feat: 优化首页入口按钮质感，提升商业产品精致度

- 按钮背景改为微渐变+毛玻璃效果(backdrop-filter) - 边框改为半透明白色，圆角从8px升级到12px - 增加内高光+外层深度阴影提升层次感 - 字间距、字重大小幅调整，更精致克制 - hover态增加accent光晕+图标变绿+放大效果 - 主按钮增加渐变绿底+内高光+绿色辉光阴影 - 增加按压态scale(0.97)反馈 - 主按钮图标hover放大1.12倍
fix: 修复剧本评分文本框随内容无限下拉导致按钮被挤出视口
2026-06-02 19:09:00 +08:00 · 2026-06-02 18:18:00 +08:00 · 2026-06-02 09:03:11 +00:00 · 2026-06-02 09:02:46 +00:00 · 2026-06-02 09:01:38 +00:00 · 2026-06-02 09:01:31 +00:00
18 changed files with 1618 additions and 1347 deletions
@@ -1,7 +1,8 @@
 import { buildApiUrl, buildAuthHeaders } from "./serverConnection";

 const TEXT_MODEL = "qwen-max";
-const VISION_MODEL = "qwen3.6-plus";
+const VISION_MODEL = "qwen3.7-plus";
+const VISION_FALLBACK_MODEL = "qwen-vl-plus";

 export interface AdVideoUserConfig {
  platform: string;
@@ -107,36 +108,63 @@ interface ChatMessage {
  content: string;
 }

+const MAX_RETRIES = 3;
+const RETRY_BASE_MS = 2000;
+const CHAT_TIMEOUT_MS = 120_000; // 2 minutes per AI call
+
+function isTransientError(err: unknown): boolean {
+  if (!(err instanceof Error)) return false;
+  const msg = err.message.toLowerCase();
+  return /\b429\b/.test(msg) || msg.includes("signal timed out") || msg.includes("aborted") || msg.includes("timeout");
+}
+
+async function retryOnTransient<T>(fn: () => Promise<T>, signal?: AbortSignal): Promise<T> {
+  for (let attempt = 0; attempt <= MAX_RETRIES; attempt++) {
+    try {
+      return await fn();
+    } catch (err) {
+      if (signal?.aborted) throw err;
+      if (attempt === MAX_RETRIES) throw err;
+      if (!isTransientError(err)) throw err;
+      const delay = RETRY_BASE_MS * 2 ** attempt + Math.random() * 1000;
+      await new Promise((r) => setTimeout(r, delay));
+    }
+  }
+  throw new Error("unreachable");
+}
+
 async function chat(
  systemPrompt: string,
  userContent: string,
  options?: { model?: string; signal?: AbortSignal },
 ): Promise<string> {
-  const messages: ChatMessage[] = [
-    { role: "system", content: systemPrompt },
-    { role: "user", content: userContent },
-  ];
-  const timeoutSignal = AbortSignal.timeout(60000);
-  const combinedSignal = options?.signal
-    ? AbortSignal.any([options.signal, timeoutSignal])
-    : timeoutSignal;
-  const res = await fetch(buildApiUrl("ai/chat"), {
-    method: "POST",
-    headers: buildAuthHeaders(),
-    body: JSON.stringify({
-      model: options?.model ?? TEXT_MODEL,
-      messages,
-      stream: false,
-      temperature: 0.4,
-    }),
-    signal: combinedSignal,
-  });
-  if (!res.ok) throw new Error(`AI 调用失败 (${res.status})`);
-  const payload = await res.json();
-  const content: string =
-    payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
-  if (!content) throw new Error("模型未返回有效内容");
-  return content;
+  return retryOnTransient(async () => {
+    const messages: ChatMessage[] = [
+      { role: "system", content: systemPrompt },
+      { role: "user", content: userContent },
+    ];
+    const timeoutSignal = AbortSignal.timeout(CHAT_TIMEOUT_MS);
+    const combinedSignal = options?.signal
+      ? AbortSignal.any([options.signal, timeoutSignal])
+      : timeoutSignal;
+    const res = await fetch(buildApiUrl("ai/chat"), {
+      method: "POST",
+      headers: buildAuthHeaders(),
+      body: JSON.stringify({
+        model: options?.model ?? TEXT_MODEL,
+        messages,
+        stream: false,
+        temperature: 0.4,
+      }),
+      signal: combinedSignal,
+    });
+    if (!res.ok) throw new Error(`AI 调用失败 (${res.status})`);
+    const payload = await res.json();
+    const content: string =
+      payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
+    if (!content) throw new Error("模型未返回有效内容");
+    return content;
+  }, options?.signal);
 }

 async function visionChat(
@@ -149,30 +177,43 @@ async function visionChat(
    ...imageUrls.map((url) => ({ type: "image_url", image_url: { url } })),
    { type: "text", text },
  ];
-  const timeoutSignal = AbortSignal.timeout(60000);
-  const combinedSignal = signal
-    ? AbortSignal.any([signal, timeoutSignal])
-    : timeoutSignal;
-  const res = await fetch(buildApiUrl("ai/chat"), {
-    method: "POST",
-    headers: buildAuthHeaders(),
-    body: JSON.stringify({
-      model: VISION_MODEL,
-      messages: [
-        { role: "system", content: systemPrompt },
-        { role: "user", content },
-      ],
-      stream: false,
-      temperature: 0.3,
-    }),
-    signal: combinedSignal,
-  });
-  if (!res.ok) throw new Error(`图片理解调用失败 (${res.status})`);
-  const payload = await res.json();
-  const out: string =
-    payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
-  if (!out) throw new Error("图片理解未返回有效内容");
-  return out;
+  const messages = [
+    { role: "system", content: systemPrompt },
+    { role: "user", content },
+  ];
+
+  for (const model of [VISION_MODEL, VISION_FALLBACK_MODEL]) {
+    const timeoutSignal = AbortSignal.timeout(CHAT_TIMEOUT_MS);
+    const combinedSignal = signal
+      ? AbortSignal.any([signal, timeoutSignal])
+      : timeoutSignal;
+    try {
+      const out = await retryOnTransient(async () => {
+        const res = await fetch(buildApiUrl("ai/chat"), {
+          method: "POST",
+          headers: buildAuthHeaders(),
+          body: JSON.stringify({ model, messages, stream: false, temperature: 0.3 }),
+          signal: combinedSignal,
+        });
+        if (!res.ok) {
+          const errBody = await res.text().catch(() => "");
+          if (model === VISION_MODEL && errBody.includes("image format")) throw new Error("IMAGE_FORMAT_FALLBACK");
+          throw new Error(`图片理解调用失败 (${res.status})`);
+        }
+        const payload = await res.json();
+        const result: string =
+          payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
+        if (!result) throw new Error("图片理解未返回有效内容");
+        return result;
+      }, signal);
+      return out;
+    } catch (err) {
+      if (err instanceof Error && err.message === "IMAGE_FORMAT_FALLBACK") continue;
+      if (model === VISION_MODEL && err instanceof Error && err.message?.includes("图片理解调用失败")) continue;
+      throw err;
+    }
+  }
+  throw new Error("图片理解调用失败，所有模型均不可用");
 }

 const IMAGE_UNDERSTANDING_PROMPT = `你是电商产品图片分析专家。请分析用户提供的产品图片，识别产品主体、外观、颜色、材质、形状、尺寸感、品牌标识、关键部件、可视化卖点和适合展示的镜头角度。请用简洁的中文段落描述，不要编造图片中看不到的信息。`;
@@ -403,6 +403,24 @@ export const aiGenerationClient = {
    return readJsonResponse<{ url: string; ossKey?: string }>(res, "Asset upload response failed");
  },

+  async uploadAssetBinary(blob: Blob, options?: { name?: string; mimeType?: string; scope?: string }): Promise<{ url: string; signedUrl?: string; ossKey?: string }> {
+    const form = new FormData();
+    form.append("file", blob, options?.name || "upload.png");
+    if (options?.scope) form.append("scope", options.scope);
+    if (options?.mimeType) form.append("mimeType", options.mimeType);
+    // Exclude Content-Type so browser auto-sets multipart/form-data with boundary
+    const { "Content-Type": _ct, ...authHeaders } = buildAuthHeaders();
+    const res = await fetch(buildApiUrl("oss/upload-binary"), {
+      method: "POST",
+      headers: authHeaders,
+      body: form,
+    });
+    if (!res.ok) {
+      await throwResponseError(res, "Binary asset upload failed");
+    }
+    return readJsonResponse<{ url: string; ossKey?: string }>(res, "Binary asset upload response failed");
+  },
+
  async uploadAssetByUrl(input: UploadAssetByUrlInput): Promise<{ url: string; signedUrl?: string; ossKey?: string }> {
    const res = await fetch(buildApiUrl("oss/upload-by-url"), {
      method: "POST",
@@ -10,39 +10,50 @@ export interface ScriptEvalResult {
  suggestions: string[];
 }

-const EVAL_SYSTEM_PROMPT = `你是一位专业的剧本评测专家。请对用户提供的剧本进行六维评分分析，并以严格的 JSON 格式返回结果。
+const EVAL_SYSTEM_PROMPT = `你是一位资深影视剧本评审专家，拥有二十年以上的编剧、制片和剧本医生经验。你精通各类影视叙事理论（三幕式、英雄之旅、起承转合、序列法），同时深度跟踪AIGC短剧/漫剧行业最新趋势。你的任务是对用户提供的剧本进行严谨、系统、多维度的量化评分。

-六个评分维度：
-1. hook（钩子设计，满分20）：开篇吸引力、悬念设置、黄金三秒法则
-2. character（角色塑造，满分15）：人物立体度、动机合理性、弧光设计
-3. plot（剧情结构，满分20）：起承转合、节奏把控、冲突设计
-4. dialogue（台词对白，满分15）：语言质感、角色差异化、潜台词
-5. visual（画面表现，满分15）：镜头感、空间层次、视觉冲击力
-6. content（内容深度，满分15）：主题表达、情感共鸣、思想内核
+【剧本类型识别】
+收到剧本后，首先判断类型：AIGC短剧/漫剧（单集5-30分钟，竖屏平台，高密度反转、强节奏）或传统影视剧本（单集40分钟以上，长视频平台，完整起承转合）。类型判定将影响各维度的评价侧重点。

