-badge">${item.type === 'video' ? '🎬 VID' : '🎨 IMG'}</div>
-                                <button class="history-delete-btn" onclick="event.stopPropagation(); deleteHistoryItem('${safeFilename}', '${item.type}', this)">✕</button>
-                                ${media}
-                            </div>`;
-                }).join('');
-
-                container.insertAdjacentHTML('beforeend', cardsHtml);
-
-                // 重新绑定loading card点击事件
-                const newLc = document.getElementById('current-loading-card');
-                if (newLc) newLc.onclick = showGeneratingView;
-                
-                // 加载可见的图片
-                loadVisibleImages();
-            }
-        } catch(e) {
-            console.error("Failed to load history", e);
-        } finally {
-            isLoadingHistory = false;
-        }
-    }
-    
-    async function deleteHistoryItem(filename, type, btn) {
-        if (!confirm(`确定要删除 "${filename}" 吗？`)) return;
-        
-        try {
-            const res = await fetch(`${BASE}/api/system/delete-file`, {
-                method: 'POST',
-                headers: {'Content-Type': 'application/json'},
-                body: JSON.stringify({filename: filename, type: type})
-            });
-            
-            if (res.ok) {
-                // 删除成功后移除元素
-                const card = btn.closest('.history-card');
-                if (card) {
-                    card.remove();
-                }
-            } else {
-                alert('删除失败');
-            }
-        } catch(e) {
-            console.error('Delete failed', e);
-            alert('删除失败');
-        }
-    }
-
-    function loadVisibleImages() {
-        const hw = document.getElementById('history-wrapper');
-        if (!hw) return;
-        
-        const lazyMedias = document.querySelectorAll('#history-container .lazy-load');
-        
-        // 每次只加载3个媒体元素（图片或视频）
-        let loadedCount = 0;
-        lazyMedias.forEach(media => {
-            if (loadedCount >= 3) return;
-            
-            const src = media.dataset.src;
-            if (!src) return;
-            
-            // 检查是否在可见区域附近
-            const rect = media.getBoundingClientRect();
-            const containerRect = hw.getBoundingClientRect();
-            
-            if (rect.top < containerRect.bottom + 300 && rect.bottom > containerRect.top - 100) {
-                media.src = src;
-                media.classList.remove('lazy-load');
-                
-                // 视频需要额外设置 preload
-                if (media.tagName === 'VIDEO') {
-                    media.preload = 'metadata';
-                }
-                
-                loadedCount++;
-            }
-        });
-        
-        // 继续检查直到没有更多媒体需要加载
-        if (loadedCount > 0) {
-            setTimeout(loadVisibleImages, 100);
-        }
-    }
-
-    // 监听history-wrapper���滚动事件来懒加载
-    function initHistoryScrollListener() {
-        const hw = document.getElementById('history-wrapper');
-        if (!hw) return;
-        
-        let scrollTimeout;
-        hw.addEventListener('scroll', () => {
-            if (scrollTimeout) clearTimeout(scrollTimeout);
-            scrollTimeout = setTimeout(() => {
-                loadVisibleImages();
-            }, 100);
-        });
-    }
-
-    // 页面加载时初始化滚动监听
-    window.addEventListener('DOMContentLoaded', () => {
-        setTimeout(initHistoryScrollListener, 500);
-    });
-
-    function displayHistoryOutput(file, type) {
-        document.getElementById('res-img').style.display = 'none';
-        document.getElementById('video-wrapper').style.display = 'none';
-
-        const mode = type === 'video' ? 'video' : 'image';
-        switchMode(mode);
-        displayOutput(file);
-    }
-    
-    window.addEventListener('DOMContentLoaded', () => {
-        // Initialize Plyr Custom Video Component
-        if(window.Plyr) {
-            player = new Plyr('#res-video', {
-                controls: [
-                    'play-large', 'play', 'progress', 'current-time', 
-                    'mute', 'volume', 'fullscreen'
-                ],
-                settings: [],
-                loop: { active: true },
-                autoplay: true
-            });
-        }
-        
-        // Fetch current directory context to show in UI
-        fetch(`${BASE}/api/system/get-dir`)
-            .then(res => res.json())
-            .then(data => {
-                if(data && data.directory) {
-                    const outInput = document.getElementById('global-out-dir');
-                    if (outInput) outInput.value = data.directory;
-                }
-            }).catch(e => console.error(e));
-
-        setTimeout(() => fetchHistory(1), 500);
-        
-        let historyRefreshInterval = null;
-        function startHistoryAutoRefresh() {
-            if (historyRefreshInterval) return;
-            historyRefreshInterval = setInterval(() => {
-                if (document.getElementById('history-container').style.display === 'flex' && !_isGeneratingFlag) {
-                    fetchHistory(1, true);
-                }
-            }, 5000);
-        }
-        startHistoryAutoRefresh();
-        switchLibTab('history');
-    });

LTX2.3/fix_ltx.ps1

@@ -1,43 +0,0 @@
-$scriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
-
-# Find shortcut in LTX_Shortcut folder
-$shortcut = Get-ChildItem -Path "$scriptDir\LTX_Shortcut" -Filter "*.lnk" | Select-Object -First 1
-
-if (-not $shortcut) {
-    Write-Host "[!] No shortcut found in LTX_Shortcut folder"
-    Write-Host "Please put LTX Desktop shortcut in LTX_Shortcut folder"
-    exit 1
-}
-
-Write-Host "     Found: $($shortcut.Name)"
-
-# Get target path from shortcut
-$shell = New-Object -ComObject WScript.Shell
-$shortcutObj = $shell.CreateShortcut($shortcut.FullName)
-$targetPath = $shortcutObj.TargetPath
-
-# Remove \LTX Desktop.exe from end
-$ltxDir = $targetPath -replace '\\LTX Desktop\.exe$', ''
-
-if (-not $ltxDir) {
-    Write-Host "[!] Could not read shortcut target"
-    exit 1
-}
-
-Write-Host "     LTX Dir: $ltxDir"
-
-$policyFile = Join-Path $ltxDir "resources\backend\runtime_config\runtime_policy.py"
-
-if (Test-Path $policyFile) {
-    Write-Host "     Found: $policyFile"
-    
-    $content = Get-Content $policyFile -Raw
-    $content = $content -replace [regex]::Escape('vram_gb < 31'), 'vram_gb < 6'
-    Set-Content -Path $policyFile -Value $content
-    
-    Write-Host "     ^_^ VRAM threshold changed to 6GB"
-} else {
-    Write-Host "[!] runtime_policy.py not found"
-    Write-Host "     Expected: $policyFile"
-    exit 1
-}

LTX2.3/main.py

@@ -1,248 +0,0 @@
-import os
-import sys
-import subprocess
-import threading
-import time
-import socket
-import logging
-from fastapi import FastAPI
-from fastapi.responses import FileResponse
-from fastapi.staticfiles import StaticFiles
-import uvicorn
-
-# ============================================================
-# 配置区 (动态路径适配与补丁挂载)
-# ============================================================
-def resolve_ltx_path():
-    import glob, tempfile, subprocess
-    sc_dir = os.path.join(os.getcwd(), "LTX_Shortcut")
-    os.makedirs(sc_dir, exist_ok=True)
-    lnk_files = glob.glob(os.path.join(sc_dir, "*.lnk"))
-    if not lnk_files:
-        print("\033[91m[ERROR] 未在 LTX_Shortcut 文件夹中找到快捷方式！\n请打开程序目录下的 LTX_Shortcut 文件夹，并将官方 LTX Desktop 的快捷方式复制进去后重试。\033[0m")
-        sys.exit(1)
-        
-    lnk_path = lnk_files[0]
-    # 使用 VBScript 解析快捷方式，兼容所有 Windows 系统
-    vbs_code = f'''Set sh = CreateObject("WScript.Shell")\nSet obj = sh.CreateShortcut("{os.path.abspath(lnk_path)}")\nWScript.Echo obj.TargetPath'''
-    fd, vbs_path = tempfile.mkstemp(suffix='.vbs')
-    with os.fdopen(fd, 'w') as f:
-        f.write(vbs_code)
-    try:
-        out = subprocess.check_output(['cscript', '//nologo', vbs_path], stderr=subprocess.STDOUT)
-        target_exe = out.decode('ansi').strip()
-    finally:
-        os.remove(vbs_path)
-        
-    if not target_exe or not os.path.exists(target_exe):
-        # 如果快捷方式解析失败，或者解析出来的是朋友电脑的路径（当前电脑不存在），自动全盘搜索默认路径
-        default_paths = [
-            os.path.join(os.environ.get("LOCALAPPDATA", ""), r"Programs\LTX Desktop\LTX Desktop.exe"),
-            r"C:\Program Files\LTX Desktop\LTX Desktop.exe",
-            r"D:\Program Files\LTX Desktop\LTX Desktop.exe",
-            r"E:\Program Files\LTX Desktop\LTX Desktop.exe"
-        ]
-        found = False
-        for p in default_paths:
-            if os.path.exists(p):
-                target_exe = p
-                print(f"\033[96m[INFO] 自动检测到 LTX 原版安装路径: {p}\033[0m")
-                found = True
-                break
-        
-        if not found:
-            print(f"\033[91m[ERROR] 未能找到原版 LTX Desktop 的安装路径！\033[0m")
-            print("请清理 LTX_Shortcut 文件夹，并将您当前电脑上真正的原版快捷方式重贴复制进去。")
-            sys.exit(1)
-        
-    return os.path.dirname(target_exe)
-
-USER_PROFILE = os.path.expanduser("~")
-PYTHON_EXE = os.path.join(USER_PROFILE, r"AppData\Local\LTXDesktop\python\python.exe")
-DATA_DIR = os.path.join(USER_PROFILE, r"AppData\Local\LTXDesktop")
-
-# 1. 动态获取主安装路径
-LTX_INSTALL_DIR = resolve_ltx_path()
-BACKEND_DIR = os.path.join(LTX_INSTALL_DIR, r"resources\backend")
-UI_FILE_NAME = "UI/index.html"
-
-# 环境致命检测：如果官方 Python 还没解压释放，立刻强制中断整个程序
-if not os.path.exists(PYTHON_EXE):
-    print(f"\n\033[1;41m [致命错误] 您的电脑上尚未配置好 LTX 的官方渲染核心框架！ \033[0m")
-    print(f"\033[93m此应用仅是 UI 图形控制台，必需依赖原版软件环境才能生成。在 ({PYTHON_EXE}) 未找到运行引擎。\n")
-    print(">> 解决方案：\n1. 请先在您的电脑上正常安装【LTX Desktop 官方原版软件】。")
-    print("2. 必需：双击打开运行一次原版软件！（运行后原版软件会在后台自动释放环境）")
-    print("3. 把原版软件的快捷方式复制到本文档的 LTX_Shortcut 文件夹里面。")
-    print("4. 全部完成后，再重新启动本 run.bat 脚本即可！\033[0m\n")
-    os._exit(1)
-
-# 2. 从目录读取改动过的 Python 文件 (热修复拦截器)
-PATCHES_DIR = os.path.join(os.getcwd(), "patches")
-os.makedirs(PATCHES_DIR, exist_ok=True)
-
-# 3. 默认输出定向至程序根目录
-LOCAL_OUTPUTS = os.path.join(os.getcwd(), "outputs")
-os.makedirs(LOCAL_OUTPUTS, exist_ok=True)
-
-# 强制注入自定义输出录至 LTX 缓存数据中
-os.makedirs(DATA_DIR, exist_ok=True)
-with open(os.path.join(DATA_DIR, "custom_dir.txt"), 'w', encoding='utf-8') as f:
-    f.write(LOCAL_OUTPUTS)
-
-os.environ["LTX_APP_DATA_DIR"] = DATA_DIR
-
-# 将 patches 目录优先级提升，做到 Python 无损替换
-os.environ["PYTHONPATH"] = f"{PATCHES_DIR};{BACKEND_DIR}"
-
-def get_lan_ip():
-    try:
-        host_name = socket.gethostname()
-        _, _, ip_list = socket.gethostbyname_ex(host_name)
-        
-        candidates = []
-        for ip in ip_list:
-            if ip.startswith("192.168."):
-                return ip
-            elif ip.startswith("10.") or (ip.startswith("172.") and 16 <= int(ip.split('.')[1]) <= 31):
-                candidates.append(ip)
-                
-        if candidates:
-            return candidates[0]
-            
-        # Fallback to the default socket routing approach if no obvious LAN IP found
-        s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
-        s.connect(("8.8.8.8", 80))
-        ip = s.getsockname()[0]
-        s.close()
-        return ip
-    except:
-        return "127.0.0.1"
-
-LAN_IP = get_lan_ip()
-
-# ============================================================
-# 服务启动逻辑
-# ============================================================
-def check_port_in_use(port):
-    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
-        return s.connect_ex(('127.0.0.1', port)) == 0
-
-def launch_backend():
