Merge branch '108' of https://github.com/HBAI-Ltd/Toonflow-app into 108
# Conflicts: # src/types/database.d.ts
This commit is contained in:
ACT丶流星雨
commit
8e10813dc8
@ -14,7 +14,7 @@ const deriveAssetSchema = z.object({
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state: z.enum(["未生成", "生成中", "已完成", "生成失败"]).describe("衍生资产生成状态"),
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type: z.enum(["role", "tool", "scene", "clip"]).describe("衍生资产类型"),
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});
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const assetItemSchema = z.object({
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export const assetItemSchema = z.object({
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id: z.number().describe("资产唯一标识"),
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name: z.string().describe("资产名称"),
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type: z.enum(["role", "tool", "scene", "clip"]).describe("资产类型"),
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@ -100,18 +100,20 @@ export default (toolCpnfig: ToolConfig) => {
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id: z.number().nullable().describe("衍生资产ID,如果新增则为空"),
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name: z.string().describe("衍生资产名称"),
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desc: z.string().describe("衍生资产描述"),
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type: z.enum(["role", "tool", "scene", "clip"]).describe("衍生资产类型"),
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}),
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execute: async (deriveAsset) => {
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const thinking = msg.thinking("正在操作资产...");
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const { projectId, scriptId } = resTool.data;
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const startTime = Date.now();
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const parentAssets = await u.db("o_assets").where("id", deriveAsset.assetsId).select("id", "type").first();
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if (!parentAssets) return "关联的资产不存在";
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const data = {
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id: deriveAsset.id ?? undefined,
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assetsId: deriveAsset.assetsId,
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projectId,
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name: deriveAsset.name,
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type: deriveAsset.type,
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type: parentAssets.type,
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describe: deriveAsset.desc,
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startTime,
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};
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@ -155,25 +157,42 @@ export default (toolCpnfig: ToolConfig) => {
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}),
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execute: async ({ id }) => {
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const thinking = msg.thinking("正在生成衍生资产...");
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const res = await new Promise((resolve) => socket.emit("generateDeriveAsset", { id }, (res: any) => resolve(res)));
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thinking.appendText(`已生成衍生资产，ID: ${id}\n`);
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thinking.updateTitle("衍生资产生成完成");
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thinking.complete();
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return res ?? "生成失败";
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new Promise((resolve) => socket.emit("generateDeriveAsset", { id }, (res: any) => resolve(res)))
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.then((res) => {
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thinking.appendText(`已生成衍生资产，ID: ${JSON.stringify(res, null, 2)}\n`);
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thinking.updateTitle("衍生资产开始完成");
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thinking.complete();
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})
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.catch((e) => {
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thinking.appendText("衍生资产生成失败:\n" + u.error(e).message);
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thinking.updateTitle("衍生资产生成失败");
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thinking.complete();
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});
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return "开始生成衍生资产";
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},
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}),
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generate_storyboard: tool({
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description: "生成分镜图片",
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inputSchema: z.object({
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storyboardIds: z.array(z.number()).describe("分镜ID列表"),
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ids: z.array(z.number()).describe("分镜面板中需要更新的分镜 ID 列表,传入id仅作对应分镜更新用，不传入则全部生成"),
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}),
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execute: async ({ storyboardIds }) => {
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execute: async ({ ids }) => {
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console.log("%c Line:176 🍒 ids", "background:#ea7e5c", ids);