-请严格按以下 JSON 格式返回（不要包含任何其他文字）：
+【评分体系（100分制，六个维度）】
+1. hook 钩子设计（20分）：开篇钩子、集末钩子、场景内钩子、悬念链完整性。短剧前3秒须有即时爆点；长剧第一幕结束前须建立核心悬念。
+2. plot 剧情结构（20分）：结构框架、节奏控制、冲突设计、逻辑自洽。短剧"每分钟有事件"，反转密度加分；长剧需处理好B线C线与主线交织。
+3. character 角色塑造（18分）：主角弧光、角色辨识度、角色动机、配角质量。短剧角色须在前2分钟建立；长剧需要内在矛盾和多阶段成长。
+4. dialogue 台词对白（15分）：角色语言区分度、信息传递效率、潜台词与留白、金句与记忆点。
+5. visual 画面表现（15分）：场景描写质量、视觉叙事技巧、镜头感与节奏、制作可行性。AIGC需考虑AI生成技术边界与一致性。
+6. content 内容深度（12分）：主题表达、情感共鸣、社会/人性洞察。
+
+【评分铁律】
+- 扣分必须明确指出剧本中的具体段落/场景/台词。
+- 严禁给出任何维度的满分，必须有扣分理由。
+- 优缺点都要充分展开，不可只批不夸或只夸不批。
+- 不因题材类型偏见降低评分，不因某一方面出色而抬高其他维度（避免光环效应）。
+- 敢于拉开各维度分数差距，避免全部给中等分数。
+
+【等级标准】按总分百分比：S≥90 | A 80-89 | B 70-79 | C 60-69 | D<60。
+
+请严格按以下 JSON 格式返回（不要包含任何其他文字，不要用代码块包裹以外的说明）：
 {
-  "dimensionScores": { "hook": 数字, "character": 数字, "plot": 数字, "dialogue": 数字, "visual": 数字, "content": 数字 },
-  "summary": "一句话总结评价",
-  "issues": ["问题1", "问题2", ...],
-  "highlights": ["亮点1", "亮点2", ...],
-  "suggestions": ["建议1", "建议2", ...]
+  "dimensionScores": { "hook": 数字, "plot": 数字, "character": 数字, "dialogue": 数字, "visual": 数字, "content": 数字 },
+  "summary": "200-300字综合评价，概括整体质量、市场潜力与目标受众匹配度",
+  "issues": ["每条指出具体维度的扣分点并引用剧本原文位置", ...],
+  "highlights": ["核心亮点，引用剧本具体场景", ...],
+  "suggestions": ["按优先级排列的改进建议（最优先/次优先/可优化）", ...]
 }`;

-const DIMENSION_WEIGHTS: Record<string, { maxScore: number; weight: number }> = {
-  hook: { maxScore: 20, weight: 0.2 },
-  character: { maxScore: 15, weight: 0.15 },
-  plot: { maxScore: 20, weight: 0.2 },
-  dialogue: { maxScore: 15, weight: 0.15 },
-  visual: { maxScore: 15, weight: 0.15 },
-  content: { maxScore: 15, weight: 0.15 },
+const DIMENSION_WEIGHTS: Record<string, { maxScore: number }> = {
+  hook: { maxScore: 20 },
+  plot: { maxScore: 20 },
+  character: { maxScore: 18 },
+  dialogue: { maxScore: 15 },
+  visual: { maxScore: 15 },
+  content: { maxScore: 12 },
 };

 function computeTotalAndGrade(scores: Record<string, number>): { totalScore: number; grade: string } {
  const totalScore = Math.round(
    Object.entries(DIMENSION_WEIGHTS).reduce((sum, [key, dim]) => {
-      const score = Math.max(0, Math.min(dim.maxScore, scores[key] ?? 0));
-      return sum + (score / dim.maxScore) * 100 * dim.weight;
+      return sum + Math.max(0, Math.min(dim.maxScore, scores[key] ?? 0));
    }, 0),
  );
  const grade = totalScore >= 90 ? "S" : totalScore >= 80 ? "A" : totalScore >= 70 ? "B" : totalScore >= 60 ? "C" : "D";
@@ -56,6 +67,7 @@ function extractJson(text: string): unknown {
 }

 export async function evaluateScript(script: string, signal?: AbortSignal): Promise<ScriptEvalResult> {
+  console.log("[API] 发送评测请求，剧本长度:", script.slice(0, 8000).length, "字符");
  const res = await fetch(buildApiUrl("ai/chat"), {
    method: "POST",
    headers: buildAuthHeaders(),
@@ -71,11 +83,15 @@ export async function evaluateScript(script: string, signal?: AbortSignal): Prom
    signal,
  });

+  console.log("[API] 响应状态:", res.status, res.statusText);
+
  if (!res.ok) {
    throw new Error(`评测请求失败 (${res.status})`);
  }

  const payload = await res.json();
+  console.log("[API] 原始响应体:", payload);
+
  const content: string = payload?.choices?.[0]?.message?.content
    ?? payload?.result?.content
    ?? payload?.content
@@ -84,7 +100,11 @@ export async function evaluateScript(script: string, signal?: AbortSignal): Prom

  if (!content) throw new Error("模型未返回有效内容");

+  console.log("[API] 模型返回内容 (前500字符):", content.slice(0, 500));
+
  const parsed = extractJson(content) as Record<string, unknown>;
+  console.log("[API] 解析后的JSON:", parsed);
+
  const dimensionScores: Record<string, number> = {};
  const rawScores = parsed.dimensionScores as Record<string, number> | undefined;
  if (!rawScores || typeof rawScores !== "object") throw new Error("评分格式异常");
@@ -95,6 +115,7 @@ export async function evaluateScript(script: string, signal?: AbortSignal): Prom
  }

  const { totalScore, grade } = computeTotalAndGrade(dimensionScores);
+  console.log("[API] 计算后总分:", totalScore, "等级:", grade);

  return {
    totalScore,
@@ -17,12 +17,7 @@ import { cloneWorkflow, createBlankWorkflow } from "../../data/workflows";
 import type { WebCanvasWorkflow, WebProjectSummary } from "../../types";
 import { getCommunityCaseCover, getWorkflowFromCase, shouldShowInCanvasCommunity } from "./communityCaseUtils";
 import { ossThumb } from "../../utils/ossImageOptimize";
-import wechatCaseImage10 from "../../../tu/微信图片_20260514125332_10_2.png";
-import wechatCaseImage11 from "../../../tu/微信图片_20260514125332_11_2.png";
-import wechatCaseImage12 from "../../../tu/微信图片_20260514125332_12_2.png";
-import wechatCaseImage7 from "../../../tu/微信图片_20260514125332_7_2.png";
-import wechatCaseImage8 from "../../../tu/微信图片_20260514125332_8_2.png";
-import wechatCaseImage9 from "../../../tu/微信图片_20260514125332_9_2.png";
+const OSS_MUBAN = "https://stringtest.oss-cn-hangzhou.aliyuncs.com/muban";

 interface CommunityPageProps {
  projects: WebProjectSummary[];
@@ -35,12 +30,12 @@ interface CommunityPageProps {
 }

 const communityCardImages = [
-  wechatCaseImage7,
-  wechatCaseImage8,
-  wechatCaseImage9,
-  wechatCaseImage10,
-  wechatCaseImage11,
-  wechatCaseImage12,
+  `${OSS_MUBAN}/dianshang1.png`,
+  `${OSS_MUBAN}/dianshang2.png`,
+  `${OSS_MUBAN}/dianshang3.png`,
+  `${OSS_MUBAN}/wechat-7.png`,
+  `${OSS_MUBAN}/wechat-8.png`,
+  `${OSS_MUBAN}/wechat-9.png`,
 ];

 const SLIDE_INTERVAL = 3000;
@@ -11,9 +11,11 @@ import {
  SkinOutlined,
 } from "@ant-design/icons";
 import { useEffect, useRef, useState, type CSSProperties, type ChangeEvent, type DragEvent, type ReactNode } from "react";
-import ecommerceGenerated from "../../assets/ecommerce-carousel-generated.png";
-import ecommerceSlide4 from "../../assets/ecommerce-hero-carousel/slide-4.png";
-import ecommerceSlide5 from "../../assets/ecommerce-hero-carousel/slide-5.png";
+
+const OSS_MUBAN = "https://stringtest.oss-cn-hangzhou.aliyuncs.com/muban";
+const ecommerceGenerated = `${OSS_MUBAN}/ecommerce-carousel-generated.png`;
+const ecommerceSlide4 = `${OSS_MUBAN}/slide-4.png`;
+const ecommerceSlide5 = `${OSS_MUBAN}/slide-5.png`;
 import ImageMentionMenu, { getImageMentionQuery, insertImageMentionValue, type MentionImageOption } from "./ImageMentionMenu";
 import EcommerceVideoWorkspace from "./EcommerceVideoWorkspace";
 import { aiGenerationClient } from "../../api/aiGenerationClient";
@@ -1319,18 +1321,15 @@ function ProductClonePage(_props: ProductClonePageProps = {}) {
  });

  const uploadProductImages = async (): Promise<string[]> => {
+    const SUPPORTED_IMAGE_TYPES = new Set(["image/jpeg", "image/png", "image/webp", "image/gif"]);
    const urls: string[] = [];
    for (const item of productImages) {
      try {
        const resp = await fetch(item.src);
-        const blob = await resp.blob();
-        const dataUrl = await new Promise<string>((resolve, reject) => {
-          const reader = new FileReader();
-          reader.onload = () => resolve(String(reader.result));
-          reader.onerror = () => reject(reader.error);
-          reader.readAsDataURL(blob);
-        });
-        const { url } = await aiGenerationClient.uploadAsset({ dataUrl, name: item.name, mimeType: blob.type });
+        const rawBlob = await resp.blob();
+        const mimeType = SUPPORTED_IMAGE_TYPES.has(rawBlob.type) ? rawBlob.type : "image/png";
+        const blob = rawBlob.type === mimeType ? rawBlob : new Blob([rawBlob], { type: mimeType });
+        const { url } = await aiGenerationClient.uploadAssetBinary(blob, { name: item.name, mimeType, scope: "ecommerce-product" });
        urls.push(url);
      } catch {
        // skip images that fail to upload
@@ -9,7 +9,6 @@ import {
  type AdVideoUserConfig,
 } from "../../api/adVideoPlanClient";
 import { aiGenerationClient } from "../../api/aiGenerationClient";
-import { uploadAssetWithProgress } from "../../api/uploadWithProgress";
 import { waitForTask } from "../../api/taskSubscription";
 import { resolveVideoRequestModel } from "../../utils/resolveVideoModel";
 import type {
@@ -34,12 +33,18 @@ export async function runVideoPlan(

  onStepStart("upload");
  const imageUrls: string[] = [];
-  for (const dataUrl of imageDataUrls) {
-    const result = await uploadAssetWithProgress(
-      { dataUrl, scope: "ecommerce-product", mimeType: "image/png" },
-      { signal },
-    );
-    imageUrls.push(result.url);
+  const SUPPORTED_IMAGE_TYPES = new Set(["image/jpeg", "image/png", "image/webp", "image/gif"]);
+  for (const srcUrl of imageDataUrls) {
+    try {
+      const resp = await fetch(srcUrl);
+      const rawBlob = await resp.blob();
+      const mimeType = SUPPORTED_IMAGE_TYPES.has(rawBlob.type) ? rawBlob.type : "image/png";
+      const blob = rawBlob.type === mimeType ? rawBlob : new Blob([rawBlob], { type: mimeType });
+      const result = await aiGenerationClient.uploadAssetBinary(blob, { mimeType, scope: "ecommerce-product" });
+      imageUrls.push(result.url);
+    } catch {
+      // skip images that fail to upload
+    }
  }
  onStepDone("upload");

