752 lines
32 KiB
TypeScript
752 lines
32 KiB
TypeScript
import { tool, Tool } from "ai";
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import { z } from "zod";
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import _ from "lodash";
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import ResTool from "@/socket/resTool";
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import u from "@/utils";
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import { urlToBase64 } from "@/utils/vm";
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export const deriveAssetSchema = z.object({
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id: z.number().describe("衍生资产ID,如果新增则为空"),
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assetsId: z.number().describe("关联的资产ID"),
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prompt: z.string().describe("生成提示词"),
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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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src: z.string().nullable().describe("衍生资产资源路径"),
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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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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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prompt: z.string().describe("生成提示词"),
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desc: z.string().describe("资产描述"),
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derive: z.array(deriveAssetSchema).describe("衍生资产列表"),
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});
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export const storyboardSchema = z.object({
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id: z.number().describe("分镜ID，必须为真实id"),
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title: z.string().describe("分镜标题"),
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description: z.string().describe("分镜描述"),
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camera: z.string().describe("镜头信息"),
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duration: z.number().describe("持续时长(秒)"),
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frameMode: z.enum(["firstFrame", "endFrame", "linesSoundEffects"]).describe("帧模式: 首帧/尾帧/台词音效"),
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prompt: z.string().describe("生成提示词"),
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lines: z.string().nullable().describe("台词内容"),
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sound: z.string().nullable().describe("音效内容"),
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mode: z
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.union([
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z.enum(["singleImage", "multiImage", "gridImage", "startEndRequired", "endFrameOptional", "startFrameOptional", "text"]),
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z.array(z.enum(["video", "image", "audio", "text"])),
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])
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.describe("视频模式"),
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associateAssetsIds: z.array(z.number()).describe("关联资产ID列表"),
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src: z.string().nullable().describe("分镜资源路径"),
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});
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export const workbenchDataSchema = z.object({
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name: z.string().describe("项目名称"),
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duration: z.string().describe("视频时长"),
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resolution: z.string().describe("分辨率"),
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fps: z.string().describe("帧率"),
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cover: z.string().optional().describe("封面图片路径"),
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gradient: z.string().optional().describe("渐变色配置"),
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});
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export const posterItemSchema = z.object({
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id: z.number().describe("海报ID"),
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image: z.string().describe("海报图片路径"),
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});
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export const flowDataSchema = z.object({
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script: z.string().describe("剧本内容"),
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scriptPlan: z.string().describe("拍摄计划"),
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assets: z.array(assetItemSchema).describe("衍生资产"),
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storyboardTable: z.string().describe("分镜表"),
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storyboard: z.array(storyboardSchema).describe("分镜面板"),
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workbench: workbenchDataSchema.describe("工作台配置"),
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poster: z
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.object({
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items: z.array(posterItemSchema).describe("海报项目列表"),
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})
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.describe("海报配置"),
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});
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export type FlowData = z.infer<typeof flowDataSchema>;
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const keySchema = z.enum(Object.keys(flowDataSchema.shape) as [keyof FlowData, ...Array<keyof FlowData>]);
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const flowDataKeyLabels = Object.fromEntries(
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Object.entries(flowDataSchema.shape).map(([key, schema]) => [key, (schema as z.ZodTypeAny).description ?? key]),
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) as Record<keyof FlowData, string>;
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interface ToolConfig {
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resTool: ResTool;
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toolsNames?: string[];
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msg: ReturnType<ResTool["newMessage"]>;
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}
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export default (toolCpnfig: ToolConfig) => {
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const { resTool, toolsNames, msg } = toolCpnfig;
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const { socket } = resTool;
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const tools: Record<string, Tool> = {
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get_flowData: tool({
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description: "获取工作区数据",
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inputSchema: z.object({
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key: keySchema.describe("数据key"),
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}),
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execute: async ({ key }) => {
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const thinking = msg.thinking(`正在获取${flowDataKeyLabels[key]}工作区数据...`);
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console.log("[tools] get_flowData", key);
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const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key }, (res: any) => resolve(res)));
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thinking.appendText(`获取到${flowDataKeyLabels[key]}:\n` + flowData[key]);
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thinking.updateTitle(`获取${flowDataKeyLabels[key]}完成`);
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thinking.complete();
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return flowData[key];
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},
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}),
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set_flowData_script: tool({
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description: "保存剧本内容到工作区",