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const thinking = msg.thinking("正在生成分镜...");
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const res = await new Promise((resolve) => socket.emit("generateStoryboard", { storyboardIds }, (res: any) => resolve(res)));
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thinking.appendText("生成的分镜数据:\n" + JSON.stringify(res, null, 2));
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thinking.updateTitle("分镜生成完成");
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thinking.complete();
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return res;
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new Promise((resolve) => socket.emit("generateStoryboard", { ids }, (res: any) => resolve(res)))
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.then((res) => {
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thinking.appendText("生成的分镜数据:\n" + JSON.stringify(res, null, 2));
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thinking.updateTitle("分镜生成完成");
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thinking.complete();
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})
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.catch((e) => {
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thinking.appendText("分镜生成失败:\n" + u.error(e).message);
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thinking.updateTitle("分镜生成失败");
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thinking.complete();
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});
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return "开始生成分镜";
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},
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}),
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};
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@ -263,96 +263,95 @@ export default async (knex: Knex, forceInit: boolean = false): Promise<void> =>
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{
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name: "剧本资产提取",
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type: "scriptAssetExtraction",
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data: `
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---
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name: universal_agent
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description: 专注于从剧本内容中提取所使用的资产（角色、场景、道具）并生成结构化资产列表的助手。
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---
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# Script Assets Extract
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你是一个专业的剧本内容分析助手，专注于从剧本文本中识别和提取所有涉及的资产（角色、场景、道具），并为每项资产生成可供下游制作流程使用的结构化描述和提示词。
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## 何时使用
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用户提供剧本内容，你需要逐段阅读并提取其中涉及的所有资产（人物角色、场景地点、道具物件），输出为结构化的资产列表。产出的资产描述将用于后续 AI 图片生成和制作流程。
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## 与系统的对应关系
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- 资产类型：
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- \`role\` — 角色（对应 \`o_assets.type = "role"\`）
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- \`scene\` — 场景（对应 \`o_assets.type = "scene"\`）
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- \`tool\` — 道具（对应 \`o_assets.type = "tool"\`）
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- 下游用途：资产提示词生成 → AI 资产图生成 → 分镜制作
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## 输出要求
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**必须通过调用 \`resultTool\` 工具返回结果**，禁止以纯文本、Markdown 表格或 JSON 代码块等形式直接输出资产列表。
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\`resultTool\` 的 schema 会对字段类型和枚举值做强校验，调用时请严格按照下方字段定义填写，确保数据结构正确、字段完整、类型匹配。
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每个资产对象包含以下字段：
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| 字段 | 类型 | 必填 | 说明 |
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| ---- | ---- | ---- | ---- |
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| \`name\` | string | 是 | 资产名称，使用剧本中的原始称呼,不做其他多余描述 |
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| \`desc\` | string | 是 | 资产描述，30-80 字的视觉化描述 |
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| \`prompt\` | string | 是 | 生成提示词，英文，用于 AI 图片生成 |
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| \`type\` | enum | 是 | 资产类型：\`role\` / \`scene\` / \`tool\` |
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## 提取规则
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### 角色（role）
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- 提取剧本中出现的所有有名字的角色
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- \`desc\`：包含外貌特征、服饰风格、体态气质等视觉要素
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- \`prompt\`：英文提示词，描述角色的外观特征，适用于 AI 角色图生成
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- 同一角色有多个称呼时，取最常用的作为 \`name\`
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- 无名龙套（如"路人甲"、"士兵"）可跳过，除非其造型对剧情有重要视觉意义
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### 场景（scene）
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- 提取剧本中出现的所有场景/地点
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- \`desc\`：包含空间结构、光照氛围、关键陈设、色调基调等视觉要素
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- \`prompt\`：英文提示词，描述场景的整体视觉风格，适用于 AI 场景图生成
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- 同一场景的不同状态（如白天/夜晚）不重复提取，在 \`desc\` 中注明即可
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### 道具（tool）
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- 提取剧本中出现的重要道具/物品
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- \`desc\`：包含外观形状、颜色材质、尺寸参考、特殊效果等视觉要素