@@ -9,12 +9,14 @@ import {
 } from "@ant-design/icons";
 import { useCallback, useEffect, useMemo, useRef, useState, type CSSProperties } from "react";
 import WelcomeSplash from "./WelcomeSplash";
-import featureEcommerceImage from "../../assets/home-features/feature-ecommerce.jpg";
-import featureScriptImage from "../../assets/home-features/feature-script.jpg";
-import featureTokenImage from "../../assets/home-features/feature-token.jpg";
-import heroImage1 from "../../../projects/public/hero-1.png";
-import heroImage2 from "../../../projects/public/hero-2.png";
-import heroImage3 from "../../../projects/public/hero-3.png";
+
+const OSS_MUBAN = "https://stringtest.oss-cn-hangzhou.aliyuncs.com/muban";
+const heroImage1 = `${OSS_MUBAN}/hero-1.png`;
+const heroImage2 = `${OSS_MUBAN}/hero-2.png`;
+const heroImage3 = `${OSS_MUBAN}/hero-3.png`;
+const featureEcommerceImage = `${OSS_MUBAN}/feature-ecommerce.jpg`;
+const featureScriptImage = `${OSS_MUBAN}/feature-script.jpg`;
+const featureTokenImage = `${OSS_MUBAN}/feature-token.jpg`;

 interface HomePageProps {
  onOpenGenerate: () => void;
@@ -1,5 +1,5 @@
 import { CopyOutlined, DownOutlined, DownloadOutlined, FileTextOutlined, ReloadOutlined, TrophyOutlined, UploadOutlined } from "@ant-design/icons";
-import { useMemo, useRef, useState, type ChangeEvent, type KeyboardEvent } from "react";
+import { useEffect, useMemo, useRef, useState, type ChangeEvent, type KeyboardEvent } from "react";
 import { evaluateScript } from "../../api/scriptEvalClient";

 interface ScoreDimension {
@@ -35,9 +35,9 @@ const scoreDimensions: ScoreDimension[] = [
  {
    key: "character",
    label: "角色塑造",
-    maxScore: 15,
-    weight: 0.15,
-    description: "人物立体度、动机合理性、弧光设计",
+    maxScore: 18,
+    weight: 0.18,
+    description: "主角弧光、角色辨识度、动机、配角质量",
  },
  {
    key: "plot",
@@ -63,9 +63,9 @@ const scoreDimensions: ScoreDimension[] = [
  {
    key: "content",
    label: "内容深度",
-    maxScore: 15,
-    weight: 0.15,
-    description: "主题表达、情感共鸣、思想内核",
+    maxScore: 12,
+    weight: 0.12,
+    description: "主题表达、情感共鸣、社会/人性洞察",
  },
 ];

@@ -170,6 +170,10 @@ function ScriptTokensPage() {
  const [copied, setCopied] = useState(false);
  const fileInputRef = useRef<HTMLInputElement>(null);

+  useEffect(() => {
+    console.log("[剧本评分] 页面已加载，ScriptTokensPage mounted");
+  }, []);
+
  const hasContent = Boolean(script.trim());
  const lineNumbers = useMemo(() => {
    const count = Math.min(160, Math.max(10, script.split(/\r\n|\r|\n/).length));
@@ -202,14 +206,26 @@ function ScriptTokensPage() {
  };