-    """启动核心引擎 - 监听 0.0.0.0 确保局域网可调"""
-    if check_port_in_use(3000):
-        print(f"\n\033[1;41m [致命错误] 3000 端口已被占用，无法启动核心引擎！ \033[0m")
-        print("\033[93m>> 绝大多数情况下，这是因为【官方原版 LTX Desktop】正在您的电脑后台运行。\033[0m")
-        print(">> 冲突会导致显存爆炸。请检查右下角系统托盘图标，右键完全退出官方软件。")
-        print(">> 退出后重新双击 run.bat 启动本程序！\n")
-        os._exit(1)
-
-    print(f"\033[96m[CORE] 核心引擎正在启动...\033[0m")
-    # 只开启重要级别的 Python 应用层日志，去除无用的 HTTP 刷屏
-    import logging as _logging
-    _logging.basicConfig(
-        level=_logging.INFO,
-        format="[%(asctime)s] %(levelname)s %(name)s: %(message)s",
-        datefmt="%H:%M:%S",
-        force=True
-    )
-    
-    # 构建绝对无损的环境拦截器：防止其他电脑被 cwd 劫持加载原版文件
-    launcher_code = f"""
-import sys
-import os
-
-patch_dir = r"{PATCHES_DIR}"
-backend_dir = r"{BACKEND_DIR}"
-
-# 防御性清除：强行剥离所有的默认 backend_dir 引用
-sys.path = [p for p in sys.path if p and os.path.normpath(p) != os.path.normpath(backend_dir)]
-sys.path = [p for p in sys.path if p and p != "." and p != ""]
-
-# 绝对插队注入：优先搜索 PATCHES_DIR
-sys.path.insert(0, patch_dir)
-sys.path.insert(1, backend_dir)
-
-import uvicorn
-from ltx2_server import app
-
-if __name__ == '__main__':
-    uvicorn.run(app, host="0.0.0.0", port=3000, log_level="info", access_log=False)
-"""
-    launcher_path = os.path.join(PATCHES_DIR, "launcher.py")
-    with open(launcher_path, "w", encoding="utf-8") as f:
-        f.write(launcher_code)
-
-    cmd = [PYTHON_EXE, launcher_path]
-    env = os.environ.copy()
-    result = subprocess.run(cmd, cwd=BACKEND_DIR, env=env)
-    if result.returncode != 0:
-        print(f"\n\033[1;41m [致命错误] 核心引擎异常崩溃退出！ (Exit Code: {result.returncode})\033[0m")
-        print(">> 请检查上述终端报错信息。确认显卡驱动是否正常。")
-        os._exit(1)
-
-ui_app = FastAPI()
-# 已移除存在安全隐患的静态资源挂载目录
-
-@ui_app.get("/")
-async def serve_index():
-    return FileResponse(os.path.join(os.getcwd(), UI_FILE_NAME))
-
-@ui_app.get("/index.css")
-async def serve_css():
-    return FileResponse(os.path.join(os.getcwd(), "UI/index.css"))
-
-@ui_app.get("/index.js")
-async def serve_js():
-    return FileResponse(os.path.join(os.getcwd(), "UI/index.js"))
-
-def launch_ui_server():
-    print(f"\033[92m[UI] 工作站已就绪！\033[0m")
-    print(f"\033[92m[LOCAL] 本机访问: http://127.0.0.1:4000\033[0m")
-    print(f"\033[93m[WIFI]  局域网访问: http://{LAN_IP}:4000\033[0m")
-    
-    # 彻底压制 WinError 10054 (客户端强制断开) 的底层警告报错
-    if sys.platform == 'win32':
-        # Uvicorn 内部会拉起循环，所以只能通过底层 Logging Filter 拦截控制台噪音
-        class WinError10054Filter(logging.Filter):
-            def filter(self, record):
-                if record.name == 'asyncio' and hasattr(record, 'exc_info') and record.exc_info:
-                    exc_type, exc_value, _ = record.exc_info
-                    if isinstance(exc_value, ConnectionResetError) and getattr(exc_value, 'winerror', None) == 10054:
-                        return False
-                if "10054" in record.getMessage() and "ConnectionResetError" in record.getMessage():
-                    return False
-                return True
-        logging.getLogger("asyncio").addFilter(WinError10054Filter())
-        
-    uvicorn.run(ui_app, host="0.0.0.0", port=4000, log_level="warning", access_log=False)
-
-if __name__ == "__main__":
-    os.system('cls' if os.name == 'nt' else 'clear')
-    print("\033[1;97;44m LTX-2 CINEMATIC WORKSTATION | NETWORK ENABLED \033[0m\n")
-    
-    threading.Thread(target=launch_backend, daemon=True).start()
-    
-    # 强制校验 3000 端口是否存活
-    print("\033[93m[SYS] 正在等待内部核心 3000 端口启动...\033[0m")
-    backend_ready = False
-    for _ in range(30):
-        try:
-            with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
-                if s.connect_ex(('127.0.0.1', 3000)) == 0:
-                    backend_ready = True
-                    break
-        except Exception:
-            pass
-        time.sleep(1)
-        
-    if backend_ready:
-        print("\033[92m[SYS] 3000 端口已通过连通性握手验证！后端装载成功。\033[0m")
-    else:
-        print("\033[1;41m [崩坏警告] 等待 30 秒后，3000 端口依然无法连通！ \033[0m")
-        print(">> Uvicorn 可能在后台陷入了死锁，或者被防火墙拦截，前端大概率将无法连接到后端！")
-        print(">> 请检查上方是否有 Python 报错。\n")
-        
-    try:
-        launch_ui_server()
-    except KeyboardInterrupt:
-        sys.exit(0)

LTX2.3/patches/api_types.py

@@ -1,306 +0,0 @@
-"""Pydantic request/response models and TypedDicts for ltx2_server."""
-
-from __future__ import annotations
-
-from typing import Literal, NamedTuple, TypeAlias, TypedDict
-from typing import Annotated
-
-from pydantic import BaseModel, Field, StringConstraints
-
-NonEmptyPrompt = Annotated[str, StringConstraints(strip_whitespace=True, min_length=1)]
-ModelFileType = Literal[
-    "checkpoint",
-    "upsampler",
-    "distilled_lora",
-    "ic_lora",
-    "depth_processor",
-    "person_detector",
-    "pose_processor",
-    "text_encoder",
-    "zit",
-]
-
-
-class ImageConditioningInput(NamedTuple):
-    """Image conditioning triplet used by all video pipelines."""
-
-    path: str
-    frame_idx: int
-    strength: float
-
-
-# ============================================================
-# TypedDicts for module-level state globals
-# ============================================================
-
-
-class GenerationState(TypedDict):
-    id: str | None
-    cancelled: bool
-    result: str | list[str] | None
-    error: str | None
-    status: str  # "idle" | "running" | "complete" | "cancelled" | "error"
-    phase: str
-    progress: int
-    current_step: int
-    total_steps: int
-
-
-JsonObject: TypeAlias = dict[str, object]
-VideoCameraMotion = Literal[
-    "none",
-    "dolly_in",
-    "dolly_out",
-    "dolly_left",
-    "dolly_right",
-    "jib_up",
-    "jib_down",
-    "static",
-    "focus_shift",
-]
-
-
-# ============================================================
-# Response Models
-# ============================================================
-
-
-class ModelStatusItem(BaseModel):
-    id: str
-    name: str
-    loaded: bool
-    downloaded: bool
-
-
-class GpuTelemetry(BaseModel):
-    name: str
-    vram: int
-    vramUsed: int
-
-
-class HealthResponse(BaseModel):
-    status: str
-    models_loaded: bool
-    active_model: str | None
-    gpu_info: GpuTelemetry
-    sage_attention: bool
-    models_status: list[ModelStatusItem]
-
-
-class GpuInfoResponse(BaseModel):
-    cuda_available: bool
-    mps_available: bool = False
-    gpu_available: bool = False
-    gpu_name: str | None
-    vram_gb: int | None
-    gpu_info: GpuTelemetry
-
-
-class RuntimePolicyResponse(BaseModel):
-    force_api_generations: bool
-
-
-class GenerationProgressResponse(BaseModel):
-    status: str
-    phase: str
-    progress: int
-    currentStep: int | None
-    totalSteps: int | None
-
-
-class ModelInfo(BaseModel):
-    id: str
-    name: str
-    description: str
-
-
-class ModelFileStatus(BaseModel):
-    id: ModelFileType
-    name: str
-    description: str
-    downloaded: bool
-    size: int
-    expected_size: int
-    required: bool = True
-    is_folder: bool = False
-    optional_reason: str | None = None
-
-
-class TextEncoderStatus(BaseModel):
-    downloaded: bool
-    size_bytes: int
-    size_gb: float
-    expected_size_gb: float
-
-
-class ModelsStatusResponse(BaseModel):
-    models: list[ModelFileStatus]
-    all_downloaded: bool
-    total_size: int
-    downloaded_size: int
-    total_size_gb: float
-    downloaded_size_gb: float
-    models_path: str
-    has_api_key: bool
-    text_encoder_status: TextEncoderStatus
-    use_local_text_encoder: bool
-
-
-class DownloadProgressResponse(BaseModel):
-    status: str
-    current_downloading_file: ModelFileType | None
-    current_file_progress: int
-    total_progress: int
-    total_downloaded_bytes: int
-    expected_total_bytes: int
-    completed_files: set[ModelFileType]
-    all_files: set[ModelFileType]
-    error: str | None
-    speed_mbps: int
-
-
-class SuggestGapPromptResponse(BaseModel):
-    status: str = "success"
-    suggested_prompt: str
-
-
-class GenerateVideoResponse(BaseModel):
-    status: str
-    video_path: str | None = None
-
-
-class GenerateImageResponse(BaseModel):
-    status: str
-    image_paths: list[str] | None = None
-
-
-class CancelResponse(BaseModel):
-    status: str
-    id: str | None = None
-
-
-class RetakeResponse(BaseModel):
-    status: str
-    video_path: str | None = None
-    result: JsonObject | None = None
-
-
-class IcLoraExtractResponse(BaseModel):
-    conditioning: str
-    original: str
-    conditioning_type: Literal["canny", "depth"]
-    frame_time: float
-
-
-class IcLoraGenerateResponse(BaseModel):
-    status: str
-    video_path: str | None = None
-
-
-class ModelDownloadStartResponse(BaseModel):
-    status: str
-    message: str | None = None
-    sessionId: str | None = None
-
-
-class TextEncoderDownloadResponse(BaseModel):
-    status: str
-    message: str | None = None
-    sessionId: str | None = None
-
-
-class StatusResponse(BaseModel):
-    status: str
-
-
-class ErrorResponse(BaseModel):
-    error: str
-    message: str | None = None
-
-
-# ============================================================
-# Request Models
-# ============================================================
-
-
-class GenerateVideoRequest(BaseModel):
-    prompt: NonEmptyPrompt
-    resolution: str = "512p"
-    model: str = "fast"
-    cameraMotion: VideoCameraMotion = "none"
-    negativePrompt: str = ""
-    duration: str = "2"
-    fps: str = "24"
-    audio: str = "false"
-    imagePath: str | None = None
-    audioPath: str | None = None
-    startFramePath: str | None = None
-    endFramePath: str | None = None
-    aspectRatio: Literal["16:9", "9:16"] = "16:9"
-
-
-class GenerateImageRequest(BaseModel):
-    prompt: NonEmptyPrompt
-    width: int = 1024
-    height: int = 1024
-    numSteps: int = 4
-    numImages: int = 1
-
-
-def _default_model_types() -> set[ModelFileType]:
-    return set()
-
-
-class ModelDownloadRequest(BaseModel):
-    modelTypes: set[ModelFileType] = Field(default_factory=_default_model_types)
-
-
-class RequiredModelsResponse(BaseModel):
-    modelTypes: list[ModelFileType]
-
-
-class SuggestGapPromptRequest(BaseModel):
-    beforePrompt: str = ""
-    afterPrompt: str = ""
-    beforeFrame: str | None = None
-    afterFrame: str | None = None
-    gapDuration: float = 5
-    mode: str = "t2v"
-    inputImage: str | None = None
-
-
-class RetakeRequest(BaseModel):
-    video_path: str
-    start_time: float = 0
-    duration: float = 0
-    prompt: str = ""
-    mode: str = "replace_video_only"
-    width: int | None = None
-    height: int | None = None
-
-
-class IcLoraExtractRequest(BaseModel):
-    video_path: str
-    conditioning_type: Literal["canny", "depth"] = "canny"
-    frame_time: float = 0
-
-
-class IcLoraImageInput(BaseModel):
-    path: str
-    frame: int = 0
-    strength: float = 1.0
-
-
-def _default_ic_lora_images() -> list[IcLoraImageInput]:
-    return []
-
-
-class IcLoraGenerateRequest(BaseModel):
-    video_path: str
-    conditioning_type: Literal["canny", "depth"]
-    prompt: NonEmptyPrompt
-    conditioning_strength: float = 1.0
-    num_inference_steps: int = 30
-    cfg_guidance_scale: float = 1.0
-    negative_prompt: str = ""
-    images: list[IcLoraImageInput] = Field(default_factory=_default_ic_lora_images)

LTX2.3/patches/app_factory.py

@@ -1,1396 +0,0 @@
-"""FastAPI app factory decoupled from runtime bootstrap side effects."""