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- \`prompt\`：英文提示词，描述道具的外观细节，适用于 AI 道具图生成
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- 仅提取有独立视觉意义或剧情功能的道具，通用物品可跳过
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## 提示词（prompt）生成规范
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- 采用逗号分隔的关键词/短语格式
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- 优先描述**视觉特征**，避免抽象概念
|
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- 包含风格关键词（如 anime style, manga style 等，根据项目风格决定）
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- 角色 prompt 示例：\`a young man, sharp eyebrows, black hair, pale skin, wearing a gray Taoist robe, slender build, cold expression\`
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- 场景 prompt 示例：\`dark cave interior, glowing crystals on walls, misty atmosphere, dim blue lighting, stone altar in center\`
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- 道具 prompt 示例：\`ancient jade pendant, oval shape, translucent green, carved dragon pattern, glowing faintly\`
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## 提取流程
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1. 通读剧本全文，识别所有出现的角色、场景、道具
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2. 对每个资产生成结构化的 \`name\`、\`desc\`、\`prompt\`、\`type\`
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3. 去重：同一资产不重复提取
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4. **必须通过调用 \`resultTool\` 工具输出完整资产列表**，不要分多次调用，一次性将所有资产放入 \`assetsList\` 数组中提交
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|
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## 提取原则
|
||||
|
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1. **忠于剧本**：所有提取基于剧本中的实际内容，不臆造未出现的资产
|
||||
2. **视觉优先**：描述和提示词聚焦视觉特征，便于 AI 图片生成
|
||||
3. **精简实用**：只提取对制作有实际意义的资产，避免过度提取
|
||||
4. **分类准确**：严格按照 role/scene/tool 分类，不混淆
|
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5. **提示词质量**：英文提示词应具体、可执行，能直接用于 AI 图片生成
|
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|
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## 注意事项
|
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|
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- 资产列表中**不要包含剧本内容本身**，仅提取所使用到的资产
|
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- 角色的随身物品如果有独立剧情功能，应单独作为道具提取
|
||||
- 场景中的固定陈设不需要单独提取为道具，除非该物件有独立剧情作用
|
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data: `---
|
||||
name: universal_agent
|
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description: 专注于从剧本内容中提取所使用的资产（角色、场景、道具）并生成结构化资产列表的助手。
|
||||
---
|
||||
|
||||
# Script Assets Extract
|
||||
|
||||
你是一个专业的剧本内容分析助手，专注于从剧本文本中识别和提取所有涉及的资产（角色、场景、道具），并为每项资产生成可供下游制作流程使用的结构化描述和提示词。
|
||||
|
||||
## 何时使用
|
||||
|
||||
用户提供剧本内容，你需要逐段阅读并提取其中涉及的所有资产（人物角色、场景地点、道具物件），输出为结构化的资产列表。产出的资产描述将用于后续 AI 图片生成和制作流程。
|
||||
|
||||
## 与系统的对应关系
|
||||
|
||||
- 资产类型：
|
||||
- \`role\` — 角色（对应 \`o_assets.type = "role"\`）
|
||||
- \`scene\` — 场景（对应 \`o_assets.type = "scene"\`）
|
||||
- \`tool\` — 道具（对应 \`o_assets.type = "tool"\`）
|
||||
- 下游用途：资产提示词生成 → AI 资产图生成 → 分镜制作
|
||||
|
||||
## 输出要求
|
||||
|
||||
**必须通过调用 \`resultTool\` 工具返回结果**，禁止以纯文本、Markdown 表格或 JSON 代码块等形式直接输出资产列表。
|
||||
\`resultTool\` 的 schema 会对字段类型和枚举值做强校验，调用时请严格按照下方字段定义填写，确保数据结构正确、字段完整、类型匹配。
|
||||
|
||||
每个资产对象包含以下字段：
|
||||
|
||||
| 字段 | 类型 | 必填 | 说明 |
|
||||
| ---- | ---- | ---- | ---- |
|
||||
| \`name\` | string | 是 | 资产名称，使用剧本中的原始称呼,不做其他多余描述 |
|
||||
| \`desc\` | string | 是 | 资产描述，30-80 字的视觉化描述 |
|
||||
| \`prompt\` | string | 是 | 生成提示词，英文，用于 AI 图片生成 |
|
||||
| \`type\` | enum | 是 | 资产类型：\`role\` / \`scene\` / \`tool\` |
|
||||
|
||||
## 提取规则
|
||||
|
||||
### 角色（role）
|
||||
|
||||
- 提取剧本中出现的所有有名字的角色
|
||||
- \`desc\`：包含外貌特征、服饰风格、体态气质等视觉要素
|
||||
- \`prompt\`：英文提示词，描述角色的外观特征，适用于 AI 角色图生成
|
||||
- 同一角色有多个称呼时，取最常用的作为 \`name\`
|
||||
- 无名龙套（如"路人甲"、"士兵"）可跳过，除非其造型对剧情有重要视觉意义
|
||||
|
||||
### 场景（scene）
|
||||
|
||||
- 提取剧本中出现的所有场景/地点
|
||||
- \`desc\`：包含空间结构、光照氛围、关键陈设、色调基调等视觉要素
|
||||
- \`prompt\`：英文提示词，描述场景的整体视觉风格，适用于 AI 场景图生成
|
||||
- 同一场景的不同状态（如白天/夜晚）不重复提取，在 \`desc\` 中注明即可
|
||||
|
||||
### 道具（tool）
|
||||
|
||||
- 提取剧本中出现的重要道具/物品
|
||||
- \`desc\`：包含外观形状、颜色材质、尺寸参考、特殊效果等视觉要素
|
||||
- \`prompt\`：英文提示词，描述道具的外观细节，适用于 AI 道具图生成
|
||||
- 仅提取有独立视觉意义或剧情功能的道具，通用物品可跳过
|
||||
|
||||
|
||||
## 提示词（prompt）生成规范
|
||||
|
||||
- 采用逗号分隔的关键词/短语格式
|
||||
- 优先描述**视觉特征**，避免抽象概念
|
||||
- 包含风格关键词（如 anime style, manga style 等，根据项目风格决定）
|
||||
- 角色 prompt 示例：\`a young man, sharp eyebrows, black hair, pale skin, wearing a gray Taoist robe, slender build, cold expression\`
|
||||
- 场景 prompt 示例：\`dark cave interior, glowing crystals on walls, misty atmosphere, dim blue lighting, stone altar in center\`
|
||||
- 道具 prompt 示例：\`ancient jade pendant, oval shape, translucent green, carved dragon pattern, glowing faintly\`
|
||||
|
||||
## 提取流程
|
||||
|
||||
1. 通读剧本全文，识别所有出现的角色、场景、道具
|
||||
2. 对每个资产生成结构化的 \`name\`、\`desc\`、\`prompt\`、\`type\`
|
||||
3. 去重：同一资产不重复提取
|
||||
4. **必须通过调用 \`resultTool\` 工具输出完整资产列表**，不要分多次调用，一次性将所有资产放入 \`assetsList\` 数组中提交
|
||||
|
||||
## 提取原则
|
||||
|
||||
1. **忠于剧本**：所有提取基于剧本中的实际内容，不臆造未出现的资产
|
||||
2. **视觉优先**：描述和提示词聚焦视觉特征，便于 AI 图片生成
|
||||
3. **精简实用**：只提取对制作有实际意义的资产，避免过度提取
|
||||
4. **分类准确**：严格按照 role/scene/tool 分类，不混淆
|
||||
5. **提示词质量**：英文提示词应具体、可执行，能直接用于 AI 图片生成
|
||||
|
||||
## 注意事项
|
||||
|
||||
- 资产列表中**不要包含剧本内容本身**，仅提取所使用到的资产
|
||||
- 角色的随身物品如果有独立剧情功能，应单独作为道具提取
|
||||
- 场景中的固定陈设不需要单独提取为道具，除非该物件有独立剧情作用
|
||||
`,
|
||||
},
|
||||
]);
|
||||
@ -469,6 +468,7 @@ export default async (knex: Knex, forceInit: boolean = false): Promise<void> =>
|
||||
table.text("model");
|
||||
table.text("resolution");
|
||||
table.text("state");
|
||||
table.text("reason");
|
||||
table.primary(["id"]);
|
||||
table.unique(["id"]);
|
||||
},
|
||||
|
||||