  const handleEvaluate = async () => {
+    console.log("[剧本评测] 点击开始评测，hasContent:", hasContent, "script长度:", script.length);
    if (!hasContent) return;
    setLoading(true);
    setResult(null);
    setEvalError(null);
    try {
+      console.log("[剧本评测] 开始评测，剧本长度:", script.length, "字符");
      const aiResult = await evaluateScript(script);
+      console.log("[剧本评测] 评测完成，结果:", {
+        总分: aiResult.totalScore,
+        等级: aiResult.grade,
+        维度得分: aiResult.dimensionScores,
+        摘要: aiResult.summary,
+        亮点: aiResult.highlights,
+        问题: aiResult.issues,
+        建议: aiResult.suggestions,
+      });
      setResult(aiResult);
    } catch (err) {
+      console.error("[剧本评测] 评测失败:", err);
      setEvalError(err instanceof Error ? err.message : "评测服务暂时不可用，请稍后重试");
    }
    setDetailsExpanded(true);
@@ -0,0 +1,88 @@
+import { FileTextOutlined, SoundOutlined } from "@ant-design/icons";
+import type { PromptMentionItem, PromptMentionTokenRange, ReferenceItem } from "./workbenchConstants";
+import { renderPromptPreviewNodes, getPromptMentionTokenRanges } from "./workbenchMentionUtils";
+
+export { getPromptMentionTokenRanges };
+
+export function findPromptMentionRangeInside(index: number, ranges: PromptMentionTokenRange[]) {
+  return ranges.find((range) => index > range.start && index < range.end);
+}
+
+export function findPromptMentionRangeOverlap(start: number, end: number, ranges: PromptMentionTokenRange[]) {
+  return ranges.find((range) => start < range.end && end > range.start);
+}
+
+export function ReferenceInlinePreview({
+  item,
+}: {
+  item: Pick<ReferenceItem, "kind" | "name" | "previewUrl">;
+}) {
+  if ((item.kind === "image" || item.kind === "video") && item.previewUrl) {
+    return item.kind === "video" ? (
+      <video src={item.previewUrl} muted playsInline />
+    ) : (
+      <img src={item.previewUrl} alt={item.name} loading="lazy" />
+    );
+  }
+
+  return item.kind === "audio" ? <SoundOutlined /> : <FileTextOutlined />;
+}
+
+export function ReferencePreview({
+  item,
+  label,
+}: {
+  item: Pick<ReferenceItem, "kind" | "name" | "previewUrl">;
+  label?: string;
+}) {
+  if ((item.kind === "image" || item.kind === "video") && item.previewUrl) {
+    return item.kind === "video" ? (
+      <video src={item.previewUrl} muted playsInline />
+    ) : (
+      <img src={item.previewUrl} alt={item.name} loading="lazy" />
+    );
+  }
+
+  return (
+    <span className="wb-composer__ref-icon">
+      {item.kind === "audio" ? <SoundOutlined /> : <FileTextOutlined />}
+      {label ? <span>{label}</span> : null}
+    </span>
+  );
+}
+
+export function PromptPreviewLayer({
+  text,
+  items,
+  onTokenPointerDown,
+}: {
+  text: string;
+  items: PromptMentionItem[];
+  onTokenPointerDown?: (index: number) => void;
+}) {
+  const nodes = renderPromptPreviewNodes(text, items);
+  if (nodes.length === 0) return null;
+
+  return (
+    <div
+      className="wb-composer__highlight"
+      aria-hidden="true"
+      onPointerDown={(event) => {
+        const target =
+          event.target instanceof Element
+            ? event.target.closest<HTMLElement>(".wb-composer__mention-inline-chip")
+            : null;
+        if (!target) return;
+
+        event.preventDefault();
+        event.stopPropagation();
+        const tokenEnd = Number(target.dataset.tokenEnd);
+        if (Number.isFinite(tokenEnd)) {
+          onTokenPointerDown?.(tokenEnd);
+        }
+      }}
+    >
+      {nodes}
+    </div>
+  );
+}
@@ -0,0 +1,264 @@
+import { DownOutlined } from "@ant-design/icons";
+import type { ReactNode } from "react";
+import type { WorkbenchOption, WorkbenchFieldGroup } from "./workbenchConstants";
+import { getRatioOptionClassName, getSettingsGridColumnsClassName } from "./workbenchReferenceUtils";
+
+export function SelectChip({
+  chipId,
+  value,
+  options,
+  disabled,
+  isOpen,
+  onToggle,
+  onClose,
+  onChange,
+  ariaLabel,
+  direction = "up",
+}: {
+  chipId: string;
+  value: string;
+  options: WorkbenchOption[];
+  disabled?: boolean;
+  isOpen: boolean;
+  onToggle: () => void;
+  onClose: () => void;
+  onChange: (value: string) => void;
+  ariaLabel?: string;
+  direction?: "up" | "down";
+}) {
+  const activeOption = options.find((option) => option.value === value);
+
+  return (
+    <div
+      className={`ai-workbench-select-chip${chipId.endsWith("-model") ? " ai-workbench-select-chip--model" : ""}${disabled ? " is-disabled" : ""}${isOpen ? " is-open" : ""}`}
+    >
+      <button
+        type="button"
+        className="ai-workbench-select-chip__trigger"
+        onClick={onToggle}
+        disabled={disabled}
+        aria-label={ariaLabel}
+        aria-haspopup="listbox"
+        aria-expanded={isOpen}
+        aria-controls={`${chipId}-listbox`}
+      >
+        <span className="ai-workbench-select-chip__copy">
+          <span className="ai-workbench-select-chip__value">{activeOption?.label || value}</span>
+        </span>
+        <DownOutlined className="ai-workbench-select-chip__arrow" />
+      </button>
+
+      {isOpen ? (
+        <div
+          id={`${chipId}-listbox`}
+          className={`ai-workbench-select-chip__dropdown ai-workbench-select-chip__dropdown--${direction} is-open`}
+          role="listbox"
+        >
+          {options.map((option, index) => {
+            const active = option.value === value;
+            return (
+              <button
+                key={option.value}
+                type="button"
+                role="option"
+                aria-selected={active}
+                className={`ai-workbench-select-chip__option${active ? " is-active" : ""}`}
+                style={{ transitionDelay: `${index * 18}ms` }}
+                onClick={() => {
+                  onChange(option.value);
+                  onClose();
+                }}
+              >
+                <span className="ai-workbench-select-chip__option-label">
+                  <span className="ai-workbench-select-chip__option-dot" aria-hidden="true" />
+                  <span className="ai-workbench-select-chip__option-copy">
+                    <span className="ai-workbench-select-chip__option-title">
+                      <span>{option.label}</span>
+                      {option.badge ? (
+                        <span className="ai-workbench-select-chip__option-badge">{option.badge}</span>
+                      ) : null}
+                    </span>
+                    {option.description ? (
+                      <span className="ai-workbench-select-chip__option-desc">{option.description}</span>
+                    ) : null}
+                  </span>
+                </span>
+              </button>
+            );
+          })}
+        </div>
+      ) : null}
+    </div>
+  );
+}
+
+export function CompoundSelectChip({
+  chipId,
+  summary,
+  groups,
+  disabled,
+  isOpen,
+  onToggle,
+  direction = "up",
+}: {
+  chipId: string;
+  summary: string;
+  groups: WorkbenchFieldGroup[];
+  disabled?: boolean;
+  isOpen: boolean;
+  onToggle: () => void;
+  direction?: "up" | "down";
+}) {
+  return (
+    <div
+      className={`ai-workbench-select-chip ai-workbench-select-chip--compound${disabled ? " is-disabled" : ""}${isOpen ? " is-open" : ""}`}
+    >
+      <button
+        type="button"
+        className="ai-workbench-select-chip__trigger"
+        onClick={onToggle}
+        disabled={disabled}
+        aria-haspopup="dialog"
+        aria-expanded={isOpen}
+        aria-controls={`${chipId}-panel`}
+      >
+        <span className="ai-workbench-select-chip__copy">
+          <span className="ai-workbench-select-chip__value">{summary}</span>
+        </span>
+        <DownOutlined className="ai-workbench-select-chip__arrow" />
+      </button>
+
+      {isOpen ? (
+        <div
+          id={`${chipId}-panel`}
+          className={`ai-workbench-select-chip__dropdown ai-workbench-select-chip__dropdown--compound ai-workbench-select-chip__dropdown--${direction} is-open`}
+          role="dialog"
+        >
+          <div className="ai-workbench-settings-panel">
+            {groups.map((group) => {
+              const currentLabel =
+                group.options.find((option) => option.value === group.value)?.label || group.value;
+              const fieldKey = `${group.kind || "pill"}-${group.label}`;
+
+              return (
+                <div
+                  key={fieldKey}
+                  className={`ai-workbench-settings-panel__field ai-workbench-settings-panel__field--${group.kind || "pill"}`}
+                >
+                  <div className="ai-workbench-settings-panel__head">
+                    <div className="ai-workbench-settings-panel__title-wrap">
+                      {group.icon ? (
+                        <span className="ai-workbench-settings-panel__title-icon">{group.icon}</span>
+                      ) : null}
+                      <div className="ai-workbench-settings-panel__title-copy">
+                        <div className="ai-workbench-settings-panel__title">{group.label}</div>
+                      </div>
+                    </div>
+                    <span className="ai-workbench-settings-panel__current">{currentLabel}</span>
+                  </div>
+
+                  <fieldset
+                    className={`ai-workbench-settings-panel__grid ai-workbench-settings-panel__grid--${group.kind || "pill"} ${getSettingsGridColumnsClassName(group.columns || 3)}`}
+                  >
+                    <legend className="ai-workbench-visually-hidden">{group.label}</legend>
+                    {group.options.map((option) => {
+                      const active = option.value === group.value;
+                      return (
+                        <button
+                          key={`${fieldKey}-${option.value}`}
+                          type="button"
+                          aria-pressed={active}
+                          className={`ai-workbench-settings-panel__option ai-workbench-settings-panel__option--${group.kind || "pill"}${active ? " is-active" : ""}`}
+                          onClick={() => group.onChange(option.value)}
+                        >
+                          {group.kind === "ratio" ? (
+                            <span className="ai-workbench-ratio-option">
+                              <span
+                                className={`ai-workbench-ratio-option__preview ${getRatioOptionClassName(option.value)}`}
+                              >
+                                <span className="ai-workbench-ratio-option__frame" />
+                              </span>
+                              <span className="ai-workbench-ratio-option__label">{option.label}</span>
+                            </span>
+                          ) : (
+                            <span>{option.label}</span>
+                          )}
+                        </button>
+                      );
+                    })}
+                  </fieldset>
+                </div>
+              );
+            })}
+          </div>
+        </div>
+      ) : null}
+    </div>
+  );
+}
+
+export function InlineOptionChip({
+  chipId,
+  value,
+  options,
+  icon,
+  disabled,
+  isOpen,
+  onToggle,
+  onClose,
+  onChange,
+  direction = "up",
+}: {
+  chipId: string;
+  value: string;
+  options: WorkbenchOption[];
+  icon?: ReactNode;
+  disabled?: boolean;
+  isOpen: boolean;
+  onToggle: () => void;
+  onClose: () => void;
+  onChange: (value: string) => void;
+  direction?: "up" | "down";
+}) {
+  const activeOption = options.find((option) => option.value === value);
+
+  return (
+    <div className={`wb-inline-chip${isOpen ? " is-open" : ""}${disabled ? " is-disabled" : ""}`}>
+      <button
+        type="button"
+        className="wb-inline-chip__trigger"
+        onClick={onToggle}
+        disabled={disabled}
+        aria-haspopup="listbox"
+        aria-expanded={isOpen}
+        aria-controls={`${chipId}-listbox`}
+      >
+        {icon ? <span className="wb-inline-chip__icon">{icon}</span> : null}
+        <span>{activeOption?.label || value}</span>
+      </button>
+      {isOpen ? (
+        <div id={`${chipId}-listbox`} className={`wb-inline-chip__menu wb-inline-chip__menu--${direction}`} role="listbox">
+          {options.map((option) => {
+            const active = option.value === value;
+            return (
+              <button
+                key={option.value}
+                type="button"
+                role="option"
+                aria-selected={active}
+                className={`wb-inline-chip__option${active ? " is-active" : ""}`}
+                onClick={() => {
+                  onChange(option.value);
+                  onClose();
+                }}
+              >
+                <span>{option.label}</span>
+                {active ? <span className="wb-inline-chip__check">✓</span> : null}
+              </button>
+            );
+          })}
+        </div>
+      ) : null}
+    </div>
+  );
+}
@@ -0,0 +1,404 @@
+import { isServerRequestError } from "../../api/serverConnection";
+import { ENTERPRISE_VIDEO_MODEL_OPTIONS } from "../../utils/enterpriseVideoPolicy";
+import type { WebGenerationPreviewTask } from "../../types";
+import type { ReactNode } from "react";
+
+export type WorkbenchMode = "chat" | "image" | "video";
+export type ToolbarMenuId =
+  | "studio-mode"
+  | "image-model"
+  | "image-settings"
+  | "image-grid-mode"
+  | "video-model"
+  | "video-mode"
+  | "video-ratio"
+  | "video-duration"
+  | "video-quality"
+  | null;
+export type ReferenceKind = "image" | "video" | "audio" | "file";
+
+export interface WorkbenchOption {
+  value: string;
+  label: string;
+  description?: string;
+  badge?: string;
+}
+
+export interface WorkbenchFieldGroup {
+  label: string;
+  value: string;
+  options: WorkbenchOption[];
+  onChange: (value: string) => void;
+  kind?: "ratio" | "pill";
+  columns?: 2 | 3 | 4;
+  icon?: ReactNode;
+}
+
+export interface ReferenceItem {
+  id: string;
+  kind: ReferenceKind;
+  name: string;
+  previewUrl?: string;
+  file?: File;
+  remoteUrl?: string;
+  token: string;
+  fingerprint?: string;
+  originalSize?: number;
+  compressed?: boolean;
+}
+