-
-from __future__ import annotations
-
-import base64
-import hmac
-import os
-
-# 防 OOM 与显存碎片化补丁：在 torch 初始化之前注入环境变量
-os.environ["PYTORCH_ALLOC_CONF"] = "expandable_segments:True"
-import torch  # 提升到顶层导入
-from collections.abc import Awaitable, Callable
-from typing import TYPE_CHECKING
-from pathlib import Path  # 必须导入，用于处理 Windows 路径
-
-from fastapi import FastAPI, Request, UploadFile, File
-from fastapi.exceptions import RequestValidationError
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse
-from pydantic import ConfigDict
-from fastapi.staticfiles import StaticFiles  # 必须导入，用于挂载静态目录
-from starlette.responses import Response as StarletteResponse
-import shutil
-import tempfile
-import time
-from api_types import ImageConditioningInput, GenerateVideoRequest
-
-from _routes._errors import HTTPError
-from _routes.generation import router as generation_router
-from _routes.health import router as health_router
-from _routes.ic_lora import router as ic_lora_router
-from _routes.image_gen import router as image_gen_router
-from _routes.models import router as models_router
-from _routes.suggest_gap_prompt import router as suggest_gap_prompt_router
-from _routes.retake import router as retake_router
-from _routes.runtime_policy import router as runtime_policy_router
-from _routes.settings import router as settings_router
-from logging_policy import log_http_error, log_unhandled_exception
-from state import init_state_service
-
-if TYPE_CHECKING:
-    from app_handler import AppHandler
-
-# 跨域配置：允许所有来源，解决本地网页调用限制
-DEFAULT_ALLOWED_ORIGINS: list[str] = ["*"]
-
-
-def _extend_generate_video_request_model() -> None:
-    """Keep custom video fields working across upstream request-model changes."""
-    annotations = dict(getattr(GenerateVideoRequest, "__annotations__", {}))
-    changed = False
-
-    for field_name in ("startFramePath", "endFramePath"):
-        if field_name not in annotations:
-            annotations[field_name] = str | None
-            setattr(GenerateVideoRequest, field_name, None)
-            changed = True
-
-    if changed:
-        GenerateVideoRequest.__annotations__ = annotations
-
-    existing_config = dict(getattr(GenerateVideoRequest, "model_config", {}) or {})
-    if existing_config.get("extra") != "allow":
-        existing_config["extra"] = "allow"
-        GenerateVideoRequest.model_config = ConfigDict(**existing_config)
-        changed = True
-
-    if changed:
-        GenerateVideoRequest.model_rebuild(force=True)
-
-
-def create_app(
-    *,
-    handler: "AppHandler",
-    allowed_origins: list[str] | None = None,
-    title: str = "LTX-2 Video Generation Server",
-    auth_token: str = "",
-    admin_token: str = "",
-) -> FastAPI:
-    """Create a configured FastAPI app bound to the provided handler."""
-    init_state_service(handler)
-    _extend_generate_video_request_model()
-
-    app = FastAPI(title=title)
-    app.state.admin_token = admin_token  # type: ignore[attr-defined]
-
-    # 彻底压制 WinError 10054 (客户端强制断开) 的底层警告报错
-    import sys, asyncio
-
-    if sys.platform == "win32":
-        try:
-            loop = asyncio.get_event_loop()
-
-            def silence_winerror_10054(loop, context):
-                exc = context.get("exception")
-                if (
-                    isinstance(exc, ConnectionResetError)
-                    and getattr(exc, "winerror", None) == 10054
-                ):
-                    return
-                loop.default_exception_handler(context)
-
-            loop.set_exception_handler(silence_winerror_10054)
-        except Exception:
-            pass
-
-    # --- 核心修复：对准 LTX 真正的输出目录 (AppData) ---
-    def get_dynamic_output_path():
-        base_dir = (
-            Path(os.environ.get("LOCALAPPDATA", os.path.expanduser("~/AppData/Local")))
-            / "LTXDesktop"
-        ).resolve()
-        config_file = base_dir / "custom_dir.txt"
-        if config_file.exists():
-            try:
-                custom_dir = config_file.read_text(encoding="utf-8").strip()
-                if custom_dir:
-                    p = Path(custom_dir)
-                    p.mkdir(parents=True, exist_ok=True)
-                    return p
-            except Exception:
-                pass
-        default_dir = base_dir / "outputs"
-        default_dir.mkdir(parents=True, exist_ok=True)
-        return default_dir
-
-    actual_output_path = get_dynamic_output_path()
-    handler.config.outputs_dir = actual_output_path
-
-    upload_tmp_path = actual_output_path / "uploads"
-
-    # 如果文件夹不存在则创建，防止挂载失败
-    if not actual_output_path.exists():
-        actual_output_path.mkdir(parents=True, exist_ok=True)
-    if not upload_tmp_path.exists():
-        upload_tmp_path.mkdir(parents=True, exist_ok=True)
-
-    # 挂载静态服务：将该目录映射到 http://127.0.0.1:3000/outputs
-    app.mount(
-        "/outputs", StaticFiles(directory=str(actual_output_path)), name="outputs"
-    )
-    # -----------------------------------------------
-
-    # 配置 CORS
-    app.add_middleware(
-        CORSMiddleware,
-        allow_origins=allowed_origins or DEFAULT_ALLOWED_ORIGINS,
-        allow_methods=["*"],
-        allow_headers=["*"],
-    )
-
-    # === [全局隔离补丁] ===
-    # 强制将每一个新的 HTTP 线程/协程请求的默认显卡都强绑定到用户选定的设备上
-    @app.middleware("http")
-    async def _sync_gpu_middleware(
-        request: Request,
-        call_next: Callable[[Request], Awaitable[StarletteResponse]],
-    ) -> StarletteResponse:
-        import torch
-
-        if (
-            torch.cuda.is_available()
-            and getattr(handler.config.device, "type", "") == "cuda"
-        ):
-            idx = handler.config.device.index
-            if idx is not None:
-                # 能够强行夺取那些底层写死了 cuda:0 而忽略 config.device 的第三方库
-                torch.cuda.set_device(idx)
-        return await call_next(request)
-
-    # 认证中间件
-    @app.middleware("http")
-    async def _auth_middleware(
-        request: Request,
-        call_next: Callable[[Request], Awaitable[StarletteResponse]],
-    ) -> StarletteResponse:
-        # 关键修复：如果是获取生成的图片，直接放行，不检查 Token
-        if (
-            request.url.path.startswith("/outputs")
-            or request.url.path == "/api/system/upload-image"
-        ):
-            return await call_next(request)
-
-        if not auth_token:
-            return await call_next(request)
-        if request.method == "OPTIONS":
-            return await call_next(request)
-
-        def _token_matches(candidate: str) -> bool:
-            return hmac.compare_digest(candidate, auth_token)
-
-        # WebSocket 认证
-        if request.headers.get("upgrade", "").lower() == "websocket":
-            if _token_matches(request.query_params.get("token", "")):
-                return await call_next(request)
-            return JSONResponse(status_code=401, content={"error": "Unauthorized"})
-
-        # HTTP 认证 (Bearer/Basic)
-        auth_header = request.headers.get("authorization", "")
-        if auth_header.startswith("Bearer ") and _token_matches(auth_header[7:]):
-            return await call_next(request)
-        if auth_header.startswith("Basic "):
-            try:
-                decoded = base64.b64decode(auth_header[6:]).decode()
-                _, _, password = decoded.partition(":")
-                if _token_matches(password):
-                    return await call_next(request)
-            except Exception:
-                pass
-        return JSONResponse(status_code=401, content={"error": "Unauthorized"})
-
-    # 异常处理逻辑
-    _FALLBACK = "An unexpected error occurred"
-
-    async def _route_http_error_handler(
-        request: Request, exc: Exception
-    ) -> JSONResponse:
-        if isinstance(exc, HTTPError):
-            log_http_error(request, exc)
-            return JSONResponse(
-                status_code=exc.status_code, content={"error": exc.detail or _FALLBACK}
-            )
-        return JSONResponse(status_code=500, content={"error": str(exc) or _FALLBACK})
-
-    async def _validation_error_handler(
-        request: Request, exc: Exception
-    ) -> JSONResponse:
-        if isinstance(exc, RequestValidationError):
-            return JSONResponse(
-                status_code=422, content={"error": str(exc) or _FALLBACK}
-            )
-        return JSONResponse(status_code=422, content={"error": str(exc) or _FALLBACK})
-
-    async def _route_generic_error_handler(
-        request: Request, exc: Exception
-    ) -> JSONResponse:
-        log_unhandled_exception(request, exc)
-        return JSONResponse(status_code=500, content={"error": str(exc) or _FALLBACK})
-
-    app.add_exception_handler(RequestValidationError, _validation_error_handler)
-    app.add_exception_handler(HTTPError, _route_http_error_handler)
-    app.add_exception_handler(Exception, _route_generic_error_handler)
-
-    # --- 系统功能接口 ---
-    @app.post("/api/system/clear-gpu")
-    async def route_clear_gpu():
-        try:
-            import torch
-            import gc
-            import asyncio
-
-            # 1. 尝试终止任务并重置运行状态
-            if getattr(handler.generation, "is_generation_running", lambda: False)():
-                try:
-                    handler.generation.cancel_generation()
-                except Exception:
-                    pass
-                await asyncio.sleep(0.5)
-
-            # 暴力重置死锁状态
-            if hasattr(handler.generation, "_generation_id"):
-                handler.generation._generation_id = None
-            if hasattr(handler.generation, "_is_generating"):
-                handler.generation._is_generating = False
-
-            # 2. 强制卸载模型: 临时屏蔽底层锁定器
-            try:
-                mock_swapped = False
-                orig_running = None
-                if hasattr(handler.pipelines, "_generation_service"):
-                    orig_running = (
-                        handler.pipelines._generation_service.is_generation_running
-                    )
-                    handler.pipelines._generation_service.is_generation_running = (
-                        lambda: False
-                    )
-                    mock_swapped = True
-                try:
-                    handler.pipelines.unload_gpu_pipeline()
-                finally:
-                    if mock_swapped:
-                        handler.pipelines._generation_service.is_generation_running = (
-                            orig_running
-                        )
-            except Exception as e:
-                print(f"Force unload warning: {e}")
-
-            # 3. 深度清理
-            gc.collect()
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
-                torch.cuda.ipc_collect()
-            return {
-                "status": "success",
-                "message": "GPU memory cleared and models unloaded",
-            }
-        except Exception as e:
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    @app.post("/api/system/reset-state")
-    async def route_reset_state():
-        """轻量级状态重置：只清除 generation 状态锁，不卸载 GPU 管线。
-        在每次新渲染开始前由前端调用，确保后端状态干净可用。"""
-        try:
-            gen = handler.generation
-            # 强制清除所有可能导致 is_generation_running() 返回 True 的标志
-            for attr in (
-                "_is_generating",
-                "_generation_id",
-                "_cancelled",
-                "_is_cancelled",
-            ):
-                if hasattr(gen, attr):
-                    if attr in ("_is_generating", "_cancelled", "_is_cancelled"):
-                        setattr(gen, attr, False)
-                    else:
-                        setattr(gen, attr, None)
-            # 某些实现用 threading.Event
-            for attr in ("_cancel_event",):
-                if hasattr(gen, attr):
-                    try:
-                        getattr(gen, attr).clear()
-                    except Exception:
-                        pass
-            print("[reset-state] Generation state has been reset cleanly.")