@ -6,35 +6,37 @@ import { validateFields } from "@/middleware/middleware";
|
||||
const router = express.Router();
|
||||
|
||||
// 获取资产
|
||||
export default router.post("/",
|
||||
validateFields({
|
||||
projectId: z.number(),
|
||||
type: z.string(),
|
||||
name: z.string().optional(),
|
||||
page: z.number(),
|
||||
limit: z.number(),
|
||||
}),
|
||||
async (req, res) => {
|
||||
const { projectId, type, name, page = 1, limit = 10, } = req.body;
|
||||
const offset = (page - 1) * limit;
|
||||
let query = u.db("o_assets").select("*").where("projectId", projectId).andWhere("type", type);
|
||||
if (name) {
|
||||
query = query.andWhere("name", "like", `%${name}%`);
|
||||
}
|
||||
// 分页查询
|
||||
const parentAssets = await query.offset(offset).limit(limit);
|
||||
export default router.post(
|
||||
"/",
|
||||
validateFields({
|
||||
projectId: z.number(),
|
||||
type: z.string(),
|
||||
name: z.string().optional(),
|
||||
page: z.number(),
|
||||
limit: z.number(),
|
||||
}),
|
||||
async (req, res) => {
|
||||
const { projectId, type, name, page = 1, limit = 10 } = req.body;
|
||||
const offset = (page - 1) * limit;
|
||||
let query = u.db("o_assets").select("*").where("projectId", projectId).andWhere("type", type);
|
||||
if (name) {
|
||||
query = query.andWhere("name", "like", `%${name}%`);
|
||||
}
|
||||
// 分页查询
|
||||
const parentAssets = await query.offset(offset).limit(limit);
|
||||
|
||||
// 统计总数
|
||||
const totalQuery = (await u
|
||||
.db("o_assets")
|
||||
.where("projectId", projectId)
|
||||
.andWhere("type", type)
|
||||
.andWhere((qb) => {
|
||||
if (name) {
|
||||
qb.andWhere("name", "like", `%${name}%`);
|
||||
}
|
||||
})
|
||||
.count("* as total")
|
||||
.first()) as any;
|
||||
res.status(200).send(success({ data: parentAssets, total: totalQuery?.total }));
|
||||
});
|
||||
// 统计总数
|
||||
const totalQuery = (await u
|
||||
.db("o_assets")
|
||||
.where("projectId", projectId)
|
||||
.andWhere("type", type)
|
||||
.andWhere((qb) => {
|
||||
if (name) {
|
||||
qb.andWhere("name", "like", `%${name}%`);
|
||||
}
|
||||
})
|
||||
.count("* as total")
|
||||
.first()) as any;
|
||||
res.status(200).send(success({ data: parentAssets, total: totalQuery?.total }));
|
||||
},
|
||||
);
|
||||
|
||||
@ -110,16 +110,20 @@ export default router.post("/", validateFields(requestSchema), async (req, res)
|
||||
|
||||
try {
|
||||
const aiImage = u.Ai.Image(model);
|
||||
await aiImage.run({
|
||||
prompt: userPrompt,
|
||||
imageBase64: item.base64 ? [item.base64] : [],
|
||||
size: resolution,
|
||||
aspectRatio: "16:9",
|
||||
taskClass: cfg.taskClass,
|
||||
describe,
|
||||
projectId,
|
||||
relatedObjects: JSON.stringify(relatedObjects),
|
||||
});
|
||||
await aiImage.run(
|
||||
{
|
||||
prompt: userPrompt,
|
||||
imageBase64: item.base64 ? [item.base64] : [],
|
||||
size: resolution,
|
||||
aspectRatio: "16:9",
|
||||
},
|
||||
{
|
||||
taskClass: cfg.taskClass,
|
||||
describe,
|
||||
projectId,
|
||||
relatedObjects: JSON.stringify(relatedObjects),
|
||||
},
|
||||
);
|
||||
aiImage.save(imagePath);
|
||||
|
||||
const imageData = await u.db("o_image").where("id", imageId).select("*").first();
|
||||
|
||||
@ -98,16 +98,20 @@ export default router.post("/", validateFields(requestSchema), async (req, res)
|
||||
try {
|
||||
// 4. 调用 AI 生成图片
|
||||
const aiImage = u.Ai.Image(model);
|
||||
await aiImage.run({
|
||||
prompt: userPrompt,
|
||||
imageBase64: base64 ? [base64] : [],
|
||||
size: resolution,
|
||||
aspectRatio: "16:9",
|
||||
taskClass: cfg.taskClass,
|
||||
describe,
|
||||
projectId,
|
||||
relatedObjects: JSON.stringify(relatedObjects),
|
||||
});
|
||||
await aiImage.run(
|
||||
{
|
||||
prompt: userPrompt,
|
||||
imageBase64: base64 ? [base64] : [],
|
||||
size: resolution,
|
||||
aspectRatio: "16:9",
|
||||
},
|
||||
{
|
||||
taskClass: cfg.taskClass,
|
||||
describe,
|
||||
projectId,
|
||||
relatedObjects: JSON.stringify(relatedObjects),
|
||||
},
|
||||
);
|
||||
aiImage.save(imagePath);
|
||||
|
||||
// 5. 更新记录 & 返回结果
|
||||
|
||||
@ -5,6 +5,7 @@ import sharp from "sharp";
|
||||
import { success } from "@/lib/responseFormat";
|
||||
import { validateFields } from "@/middleware/middleware";
|
||||
import { Output } from "ai";
|
||||
import { urlToBase64 } from "@/utils/vm";
|
||||
const router = express.Router();
|
||||
|
||||
export default router.post(
|
||||
@ -19,7 +20,25 @@ export default router.post(
|
||||
|
||||
const projectSettingData = await u.db("o_project").where("id", projectId).select("imageModel", "imageQuality", "artStyle").first();
|
||||
|
||||
const assetsDataArr = await u.db("o_assets").whereIn("id", assetIds).select("id", "describe", "name", "type");
|
||||
const assetsDataArr = await u.db("o_assets").whereIn("id", assetIds).select("id", "describe", "name", "type", "assetsId");
|
||||
const parentIds = assetsDataArr.map((item) => item.assetsId).filter((id) => id !== null);
|
||||
const parentAssetsData = await u
|
||||
.db("o_assets")
|
||||
.leftJoin("o_image", "o_assets.imageId", "o_image.id")
|
||||
.whereIn("o_assets.id", parentIds as number[])
|
||||
.select("o_assets.id", "o_image.filePath");
|
||||
const assetsSrcArr = await Promise.all(
|
||||
parentAssetsData.map(async (item) => {
|
||||
return {
|
||||
src: await u.oss.getFileUrl(item.filePath),
|
||||
id: item.id,
|
||||
};
|
||||
}),
|
||||
);
|
||||
const imageUrlRecord: Record<number, string> = {};
|
||||
assetsSrcArr.forEach((item) => {
|
||||
imageUrlRecord[item.id] = item.src;
|
||||
});
|
||||
const rolePrompt = u.getArtPrompt(projectSettingData!.artStyle!, "art_character_derivative");
|
||||
const toolPrompt = u.getArtPrompt(projectSettingData!.artStyle!, "art_prop_derivative");
|