+export type PromptMentionItem = Pick<ReferenceItem, "token" | "id" | "name" | "kind" | "previewUrl" | "remoteUrl">;
+
+export interface PromptMentionTokenRange {
+  start: number;
+  end: number;
+  item: PromptMentionItem;
+}
+
+export interface ChatAttachment {
+  kind: ReferenceKind;
+  name: string;
+  token: string;
+  previewUrl?: string;
+  remoteUrl?: string;
+}
+
+export interface ChatMessage {
+  id: string;
+  role: "user" | "assistant";
+  author: string;
+  mode: WorkbenchMode;
+  body: string;
+  prompt?: string;
+  createdAt: string;
+  status?: "thinking" | "queued" | "completed" | "failed";
+  taskId?: string;
+  conversationId?: number;
+  taskProgress?: number;
+  taskStatusLabel?: string;
+  attachments?: ChatAttachment[];
+  resultUrl?: string;
+  resultType?: "image" | "video";
+  resultOriginalUrl?: string;
+  resultOssKey?: string;
+  resultMimeType?: string;
+  result?: {
+    title: string;
+    summary: string;
+    specs: string[];
+  };
+}
+
+export interface DeleteDialogState {
+  projectId: string;
+  title: string;
+}
+
+export interface WorkbenchKeepaliveTask {
+  taskId: string;
+  conversationId: number;
+  assistantMessageId: string;
+  concurrencySlotId?: string;
+  operation?: "generation" | "video-super-resolution";
+  mode: "image" | "video";
+  modelLabel: string;
+  specs: string[];
+  referenceCount: number;
+  progress: number;
+  statusLabel: string;
+  startedAt: number;
+}
+
+export interface WorkbenchResultActionPayload {
+  title: string;
+  prompt: string;
+  resultUrl: string;
+  resultType: "image" | "video";
+  taskId?: string;
+  resultOriginalUrl?: string;
+  resultOssKey?: string;
+  resultMimeType?: string;
+}
+
+// ─── Constants ───────────────────────────────────────────────────────
+
+export const MESSAGE_STORAGE_KEY = "omniai-web-workbench-messages";
+export const ACTIVE_CONVERSATION_STORAGE_KEY = "omniai-web-workbench-active-conversation-id";
+export const PROMPT_HISTORY_STORAGE_KEY = "omniai-web-workbench-prompt-history";
+export const TASK_KEEPALIVE_STORAGE_KEY = "omniai-web-workbench-active-tasks";
+export const WORKBENCH_TASK_STALE_MS = 6 * 60 * 60 * 1000;
+export const WORKBENCH_TASK_MAX_POLL_FAILURES = 10;
+export const REFERENCE_IMAGE_COMPRESS_THRESHOLD = 10 * 1024 * 1024;
+export const REFERENCE_IMAGE_MAX_DIMENSION = 1920;
+export const REFERENCE_IMAGE_INITIAL_QUALITY = 0.84;
+export const REFERENCE_IMAGE_MIN_QUALITY = 0.62;
+export const CHAT_MODEL = "gemini-3.1-pro";
+
+export const CHAT_NATURAL_SYSTEM_PROMPT = [
+  "你是 OmniAI 的创作协作助手，像一个正在一起工作的同伴一样说话。",
+  `默认使用自然、简洁的中文，不要官腔，不要机械套话，不要频繁使用“首先、其次、最后”这种模板。`,
+  "先直接回应用户当前关心的点；需要拆解时，用短段落或少量要点，把下一步说清楚。",
+  `不说“作为一个 AI”，不做空泛总结，不编造不确定的信息。`,
+  "当用户在排查问题或调整页面时，优先给判断、原因和可执行的下一步。",
+].join("\n");
+
+export const CHAT_TURN_STYLE_REMINDER = [
+  "本轮回答继续保持像正常人协作的口吻：",
+  `不要以"好的，以下是""当然可以""根据你的需求"这类模板开头。`,
+  "能一句话说清就先一句话说清；需要展开时再分点。",
+  "少用宏大标题，多用具体判断和下一步动作。",
+].join("\n");
+
+export const NON_CONVERSATIONAL_ASSISTANT_TEXT = new Set([
+  "我先看一下上下文，马上接上。",
+  "我在整理，马上说清楚。",
+  "正在读取当前模式、模型、规格和参考素材，准备创建生成任务。",
+  "Task submitted, generating...",
+  "任务已提交，正在生成中...",
+  "AI 正在整理回答...",
+]);
+
+export const MODE_META: Record<
+  WorkbenchMode,
+  {
+    label: string;
+    menuLabel: string;
+    accent: string;
+    placeholder: string;
+    description: string;
+    subline: string;
+    taskType: WebGenerationPreviewTask["type"];
+  }
+> = {
+  chat: {
+    label: "OmniChat",
+    menuLabel: "对话模式",
+    accent: "#6be7ff",
+    placeholder: "把创意、脚本、素材要求或工作流目标发给我",
+    description: "直接对话、拆解需求、整理上下文，并把想法推进到可执行结果。",
+    subline: "适合连续协作、问答推演、脚本整理和工作流规划。",
+    taskType: "agent",
+  },
+  image: {
+    label: "图像生成",
+    menuLabel: "图像生成",
+    accent: "#00b1cc",
+    placeholder: "描述角色、场景、商品图、首帧或尾帧画面",
+    description: "在同一界面完成文生图、图生图、参考图管理和候选筛选。",
+    subline: "模型、比例、清晰度和多宫格保持在同一条工作链里。",
+    taskType: "image",
+  },
+  video: {
+    label: "视频生成",
+    menuLabel: "视频生成",
+    accent: "#2197ff",
+    placeholder: "描述成片目标、人物、场景、镜头运动、节奏、比例和时长",
+    description: "用统一工作台管理起始帧、动作描述、镜头节奏和视频输出。",
+    subline: "支持首尾帧、参考素材、比例、时长和画质等关键设置。",
+    taskType: "video",
+  },
+};
+
+export const MODE_OPTIONS: WorkbenchOption[] = (Object.keys(MODE_META) as WorkbenchMode[]).map((mode) => ({
+  value: mode,
+  label: MODE_META[mode].menuLabel,
+  description: MODE_META[mode].subline,
+}));
+
+export const IMAGE_MODEL_OPTIONS: WorkbenchOption[] = [
+  { value: "wan2.7-image-pro", label: "wan 2.7 Pro 4K · 0.20 积分" },
+  { value: "wan2.7-image", label: "wan 2.7 · 0.20 积分" },
+  { value: "gpt-image-2", label: "GPT-Image-2 · 0.20 积分" },
+  { value: "gpt-image-2-vip", label: "GPT-Image-2 VIP · 0.20 积分" },
+  { value: "nano-banana-pro", label: "Nano Banana Pro · 0.20 积分" },
+  { value: "nano-banana-2", label: "Nano Banana 2 · 0.20 积分" },
+  { value: "nano-banana-fast", label: "Nano Banana · 0.20 积分" },
+];
+
+export const VIDEO_MODEL_OPTIONS: WorkbenchOption[] = ENTERPRISE_VIDEO_MODEL_OPTIONS.map((option) => ({ ...option }));
+export const RATIO_OPTIONS: WorkbenchOption[] = [
+  { value: "21:9", label: "21:9" },
+  { value: "16:9", label: "16:9" },
+  { value: "4:3", label: "4:3" },
+  { value: "1:1", label: "1:1" },
+  { value: "3:4", label: "3:4" },
+  { value: "9:16", label: "9:16" },
+];
+
+export const GRID_MODE_OPTIONS: WorkbenchOption[] = [
+  { value: "single", label: "单图" },
+  { value: "grid-4", label: "4 宫格" },
+  { value: "grid-9", label: "9 宫格" },
+  { value: "grid-25", label: "25 宫格" },
+];
+
+export const VIDEO_FRAME_OPTIONS: WorkbenchOption[] = [
+  { value: "omni", label: "全能参考" },
+  { value: "start-end", label: "首尾帧" },
+];
+
+export const VIDEO_DURATION_OPTIONS: WorkbenchOption[] = [
+  { value: "4", label: "4s" },
+  { value: "5", label: "5s" },
+  { value: "6", label: "6s" },
+  { value: "7", label: "7s" },
+  { value: "8", label: "8s" },
+  { value: "9", label: "9s" },
+  { value: "10", label: "10s" },
+  { value: "11", label: "11s" },
+  { value: "12", label: "12s" },
+  { value: "13", label: "13s" },
+  { value: "14", label: "14s" },
+  { value: "15", label: "15s" },
+];
+
+// ─── Shared helpers ──────────────────────────────────────────────────
+
+export function getCachedRole(): string {
+  try {
+    const raw = window.localStorage.getItem("omniai-web-session");
+    if (!raw) return "";
+    return String(JSON.parse(raw)?.user?.role || "").trim().toLowerCase();
+  } catch { return ""; }
+}
+
+export function getSessionUserId(): string {
+  try {
+    const raw = window.localStorage.getItem("omniai-web-session");
+    if (!raw) return "anon";
+    const id = JSON.parse(raw)?.user?.id;
+    return id ? String(id) : "anon";
+  } catch { return "anon"; }
+}
+
+export function userKey(base: string): string {
+  return `${base}:${getSessionUserId()}`;
+}
+
+export function createId(prefix: string) {
+  return `${prefix}-${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
+}
+
+export function formatWorkbenchTimestamp(date = new Date()): string {
+  const year = date.getFullYear();
+  const month = String(date.getMonth() + 1).padStart(2, "0");
+  const day = String(date.getDate()).padStart(2, "0");
+  const hours = String(date.getHours()).padStart(2, "0");
+  const minutes = String(date.getMinutes()).padStart(2, "0");
+  return `${year}-${month}-${day} ${hours}:${minutes}`;
+}
+
+export function parseWorkbenchTimestampValue(value: string): number {
+  const matched = value.match(/^(\d{4})-(\d{2})-(\d{2})\s+(\d{2}):(\d{2})/);
+  if (matched) {
+    const [, year, month, day, hours, minutes] = matched;
+    return new Date(Number(year), Number(month) - 1, Number(day), Number(hours), Number(minutes)).getTime();
+  }
+  const parsed = Date.parse(value);
+  return Number.isFinite(parsed) ? parsed : NaN;
+}
+
+export function buildChatAttachments(items: ReferenceItem[]): ChatAttachment[] {
+  return items.map((item) => ({
+    kind: item.kind,
+    name: item.name,
+    token: item.token,
+    previewUrl: item.remoteUrl || item.previewUrl,
+    remoteUrl: item.remoteUrl,
+  }));
+}
+
+export function buildNaturalChatHistoryMessages(messages: ChatMessage[]): Array<{ role: "user" | "assistant"; content: string }> {
+  return messages
+    .filter((message) => {
+      const body = message.body.trim();
+      if (!body) return false;
+      if (message.role === "user") return true;
+      if (message.mode !== "chat") return false;
+      if (message.status === "thinking" || message.status === "queued") return false;
+      if (NON_CONVERSATIONAL_ASSISTANT_TEXT.has(body)) return false;
+      return true;
+    })
+    .slice(-10)
+    .map((message) => ({
+      role: message.role,
+      content: message.body.trim(),
+    }));
+}
+
+export function getErrorText(error: unknown): string {
+  return error instanceof Error ? error.message : String(error || "Unknown error");
+}
+
+export function isAuthFailure(error: unknown): boolean {
+  return isServerRequestError(error) && (error.status === 401 || error.status === 403);
+}
+
+export function isInsufficientBalance(error: unknown): boolean {
+  if (isServerRequestError(error) && error.status === 402) return true;
+  const msg = error instanceof Error ? error.message : String(error || "");
+  return /余额不足|积分不足|insufficient.?balance/i.test(msg);
+}
+
+export function isInsufficientBalanceMessage(msg: string | undefined | null): boolean {
+  if (!msg) return false;
+  return /余额不足|积分不足|insufficient.?balance/i.test(msg);
+}
+
+export function isTransientMessage(message: ChatMessage): boolean {
+  return (message.status === "thinking" || message.status === "queued") && !message.taskId;
+}
+
+export function getPersistableMessages(messages: ChatMessage[]): ChatMessage[] {
+  return messages.filter((message, index) => {
+    if (isTransientMessage(message)) return false;
+    if (message.role === "assistant") return true;
+    const nextMessage = messages[index + 1];
+    return (
+      nextMessage?.role === "assistant" &&
+      nextMessage.conversationId === message.conversationId &&
+      !isTransientMessage(nextMessage)
+    );
+  });
+}
+
+export function shouldPersistPatch(patch: Partial<ChatMessage>): boolean {
+  return (
+    patch.status === "completed" ||
+    patch.status === "failed" ||
+    typeof patch.taskId === "string" ||
+    typeof patch.resultUrl === "string" ||
+    typeof patch.resultOssKey === "string" ||
+    typeof patch.resultOriginalUrl === "string" ||
+    typeof patch.resultMimeType === "string"
+  );
+}
+
+export function buildAssistantResult(
+  mode: WorkbenchMode,
+  model: string,
+  specs: string[],
+  referenceCount: number,
+): ChatMessage["result"] {
+  if (mode === "image") {
+    return {
+      title: "图像任务已创建",
+      summary: referenceCount > 0 ? "已携带参考图，后续结果会进入资产库和画布。" : "已按当前模型和规格进入图像生成流程。",
+      specs,
+    };
+  }
+
+  if (mode === "video") {
+    return {
+      title: "视频任务已创建",
+      summary: referenceCount > 0 ? "已携带参考素材，生成后可继续拆分镜头并发布案例。" : "已按当前镜头设置进入视频生成流程。",
+      specs,
+    };
+  }
+
+  return {
+    title: "Agent 已接管",
+    summary: "我会把当前输入整理成脚本、分镜、素材需求和可复制的工作流节点。",
+    specs: [model, ...specs],
+  };
+}
@@ -0,0 +1,80 @@
+import type { ReactNode } from "react";
+import type { PromptMentionItem, PromptMentionTokenRange } from "./workbenchConstants";
+
+export function escapeRegExp(value: string) {
+  return value.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
+}
+
+export function normalizePromptWhitespace(value: string) {
+  return value.replace(/[ \t]{2,}/g, " ").trim();
+}
+
+export function removePromptMentionTokenFromText(text: string, token: string) {
+  if (!token) return text;
+  const escapedToken = escapeRegExp(token);
+  return normalizePromptWhitespace(
+    text.replace(new RegExp(`(^|\\s)${escapedToken}(?=\\s|$)`, "g"), " "),
+  );
+}
+
+export function removePromptTextRange(text: string, start: number, end: number) {
+  return normalizePromptWhitespace(`${text.slice(0, start)}${text.slice(end)}`);
+}
+
+export function getPromptMentionTokenRanges(text: string, items: PromptMentionItem[]): PromptMentionTokenRange[] {
+  if (!text || !items.length) return [];
+  const ranges: PromptMentionTokenRange[] = [];
+  for (const item of items) {
+    const idx = text.indexOf(item.token);
+    if (idx >= 0) {
+      ranges.push({ start: idx, end: idx + item.token.length, item });
+    }
+  }
+  return ranges.sort((a, b) => a.start - b.start);
+}
+
+export function renderPromptPreviewNodes(
+  text: string,
+  items: PromptMentionItem[],
+): ReactNode[] {
+  if (!text) return [];
+
+  const tokens = Array.from(new Set(items.map((item) => item.token))).sort((a, b) => b.length - a.length);
+  const tokenMap = new Map(items.map((item) => [item.token, item]));
+  const nodes: ReactNode[] = [];
+  let cursor = 0;
+  let index = 0;
+
+  while (cursor < text.length) {
+    const matchedToken = tokens.find((token) => text.startsWith(token, cursor));
+
+    if (matchedToken) {
+      const matchedItem = tokenMap.get(matchedToken);
+      if (matchedItem) {
+        nodes.push(
+          <span key={`mention-${index}`} className="wb-prompt-mention-chip" data-token={matchedItem.token}>
+            {matchedItem.token}
+          </span>,
+        );
+        cursor += matchedToken.length;
+        index += 1;
+        continue;
+      }
+    }
+
+    const nextTokenStart = tokens.reduce((closest, token) => {
+      const pos = text.indexOf(token, cursor + 1);
+      return pos >= 0 && (closest < 0 || pos < closest) ? pos : closest;
+    }, -1);
+
+    const end = nextTokenStart >= 0 ? nextTokenStart : text.length;
+    const segment = text.slice(cursor, end);
+    if (segment) {
+      nodes.push(<span key={`text-${index}`}>{segment}</span>);
+      index += 1;
+    }
+    cursor = end;
+  }
+
+  return nodes;
+}
@@ -0,0 +1,211 @@
+import {
+  REFERENCE_IMAGE_COMPRESS_THRESHOLD,
+  REFERENCE_IMAGE_MAX_DIMENSION,
+  REFERENCE_IMAGE_INITIAL_QUALITY,
+  REFERENCE_IMAGE_MIN_QUALITY,
+  type WorkbenchMode,
+  type ReferenceKind,
+  type ReferenceItem,
+  type WorkbenchOption,
+} from "./workbenchConstants";
+import { resolvePreUploadedUrl } from "../../api/referenceUploadService";
+
+export function getRatioOptionClassName(value: string) {
+  return `ai-workbench-ratio-option__preview--${value.replace(":", "-")}`;
+}
+
+export function getSettingsGridColumnsClassName(columns: 2 | 3 | 4 = 3) {