-            return {"status": "success", "message": "Generation state reset"}
-        except Exception as e:
-            import traceback
-
-            traceback.print_exc()
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    @app.post("/api/system/set-dir")
-    async def route_set_dir(request: Request):
-        try:
-            data = await request.json()
-            new_dir = data.get("directory", "").strip()
-            base_dir = (
-                Path(
-                    os.environ.get(
-                        "LOCALAPPDATA", os.path.expanduser("~/AppData/Local")
-                    )
-                )
-                / "LTXDesktop"
-            ).resolve()
-            config_file = base_dir / "custom_dir.txt"
-            if new_dir:
-                p = Path(new_dir)
-                p.mkdir(parents=True, exist_ok=True)
-                config_file.write_text(new_dir, encoding="utf-8")
-            else:
-                if config_file.exists():
-                    config_file.unlink()
-            # 立即更新全局 config 控制
-            handler.config.outputs_dir = get_dynamic_output_path()
-            return {"status": "success", "directory": str(get_dynamic_output_path())}
-        except Exception as e:
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    @app.get("/api/system/get-dir")
-    async def route_get_dir():
-        return {"status": "success", "directory": str(get_dynamic_output_path())}
-
-    @app.get("/api/system/browse-dir")
-    async def route_browse_dir():
-        try:
-            import subprocess
-
-            # 强制将对话框置顶层：通过 STA 线程 + Topmost 属性，避免被窗口锥入后台
-            ps_script = (
-                "[System.Reflection.Assembly]::LoadWithPartialName('System.Windows.Forms') | Out-Null;"
-                "[System.Reflection.Assembly]::LoadWithPartialName('System.Drawing') | Out-Null;"
-                "$f = New-Object System.Windows.Forms.FolderBrowserDialog;"
-                "$f.Description = '\u9009\u62e9 LTX \u89c6\u9891\u548c\u56fe\u50cf\u751f\u6210\u7684\u5168\u5c40\u8f93\u51fa\u76ee\u5f55';"
-                "$f.ShowNewFolderButton = $true;"
-                # 创建一个雐形助手窗口作为 parent 确保对话框在最顶层
-                "$owner = New-Object System.Windows.Forms.Form;"
-                "$owner.TopMost = $true;"
-                "$owner.StartPosition = 'CenterScreen';"
-                "$owner.Size = New-Object System.Drawing.Size(1, 1);"
-                "$owner.Show();"
-                "$owner.BringToFront();"
-                "$owner.Focus();"
-                "if ($f.ShowDialog($owner) -eq 'OK') { echo $f.SelectedPath };"
-                "$owner.Dispose();"
-            )
-
-            def run_ps():
-                process = subprocess.Popen(
-                    ["powershell", "-STA", "-NoProfile", "-Command", ps_script],
-                    stdout=subprocess.PIPE,
-                    stderr=subprocess.PIPE,
-                    text=True,
-                    # 移除 CREATE_NO_WINDOW 以允许 UI 线程正常弹出
-                )
-                stdout, _ = process.communicate()
-                return stdout.strip()
-
-            from starlette.concurrency import run_in_threadpool
-
-            selected_dir = await run_in_threadpool(run_ps)
-            return {"status": "success", "directory": selected_dir}
-        except Exception as e:
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    @app.get("/api/system/file")
-    async def route_serve_file(path: str):
-        from fastapi.responses import FileResponse
-
-        if os.path.exists(path):
-            return FileResponse(path)
-        return JSONResponse(status_code=404, content={"error": "File not found"})
-
-    @app.get("/api/system/list-gpus")
-    async def route_list_gpus():
-        try:
-            import torch
-
-            gpus = []
-            if torch.cuda.is_available():
-                current_idx = 0
-                dev = getattr(handler.config, "device", None)
-                if dev is not None and getattr(dev, "index", None) is not None:
-                    current_idx = dev.index
-                for i in range(torch.cuda.device_count()):
-                    try:
-                        name = torch.cuda.get_device_name(i)
-                    except Exception:
-                        name = f"GPU {i}"
-                    try:
-                        vram_bytes = torch.cuda.get_device_properties(i).total_memory
-                        vram_gb = vram_bytes / (1024**3)
-                        vram_mb = vram_bytes / (1024**2)
-                    except Exception:
-                        vram_gb = 0.0
-                        vram_mb = 0
-                    gpus.append(
-                        {
-                            "id": i,
-                            "name": name,
-                            "vram": f"{vram_gb:.1f} GB",
-                            "vram_mb": int(vram_mb),
-                            "active": (i == current_idx),
-                        }
-                    )
-            return {"status": "success", "gpus": gpus}
-        except Exception as e:
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    @app.post("/api/system/switch-gpu")
-    async def route_switch_gpu(request: Request):
-        try:
-            import torch
-            import gc
-            import asyncio
-
-            data = await request.json()
-            gpu_id = data.get("gpu_id")
-
-            if (
-                gpu_id is None
-                or not torch.cuda.is_available()
-                or gpu_id >= torch.cuda.device_count()
-            ):
-                return JSONResponse(
-                    status_code=400, content={"error": "Invalid GPU ID"}
-                )
-
-            # 先尝试终止任何可能的卡死任务
-            if getattr(handler.generation, "is_generation_running", lambda: False)():
-                try:
-                    handler.generation.cancel_generation()
-                except Exception:
-                    pass
-                await asyncio.sleep(0.5)
-            if hasattr(handler.generation, "_generation_id"):
-                handler.generation._generation_id = None
-            if hasattr(handler.generation, "_is_generating"):
-                handler.generation._is_generating = False
-
-            # 1. 卸载当前 GPU 上的模型: 临时屏蔽底层锁定器
-            try:
-                mock_swapped = False
-                orig_running = None
-                if hasattr(handler.pipelines, "_generation_service"):
-                    orig_running = (
-                        handler.pipelines._generation_service.is_generation_running
-                    )
-                    handler.pipelines._generation_service.is_generation_running = (
-                        lambda: False
-                    )
-                    mock_swapped = True
-                try:
-                    handler.pipelines.unload_gpu_pipeline()
-                finally:
-                    if mock_swapped:
-                        handler.pipelines._generation_service.is_generation_running = (
-                            orig_running
-                        )
-            except Exception:
-                pass
-            gc.collect()
-            torch.cuda.empty_cache()
-
-            # 2. 切换全局设备配置
-            new_device = torch.device(f"cuda:{gpu_id}")
-            handler.config.device = new_device
-
-            # 3. 核心修复：设置当前进程的默认 CUDA 设备
-            # 这会影响到 torch.cuda.current_device() 和后续的模型加载
-            torch.cuda.set_device(gpu_id)
-
-            # 针对底层库可能直接读取 CUDA_VISIBLE_DEVICES 的情况
-            # 注意：torch 初始化后修改此变量不一定生效，但对某些库可能有引导作用
-            os.environ["CUDA_VISIBLE_DEVICES"] = str(gpu_id)
-
-            # 4. 【核心修复】同步更新 TextEncoder 的设备指针
-            # 根本原因: LTXTextEncoder.self.device 在初始化时硬绑定了旧 GPU，
-            # 切换设备后 text context 仍在旧 GPU 上，与已迁移到新 GPU 的
-            # Transformer 产生 "cuda:0 and cuda:1" 设备不一致冲突。
-            try:
-                te_state = None
-                # 尝试多种路径访问 text_encoder 状态
-                if hasattr(handler, "state") and hasattr(handler.state, "text_encoder"):
-                    te_state = handler.state.text_encoder
-                elif hasattr(handler, "_state") and hasattr(
-                    handler._state, "text_encoder"
-                ):
-                    te_state = handler._state.text_encoder
-
-                if te_state is not None:
-                    # 4a. 更新 LTXTextEncoder 服务自身的 device 属性
-                    if hasattr(te_state, "service") and hasattr(
-                        te_state.service, "device"
-                    ):
-                        te_state.service.device = new_device
-                        print(f"[TextEncoder] device updated to {new_device}")
-
-                    # 4b. 将缓存的 encoder 权重迁移到 CPU，下次推理时再按新设备重加载
-                    if (
-                        hasattr(te_state, "cached_encoder")
-                        and te_state.cached_encoder is not None
-                    ):
-                        try:
-                            te_state.cached_encoder.to(torch.device("cpu"))
-                        except Exception:
-                            pass
-                        te_state.cached_encoder = None
-                        print(
-                            "[TextEncoder] cached encoder cleared (will reload on new GPU)"
-                        )
-
-                    # 4c. 清除 API embeddings 缓存（tensor 绑定旧 GPU）
-                    if hasattr(te_state, "api_embeddings"):
-                        te_state.api_embeddings = None
-
-                    # 4d. 清除 prompt cache（其中 tensor 也绑定旧 GPU）
-                    if hasattr(te_state, "prompt_cache") and te_state.prompt_cache:
-                        te_state.prompt_cache.clear()
-                        print("[TextEncoder] prompt cache cleared")
-            except Exception as _te_err:
-                print(f"[TextEncoder] device sync warning (non-fatal): {_te_err}")
-
-            print(
-                f"Switched active GPU to: {torch.cuda.get_device_name(gpu_id)} (ID: {gpu_id})"
-            )
-            return {"status": "success", "message": f"Switched to GPU {gpu_id}"}
-        except Exception as e:
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    # --- 核心增强：首尾帧插值与视频超分支持 ---
-    from handlers.video_generation_handler import VideoGenerationHandler
-    from services.retake_pipeline.ltx_retake_pipeline import LTXRetakePipeline
-    from server_utils.media_validation import normalize_optional_path
-    from PIL import Image
-
-    # 1. 增强插值功能 (Monkey Patch VideoGenerationHandler)
-    _orig_generate = VideoGenerationHandler.generate
-    _orig_generate_video = VideoGenerationHandler.generate_video
-
-    def patched_generate(self, req: GenerateVideoRequest):
-        # === [DEBUG] 打印当前生成状态 ===
-        gen = self._generation
-        is_running = (
-            gen.is_generation_running()
-            if hasattr(gen, "is_generation_running")
-            else "?方法不存在"
-        )
-        gen_id = getattr(gen, "_generation_id", "?属性不存在")
-        is_gen = getattr(gen, "_is_generating", "?属性不存在")
-        cancelled = getattr(
-            gen, "_cancelled", getattr(gen, "_is_cancelled", "?属性不存在")
-        )
-        print(f"\n[PATCH][patched_generate] ==> 收到新请求")
-        print(f"  is_generation_running() = {is_running}")
-        print(f"  _generation_id          = {gen_id}")
-        print(f"  _is_generating          = {is_gen}")
-        print(f"  _cancelled              = {cancelled}")
-        start_frame_path = normalize_optional_path(getattr(req, "startFramePath", None))
-        end_frame_path = normalize_optional_path(getattr(req, "endFramePath", None))
-        aspect_ratio = getattr(req, "aspectRatio", None)
-        print(f"  startFramePath          = {start_frame_path}")
-        print(f"  endFramePath            = {end_frame_path}")
-        print(f"  aspectRatio             = {aspect_ratio}")
-
-        # 检查是否有音频
-        audio_path = normalize_optional_path(getattr(req, "audioPath", None))
-        print(f"[PATCH] audio_path = {audio_path}")
-
-        # 检查是否有图片（图生视频）
-        image_path = normalize_optional_path(getattr(req, "imagePath", None))
-        print(f"[PATCH] image_path = {image_path}")
-
-        # 始终使用自定义逻辑（支持首尾帧和竖屏）
-        print(f"[PATCH] 使用自定义逻辑处理")
-
-        # 计算分辨率
-        import uuid
-
-        resolution = req.resolution
-        duration = int(float(req.duration))
-        fps = int(float(req.fps))
-
-        # 720p 分辨率：横屏 1280x720，竖屏 720x1280
-        RESOLUTION_MAP = {
-            "540p": (960, 540),
-            "720p": (1280, 720),
-            "1080p": (1920, 1080),
-        }
-
-        def get_16_9_size(res):
-            return RESOLUTION_MAP.get(res, (1280, 720))
-
-        def get_9_16_size(res):
-            w, h = get_16_9_size(res)
-            return h, w  # 交换宽高
-
-        if req.aspectRatio == "9:16":
-            width, height = get_9_16_size(resolution)
-        else:
-            width, height = get_16_9_size(resolution)
-
-        # 计算帧数
-        num_frames = ((duration * fps) // 8) * 8 + 1
-        num_frames = max(num_frames, 9)
-
-        print(f"[PATCH] 计算得到的分辨率: {width}x{height}, 帧数: {num_frames}")
-
-        # 设置首尾帧路径
-        self._start_frame_path = start_frame_path
-        self._end_frame_path = end_frame_path
-
-        # 无论有没有音频，都使用自定义逻辑支持首尾帧
-        try:
-            result = patched_generate_video(
-                self,
-                prompt=req.prompt,
-                image=None,
-                image_path=image_path,
-                height=height,
-                width=width,
-                num_frames=num_frames,
-                fps=fps,
-                seed=self._resolve_seed(),
-                camera_motion=req.cameraMotion,
-                negative_prompt=req.negativePrompt,
-                audio_path=audio_path,
-            )
-            print(f"[PATCH][patched_generate] <== 完成, 返回状态: complete")
-            return type("Response", (), {"status": "complete", "video_path": result})()
-        except Exception as e:
-            import traceback
-
-            print(f"[PATCH][patched_generate] 错误: {e}")
-            traceback.print_exc()
-            raise
-
-    def patched_generate_video(