||||
const scenePrompt = u.getArtPrompt(projectSettingData!.artStyle!, "art_scene_derivative");
|
||||
@ -28,7 +47,7 @@ export default router.post(
|
||||
tool: toolPrompt,
|
||||
scene: scenePrompt,
|
||||
};
|
||||
|
||||
const imageData = [];
|
||||
for (const item of assetsDataArr) {
|
||||
const { text } = await u.Ai.Text("universalAi").invoke({
|
||||
system: `
|
||||
@ -54,26 +73,42 @@ export default router.post(
|
||||
resolution: projectSettingData?.imageQuality,
|
||||
model: projectSettingData?.imageModel,
|
||||
});
|
||||
u.Ai.Image(projectSettingData?.imageModel as `${string}:${string}`)
|
||||
.run({
|
||||
const imageBase64 = imageUrlRecord[item.assetsId!] ? await urlToBase64(imageUrlRecord[item.assetsId!]) : null;
|
||||
try {
|
||||
const imageCls = await u.Ai.Image(projectSettingData?.imageModel as `${string}:${string}`).run({
|
||||
prompt: text,
|
||||
imageBase64: [],
|
||||
imageBase64: imageBase64 ? [imageBase64] : [],
|
||||
size: projectSettingData?.imageQuality as "1K" | "2K" | "4K",
|
||||
aspectRatio: "16:9",
|
||||
taskClass: "生成图片",
|
||||
describe: "资产图片生成",
|
||||
relatedObjects: JSON.stringify(repeloadObj),
|
||||
projectId: projectId,
|
||||
})
|
||||
.then(async (imageCls) => {
|
||||
const savePath = `/${projectId}/assets/${scriptId}/${u.uuid()}.jpg`;
|
||||
await imageCls.save(savePath);
|
||||
// 更新对应数据库
|
||||
await u.db("o_assets").where("id", item.id).update({ imageId: imageId });
|
||||
await u.db("o_image").where({ id: imageId }).update({ state: "已完成", filePath: savePath });
|
||||
});
|
||||
const savePath = `/${projectId}/assets/${scriptId}/${u.uuid()}.jpg`;
|
||||
await imageCls.save(savePath);
|
||||
// 更新对应数据库
|
||||
await u.db("o_assets").where("id", item.id).update({ imageId: imageId });
|
||||
await u.db("o_image").where({ id: imageId }).update({ state: "已完成", filePath: savePath });
|
||||
imageData.push({
|
||||
id: item.id,
|
||||
state: "已完成",
|
||||
src: await u.oss.getFileUrl(savePath),
|
||||
});
|
||||
} catch (e) {
|
||||
console.log("%c Line:95 🥛 e", "background:#fca650", e);
|
||||
await u
|
||||
.db("o_image")
|
||||
.where({ id: imageId })
|
||||
.update({ state: "生成失败", reason: u.error(e).message });
|
||||
imageData.push({
|
||||
id: item.id,
|
||||
state: "生成失败",
|
||||
src: "",
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return res.status(200).send(success());
|
||||
return res.status(200).send(success(imageData));
|
||||
},
|
||||
);
|
||||
|
||||
@ -4,28 +4,137 @@ import { z } from "zod";
|
||||
import sharp from "sharp";
|
||||
import { success } from "@/lib/responseFormat";
|
||||
import { validateFields } from "@/middleware/middleware";
|
||||
import { Output } from "ai";
|
||||
import { Output, tool } from "ai";
|
||||
import { urlToBase64 } from "@/utils/vm";
|
||||
import { assetItemSchema } from "@/agents/productionAgent/tools";
|
||||
const router = express.Router();
|
||||
export type AssetData = z.infer<typeof assetItemSchema>;
|
||||
|
||||
export default router.post(
|
||||
"/",
|
||||
validateFields({
|
||||
storyboardIds: z.array(z.number()),
|
||||
storyboardIds: z.array(z.number()).optional(),
|
||||
projectId: z.number(),
|
||||
scriptId: z.number(),
|
||||
script: z.string(),
|
||||
scriptPlan: z.string(),
|
||||
storyboardTable: z.string(),
|
||||
assets: z.array(assetItemSchema),
|
||||
}),
|
||||
async (req, res) => {
|
||||
const { storyboardIds, projectId, scriptId } = req.body;
|
||||
const {
|
||||
storyboardIds,
|
||||
projectId,
|
||||
scriptId,
|
||||
script,
|
||||
scriptPlan,
|
||||
storyboardTable,
|
||||
assets,
|
||||
}: {
|
||||
storyboardIds: number[];
|
||||
projectId: number;
|
||||
scriptId: number;
|
||||
script: string;
|
||||
scriptPlan: string;
|
||||
storyboardTable: string;
|
||||
assets: AssetData[];
|
||||
} = req.body;
|
||||
// 当没有 storyboardIds 时，通过 AI 生成新的分镜面板数据
|
||||
let finalStoryboardIds: number[] = storyboardIds || [];
|
||||
if (!storyboardIds || storyboardIds.length === 0) {
|
||||
const createdIds: number[] = [];
|
||||
const resultTools = tool({
|
||||
description: "结果输出工具（必须调用）",
|
||||
inputSchema: z.object({
|
||||
items: z.array(
|
||||
z.object({
|
||||
title: z.string().describe("分镜名称"),
|
||||
description: z.string().describe("分镜详细描述"),
|
||||
relatedAssets: z.array(z.number()).describe("关联衍生资产id数组"),
|
||||
}),
|
||||
),
|
||||
}),
|
||||
execute: async (resData) => {
|
||||
console.log("%c Line:46 🌰 resData", "background:#93c0a4", resData.items);
|
||||
for (const item of resData.items) {
|
||||
const [id] = await u.db("o_storyboard").insert({
|
||||
title: item.title,
|
||||
description: item.description,
|
||||
scriptId: scriptId,
|
||||
});
|
||||
createdIds.push(id);
|
||||
if (item.relatedAssets.length === 0) continue;
|
||||
await u.db("o_assets2Storyboard").insert(item.relatedAssets.map((i) => ({ storyboardId: id, assetId: i })));
|
||||
console.log("%c Line:68 🍷 createdIds", "background:#33a5ff", createdIds);
|
||||
}
|
||||
return true;
|
||||
},
|
||||
});
|
||||
const { text } = await u.Ai.Text("universalAi").invoke({
|
||||
system: `
|
||||
你需要根据用户提供的剧本、分镜表、拍摄计划和资产列表，来生成一个分镜面板，内容结构为 [{title:"分镜名称",description:"分镜详细描述",relatedAssets:关联衍生资产id}]。
|
||||
你必须调用 resultTools 来输出结果，传入的参数需要包含 items 字段，items 是一个数组，每个元素包含 title（分镜名称）,description（分镜详细描述）,relatedAssets（关联衍生资产id数组）。请直接输出调用工具的代码，不要做任何多余的描述性文字，必须等待工具调用完成。调用工具后你本身的回复 请保持空白，不要添加任何内容。`,
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: `
|
||||
====== 剧本 ======
|
||||
${script}
|
||||
====== 分镜表 ======
|
||||
${storyboardTable}
|
||||
====== 拍摄计划 ======
|
||||
${scriptPlan}
|
||||
====== 资产列表 ======
|
||||
${assets.map((i) => i.derive.map((t) => `衍生资产名称:${t.name},衍生资产类型:${t.type},关联资产ID:${t.assetsId}`).join("\n")).join("\n")}