+  return `ai-workbench-settings-panel__grid--cols-${columns}`;
+}
+
+export function getReferenceAccept(mode: WorkbenchMode, videoFrameMode?: string) {
+  if (mode === "chat") return ".docx,.txt,.md,.xlsx,.xls,.png,.jpg,.jpeg,.gif,.webp";
+  if (mode === "image") return "image/*";
+  if (videoFrameMode === "start-end") return "image/*";
+  return "image/*,video/mp4,video/quicktime,video/webm,video/x-msvideo,.mp4,.mov,.webm,.avi,audio/mpeg,audio/mp3,audio/wav,audio/x-wav,.mp3,.wav";
+}
+
+export function getReferenceUploadLabel(mode: WorkbenchMode) {
+  if (mode === "video") return "参考内容";
+  if (mode === "image") return "参考图";
+  return "附件";
+}
+
+export function getReferenceLimit(mode: WorkbenchMode, videoFrameMode?: string) {
+  if (mode === "video" && videoFrameMode === "start-end") return 2;
+  if (mode === "video") return 12;
+  if (mode === "image") return 9;
+  return 4;
+}
+
+export function getReferenceKindLabel(kind: ReferenceKind) {
+  if (kind === "image") return "图片";
+  if (kind === "video") return "视频";
+  if (kind === "audio") return "音频";
+  return "附件";
+}
+
+export function getReferenceEmptyCopy(mode: WorkbenchMode) {
+  if (mode === "video") return "上传最多12个参考素材，首尾帧模式仅保留2张图片，输入文字或 @ 引用内容，自由组合图、文、音、视频多元素";
+  if (mode === "image") return "最多上传9张参考图，输入文字或 @ 引用内容，控制角色、风格和构图";
+  return "上传附件后可用 @ 引用，帮助 Agent 读取上下文";
+}
+
+export function hexToRgbTriplet(hex: string) {
+  const normalized = hex.replace("#", "");
+  const full = normalized.length === 3
+    ? normalized
+        .split("")
+        .map((char) => `${char}${char}`)
+        .join("")
+    : normalized;
+
+  const value = Number.parseInt(full, 16);
+  const r = (value >> 16) & 255;
+  const g = (value >> 8) & 255;
+  const b = value & 255;
+  return `${r}, ${g}, ${b}`;
+}
+
+export function inferReferenceKind(file: File, mode: WorkbenchMode): ReferenceKind {
+  if (file.type.startsWith("image/")) return "image";
+  if (file.type.startsWith("video/")) return "video";
+  if (file.type.startsWith("audio/")) return "audio";
+  return mode === "chat" ? "file" : "image";
+}
+
+export function disposeReferencePreview(item: Pick<ReferenceItem, "previewUrl">) {
+  if (item.previewUrl) URL.revokeObjectURL(item.previewUrl);
+}
+
+export function fileToDataUrl(file: File) {
+  return new Promise<string>((resolve, reject) => {
+    const reader = new FileReader();
+    reader.onload = () => {
+      typeof reader.result === "string" ? resolve(reader.result) : reject(new Error("Unable to read reference file"));
+    };
+    reader.onerror = () => reject(reader.error || new Error("Unable to read reference file"));
+    reader.readAsDataURL(file);
+  });
+}
+
+export function bytesToHex(buffer: ArrayBuffer) {
+  return Array.from(new Uint8Array(buffer))
+    .map((byte) => byte.toString(16).padStart(2, "0"))
+    .join("");
+}
+
+export async function buildReferenceFingerprint(file: File, kind: ReferenceKind) {
+  if (kind === "image" && window.crypto?.subtle) {
+    const digest = await window.crypto.subtle.digest("SHA-256", await file.arrayBuffer());
+    return `image:${bytesToHex(digest)}`;
+  }
+  return `${kind}:${file.name}:${file.size}:${file.lastModified}:${file.type}`;
+}
+
+export function canCompressReferenceImage(file: File) {
+  return (
+    file.size > REFERENCE_IMAGE_COMPRESS_THRESHOLD &&
+    file.type.startsWith("image/") &&
+    !/svg|gif/i.test(file.type)
+  );
+}
+
+function canvasToBlob(canvas: HTMLCanvasElement, type: string, quality: number) {
+  return new Promise<Blob | null>((resolve) => {
+    canvas.toBlob(resolve, type, quality);
+  });
+}
+
+function getCompressedImageName(fileName: string) {
+  const baseName = fileName.replace(/\.[^.]+$/, "");
+  return `${baseName || "reference"}.jpg`;
+}
+
+export async function compressReferenceImageIfNeeded(file: File) {
+  if (!canCompressReferenceImage(file)) {
+    return { file, compressed: false };
+  }
+
+  try {
+    const bitmap = await createImageBitmap(file);
+    const scale = Math.min(1, REFERENCE_IMAGE_MAX_DIMENSION / Math.max(bitmap.width, bitmap.height));
+    let width = Math.max(1, Math.round(bitmap.width * scale));
+    let height = Math.max(1, Math.round(bitmap.height * scale));
+    const canvas = document.createElement("canvas");
+    const context = canvas.getContext("2d");
+    if (!context) {
+      bitmap.close();
+      return { file, compressed: false };
+    }
+
+    const render = () => {
+      canvas.width = width;
+      canvas.height = height;
+      context.fillStyle = "#ffffff";
+      context.fillRect(0, 0, width, height);
+      context.drawImage(bitmap, 0, 0, width, height);
+    };
+
+    const encode = async () => {
+      let quality = REFERENCE_IMAGE_INITIAL_QUALITY;
+      let nextBlob = await canvasToBlob(canvas, "image/jpeg", quality);
+      while (nextBlob && nextBlob.size > REFERENCE_IMAGE_COMPRESS_THRESHOLD && quality > REFERENCE_IMAGE_MIN_QUALITY) {
+        quality = Math.max(REFERENCE_IMAGE_MIN_QUALITY, quality - 0.08);
+        nextBlob = await canvasToBlob(canvas, "image/jpeg", quality);
+      }
+      return nextBlob;
+    };
+
+    render();
+    let blob = await encode();
+    while (blob && blob.size > REFERENCE_IMAGE_COMPRESS_THRESHOLD && Math.max(width, height) > 960) {
+      width = Math.max(1, Math.round(width * 0.82));
+      height = Math.max(1, Math.round(height * 0.82));
+      render();
+      blob = await encode();
+    }
+    bitmap.close();
+
+    if (!blob || blob.size >= file.size) {
+      return { file, compressed: false };
+    }
+
+    return {
+      file: new File([blob], getCompressedImageName(file.name), {
+        type: "image/jpeg",
+        lastModified: file.lastModified,
+      }),
+      compressed: true,
+    };
+  } catch {
+    return { file, compressed: false };
+  }
+}
+
+export function buildReferenceToken(kind: ReferenceKind, index: number) {
+  if (kind === "image") return `@图片${index}`;
+  if (kind === "video") return `@视频${index}`;
+  if (kind === "audio") return `@音频${index}`;
+  return `@附件${index}`;
+}
+
+export async function resolveReferenceUrls(items: ReferenceItem[]): Promise<string[]> {
+  const tasks = items.map(async (item) => {
+    if (item.remoteUrl) return item.remoteUrl;
+    if (!item.file) {
+      if (item.previewUrl && /^https?:\/\//i.test(item.previewUrl)) {
+        return item.previewUrl;
+      }
+      return null;
+    }
+    const url = await resolvePreUploadedUrl(item.file, item.name, item.fingerprint);
+    if (url) {
+      item.remoteUrl = url;
+      return url;
+    }
+    return null;
+  });
+  const results = await Promise.all(tasks);
+  return results.filter((url): url is string => url !== null);
+}
@@ -0,0 +1,173 @@
+import {
+  userKey,
+  MESSAGE_STORAGE_KEY,
+  ACTIVE_CONVERSATION_STORAGE_KEY,
+  PROMPT_HISTORY_STORAGE_KEY,
+  TASK_KEEPALIVE_STORAGE_KEY,
+  WORKBENCH_TASK_STALE_MS,
+  type ChatMessage,
+  type WorkbenchKeepaliveTask,
+} from "./workbenchConstants";
+import { parseWorkbenchTimestampValue } from "./workbenchConstants";
+
+export function readStoredMessages(): ChatMessage[] {
+  if (typeof window === "undefined") return [];
+  try {
+    const raw = window.localStorage.getItem(userKey(MESSAGE_STORAGE_KEY));
+    if (!raw) return [];
+    const parsed = JSON.parse(raw) as unknown;
+    if (!Array.isArray(parsed)) return [];
+    return parsed.filter((item): item is ChatMessage => {
+      if (!item || typeof item !== "object") return false;
+      const candidate = item as Partial<ChatMessage>;
+      return (
+        typeof candidate.id === "string" &&
+        (candidate.role === "user" || candidate.role === "assistant") &&
+        typeof candidate.body === "string"
+      );
+    });
+  } catch {
+    return [];
+  }
+}
+
+export function readStoredPromptHistory(): string[] {
+  if (typeof window === "undefined") return [];
+  try {
+    const raw = window.localStorage.getItem(userKey(PROMPT_HISTORY_STORAGE_KEY));
+    if (!raw) return [];
+    const parsed = JSON.parse(raw) as unknown;
+    return Array.isArray(parsed) ? parsed.filter((item): item is string => typeof item === "string") : [];
+  } catch {
+    return [];
+  }
+}
+
+export function readStoredActiveConversationId(messages: ChatMessage[] = []): number | null {
+  if (typeof window === "undefined") return null;
+  try {
+    const raw = window.localStorage.getItem(userKey(ACTIVE_CONVERSATION_STORAGE_KEY));
+    const value = raw ? Number(raw) : NaN;
+    if (Number.isFinite(value) && value > 0) return value;
+  } catch {
+    // Active conversation recovery is optional.
+  }
+  for (let index = messages.length - 1; index >= 0; index -= 1) {
+    const candidate = messages[index]?.conversationId;
+    if (typeof candidate === "number" && Number.isFinite(candidate) && candidate > 0) {
+      return candidate;
+    }
+  }
+  return null;
+}
+
+export function persistActiveConversationId(conversationId: number | null) {
+  if (typeof window === "undefined") return;
+  try {
+    if (conversationId && Number.isFinite(conversationId)) {
+      window.localStorage.setItem(userKey(ACTIVE_CONVERSATION_STORAGE_KEY), String(conversationId));
+    } else {
+      window.localStorage.removeItem(userKey(ACTIVE_CONVERSATION_STORAGE_KEY));
+    }
+  } catch {
+    // Local history is a convenience; generation still works without it.
+  }
+}
+
+export function persistMessages(messages: ChatMessage[]) {
+  try {
+    window.localStorage.setItem(userKey(MESSAGE_STORAGE_KEY), JSON.stringify(messages.slice(-60)));
+  } catch {
+    // Local history is a convenience; generation still works without it.
+  }
+}
+
+export function clearWorkbenchLocalState() {
+  if (typeof window === "undefined") return;
+  try {
+    window.localStorage.removeItem(userKey(MESSAGE_STORAGE_KEY));
+    window.localStorage.removeItem(userKey(ACTIVE_CONVERSATION_STORAGE_KEY));
+    window.localStorage.removeItem(userKey(TASK_KEEPALIVE_STORAGE_KEY));
+  } catch {
+    // Logout cleanup should never block the UI.
+  }
+}
+
+export function persistPromptHistory(history: string[]) {
+  try {
+    window.localStorage.setItem(userKey(PROMPT_HISTORY_STORAGE_KEY), JSON.stringify(history.slice(0, 20)));
+  } catch {
+    // Local history is optional.
+  }
+}
+
+// ─── Keepalive task persistence ──────────────────────────────────────
+
+export function buildRecoverableTaskFromMessage(conversationId: number, message: ChatMessage): WorkbenchKeepaliveTask | null {
+  if (message.role !== "assistant") return null;
+  if (!(message.status === "thinking" && message.taskId && message.mode !== "chat")) return null;
+  if (message.mode !== "image" && message.mode !== "video") return null;
+  if (Date.now() - parseWorkbenchTimestampValue(message.createdAt) > WORKBENCH_TASK_STALE_MS) return null;
+
+  const specs = message.result?.specs || [];
+  return {
+    taskId: message.taskId,
+    conversationId,
+    assistantMessageId: message.id,
+    operation: message.taskStatusLabel?.includes("超分") ? "video-super-resolution" : "generation",
+    mode: message.mode,
+    modelLabel: specs[0] || message.author || message.mode,
+    specs,
+    referenceCount: message.attachments?.length || 0,
+    progress: Math.max(10, Math.min(99, Number(message.taskProgress || 30))),
+    statusLabel: message.taskStatusLabel || "任务恢复中...",
+    startedAt: parseWorkbenchTimestampValue(message.createdAt) || Date.now(),
+  };
+}
+
+export function readStoredKeepaliveTasks(): Record<string, WorkbenchKeepaliveTask> {
+  if (typeof window === "undefined") return {};
+  try {
+    const raw = window.localStorage.getItem(userKey(TASK_KEEPALIVE_STORAGE_KEY));
+    if (!raw) return {};
+    const parsed = JSON.parse(raw) as unknown;
+    if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) return {};
+
+    const tasks: Record<string, WorkbenchKeepaliveTask> = {};
+    Object.values(parsed as Record<string, Partial<WorkbenchKeepaliveTask>>).forEach((task) => {
+      if (
+        task &&
+        typeof task.taskId === "string" &&
+        typeof task.conversationId === "number" &&
+        typeof task.assistantMessageId === "string" &&
+        (task.mode === "image" || task.mode === "video")
+      ) {
+        tasks[task.taskId] = {
+          taskId: task.taskId,
+          conversationId: task.conversationId,
+          assistantMessageId: task.assistantMessageId,
+          concurrencySlotId: typeof task.concurrencySlotId === "string" ? task.concurrencySlotId : undefined,
+          operation: task.operation === "video-super-resolution" ? "video-super-resolution" : "generation",
+          mode: task.mode,
+          modelLabel: task.modelLabel || task.mode,
+          specs: Array.isArray(task.specs) ? task.specs.filter((item): item is string => typeof item === "string") : [],
+          referenceCount: Number(task.referenceCount || 0),
+          progress: Number(task.progress || 0),
+          statusLabel: task.statusLabel || "Generating...",
+          startedAt: Number(task.startedAt || Date.now()),
+        };
+      }
+    });
+    return tasks;
+  } catch {
+    return {};
+  }
+}
+
+export function persistKeepaliveTasks(tasks: Record<string, WorkbenchKeepaliveTask>) {
+  try {
+    window.localStorage.setItem(userKey(TASK_KEEPALIVE_STORAGE_KEY), JSON.stringify(tasks));
+  } catch {
+    // Task restore is best-effort.
+  }
+}
@@ -148,37 +148,83 @@
  min-width: 0;
  min-height: 72px;
  padding: 0 28px;
-  border: 1px solid var(--border-subtle);
-  border-radius: 8px;
-  background: var(--bg-inset);
+  border: 1px solid rgba(255, 255, 255, 0.08);
+  border-radius: 12px;
+  background: linear-gradient(180deg, rgba(20, 23, 26, 0.72) 0%, rgba(15, 17, 19, 0.84) 100%);
+  backdrop-filter: blur(12px);
+  -webkit-backdrop-filter: blur(12px);
+  box-shadow:
+    0 1px 0 rgba(255, 255, 255, 0.04) inset,
+    0 2px 8px rgba(0, 0, 0, 0.28);
  color: var(--fg-body);
  cursor: pointer;
-  font-size: 17px;
-  font-weight: 850;
-  transition: border-color 160ms ease, background 160ms ease, color 160ms ease, transform 160ms ease;
+  font-size: 16px;
+  font-weight: 700;
+  letter-spacing: 0.03em;
+  transition:
+    border-color 240ms ease,
+    background 240ms ease,
+    color 240ms ease,
+    transform 240ms cubic-bezier(0.34, 1.2, 0.64, 1),
+    box-shadow 240ms ease;
 }