-        self,
-        prompt,
-        image,
-        image_path=None,
-        height=None,
-        width=None,
-        num_frames=None,
-        fps=None,
-        seed=None,
-        camera_motion=None,
-        negative_prompt=None,
-        audio_path=None,
-    ):
-        # === [DEBUG] 打印当前生成状态 ===
-        gen = self._generation
-        is_running = (
-            gen.is_generation_running()
-            if hasattr(gen, "is_generation_running")
-            else "?方法不存在"
-        )
-        gen_id = getattr(gen, "_generation_id", "?属性不存在")
-        is_gen = getattr(gen, "_is_generating", "?属性不存在")
-        print(f"[PATCH][patched_generate_video] ==> 开始推理")
-        print(f"  is_generation_running() = {is_running}")
-        print(f"  _generation_id          = {gen_id}")
-        print(f"  _is_generating          = {is_gen}")
-        print(
-            f"  resolution              = {width}x{height}, frames={num_frames}, fps={fps}"
-        )
-        print(f"  image param             = {type(image)}, {image is not None}")
-        print(f"  image_path              = {image_path}")
-        # ==================================
-        from ltx_pipelines.utils.args import (
-            ImageConditioningInput as LtxImageConditioningInput,
-        )
-
-        images_inputs = []
-        temp_paths = []
-        start_path = getattr(self, "_start_frame_path", None)
-        end_path = getattr(self, "_end_frame_path", None)
-        print(f"[PATCH] start_path={start_path}, end_path={end_path}")
-
-        # 如果没有首尾帧但有 image_path，使用 image_path 作为起始帧
-        if not start_path and not end_path and image_path:
-            print(f"[PATCH] 使用 image_path 作为起始帧: {image_path}")
-            start_path = image_path
-
-        # 检查是否有来自 imagePath 的数据（当只用首帧时）
-        has_image_param = image is not None
-        if has_image_param:
-            print(f"[PATCH] image param is available, will be used as start frame")
-
-        latent_num_frames = (num_frames - 1) // 8 + 1
-        last_latent_idx = latent_num_frames - 1
-        print(
-            f"[PATCH] latent_num_frames={latent_num_frames}, last_latent_idx={last_latent_idx}"
-        )
-
-        target_start_path = start_path if start_path else None
-        if not target_start_path and image is not None:
-            tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
-            image.save(tmp)
-            temp_paths.append(tmp)
-            target_start_path = tmp
-            print(f"[PATCH] Using image param as start frame: {target_start_path}")
-
-        if target_start_path:
-            start_img = self._prepare_image(target_start_path, width, height)
-            tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
-            start_img.save(tmp)
-            temp_paths.append(tmp)
-            # 转换 Windows 路径为正斜杠
-            tmp_normalized = tmp.replace("\\", "/")
-            images_inputs.append(
-                LtxImageConditioningInput(
-                    path=tmp_normalized, frame_idx=0, strength=1.0
-                )
-            )
-            print(f"[PATCH] Added start frame: {tmp_normalized}, frame_idx=0")
-
-        if end_path:
-            end_img = self._prepare_image(end_path, width, height)
-            tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
-            end_img.save(tmp)
-            temp_paths.append(tmp)
-            # 转换 Windows 路径为正斜杠
-            tmp_normalized = tmp.replace("\\", "/")
-            images_inputs.append(
-                LtxImageConditioningInput(
-                    path=tmp_normalized, frame_idx=last_latent_idx, strength=1.0
-                )
-            )
-            print(
-                f"[PATCH] Added end frame: {tmp_normalized}, frame_idx={last_latent_idx}"
-            )
-
-        print(f"[PATCH] images_inputs count: {len(images_inputs)}")
-        if images_inputs:
-            for idx, img in enumerate(images_inputs):
-                print(
-                    f"[PATCH] images_inputs[{idx}]: path={getattr(img, 'path', 'N/A')}, frame_idx={getattr(img, 'frame_idx', 'N/A')}, strength={getattr(img, 'strength', 'N/A')}"
-                )
-
-        print(f"[PATCH] audio_path = {audio_path}")
-
-        if self._generation.is_generation_cancelled():
-            raise RuntimeError("Generation was cancelled")
-
-        # 导入 uuid
-        import uuid
-
-        generation_id = uuid.uuid4().hex[:8]
-
-        # 根据是否有音频选择不同的 pipeline
-        if audio_path:
-            print(f"[PATCH] 加载 A2V pipeline（支持音频）")
-            pipeline_state = self._pipelines.load_a2v_pipeline()
-            num_inference_steps = 11  # A2V 需要这个参数
-        else:
-            print(f"[PATCH] 加载 Fast pipeline")
-            pipeline_state = self._pipelines.load_gpu_pipeline(
-                "fast", should_warm=False
-            )
-            num_inference_steps = None
-
-        # 启动 generation 状态（在 pipeline 加载之后）
-        self._generation.start_generation(generation_id)
-
-        # 处理 negative_prompt
-        neg_prompt = (
-            negative_prompt if negative_prompt else self.config.default_negative_prompt
-        )
-        enhanced_prompt = prompt + self.config.camera_motion_prompts.get(
-            camera_motion, ""
-        )
-
-        # 强制使用动态目录，忽略底层原始逻辑
-        dyn_dir = get_dynamic_output_path()
-        output_path = dyn_dir / f"generation_{uuid.uuid4().hex[:8]}.mp4"
-
-        try:
-            self._text.prepare_text_encoding(enhanced_prompt, enhance_prompt=False)
-            # 调整为 32 的倍数（LTX 要求）
-            height = round(height / 32) * 32
-            width = round(width / 32) * 32
-
-            if audio_path:
-                # A2V pipeline 参数
-                gen_kwargs = {
-                    "prompt": enhanced_prompt,
-                    "negative_prompt": neg_prompt,
-                    "seed": seed,
-                    "height": height,
-                    "width": width,
-                    "num_frames": num_frames,
-                    "frame_rate": fps,
-                    "num_inference_steps": num_inference_steps,
-                    "images": images_inputs,
-                    "audio_path": audio_path,
-                    "audio_start_time": 0.0,
-                    "audio_max_duration": None,
-                    "output_path": str(output_path),
-                }
-            else:
-                # Fast pipeline 参数
-                gen_kwargs = {
-                    "prompt": enhanced_prompt,
-                    "seed": seed,
-                    "height": height,
-                    "width": width,
-                    "num_frames": num_frames,
-                    "frame_rate": fps,
-                    "images": images_inputs,
-                    "output_path": str(output_path),
-                }
-
-            pipeline_state.pipeline.generate(**gen_kwargs)
-
-            # 标记完成
-            self._generation.complete_generation(str(output_path))
-            return str(output_path)
-        finally:
-            self._text.clear_api_embeddings()
-            for p in temp_paths:
-                if os.path.exists(p):
-                    os.unlink(p)
-            self._start_frame_path = None
-            self._end_frame_path = None
-
-    VideoGenerationHandler.generate = patched_generate
-    VideoGenerationHandler.generate_video = patched_generate_video
-
-    # 2. 增强视频超分功能 (Monkey Patch LTXRetakePipeline)
-    _orig_ltx_retake_run = LTXRetakePipeline._run
-
-    def patched_ltx_retake_run(
-        self, video_path, prompt, start_time, end_time, seed, **kwargs
-    ):
-        # 拦截并修改目标宽高
-        target_w = getattr(self, "_target_width", None)
-        target_h = getattr(self, "_target_height", None)
-        target_strength = getattr(self, "_target_strength", 0.7)
-        is_upscale = target_w is not None and target_h is not None
-
-        import ltx_pipelines.utils.media_io as media_io
-        import services.retake_pipeline.ltx_retake_pipeline as lrp
-        import ltx_pipelines.utils.samplers as samplers
-        import ltx_pipelines.utils.helpers as helpers
-
-        _orig_get_meta = media_io.get_videostream_metadata
-        _orig_lrp_get_meta = getattr(lrp, "get_videostream_metadata", _orig_get_meta)
-        _orig_euler_loop = samplers.euler_denoising_loop
-        _orig_noise_video = helpers.noise_video_state
-
-        fps, num_frames, src_w, src_h = _orig_get_meta(video_path)
-
-        if is_upscale:
-            print(
-                f">>> 启动超分内核: {src_w}x{src_h} -> {target_w}x{target_h} (强度: {target_strength})"
-            )
-
-            # 1. 注入分辨率
-            def get_meta_patched(path):
-                return fps, num_frames, target_w, target_h
-
-            media_io.get_videostream_metadata = get_meta_patched
-            lrp.get_videostream_metadata = get_meta_patched
-
-            # 2. 注入起始噪声 (SDEdit 核心：加噪到指定强度)
-            def noise_video_patched(*args, **kwargs_inner):
-                kwargs_inner["noise_scale"] = target_strength
-                return _orig_noise_video(*args, **kwargs_inner)
-
-            helpers.noise_video_state = noise_video_patched
-
-            # 3. 注入采样起点 (从对应噪声位开始去噪)
-            def patched_euler_loop(
-                sigmas, video_state, audio_state, stepper, denoise_fn
-            ):
-                full_len = len(sigmas)
-                skip_idx = 0
-                for i, s in enumerate(sigmas):
-                    if s <= target_strength:
-                        skip_idx = i
-                        break
-                skip_idx = min(skip_idx, full_len - 2)
-                new_sigmas = sigmas[skip_idx:]
-                print(
-                    f">>> 采样拦截成功: 原步数 {full_len}, 现步数 {len(new_sigmas)}, 起始强度 {new_sigmas[0].item():.2f}"
-                )
-                return _orig_euler_loop(
-                    new_sigmas, video_state, audio_state, stepper, denoise_fn
-                )
-
-            samplers.euler_denoising_loop = patched_euler_loop
-
-            kwargs["regenerate_video"] = False
-            kwargs["regenerate_audio"] = False
-
-            try:
-                return _orig_ltx_retake_run(
-                    self, video_path, prompt, start_time, end_time, seed, **kwargs
-                )
-            finally:
-                media_io.get_videostream_metadata = _orig_get_meta
-                lrp.get_videostream_metadata = _orig_lrp_get_meta
-                samplers.euler_denoising_loop = _orig_euler_loop
-                helpers.noise_video_state = _orig_noise_video
-
-        return _orig_ltx_retake_run(
-            self, video_path, prompt, start_time, end_time, seed, **kwargs
-        )
-
-        return _orig_ltx_retake_run(
-            self, video_path, prompt, start_time, end_time, seed, **kwargs
-        )
-
-    LTXRetakePipeline._run = patched_ltx_retake_run
-
-    # --- 最终视频超分接口实现 ---
-    @app.post("/api/system/upscale-video")
-    async def route_upscale_video(request: Request):
-        try:
-            import uuid
-            import os
-            from datetime import datetime
-            from ltx_pipelines.utils.media_io import get_videostream_metadata
-            from ltx_core.types import SpatioTemporalScaleFactors
-
-            data = await request.json()
-            video_path = data.get("video_path")
-            target_res = data.get("resolution", "1080p")
-            prompt = data.get("prompt", "high quality, detailed, 4k")
-            strength = data.get("strength", 0.7)  # 获取前端传来的重绘幅度
-
-            if not video_path or not os.path.exists(video_path):
-                return JSONResponse(
-                    status_code=400, content={"error": "Invalid video path"}
-                )
-
-            # 计算目标宽高 (必须是 32 的倍数)
-            res_map = {"1080p": (1920, 1088), "720p": (1280, 704), "544p": (960, 544)}
-            target_w, target_h = res_map.get(target_res, (1920, 1088))
-
-            fps, num_frames, _, _ = get_videostream_metadata(video_path)
-
-            # 校验帧数 8k+1，如果不符则自动调整
-            scale = SpatioTemporalScaleFactors.default()
-            if (num_frames - 1) % scale.time != 0:
-                # 计算需要调整到的最近的有效帧数 (8k+1)
-                # 找到最接近的8k+1帧数
-                target_k = (num_frames - 1) // scale.time
-                # 选择最接近的k值：向下或向上取整
-                current_k = (num_frames - 1) // scale.time
-                current_remainder = (num_frames - 1) % scale.time
-
-                # 比较向上和向下取整哪个更接近
-                down_k = current_k
-                up_k = current_k + 1
-
-                # 向下取整的帧数
-                down_frames = down_k * scale.time + 1
-                # 向上取整的帧数
-                up_frames = up_k * scale.time + 1
-
-                # 选择差异最小的
-                if abs(num_frames - down_frames) <= abs(num_frames - up_frames):
-                    adjusted_frames = down_frames
-                else:
-                    adjusted_frames = up_frames
-
-                print(
-                    f">>> 帧数调整: {num_frames} -> {adjusted_frames} (符合 8k+1 规则)"
-                )
-
-                # 调整视频帧数 - 截断多余的帧或填充黑帧
-                adjusted_video_path = None
-                try:
-                    import cv2
-                    import numpy as np
-                    import tempfile
-
-                    # 使用cv2读取视频
-                    cap = cv2.VideoCapture(video_path)
-                    if not cap.isOpened():
-                        raise Exception("无法打开视频文件")
-
-                    frames = []
-                    while True:
-                        ret, frame = cap.read()
-                        if not ret:
-                            break
-                        frames.append(frame)
-                    cap.release()
-
-                    original_frame_count = len(frames)
-
-                    if adjusted_frames < original_frame_count:
-                        # 截断多余的帧
-                        frames = frames[:adjusted_frames]
-                        print(
-                            f">>> 已截断视频: {original_frame_count} -> {len(frames)} 帧"
-                        )
-                    else:
-                        # 填充黑帧 (复制最后一帧)
-                        last_frame = frames[-1] if frames else None
-                        if last_frame is not None:
-                            h, w = last_frame.shape[:2]
-                            black_frame = np.zeros((h, w, 3), dtype=np.uint8)
-                            while len(frames) < adjusted_frames:
-                                frames.append(black_frame.copy())
-                        print(
-                            f">>> 已填充视频: {original_frame_count} -> {len(frames)} 帧"
-                        )
-
-                    # 保存调整后的视频到临时文件
-                    adjusted_video_fd = tempfile.NamedTemporaryFile(
-                        suffix=".mp4", delete=False
-                    )
-                    adjusted_video_path = adjusted_video_fd.name
-                    adjusted_video_fd.close()
-
-                    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
-                    out = cv2.VideoWriter(
-                        adjusted_video_path,
-                        fourcc,
-                        fps,
-                        (frames[0].shape[1], frames[0].shape[0]),
-                    )
-                    for frame in frames:
-                        out.write(frame)
-                    out.release()
-
-                    video_path = adjusted_video_path
-                    num_frames = adjusted_frames
-                    print(
-                        f">>> 视频帧数调整完成: {original_frame_count} -> {num_frames}"
-                    )
-
-                except ImportError:
-                    # cv2不可用，尝试使用LTX内置方法
-                    try:
-                        from ltx_pipelines.utils.media_io import (
-                            read_video_stream,
-                            write_video_stream,
-                        )
-                        import numpy as np
-
-                        frames, audio_data = read_video_stream(video_path, fps)
-                        original_frame_count = len(frames)
-
-                        if adjusted_frames < original_frame_count:
-                            frames = frames[:adjusted_frames]
-                        else:
-                            while len(frames) < adjusted_frames:
-                                frames = np.concatenate([frames, frames[-1:]], axis=0)
-
-                        import tempfile
-
-                        adjusted_video_fd = tempfile.NamedTemporaryFile(
-                            suffix=".mp4", delete=False
-                        )
-                        adjusted_video_path = adjusted_video_fd.name
-                        adjusted_video_fd.close()
-
-                        write_video_stream(adjusted_video_path, frames, fps)
-                        video_path = adjusted_video_path
-                        num_frames = adjusted_frames
-                        print(
-                            f">>> 视频帧数调整完成: {original_frame_count} -> {num_frames}"
-                        )
-
-                    except Exception as e2:
-                        print(f">>> 视频帧数自动调整失败: {e2}")
-                        return JSONResponse(
-                            status_code=400,
-                            content={
-                                "error": f"视频帧数({num_frames})不符合 8k+1 规则，且自动调整失败。请手动将视频帧数调整为 8k+1 格式（如 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97, 105 等）。"
-                            },
-                        )
-                except Exception as e:
-                    print(f">>> 视频帧数自动调整失败: {e}")
-                    return JSONResponse(
-                        status_code=400,
-                        content={
-                            "error": f"视频帧数({num_frames})不符合 8k+1 规则，且自动调整失败。请手动将视频帧数调整为 8k+1 格式（如 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97, 105 等）。"
-                        },
-                    )
-
-            # 1. 加载模型
-            pipeline_state = handler.pipelines.load_retake_pipeline(distilled=True)
-
-            # 3. 启动任务
-            generation_id = uuid.uuid4().hex[:8]
-            handler.generation.start_generation(generation_id)
-
-            # 核心修正：确保文件保存在动态的输出目录
-            save_dir = get_dynamic_output_path()
-            filename = f"upscale_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{generation_id}.mp4"
-            full_output_path = save_dir / filename
-
-            # 3. 执行真正的超分逻辑
-            try:
-                # 注入目标分辨率和重绘幅度
-                pipeline_state.pipeline._target_width = target_w
-                pipeline_state.pipeline._target_height = target_h
-                pipeline_state.pipeline._target_strength = strength
-
-                def do_generate():
-                    pipeline_state.pipeline.generate(
-                        video_path=str(video_path),
-                        prompt=prompt,
-                        start_time=0.0,
-                        end_time=float(num_frames / fps),
-                        seed=int(time.time()) % 2147483647,
-                        output_path=str(full_output_path),
-                        distilled=True,
-                        regenerate_video=True,
-                        regenerate_audio=False,
-                    )
-
-                # 重要修复：放到线程池运行，避免阻塞主循环导致前端拿不到显存数据
-                from starlette.concurrency import run_in_threadpool
-
-                await run_in_threadpool(do_generate)
-
-                handler.generation.complete_generation(str(full_output_path))
-                return {"status": "complete", "video_path": filename}
-            except Exception as e:
-                # OOM 异常逃逸修复：强制返回友好的异常信息
-                try:
-                    handler.generation.cancel_generation()
-                except Exception:
-                    pass
-                if hasattr(handler.generation, "_generation_id"):
-                    handler.generation._generation_id = None
-                if hasattr(handler.generation, "_is_generating"):
-                    handler.generation._is_generating = False
-
-                error_msg = str(e)
-                if "CUDA out of memory" in error_msg:
-                    error_msg = "🚨 显存不足 (OOM)：视频时长过长或目标分辨率超出了当前显卡的承载极限，请降低目标分辨率重试！"
-                raise RuntimeError(error_msg) from e
-            finally:
-                if hasattr(pipeline_state.pipeline, "_target_width"):
-                    del pipeline_state.pipeline._target_width
-                if hasattr(pipeline_state.pipeline, "_target_height"):
-                    del pipeline_state.pipeline._target_height
-                if hasattr(pipeline_state.pipeline, "_target_strength"):
-                    del pipeline_state.pipeline._target_strength
-                import gc
-
-                gc.collect()
-                if (
-                    getattr(torch, "cuda", None) is not None
-                    and torch.cuda.is_available()
-                ):
-                    torch.cuda.empty_cache()
-
-        except Exception as e:
-            import traceback
-
-            traceback.print_exc()
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    # ------------------
-
-    @app.post("/api/system/upload-image")
-    async def route_upload_image(request: Request):
-        try:
-            import uuid
-            import base64
-
-            # 接收 JSON 而不是 Multipart，绕过 python-multipart 缺失问题
-            data = await request.json()
-            b64_data = data.get("image")
-            filename = data.get("filename", "image.png")
-
-            if not b64_data:
-                return JSONResponse(
-                    status_code=400, content={"error": "No image data provided"}
-                )
-
-            # 处理 base64 头部 (例如 data:image/png;base64,...)
-            if "," in b64_data:
-                b64_data = b64_data.split(",")[1]
-
-            image_bytes = base64.b64decode(b64_data)
-
-            # 确保上传目录存在
-            upload_dir = get_dynamic_output_path() / "uploads"
-            upload_dir.mkdir(parents=True, exist_ok=True)
-
-            safe_filename = "".join([c for c in filename if c.isalnum() or c in "._-"])
-            file_path = upload_dir / f"up_{uuid.uuid4().hex[:6]}_{safe_filename}"
-
-            with file_path.open("wb") as buffer:
-                buffer.write(image_bytes)
-
-            return {"status": "success", "path": str(file_path)}
-        except Exception as e:
-            import traceback
-
-            error_msg = f"{type(e).__name__}: {str(e)}\n{traceback.format_exc()}"
-            print(f"Upload error: {error_msg}")
-            return JSONResponse(
-                status_code=500, content={"error": str(e), "detail": error_msg}
-            )
-
-    # ------------------
-
-    @app.get("/api/system/history")
-    async def route_get_history(request: Request):
-        try:
-            import os
-
-            page = int(request.query_params.get("page", 1))
-            limit = int(request.query_params.get("limit", 20))
-
-            history = []
-            dyn_path = get_dynamic_output_path()
-            if dyn_path.exists():
-                for filename in os.listdir(dyn_path):
-                    if filename == "uploads":
-                        continue
-                    full_path = dyn_path / filename
-                    if full_path.is_file() and filename.lower().endswith(
-                        (".mp4", ".png", ".jpg", ".webp")
-                    ):
-                        mtime = os.path.getmtime(full_path)
-                        history.append(
-                            {
-                                "filename": filename,
-                                "type": "video"
-                                if filename.lower().endswith(".mp4")
-                                else "image",
-                                "mtime": mtime,
-                                "fullpath": str(full_path),
-                            }
-                        )
-            history.sort(key=lambda x: x["mtime"], reverse=True)
-
-            total_items = len(history)
-            total_pages = (total_items + limit - 1) // limit
-            start_idx = (page - 1) * limit
-            end_idx = start_idx + limit
-
-            return {
-                "status": "success",
-                "history": history[start_idx:end_idx],
-                "total_pages": total_pages,
-                "current_page": page,
-                "total_items": total_items,
-            }
-        except Exception as e:
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    @app.post("/api/system/delete-file")
-    async def route_delete_file(request: Request):
-        try:
-            import os
-
-            data = await request.json()
-            filename = data.get("filename", "")
-
-            if not filename:
-                return JSONResponse(
-                    status_code=400, content={"error": "Filename is required"}
-                )
-
-            dyn_path = get_dynamic_output_path()
-            file_path = dyn_path / filename
-
-            if file_path.exists() and file_path.is_file():
-                file_path.unlink()
-                return {"status": "success", "message": "File deleted"}
-            else:
-                return JSONResponse(
-                    status_code=404, content={"error": "File not found"}
-                )
-        except Exception as e:
-            return JSONResponse(status_code=500, content={"error": str(e)})
-
-    # 路由注册
-    app.include_router(health_router)
-    app.include_router(generation_router)
-    app.include_router(models_router)
-    app.include_router(settings_router)
-    app.include_router(image_gen_router)
-    app.include_router(suggest_gap_prompt_router)
-    app.include_router(retake_router)
-    app.include_router(ic_lora_router)
-    app.include_router(runtime_policy_router)
-
-    # --- [安全补丁] 状态栏显示修复 ---
-
-    # --- 最终状态栏修复补丁: 只要服务运行且 GPU 没死，就视为就绪 ---
-    from handlers.health_handler import HealthHandler
-
-    if not hasattr(HealthHandler, "_fixed_v2"):
-        _orig_get_health = HealthHandler.get_health
-
-        def patched_health_v2(self):
-            resp = _orig_get_health(self)
-            # 解析：如果后端逻辑还在判断模型未加载，我们检查一下核心状态
-            # 如果系统没有崩溃，我们就强制标记为已加载，让前端允许交互
-            if not resp.models_loaded:
-                # 我们认为只要 API 能通，底层状态服务(state)只要存在，就视为由于异步加载引起的暂时性 False
-                # 直接返回 True，前端会显示"待机就绪"
-                resp.models_loaded = True
-            return resp
-
-        HealthHandler.get_health = patched_health_v2
-        HealthHandler._fixed_v2 = True
-    # ------------------------------------------------------------
-
-    # --- 修复显存采集指针：使得显存监控永远对准当前选定工作的 GPU ---
-    from services.gpu_info.gpu_info_impl import GpuInfoImpl
-
-    if not hasattr(GpuInfoImpl, "_fixed_vram_patch"):
-        _orig_get_gpu_info = GpuInfoImpl.get_gpu_info
-
-        def patched_get_gpu_info(self):
-            import torch
-
-            if self.get_cuda_available():
-                idx = 0
-                if (
-                    hasattr(handler.config.device, "index")
-                    and handler.config.device.index is not None
-                ):
-                    idx = handler.config.device.index
-                try:
-                    import pynvml
-
-                    pynvml.nvmlInit()
-                    handle = pynvml.nvmlDeviceGetHandleByIndex(idx)
-                    raw_name = pynvml.nvmlDeviceGetName(handle)
-                    name = (
-                        raw_name.decode("utf-8", errors="replace")
-                        if isinstance(raw_name, bytes)
-                        else str(raw_name)
-                    )
-                    memory = pynvml.nvmlDeviceGetMemoryInfo(handle)
-                    pynvml.nvmlShutdown()
-                    return {
-                        "name": f"{name} [ID: {idx}]",
-                        "vram": memory.total // (1024 * 1024),
-                        "vramUsed": memory.used // (1024 * 1024),
-                    }
-                except Exception:
-                    pass
-            return _orig_get_gpu_info(self)
-
-        GpuInfoImpl.get_gpu_info = patched_get_gpu_info
-        GpuInfoImpl._fixed_vram_patch = True
-
-    return app

LTX2.3/patches/handlers/video_generation_handler.py

@@ -1,673 +0,0 @@
-"""Video generation orchestration handler."""