|
||||
`,
|
||||
},
|
||||
],
|
||||
tools: { resultTools },
|
||||
});
|
||||
console.log("%c Line:52 🍢 text", "background:#93c0a4", text);
|
||||
finalStoryboardIds = createdIds;
|
||||
}
|
||||
await u.db("o_storyboard").whereIn("id", finalStoryboardIds).where("scriptId", scriptId).update({ state: "生成中" });
|
||||
console.log("%c Line:98 🍯 finalStoryboardIds", "background:#3f7cff", finalStoryboardIds);
|
||||
|
||||
if (finalStoryboardIds.length === 0) {
|
||||
res.status(200).send(success());
|
||||
return;
|
||||
}
|
||||
|
||||
const projectSettingData = await u.db("o_project").where("id", projectId).select("imageModel", "imageQuality", "artStyle").first();
|
||||
|
||||
const sceneArkPrompt = u.getArtPrompt(projectSettingData?.artStyle || "", "art_storyboard");
|
||||
const storyboardData = await u.db("o_storyboard").whereIn("id", storyboardIds).select("id", "description", "title");
|
||||
|
||||
const storyboardData = await u.db("o_storyboard").where("scriptId", scriptId).whereIn("id", finalStoryboardIds);
|
||||
const assetData = await u
|
||||
.db("o_assets")
|
||||
.leftJoin("o_assets2Storyboard", "o_assets.id", "o_assets2Storyboard.assetId")
|
||||
.whereIn("o_assets2Storyboard.storyboardId", finalStoryboardIds)
|
||||
.select("o_assets2Storyboard.storyboardId", "o_assets.imageId");
|
||||
const assetRecord: Record<number, number[]> = {};
|
||||
assetData.forEach((item: any) => {
|
||||
if (!assetRecord[item.storyboardId]) {
|
||||
assetRecord[item.storyboardId] = [];
|
||||
}
|
||||
assetRecord[item.storyboardId].push(item.imageId);
|
||||
});
|
||||
res.status(200).send(
|
||||
success(
|
||||
storyboardData.map((i) => ({
|
||||
id: i.id,
|
||||
title: i.title,
|
||||
description: i.description,
|
||||
prompt: "",
|
||||
associateAssetsIds: assetRecord[i.id!],
|
||||
src: null,
|
||||
state: i.state,
|
||||
})),
|
||||
),
|
||||
);
|
||||
for (const item of storyboardData) {
|
||||
const { text } = await u.Ai.Text("universalAi").invoke({
|
||||
system: `
|
||||
你需要根据用户提供的分镜的标题与描述，结合当前项目的美术风格，为我优化提示词以便生成更符合项目美术风格的分镜图片。请你只优化提示词，不要添加任何额外的描述性文字，请以JSON格式输出: [{id:"对应分镜ID",prompt:"分镜提示词"}]。
|
||||
你需要根据用户提供的分镜的标题与描述，结合当前项目的美术风格，为我生成一段提示词以便生成更符合项目美术风格的分镜图片。直接输出提示词，不做任何解释说明。
|
||||
美术风格：${sceneArkPrompt}`,
|
||||
messages: [
|
||||
{
|
||||
@ -34,6 +143,8 @@ export default router.post(
|
||||
},
|
||||
],
|
||||
});
|
||||
console.log("%c Line:27 🍫 text", "background:#ffdd4d", text);
|
||||
|
||||
const repeloadObj = {
|
||||
prompt: text,
|
||||
size: projectSettingData?.imageQuality as "1K" | "2K" | "4K",
|
||||
@ -46,7 +157,7 @@ export default router.post(
|
||||
u.Ai.Image(projectSettingData?.imageModel as `${string}:${string}`)
|
||||
.run({
|
||||
prompt: text,
|
||||
imageBase64: [],
|
||||
imageBase64: await getAssetsImageBase64(assetRecord[item.id!] || []),
|
||||
size: projectSettingData?.imageQuality as "1K" | "2K" | "4K",
|
||||
aspectRatio: "16:9",
|
||||
taskClass: "生成图片",
|
||||
@ -72,7 +183,28 @@ export default router.post(
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
return res.status(200).send(success());
|
||||
},
|
||||
);
|
||||
async function getAssetsImageBase64(imageIds: number[]) {
|
||||
if (imageIds.length === 0) return [];
|
||||
const imagePaths = await u
|
||||
.db("o_assets")
|
||||
.leftJoin("o_image", "o_assets.imageId", "o_image.id")
|
||||
.whereIn("o_assets.id", imageIds)
|
||||
.select("o_assets.id", "o_image.filePath");
|
||||
if (!imagePaths.length) return [];
|
||||
const imageUrls = await Promise.all(
|
||||
imagePaths.map(async (i) => {
|
||||
if (i.filePath) {
|
||||
try {
|
||||
return await urlToBase64(await u.oss.getFileUrl(i.filePath));
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
} else {
|
||||
return null;
|
||||
}
|
||||
}),
|
||||
);
|
||||
return imageUrls.filter(Boolean) as string[];
|
||||
}
|
||||
|
||||
@ -105,19 +105,23 @@ export default router.post(
|
||||
console.log("%c Line:110 🍑 prompt", "background:#b03734", prompt);
|
||||
|
||||
const aiVideo = u.Ai.Video(model);
|
||||
await aiVideo.run({
|
||||
projectId,
|
||||
prompt,
|
||||
imageBase64: base64.filter((item) => item !== null) as string[],
|
||||
mode,
|
||||
duration,
|
||||
aspectRatio: (ratio?.videoRatio as `${number}:${number}`) || "16:9",
|
||||
resolution,
|
||||
audio,
|
||||
taskClass: "视频生成",
|
||||
describe: "根据提示词生成视频",
|
||||
relatedObjects: JSON.stringify(relatedObjects),
|
||||
});
|
||||
await aiVideo.run(
|
||||
{
|
||||
prompt,
|
||||
imageBase64: base64.filter((item) => item !== null) as string[],
|
||||
mode,
|
||||
duration,
|
||||
aspectRatio: (ratio?.videoRatio as `${number}:${number}`) || "16:9",
|
||||
resolution,
|
||||
audio,
|
||||
},
|
||||
{
|
||||
projectId,
|
||||
taskClass: "视频生成",
|
||||
describe: "根据提示词生成视频",
|
||||
relatedObjects: JSON.stringify(relatedObjects),
|
||||
},
|
||||
);
|
||||
await aiVideo.save(videoPath);
|
||||
await u.db("o_video").where("id", videoId).update({ state: "生成成功" });
|
||||
// await u.db("o_videoConfig").where("storyboardId", storyboardId).update({ videoId, updateTime: Date.now() });
|
||||
|
||||
@ -25,23 +25,10 @@ async function getVendorTemplateFn(fnName: FnName, modelName: `${string}:${strin
|
||||
const selectedModel = modelList.find((i: any) => i.modelName == name);
|
||||
if (!selectedModel) throw new Error(`未找到模型 ${name} id=${id}`);
|
||||
const jsCode = transform(vendorConfigData.code!, { transforms: ["typescript"] }).code;
|
||||
const running = u.vm(jsCode);
|
||||
Object.assign(running.vendor.inputValues, JSON.parse(vendorConfigData.inputValues ?? "{}"));
|
||||
running.vendor.models = modelList;
|
||||
const fn = running[fnName];
|
||||