 .omni-home__entry .anticon {
-  font-size: 18px;
+  font-size: 19px;
+  transition: color 240ms ease, transform 240ms ease;
 }

 .omni-home__entry:hover {
-  border-color: var(--border-default);
-  background: var(--bg-hover);
+  border-color: rgba(255, 255, 255, 0.16);
+  background: linear-gradient(180deg, rgba(28, 32, 36, 0.78) 0%, rgba(18, 22, 25, 0.88) 100%);
+  box-shadow:
+    0 1px 0 rgba(255, 255, 255, 0.06) inset,
+    0 0 24px rgba(var(--accent-rgb), 0.06),
+    0 4px 16px rgba(0, 0, 0, 0.36);
  color: #ffffff;
-  transform: translateY(-1px);
+  transform: translateY(-2px);
+}
+
+.omni-home__entry:hover .anticon {
+  color: var(--accent);
+  transform: scale(1.08);
+}
+
+.omni-home__entry:active {
+  transform: translateY(0) scale(0.97);
+  box-shadow:
+    0 1px 0 rgba(255, 255, 255, 0.02) inset,
+    0 1px 4px rgba(0, 0, 0, 0.32);
+  transition-duration: 80ms;
 }

 .omni-home__entry--primary {
-  border-color: var(--accent);
-  background: var(--accent);
-  color: var(--dg-button-text, #061014);
+  border-color: rgba(var(--accent-rgb), 0.48);
+  background: linear-gradient(180deg, rgba(0, 255, 136, 0.22) 0%, rgba(0, 220, 118, 0.14) 100%), var(--accent);
+  box-shadow:
+    0 1px 0 rgba(255, 255, 255, 0.12) inset,
+    0 0 28px rgba(var(--accent-rgb), 0.18),
+    0 2px 12px rgba(0, 0, 0, 0.28);
+  color: #061014;
 }