-
-from __future__ import annotations
-
-import logging
-import os
-import tempfile
-import time
-import uuid
-from datetime import datetime
-from pathlib import Path
-from threading import RLock
-from typing import TYPE_CHECKING
-
-from PIL import Image
-
-from api_types import (
-    GenerateVideoRequest,
-    GenerateVideoResponse,
-    ImageConditioningInput,
-    VideoCameraMotion,
-)
-from _routes._errors import HTTPError
-from handlers.base import StateHandlerBase
-from handlers.generation_handler import GenerationHandler
-from handlers.pipelines_handler import PipelinesHandler
-from handlers.text_handler import TextHandler
-from runtime_config.model_download_specs import resolve_model_path
-from server_utils.media_validation import (
-    normalize_optional_path,
-    validate_audio_file,
-    validate_image_file,
-)
-from services.interfaces import LTXAPIClient
-from state.app_state_types import AppState
-from state.app_settings import should_video_generate_with_ltx_api
-
-if TYPE_CHECKING:
-    from runtime_config.runtime_config import RuntimeConfig
-
-logger = logging.getLogger(__name__)
-
-FORCED_API_MODEL_MAP: dict[str, str] = {
-    "fast": "ltx-2-3-fast",
-    "pro": "ltx-2-3-pro",
-}
-FORCED_API_RESOLUTION_MAP: dict[str, dict[str, str]] = {
-    "1080p": {"16:9": "1920x1080", "9:16": "1080x1920"},
-    "1440p": {"16:9": "2560x1440", "9:16": "1440x2560"},
-    "2160p": {"16:9": "3840x2160", "9:16": "2160x3840"},
-}
-A2V_FORCED_API_RESOLUTION = "1920x1080"
-FORCED_API_ALLOWED_ASPECT_RATIOS = {"16:9", "9:16"}
-FORCED_API_ALLOWED_FPS = {24, 25, 48, 50}
-
-
-def _get_allowed_durations(model_id: str, resolution_label: str, fps: int) -> set[int]:
-    if model_id == "ltx-2-3-fast" and resolution_label == "1080p" and fps in {24, 25}:
-        return {6, 8, 10, 12, 14, 16, 18, 20}
-    return {6, 8, 10}
-
-
-class VideoGenerationHandler(StateHandlerBase):
-    def __init__(
-        self,
-        state: AppState,
-        lock: RLock,
-        generation_handler: GenerationHandler,
-        pipelines_handler: PipelinesHandler,
-        text_handler: TextHandler,
-        ltx_api_client: LTXAPIClient,
-        config: RuntimeConfig,
-    ) -> None:
-        super().__init__(state, lock, config)
-        self._generation = generation_handler
-        self._pipelines = pipelines_handler
-        self._text = text_handler
-        self._ltx_api_client = ltx_api_client
-
-    def generate(self, req: GenerateVideoRequest) -> GenerateVideoResponse:
-        if should_video_generate_with_ltx_api(
-            force_api_generations=self.config.force_api_generations,
-            settings=self.state.app_settings,
-        ):
-            return self._generate_forced_api(req)
-
-        if self._generation.is_generation_running():
-            raise HTTPError(409, "Generation already in progress")
-
-        resolution = req.resolution
-
-        duration = int(float(req.duration))
-        fps = int(float(req.fps))
-
-        audio_path = normalize_optional_path(req.audioPath)
-        if audio_path:
-            return self._generate_a2v(req, duration, fps, audio_path=audio_path)
-
-        logger.info("Resolution %s - using fast pipeline", resolution)
-
-        RESOLUTION_MAP_16_9: dict[str, tuple[int, int]] = {
-            "540p": (960, 540),
-            "720p": (1280, 720),
-            "1080p": (1920, 1080),
-        }
-
-        def get_16_9_size(res: str) -> tuple[int, int]:
-            return RESOLUTION_MAP_16_9.get(res, (1280, 720))
-
-        def get_9_16_size(res: str) -> tuple[int, int]:
-            w, h = get_16_9_size(res)
-            return h, w
-
-        match req.aspectRatio:
-            case "9:16":
-                width, height = get_9_16_size(resolution)
-            case "16:9":
-                width, height = get_16_9_size(resolution)
-
-        num_frames = self._compute_num_frames(duration, fps)
-
-        image = None
-        image_path = normalize_optional_path(req.imagePath)
-        if image_path:
-            image = self._prepare_image(image_path, width, height)
-            logger.info("Image: %s -> %sx%s", image_path, width, height)
-
-        generation_id = self._make_generation_id()
-        seed = self._resolve_seed()
-
-        try:
-            self._pipelines.load_gpu_pipeline("fast", should_warm=False)
-            self._generation.start_generation(generation_id)
-
-            output_path = self.generate_video(
-                prompt=req.prompt,
-                image=image,
-                height=height,
-                width=width,
-                num_frames=num_frames,
-                fps=fps,
-                seed=seed,
-                camera_motion=req.cameraMotion,
-                negative_prompt=req.negativePrompt,
-            )
-
-            self._generation.complete_generation(output_path)
-            return GenerateVideoResponse(status="complete", video_path=output_path)
-
-        except Exception as e:
-            self._generation.fail_generation(str(e))
-            if "cancelled" in str(e).lower():
-                logger.info("Generation cancelled by user")
-                return GenerateVideoResponse(status="cancelled")
-
-            raise HTTPError(500, str(e)) from e
-
-    def generate_video(
-        self,
-        prompt: str,
-        image: Image.Image | None,
-        height: int,
-        width: int,
-        num_frames: int,
-        fps: float,
-        seed: int,
-        camera_motion: VideoCameraMotion,
-        negative_prompt: str,
-    ) -> str:
-        t_total_start = time.perf_counter()
-        gen_mode = "i2v" if image is not None else "t2v"
-        logger.info(
-            "[%s] Generation started (model=fast, %dx%d, %d frames, %d fps)",
-            gen_mode,
-            width,
-            height,
-            num_frames,
-            int(fps),
-        )
-
-        if self._generation.is_generation_cancelled():
-            raise RuntimeError("Generation was cancelled")
-
-        if not resolve_model_path(
-            self.models_dir, self.config.model_download_specs, "checkpoint"
-        ).exists():
-            raise RuntimeError(
-                "Models not downloaded. Please download the AI models first using the Model Status menu."
-            )
-
-        total_steps = 8
-
-        self._generation.update_progress("loading_model", 5, 0, total_steps)
-        t_load_start = time.perf_counter()
-        pipeline_state = self._pipelines.load_gpu_pipeline("fast", should_warm=False)
-        t_load_end = time.perf_counter()
-        logger.info("[%s] Pipeline load: %.2fs", gen_mode, t_load_end - t_load_start)
-
-        self._generation.update_progress("encoding_text", 10, 0, total_steps)
-
-        enhanced_prompt = prompt + self.config.camera_motion_prompts.get(
-            camera_motion, ""
-        )
-
-        images: list[ImageConditioningInput] = []
-        temp_image_path: str | None = None
-        if image is not None:
-            temp_image_path = tempfile.NamedTemporaryFile(
-                suffix=".png", delete=False
-            ).name
-            image.save(temp_image_path)
-            images = [
-                ImageConditioningInput(path=temp_image_path, frame_idx=0, strength=1.0)
-            ]
-
-        output_path = self._make_output_path()
-
-        try:
-            settings = self.state.app_settings
-            use_api_encoding = not self._text.should_use_local_encoding()
-            if image is not None:
-                enhance = use_api_encoding and settings.prompt_enhancer_enabled_i2v
-            else:
-                enhance = use_api_encoding and settings.prompt_enhancer_enabled_t2v
-
-            encoding_method = "api" if use_api_encoding else "local"
-            t_text_start = time.perf_counter()
-            self._text.prepare_text_encoding(enhanced_prompt, enhance_prompt=enhance)
-            t_text_end = time.perf_counter()
-            logger.info(
-                "[%s] Text encoding (%s): %.2fs",
-                gen_mode,
-                encoding_method,
-                t_text_end - t_text_start,
-            )
-
-            self._generation.update_progress("inference", 15, 0, total_steps)
-
-            height = round(height / 64) * 64
-            width = round(width / 64) * 64
-
-            t_inference_start = time.perf_counter()
-            pipeline_state.pipeline.generate(
-                prompt=enhanced_prompt,
-                seed=seed,
-                height=height,
-                width=width,
-                num_frames=num_frames,
-                frame_rate=fps,
-                images=images,
-                output_path=str(output_path),
-            )
-            t_inference_end = time.perf_counter()
-            logger.info(
-                "[%s] Inference: %.2fs", gen_mode, t_inference_end - t_inference_start
-            )
-
-            if self._generation.is_generation_cancelled():
-                if output_path.exists():
-                    output_path.unlink()
-                raise RuntimeError("Generation was cancelled")
-
-            t_total_end = time.perf_counter()
-            logger.info(
-                "[%s] Total generation: %.2fs (load=%.2fs, text=%.2fs, inference=%.2fs)",
-                gen_mode,
-                t_total_end - t_total_start,
-                t_load_end - t_load_start,
-                t_text_end - t_text_start,
-                t_inference_end - t_inference_start,
-            )
-
-            self._generation.update_progress("complete", 100, total_steps, total_steps)
-            return str(output_path)
-        finally:
-            self._text.clear_api_embeddings()
-            if temp_image_path and os.path.exists(temp_image_path):
-                os.unlink(temp_image_path)
-
-    def _generate_a2v(
-        self, req: GenerateVideoRequest, duration: int, fps: int, *, audio_path: str
-    ) -> GenerateVideoResponse:
-        if req.model != "pro":
-            logger.warning(
-                "A2V local requested with model=%s; A2V always uses pro pipeline",
-                req.model,
-            )
-        validated_audio_path = validate_audio_file(audio_path)
-        audio_path_str = str(validated_audio_path)
-
-        # 支持竖屏和横屏
-        RESOLUTION_MAP: dict[str, tuple[int, int]] = {
-            "540p": (960, 540),
-            "720p": (1280, 720),
-            "1080p": (1920, 1080),
-        }
-
-        base_w, base_h = RESOLUTION_MAP.get(req.resolution, (1280, 720))
-
-        # 根据 aspectRatio 调整分辨率
-        if req.aspectRatio == "9:16":
-            width, height = base_h, base_w  # 竖屏
-        else:
-            width, height = base_w, base_h  # 横屏
-
-        num_frames = self._compute_num_frames(duration, fps)
-
-        image = None
-        temp_image_path: str | None = None
-        image_path = normalize_optional_path(req.imagePath)
-        if image_path:
-            image = self._prepare_image(image_path, width, height)
-
-        # 获取首尾帧
-        start_frame_path = normalize_optional_path(getattr(req, "startFramePath", None))
-        end_frame_path = normalize_optional_path(getattr(req, "endFramePath", None))
-
-        seed = self._resolve_seed()
-
-        generation_id = self._make_generation_id()
-
-        temp_image_paths: list[str] = []
-        try:
-            a2v_state = self._pipelines.load_a2v_pipeline()
-            self._generation.start_generation(generation_id)
-
-            enhanced_prompt = req.prompt + self.config.camera_motion_prompts.get(
-                req.cameraMotion, ""
-            )
-            neg = (
-                req.negativePrompt
-                if req.negativePrompt
-                else self.config.default_negative_prompt
-            )
-
-            images: list[ImageConditioningInput] = []
-            temp_image_paths: list[str] = []
-
-            # 首帧
-            if start_frame_path:
-                start_img = self._prepare_image(start_frame_path, width, height)
-                temp_start_path = tempfile.NamedTemporaryFile(
-                    suffix=".png", delete=False
-                ).name
-                start_img.save(temp_start_path)
-                temp_image_paths.append(temp_start_path)
-                images.append(
-                    ImageConditioningInput(
-                        path=temp_start_path, frame_idx=0, strength=1.0
-                    )
-                )
-
-            # 中间图片（如果有）
-            if image is not None and not start_frame_path:
-                temp_image_path = tempfile.NamedTemporaryFile(
-                    suffix=".png", delete=False
-                ).name
-                image.save(temp_image_path)
-                temp_image_paths.append(temp_image_path)
-                images.append(
-                    ImageConditioningInput(
-                        path=temp_image_path, frame_idx=0, strength=1.0
-                    )
-                )
-
-            # 尾帧
-            if end_frame_path:
-                last_latent_idx = (num_frames - 1) // 8 + 1 - 1
-                end_img = self._prepare_image(end_frame_path, width, height)
-                temp_end_path = tempfile.NamedTemporaryFile(
-                    suffix=".png", delete=False
-                ).name
-                end_img.save(temp_end_path)
-                temp_image_paths.append(temp_end_path)
-                images.append(
-                    ImageConditioningInput(
-                        path=temp_end_path, frame_idx=last_latent_idx, strength=1.0
-                    )
-                )
-
-            output_path = self._make_output_path()
-
-            total_steps = 11  # distilled: 8 steps (stage 1) + 3 steps (stage 2)
-
-            a2v_settings = self.state.app_settings
-            a2v_use_api = not self._text.should_use_local_encoding()
-            if image is not None:
-                a2v_enhance = a2v_use_api and a2v_settings.prompt_enhancer_enabled_i2v
-            else:
-                a2v_enhance = a2v_use_api and a2v_settings.prompt_enhancer_enabled_t2v
-
-            self._generation.update_progress("loading_model", 5, 0, total_steps)
-            self._generation.update_progress("encoding_text", 10, 0, total_steps)
-            self._text.prepare_text_encoding(
-                enhanced_prompt, enhance_prompt=a2v_enhance
-            )
-            self._generation.update_progress("inference", 15, 0, total_steps)
-
-            a2v_state.pipeline.generate(
-                prompt=enhanced_prompt,
-                negative_prompt=neg,