const fn = u.vm(jsCode)[fnName];
|
||||
if (!fn) throw new Error(`未找到供应商配置中的函数 ${fnName} id=${id}`);
|
||||
if (fnName == "textRequest") {
|
||||
const model = fn(selectedModel);
|
||||
if (!model) throw new Error(`供应商 textRequest 返回无效模型 id=${id}`);
|
||||
return model;
|
||||
}
|
||||
return async <T>(input: T) => {
|
||||
const result = await fn(input, selectedModel);
|
||||
if (result === undefined || result === null) {
|
||||
throw new Error(`供应商函数 ${fnName} 未返回有效结果 id=${id}`);
|
||||
}
|
||||
return result;
|
||||
};
|
||||
if (fnName == "textRequest") return fn(selectedModel);
|
||||
else return <T>(input: T) => fn(input, selectedModel);
|
||||
}
|
||||
|
||||
async function withTaskRecord<T>(
|
||||
@ -113,6 +100,9 @@ interface ImageConfig {
|
||||
imageBase64: string[]; //输入的图片提示词
|
||||
size: "1K" | "2K" | "4K"; // 图片尺寸
|
||||
aspectRatio: `${number}:${number}`; // 长宽比
|
||||
}
|
||||
|
||||
interface TaskRecord {
|
||||
taskClass: string; // 任务分类
|
||||
describe: string; // 任务描述
|
||||
relatedObjects: string; // 相关对象信息，便于后续分析和追踪
|
||||
@ -125,8 +115,8 @@ class AiImage {
|
||||
constructor(key: `${string}:${string}`) {
|
||||
this.key = key;
|
||||
}
|
||||
async run(input: ImageConfig) {
|
||||
return withTaskRecord(this.key, input.taskClass, input.describe, input.relatedObjects, input.projectId, async (modelName) => {
|
||||
async run(input: ImageConfig, taskRecord: TaskRecord) {
|
||||
return withTaskRecord(this.key, taskRecord.taskClass, taskRecord.describe, taskRecord.relatedObjects, taskRecord.projectId, async (modelName) => {
|
||||
const fn = await getVendorTemplateFn("imageRequest", modelName);
|
||||
this.result = await fn(input);
|
||||
if (this.result.startsWith("http")) this.result = await urlToBase64(this.result);
|
||||
@ -139,7 +129,6 @@ class AiImage {
|
||||
}
|
||||
}
|
||||
interface VideoConfig {
|
||||
projectId: number; // 项目ID
|
||||
prompt: string; //视频提示词
|
||||
imageBase64: string[]; //输入的图片提示词
|
||||
aspectRatio: `${number}:${number}`; // 长宽比
|
||||
@ -147,9 +136,6 @@ interface VideoConfig {
|
||||
duration: number; // 视频时长，单位秒
|
||||
resolution: string; // 视频分辨率
|
||||
audio: boolean; // 是否需要配音
|
||||
taskClass: string; // 任务分类
|
||||
describe: string; // 任务描述
|
||||
relatedObjects: string; // 相关对象信息，便于后续分析和追踪
|
||||
}
|
||||
|
||||
class AiVideo {
|
||||
@ -158,8 +144,8 @@ class AiVideo {
|
||||
constructor(key: `${string}:${string}`) {
|
||||
this.key = key;
|
||||
}
|
||||
async run(input: VideoConfig) {
|
||||
return withTaskRecord(this.key, input.taskClass, input.describe, input.relatedObjects, input.projectId, async (modelName) => {
|
||||
async run(input: VideoConfig, taskRecord: TaskRecord) {
|
||||
return withTaskRecord(this.key, taskRecord.taskClass, taskRecord.describe, taskRecord.relatedObjects, taskRecord.projectId, async (modelName) => {
|
||||
const fn = await getVendorTemplateFn("videoRequest", modelName);
|
||||
this.result = await fn(input);
|
||||
if (this.result.startsWith("http")) this.result = await urlToBase64(this.result);
|
||||
@ -177,8 +163,8 @@ class AiAudio {
|
||||
constructor(key: `${string}:${string}`) {
|
||||
this.key = key;
|
||||
}
|
||||
async run(input: VideoConfig) {
|
||||
return withTaskRecord(this.key, input.taskClass, input.describe, input.relatedObjects, input.projectId, async (modelName) => {
|
||||
async run(input: VideoConfig, taskRecord: TaskRecord) {
|
||||
return withTaskRecord(this.key, taskRecord.taskClass, taskRecord.describe, taskRecord.relatedObjects, taskRecord.projectId, async (modelName) => {
|
||||
const fn = await getVendorTemplateFn("ttsRequest", modelName);
|
||||
this.result = await fn(input);
|
||||
if (this.result.startsWith("http")) this.result = await urlToBase64(this.result);
|
||||
|
||||
68
yarn.lock
68
yarn.lock
@ -40,10 +40,10 @@
|
||||
"@hono/node-server" "^1.13.7"
|
||||
hono "^4.6.14"
|
||||
|
||||
"@ai-sdk/gateway@3.0.82":
|
||||
version "3.0.82"
|
||||
resolved "https://registry.npmmirror.com/@ai-sdk/gateway/-/gateway-3.0.82.tgz#904f150486ad3f9456c71ba6732c3f4b518c76d1"
|
||||
integrity sha512-ddB9FrkHZank1zyx13vypU0RrPjsXWj3NvlsrJ4yFQnrpR+xh48W4wO9ijndUueBsaADjlvMz2Ghv8yq5tZGCQ==
|
||||
"@ai-sdk/gateway@3.0.83":
|
||||
version "3.0.83"
|
||||
resolved "https://registry.npmmirror.com/@ai-sdk/gateway/-/gateway-3.0.83.tgz#214812d3a2f15447adf4ee81d3ed77dd137b41b3"
|
||||
integrity sha512-LvlWujbSdEkTBXBLFtF7GS6riXdHhH0O+DpDrCaNQvXeHmSF2jKsOg7JWXiCgygAHM5cWFAO3JYmZp83DjiuBQ==
|
||||
dependencies:
|
||||
"@ai-sdk/provider" "3.0.8"
|
||||
"@ai-sdk/provider-utils" "4.0.21"
|
||||
@ -423,9 +423,9 @@
|
||||
integrity sha512-k2Ty1JcVojjJFwrg/ThKi2ujJ7XNLYaFGNB/bWT9wGR+oSMJHMa5w+CUq6p/pVrKeNNgA7pCqEcjSnHVoqJQFw==
|
||||
|
||||
"@hono/node-server@^1.13.7":
|
||||
version "1.19.11"
|
||||
resolved "https://registry.npmmirror.com/@hono/node-server/-/node-server-1.19.11.tgz#dc419f0826dd2504e9fc86ad289d5636a0444e2f"
|
||||
integrity sha512-dr8/3zEaB+p0D2n/IUrlPF1HZm586qgJNXK1a9fhg/PzdtkK7Ksd5l312tJX2yBuALqDYBlG20QEbayqPyxn+g==
|
||||
version "1.19.12"
|
||||
resolved "https://registry.npmmirror.com/@hono/node-server/-/node-server-1.19.12.tgz#dae075247959b6d7d2dba4c8bdc8c452ca0c7b40"
|
||||
integrity sha512-txsUW4SQ1iilgE0l9/e9VQWmELXifEFvmdA1j6WFh/aFPj99hIntrSsq/if0UWyGVkmrRPKA1wCeP+UCr1B9Uw==
|
||||
|
||||
"@huggingface/jinja@^0.5.3":
|
||||
version "0.5.6"
|
||||
@ -1042,9 +1042,9 @@
|
||||
integrity sha512-Fw28YZpRnA3cAHHDlkt7xQHiJ0fcL+NRcIqsocZQUSmbzeIKRpwttJjik5ZGanXP+vlA4SbTg+AbA3bP363l+w==
|
||||
|
||||
"@xmldom/xmldom@^0.8.8":
|
||||
version "0.8.11"
|
||||
resolved "https://registry.npmmirror.com/@xmldom/xmldom/-/xmldom-0.8.11.tgz#b79de2d67389734c57c52595f7a7305e30c2d608"
|
||||