 .omni-home__entry--primary:hover {
-  border-color: var(--accent-hover, var(--accent));
-  background: var(--accent-hover, var(--accent));
-  color: var(--dg-button-text, #061014);
+  border-color: rgba(var(--accent-rgb), 0.64);
+  background: linear-gradient(180deg, rgba(0, 255, 136, 0.28) 0%, rgba(0, 230, 124, 0.18) 100%), var(--accent-hover);
+  box-shadow:
+    0 1px 0 rgba(255, 255, 255, 0.16) inset,
+    0 0 40px rgba(var(--accent-rgb), 0.28),
+    0 6px 24px rgba(0, 0, 0, 0.36);
+  color: #061014;
+}
+
+.omni-home__entry--primary .anticon {
+  color: #061014;
+}
+
+.omni-home__entry--primary:hover .anticon {
+  color: #061014;
+  transform: scale(1.12);
 }

 .omni-home__carousel {
@@ -3400,6 +3400,7 @@
  width: 100%;
  height: 100%;
  min-height: 520px;
+  max-height: 520px;
  padding: 18px 22px;
  border: none;
  outline: none;
@@ -3409,6 +3410,7 @@
  font-size: 14px;
  line-height: 1.9;
  resize: none;
+  overflow-y: auto;
 }

 .script-eval-v4-text-input::placeholder {
@@ -4268,6 +4270,11 @@
 .script-eval-v4-text-shell,
 .script-eval-v4-text-input {
  min-height: calc(100vh - 422px);
+  max-height: calc(100vh - 422px);
+}
+
+.script-eval-v4-text-input {
+  overflow-y: auto;
 }

 .script-eval-v4-score-card {
@@ -22,7 +22,7 @@ export default defineConfig({
    host: "127.0.0.1",
  },
  esbuild: {
-    drop: ["console", "debugger"],
+    drop: ["debugger"],
  },
  build: {
    sourcemap: "hidden",
Author	SHA1	Message	Date
ludan	324ebf5ce5	feat: 优化首页入口按钮质感，提升商业产品精致度 - 按钮背景改为微渐变+毛玻璃效果(backdrop-filter) - 边框改为半透明白色，圆角从8px升级到12px - 增加内高光+外层深度阴影提升层次感 - 字间距、字重大小幅调整，更精致克制 - hover态增加accent光晕+图标变绿+放大效果 - 主按钮增加渐变绿底+内高光+绿色辉光阴影 - 增加按压态scale(0.97)反馈 - 主按钮图标hover放大1.12倍	2026-06-02 19:09:00 +08:00
ludan	9ababfda46	fix: 修复剧本评分文本框随内容无限下拉导致按钮被挤出视口 - textarea 增加 max-height 限制高度不随内容增长 - textarea 增加 overflow-y: auto 启用内部滚动 - text-shell 同步增加 max-height 约束	2026-06-02 18:18:00 +08:00
stringadmin	94080f30f7	Merge pull request 'feat: 升级剧本评分系统为 DeepSeek V4 多维评分体系' (#4 ) from feat/script-eval-deepseek-v4 into master Reviewed-on: #4	2026-06-02 09:03:11 +00:00
stringadmin	7d446dfc5f	Merge branch 'master' into feat/script-eval-deepseek-v4	2026-06-02 09:02:46 +00:00
stringadmin	d71437b09c	Merge pull request 'Fix/ecommerce 502 bug' (#3 ) from fix/ecommerce-502-bug into master Reviewed-on: #3	2026-06-02 09:01:38 +00:00
stringadmin	f1bfbf8608	Merge branch 'master' into fix/ecommerce-502-bug	2026-06-02 09:01:31 +00:00
stringadmin	94c1453c9b	fix: upload-binary Content-Type fix, 429/timeout retry, 120s timeout - Remove Content-Type: application/json from uploadAssetBinary FormData request - Add retryOnTransient for 429 + timeout + signal timed out errors - Increase AI chat timeout from 60s to 120s per call - Apply retry logic to both chat() and visionChat()	2026-06-02 16:58:59 +08:00
stringadmin	9504f8ee87	fix(ecommerce): replace base64 upload with binary blob in video service runVideoPlan was passing blob URLs as "dataUrl" to uploadAssetWithProgress, which sent them to /api/oss/upload (base64 path). Blob URLs don't match DATA_URL_PATTERN regex, causing corrupt 44-byte files on OSS. Now uses uploadAssetBinary (FormData multipart) via /api/oss/upload-binary, fetching blob → uploading binary directly, same as EcommercePage path. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>	2026-06-02 16:16:09 +08:00
ludan	d1b5d64bc8	feat: 升级剧本评分系统为 DeepSeek V4 多维评分体系变更内容： - scriptEvalClient: 替换系统提示词为 DeepSeek V4 完整版（六维评分细则、评分类别、评分铁律、等级标准），维度满分调整为 hook 20/plot 20/ character 18/dialogue 15/visual 15/content 12，总分算法改为直接累加，模型使用 qwen3.7-max，增加请求链路 console 日志 - ScriptTokensPage: 同步维度满分和描述（角色塑造 18、内容深度 12），增加页面挂载和评测流程的 console 日志 - vite.config: esbuild.drop 移除 "console"，保留 "debugger"，确保开发环境 console 日志正常输出	2026-06-02 16:04:26 +08:00
stringadmin	44c748b0dc	feat(ecommerce): use FormData binary upload instead of base64 dataUrl - Add uploadAssetBinary method to aiGenerationClient (FormData + busboy) - Replace base64 dataUrl upload in uploadProductImages with direct blob upload via /oss/upload-binary multipart endpoint - This eliminates the DATA_URL_PATTERN regex parsing bug that produced 44-byte corrupt files on OSS, causing DashScope "image format illegal" errors Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>	2026-06-02 16:03:50 +08:00
stringadmin	160552b45e	fix(ecommerce): 502 bug - vision model upgrade + MIME normalization + fallback - Upgrade VISION_MODEL to qwen3.7-plus (latest, confirmed working with image_url) - Add VISION_FALLBACK_MODEL = qwen-vl-plus for retry on "image format" errors - Normalize upload MIME types: unsupported formats (HEIC/AVIF) fall back to image/png to prevent server saving as .bin which DashScope can't read - Server-side: add image/avif, image/heic, image/heif to MIME_EXTENSIONS Root cause: DashScope returned "image format is illegal" when uploaded images had unrecognized MIME types → saved as .bin → DashScope couldn't decode. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>	2026-06-02 15:20:23 +08:00
stringadmin	c13bf800cc	Merge pull request 'fix: replace hardcoded local image paths with OSS URLs' (#2 ) from fix/remove-hardcoded-image-paths into master Reviewed-on: #2	2026-06-02 06:47:08 +00:00
stringadmin	16bf7bbdad	fix: replace hardcoded local image paths with OSS URLs Remove all local file imports referencing ../../../tu/ and ../../assets/ directories. Replace with OSS muban prefix URLs: https://stringtest.oss-cn-hangzhou.aliyuncs.com/muban/ This fixes build failure on server (missing local image files) and ensures images load from centralized OSS storage. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>	2026-06-02 14:34:55 +08:00
stringadmin	4b6f864aa9	Merge pull request 'refactor(workbench): extract types, constants, utils, sub-components from WorkbenchPage' (#1 ) from feature/workbench-refactor into master Reviewed-on: #1	2026-06-02 06:20:32 +00:00
stringadmin	59efc78c0e	refactor(workbench): extract types, constants, utils, sub-components from WorkbenchPage WorkbenchPage.tsx: 4146 → 3047 lines (-27%) Extracted to 6 sibling modules: - workbenchConstants.ts (403L): types, MODE_META, option arrays, shared helpers - workbenchStorage.ts (172L): localStorage read/write/persist functions - workbenchReferenceUtils.ts (210L): image compression, fingerprint, file helpers - workbenchMentionUtils.tsx (79L): prompt mention parsing and token rendering - WorkbenchPromptPreview.tsx (87L): ReferencePreview, PromptPreviewLayer components - WorkbenchSelectChips.tsx (263L): SelectChip, CompoundSelectChip, InlineOptionChip All extracted code is imported back via ES module imports — no logic changes. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>	2026-06-02 14:18:26 +08:00