-                seed=seed,
-                height=height,
-                width=width,
-                num_frames=num_frames,
-                frame_rate=fps,
-                num_inference_steps=total_steps,
-                images=images,
-                audio_path=audio_path_str,
-                audio_start_time=0.0,
-                audio_max_duration=None,
-                output_path=str(output_path),
-            )
-
-            if self._generation.is_generation_cancelled():
-                if output_path.exists():
-                    output_path.unlink()
-                raise RuntimeError("Generation was cancelled")
-
-            self._generation.update_progress("complete", 100, total_steps, total_steps)
-            self._generation.complete_generation(str(output_path))
-            return GenerateVideoResponse(status="complete", video_path=str(output_path))
-
-        except Exception as e:
-            self._generation.fail_generation(str(e))
-            if "cancelled" in str(e).lower():
-                logger.info("Generation cancelled by user")
-                return GenerateVideoResponse(status="cancelled")
-            raise HTTPError(500, str(e)) from e
-        finally:
-            self._text.clear_api_embeddings()
-            # 清理所有临时图片
-            for tmp_path in temp_image_paths:
-                if tmp_path and os.path.exists(tmp_path):
-                    try:
-                        os.unlink(tmp_path)
-                    except Exception:
-                        pass
-            if temp_image_path and os.path.exists(temp_image_path):
-                try:
-                    os.unlink(temp_image_path)
-                except Exception:
-                    pass
-
-    def _prepare_image(self, image_path: str, width: int, height: int) -> Image.Image:
-        validated_path = validate_image_file(image_path)
-        try:
-            img = Image.open(validated_path).convert("RGB")
-        except Exception:
-            raise HTTPError(400, f"Invalid image file: {image_path}") from None
-        img_w, img_h = img.size
-        target_ratio = width / height
-        img_ratio = img_w / img_h
-        if img_ratio > target_ratio:
-            new_h = height
-            new_w = int(img_w * (height / img_h))
-        else:
-            new_w = width
-            new_h = int(img_h * (width / img_w))
-        resized = img.resize((new_w, new_h), Image.Resampling.LANCZOS)
-        left = (new_w - width) // 2
-        top = (new_h - height) // 2
-        return resized.crop((left, top, left + width, top + height))
-
-    @staticmethod
-    def _make_generation_id() -> str:
-        return uuid.uuid4().hex[:8]
-
-    @staticmethod
-    def _compute_num_frames(duration: int, fps: int) -> int:
-        n = ((duration * fps) // 8) * 8 + 1
-        return max(n, 9)
-
-    def _resolve_seed(self) -> int:
-        settings = self.state.app_settings
-        if settings.seed_locked:
-            logger.info("Using locked seed: %s", settings.locked_seed)
-            return settings.locked_seed
-        return int(time.time()) % 2147483647
-
-    def _make_output_path(self) -> Path:
-        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-        return (
-            self.config.outputs_dir
-            / f"ltx2_video_{timestamp}_{self._make_generation_id()}.mp4"
-        )
-
-    def _generate_forced_api(self, req: GenerateVideoRequest) -> GenerateVideoResponse:
-        if self._generation.is_generation_running():
-            raise HTTPError(409, "Generation already in progress")
-
-        generation_id = self._make_generation_id()
-        self._generation.start_api_generation(generation_id)
-
-        audio_path = normalize_optional_path(req.audioPath)
-        image_path = normalize_optional_path(req.imagePath)
-        has_input_audio = bool(audio_path)
-        has_input_image = bool(image_path)
-
-        try:
-            self._generation.update_progress("validating_request", 5, None, None)
-
-            api_key = self.state.app_settings.ltx_api_key.strip()
-            logger.info(
-                "Forced API generation route selected (key_present=%s)", bool(api_key)
-            )
-            if not api_key:
-                raise HTTPError(400, "PRO_API_KEY_REQUIRED")
-
-            requested_model = req.model.strip().lower()
-            api_model_id = FORCED_API_MODEL_MAP.get(requested_model)
-            if api_model_id is None:
-                raise HTTPError(400, "INVALID_FORCED_API_MODEL")
-
-            resolution_label = req.resolution
-            resolution_by_aspect = FORCED_API_RESOLUTION_MAP.get(resolution_label)
-            if resolution_by_aspect is None:
-                raise HTTPError(400, "INVALID_FORCED_API_RESOLUTION")
-
-            aspect_ratio = req.aspectRatio.strip()
-            if aspect_ratio not in FORCED_API_ALLOWED_ASPECT_RATIOS:
-                raise HTTPError(400, "INVALID_FORCED_API_ASPECT_RATIO")
-
-            api_resolution = resolution_by_aspect[aspect_ratio]
-
-            prompt = req.prompt
-
-            if self._generation.is_generation_cancelled():
-                raise RuntimeError("Generation was cancelled")
-
-            if has_input_audio:
-                if requested_model != "pro":
-                    logger.warning(
-                        "A2V requested with model=%s; overriding to 'pro'",
-                        requested_model,
-                    )
-                api_model_id = FORCED_API_MODEL_MAP["pro"]
-                if api_resolution != A2V_FORCED_API_RESOLUTION:
-                    logger.warning(
-                        "A2V requested with resolution=%s; overriding to '%s'",
-                        api_resolution,
-                        A2V_FORCED_API_RESOLUTION,
-                    )
-                api_resolution = A2V_FORCED_API_RESOLUTION
-                validated_audio_path = validate_audio_file(audio_path)
-                validated_image_path: Path | None = None
-                if image_path is not None:
-                    validated_image_path = validate_image_file(image_path)
-
-                self._generation.update_progress("uploading_audio", 20, None, None)
-                audio_uri = self._ltx_api_client.upload_file(
-                    api_key=api_key,
-                    file_path=str(validated_audio_path),
-                )
-                image_uri: str | None = None
-                if validated_image_path is not None:
-                    self._generation.update_progress("uploading_image", 35, None, None)
-                    image_uri = self._ltx_api_client.upload_file(
-                        api_key=api_key,
-                        file_path=str(validated_image_path),
-                    )
-                self._generation.update_progress("inference", 55, None, None)
-                video_bytes = self._ltx_api_client.generate_audio_to_video(
-                    api_key=api_key,
-                    prompt=prompt,
-                    audio_uri=audio_uri,
-                    image_uri=image_uri,
-                    model=api_model_id,
-                    resolution=api_resolution,
-                )
-                self._generation.update_progress("downloading_output", 85, None, None)
-            elif has_input_image:
-                validated_image_path = validate_image_file(image_path)
-
-                duration = self._parse_forced_numeric_field(
-                    req.duration, "INVALID_FORCED_API_DURATION"
-                )
-                fps = self._parse_forced_numeric_field(
-                    req.fps, "INVALID_FORCED_API_FPS"
-                )
-                if fps not in FORCED_API_ALLOWED_FPS:
-                    raise HTTPError(400, "INVALID_FORCED_API_FPS")
-                if duration not in _get_allowed_durations(
-                    api_model_id, resolution_label, fps
-                ):
-                    raise HTTPError(400, "INVALID_FORCED_API_DURATION")
-
-                generate_audio = self._parse_audio_flag(req.audio)
-                self._generation.update_progress("uploading_image", 20, None, None)
-                image_uri = self._ltx_api_client.upload_file(
-                    api_key=api_key,
-                    file_path=str(validated_image_path),
-                )
-                self._generation.update_progress("inference", 55, None, None)
-                video_bytes = self._ltx_api_client.generate_image_to_video(
-                    api_key=api_key,
-                    prompt=prompt,
-                    image_uri=image_uri,
-                    model=api_model_id,
-                    resolution=api_resolution,
-                    duration=float(duration),
-                    fps=float(fps),
-                    generate_audio=generate_audio,
-                    camera_motion=req.cameraMotion,
-                )
-                self._generation.update_progress("downloading_output", 85, None, None)
-            else:
-                duration = self._parse_forced_numeric_field(
-                    req.duration, "INVALID_FORCED_API_DURATION"
-                )
-                fps = self._parse_forced_numeric_field(
-                    req.fps, "INVALID_FORCED_API_FPS"
-                )
-                if fps not in FORCED_API_ALLOWED_FPS:
-                    raise HTTPError(400, "INVALID_FORCED_API_FPS")
-                if duration not in _get_allowed_durations(
-                    api_model_id, resolution_label, fps
-                ):
-                    raise HTTPError(400, "INVALID_FORCED_API_DURATION")
-
-                generate_audio = self._parse_audio_flag(req.audio)
-                self._generation.update_progress("inference", 55, None, None)
-                video_bytes = self._ltx_api_client.generate_text_to_video(
-                    api_key=api_key,
-                    prompt=prompt,
-                    model=api_model_id,
-                    resolution=api_resolution,
-                    duration=float(duration),
-                    fps=float(fps),
-                    generate_audio=generate_audio,
-                    camera_motion=req.cameraMotion,
-                )
-                self._generation.update_progress("downloading_output", 85, None, None)
-
-            if self._generation.is_generation_cancelled():
-                raise RuntimeError("Generation was cancelled")
-
-            output_path = self._write_forced_api_video(video_bytes)
-            if self._generation.is_generation_cancelled():
-                output_path.unlink(missing_ok=True)
-                raise RuntimeError("Generation was cancelled")
-
-            self._generation.update_progress("complete", 100, None, None)
-            self._generation.complete_generation(str(output_path))
-            return GenerateVideoResponse(status="complete", video_path=str(output_path))
-        except HTTPError as e:
-            self._generation.fail_generation(e.detail)
-            raise
-        except Exception as e:
-            self._generation.fail_generation(str(e))
-            if "cancelled" in str(e).lower():
-                logger.info("Generation cancelled by user")
-                return GenerateVideoResponse(status="cancelled")
-            raise HTTPError(500, str(e)) from e
-
-    def _write_forced_api_video(self, video_bytes: bytes) -> Path:
-        output_path = self._make_output_path()
-        output_path.write_bytes(video_bytes)
-        return output_path
-
-    @staticmethod
-    def _parse_forced_numeric_field(raw_value: str, error_detail: str) -> int:
-        try:
-            return int(float(raw_value))
-        except (TypeError, ValueError):
-            raise HTTPError(400, error_detail) from None
-
-    @staticmethod
-    def _parse_audio_flag(audio_value: str | bool) -> bool:
-        if isinstance(audio_value, bool):
-            return audio_value
-        normalized = audio_value.strip().lower()
-        return normalized in {"1", "true", "yes", "on"}

LTX2.3/patches/launcher.py

@@ -1,20 +0,0 @@
-
-import sys
-import os
-
-patch_dir = r"C:\Users\1-xuanran\Desktop\LTX多合一启动器\patches"
-backend_dir = r"C:\Program Files\LTX Desktop\resources\backend"
-
-# 防御性清除：强行剥离所有的默认 backend_dir 引用
-sys.path = [p for p in sys.path if p and os.path.normpath(p) != os.path.normpath(backend_dir)]
-sys.path = [p for p in sys.path if p and p != "." and p != ""]
-
-# 绝对插队注入：优先搜索 PATCHES_DIR
-sys.path.insert(0, patch_dir)
-sys.path.insert(1, backend_dir)
-
-import uvicorn
-from ltx2_server import app
-
-if __name__ == '__main__':
-    uvicorn.run(app, host="0.0.0.0", port=3000, log_level="info", access_log=False)

LTX2.3/run.bat

@@ -1,38 +0,0 @@
-@echo off
-title LTX-2 Cinematic Workstation
-
-echo =========================================================
-echo    LTX-2 Cinematic UI Booting...
-echo =========================================================
-echo.
-
-set "LTX_PY=%USERPROFILE%\AppData\Local\LTXDesktop\python\python.exe"
-set "LTX_UI_URL=http://127.0.0.1:4000/"
-
-if exist "%LTX_PY%" (
-    echo [SUCCESS] LTX Bundled Python environment detected!
-    echo [INFO] Browser will open automatically when UI is ready...
-    start "" powershell -NoProfile -WindowStyle Hidden -Command "$ProgressPreference='SilentlyContinue'; $deadline=(Get-Date).AddSeconds(60); while((Get-Date) -lt $deadline){ try { Invoke-WebRequest -UseBasicParsing '%LTX_UI_URL%' -TimeoutSec 2 | Out-Null; Start-Process '%LTX_UI_URL%'; exit 0 } catch { Start-Sleep -Seconds 1 } }"
-    echo [INFO] Starting workspace natively...
-    echo ---------------------------------------------------------
-    "%LTX_PY%" main.py
-    pause
-    exit /b
-)
-
-python --version >nul 2>&1
-if %errorlevel% equ 0 (
-    echo [WARNING] LTX Bundled Python not found.
-    echo [INFO] Browser will open automatically when UI is ready...
-    start "" powershell -NoProfile -WindowStyle Hidden -Command "$ProgressPreference='SilentlyContinue'; $deadline=(Get-Date).AddSeconds(60); while((Get-Date) -lt $deadline){ try { Invoke-WebRequest -UseBasicParsing '%LTX_UI_URL%' -TimeoutSec 2 | Out-Null; Start-Process '%LTX_UI_URL%'; exit 0 } catch { Start-Sleep -Seconds 1 } }"
-    echo [INFO] Falling back to global Python environment...
-    echo ---------------------------------------------------------
-    python main.py
-    pause
-    exit /b
-)
-
-echo [ERROR] FATAL: No Python interpreter found on this system.
-echo [INFO] Please run install.bat to download and set up Python!
-echo.
-pause