integrity sha512-cQzWCtO6C8TQiYl1ruKNn2U6Ao4o4WBBcbL61yJl84x+j5sOWWFU9X7DpND8XZG3daDppSsigMdfAIl2upQBRw==
|
||||
version "0.8.12"
|
||||
resolved "https://registry.npmmirror.com/@xmldom/xmldom/-/xmldom-0.8.12.tgz#cf488a5435fa06c7374ad1449c69cea0f823624b"
|
||||
integrity sha512-9k/gHF6n/pAi/9tqr3m3aqkuiNosYTurLLUtc7xQ9sxB/wm7WPygCv8GYa6mS0fLJEHhqMC1ATYhz++U/lRHqg==
|
||||
|
||||
abbrev@1, abbrev@^1.0.0:
|
||||
version "1.1.1"
|
||||
@ -1117,11 +1117,11 @@ aggregate-error@^3.0.0:
|
||||
indent-string "^4.0.0"
|
||||
|
||||
ai@^6.0.67:
|
||||
version "6.0.140"
|
||||
resolved "https://registry.npmmirror.com/ai/-/ai-6.0.140.tgz#1135f3fa05c760e346984f02f55de8e2b9800691"
|
||||
integrity sha512-+jf6fQDPZe+gQlzPoP5mzy+DdfYOpE0cgUm99U8OxVTIPv19gCDuNzlKTZSntcQzLbo6LFXyNhJdV7XTWQ+5vA==
|
||||
version "6.0.141"
|
||||
resolved "https://registry.npmmirror.com/ai/-/ai-6.0.141.tgz#c476280ae69b13ad11f2671e49a24ac0412a0b54"
|
||||
integrity sha512-+GomGQWaId3xN0wcugUW/H7xMMaFkID2PiS7K/Wugj45G3efv0BXhQ3psRZoQVoRbOpdNoUqcK/KTB+FR4h6qg==
|
||||
dependencies:
|
||||
"@ai-sdk/gateway" "3.0.82"
|
||||
"@ai-sdk/gateway" "3.0.83"
|
||||
"@ai-sdk/provider" "3.0.8"
|
||||
"@ai-sdk/provider-utils" "4.0.21"
|
||||
"@opentelemetry/api" "1.9.0"
|
||||
@ -1303,13 +1303,13 @@ axios-retry@^4.5.0:
|
||||
is-retry-allowed "^2.2.0"
|
||||
|
||||
axios@^1.13.2:
|
||||
version "1.13.6"
|
||||
resolved "https://registry.npmmirror.com/axios/-/axios-1.13.6.tgz#c3f92da917dc209a15dd29936d20d5089b6b6c98"
|
||||
integrity sha512-ChTCHMouEe2kn713WHbQGcuYrr6fXTBiu460OTwWrWob16g1bXn4vtz07Ope7ewMozJAnEquLk5lWQWtBig9DQ==
|
||||
version "1.14.0"
|
||||
resolved "https://registry.npmmirror.com/axios/-/axios-1.14.0.tgz#7c29f4cf2ea91ef05018d5aa5399bf23ed3120eb"
|
||||
integrity sha512-3Y8yrqLSwjuzpXuZ0oIYZ/XGgLwUIBU3uLvbcpb0pidD9ctpShJd43KSlEEkVQg6DS0G9NKyzOvBfUtDKEyHvQ==
|
||||
dependencies:
|
||||
follow-redirects "^1.15.11"
|
||||
form-data "^4.0.5"
|
||||
proxy-from-env "^1.1.0"
|
||||
proxy-from-env "^2.1.0"
|
||||
|
||||
balanced-match@^1.0.0:
|
||||
version "1.0.2"
|
||||
@ -1396,17 +1396,17 @@ boolean@^3.0.1:
|
||||
integrity sha512-d0II/GO9uf9lfUHH2BQsjxzRJZBdsjgsBiW4BvhWk/3qoKwQFjIDVN19PfX8F2D/r9PCMTtLWjYVCFrpeYUzsw==
|
||||
|
||||
brace-expansion@^1.1.7:
|
||||
version "1.1.12"
|
||||
resolved "https://registry.npmmirror.com/brace-expansion/-/brace-expansion-1.1.12.tgz#ab9b454466e5a8cc3a187beaad580412a9c5b843"
|
||||
integrity sha512-9T9UjW3r0UW5c1Q7GTwllptXwhvYmEzFhzMfZ9H7FQWt+uZePjZPjBP/W1ZEyZ1twGWom5/56TF4lPcqjnDHcg==
|
||||
version "1.1.13"
|
||||
resolved "https://registry.npmmirror.com/brace-expansion/-/brace-expansion-1.1.13.tgz#d37875c01dc9eff988dd49d112a57cb67b54efe6"
|
||||
integrity sha512-9ZLprWS6EENmhEOpjCYW2c8VkmOvckIJZfkr7rBW6dObmfgJ/L1GpSYW5Hpo9lDz4D1+n0Ckz8rU7FwHDQiG/w==
|
||||
dependencies:
|
||||
balanced-match "^1.0.0"
|
||||
concat-map "0.0.1"
|
||||
|
||||
brace-expansion@^2.0.1, brace-expansion@^2.0.2:
|
||||
version "2.0.2"
|
||||
resolved "https://registry.npmmirror.com/brace-expansion/-/brace-expansion-2.0.2.tgz#54fc53237a613d854c7bd37463aad17df87214e7"
|
||||
integrity sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==
|
||||
version "2.0.3"
|
||||
resolved "https://registry.npmmirror.com/brace-expansion/-/brace-expansion-2.0.3.tgz#0493338bdd58e319b1039c67cf7ee439892c01d9"
|
||||
integrity sha512-MCV/fYJEbqx68aE58kv2cA/kiky1G8vux3OR6/jbS+jIMe/6fJWa0DTzJU7dqijOWYwHi1t29FlfYI9uytqlpA==
|
||||
dependencies:
|
||||
balanced-match "^1.0.0"
|
||||
|
||||
@ -1870,9 +1870,9 @@ cross-spawn@^7.0.1, cross-spawn@^7.0.6:
|
||||
which "^2.0.1"
|
||||
|
||||
custom-electron-titlebar@^4.2.8:
|
||||
version "4.4.0"
|
||||
resolved "https://registry.npmmirror.com/custom-electron-titlebar/-/custom-electron-titlebar-4.4.0.tgz#0b6aff12db97babf237d052e0d2ea24623de4783"
|
||||
integrity sha512-bvYxxDQiG/23eMPDAdhjjOXviEXnShHRo8VCDCouVfVDdG3Xs8SkXISYDZK3pyhINsrrJ21s9tSU7h59WDr5oA==
|
||||
version "4.4.1"
|
||||
resolved "https://registry.npmmirror.com/custom-electron-titlebar/-/custom-electron-titlebar-4.4.1.tgz#aea64f009697c9771cb2a67d2eb5ac8059696906"
|
||||
integrity sha512-I+sOGBdslrGpuCWlhda8P0vtRAZK+W2NzjHLsxTiE2bNmhAIs9YLDe6iRBExwU1xVZt+J1hSXzUT67BlAuMWLA==
|
||||
|
||||
debug@2.6.9:
|
||||
version "2.6.9"
|
||||
@ -3212,9 +3212,9 @@ keyv@^4.0.0:
|
||||
json-buffer "3.0.1"
|
||||
|
||||
knex@^3.1.0, knex@^3.2.5:
|
||||
version "3.2.6"
|
||||
resolved "https://registry.npmmirror.com/knex/-/knex-3.2.6.tgz#d6653ebf7961a83ae0014db1a7c56c75ce1ffa00"
|
||||
integrity sha512-26I1Tvx0D9SOsFBF9jRWT/JdE3FPI52jAwYpXfREEtnoqgjGvAi8/ux8ktjaTC9IQcAVTCrREkOpa7lrjeAcow==
|
||||
version "3.2.7"
|
||||
resolved "https://registry.npmmirror.com/knex/-/knex-3.2.7.tgz#53bc16470217f12fef516a7a649794a405d3473d"
|
||||
integrity sha512-VxdDE72x7Tc08E5yCu8HqYoeOm0HOjAraOtYiGSAUJTYkydwfSGBOpQqYHrzM5vjLNzw2JDL2vDH8m7DjIjtgA==
|
||||
dependencies:
|
||||
colorette "2.0.19"
|
||||
commander "^10.0.0"
|
||||
@ -4237,10 +4237,10 @@ proxy-addr@^2.0.7:
|
||||
forwarded "0.2.0"
|
||||
ipaddr.js "1.9.1"
|
||||
|
||||
proxy-from-env@^1.1.0:
|
||||
version "1.1.0"
|
||||
resolved "https://registry.npmmirror.com/proxy-from-env/-/proxy-from-env-1.1.0.tgz#e102f16ca355424865755d2c9e8ea4f24d58c3e2"
|
||||
integrity sha512-D+zkORCbA9f1tdWRK0RaCR3GPv50cMxcrz4X8k5LTSUD1Dkw47mKJEZQNunItRTkWwgtaUSo1RVFRIG9ZXiFYg==
|
||||
proxy-from-env@^2.1.0:
|
||||
version "2.1.0"
|
||||
resolved "https://registry.npmmirror.com/proxy-from-env/-/proxy-from-env-2.1.0.tgz#a7487568adad577cfaaa7e88c49cab3ab3081aba"
|
||||
integrity sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA==
|
||||
|
||||
pstree.remy@^1.1.8:
|
||||
version "1.1.8"
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user