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inputSchema: z.object({ value: flowDataSchema.shape.script }),
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execute: async ({ value }) => {
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console.log("[tools] set_flowData script", value);
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const thinking = msg.thinking("正在保存 剧本 数据");
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socket.emit("setFlowData", { key: "script", value });
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thinking.updateTitle("保存 剧本 数据完成");
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thinking.complete();
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return true;
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},
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}),
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set_flowData_scriptPlan: tool({
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description: "保存拍摄计划到工作区",
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inputSchema: z.object({ value: flowDataSchema.shape.scriptPlan }),
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execute: async ({ value }) => {
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console.log("[tools] set_flowData scriptPlan", value);
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const thinking = msg.thinking("正在保存 拍摄计划 数据");
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socket.emit("setFlowData", { key: "scriptPlan", value });
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thinking.updateTitle("保存 拍摄计划 数据完成");
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thinking.complete();
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return true;
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},
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}),
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add_flowData_assets: tool({
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description: "新增对应衍生资产列表到工作区，严禁包含 不需要新增的数据",
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inputSchema: z.object({ value: z.array(deriveAssetSchema.omit({ id: true })).describe("需要新增的衍生资产列表") }),
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execute: async ({ value }) => {
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console.log("[tools] set_flowData add_flowData_assets", value);
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const thinking = msg.thinking("正在保存 衍生资产 数据");
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const setData = [...value] as z.infer<typeof deriveAssetSchema>[];
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const { projectId, scriptId } = resTool.data;
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const startTime = Date.now();
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// 并行插入所有 o_assets 记录
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await Promise.all(
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setData.map(async (i) => {
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const [insertedId] = await u.db("o_assets").insert({
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assetsId: +i.assetsId || null,
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projectId,
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name: i.name,
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type: i.type,
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prompt: i.prompt,
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describe: i.desc,
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startTime,
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});
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i.id = insertedId;
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}),
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);
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// 批量插入 o_scriptAssets
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await u.db("o_scriptAssets").insert(setData.map((i) => ({ scriptId, assetId: i.id })));
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const watiAddAssetsMap: Record<number, z.infer<typeof deriveAssetSchema>[]> = {};
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setData.forEach((i) => {
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if (watiAddAssetsMap[i.assetsId]) {
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watiAddAssetsMap[i.assetsId].push(i);
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} else {
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watiAddAssetsMap[i.assetsId] = [i];
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}
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});
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const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key: "assets" }, (res: any) => resolve(res)));
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const assetsData = flowData.assets;
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assetsData.forEach((i) => {
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if (watiAddAssetsMap[i.id]) {
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i.derive = [...(i.derive || []), ...watiAddAssetsMap[i.id]];
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}
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});
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thinking.updateTitle("保存 衍生资产 数据完成");
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thinking.complete();
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socket.emit("setFlowData", { key: "assets", value: assetsData });
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return true;
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},
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}),
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update_flowData_assets: tool({
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description: "更新对应衍生资产列表到工作区",
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inputSchema: z.object({ value: z.array(deriveAssetSchema).describe("需要更新的衍生资产列表") }),
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execute: async ({ value }) => {
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console.log("[tools] update_flowData update_flowData_assets", value);
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const thinking = msg.thinking("正在保存 衍生资产 数据");
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for (const i of value) {
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await u
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.db("o_assets")
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.where("id", i.id)
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.update({
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assetsId: +i.assetsId || null,
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projectId: resTool.data.projectId,
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name: i.name,
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type: i.type,
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prompt: i.prompt,
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describe: i.desc,
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});
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}
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// 按 assetsId 分组，构建更新映射
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const updateAssetsMap: Record<number, z.infer<typeof deriveAssetSchema>[]> = {};
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value.forEach((i) => {
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if (updateAssetsMap[i.assetsId]) {
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updateAssetsMap[i.assetsId].push(i);
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} else {
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updateAssetsMap[i.assetsId] = [i];
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}
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});
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const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key: "assets" }, (res: any) => resolve(res)));
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const assetsData = flowData.assets;
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// 将 derive 中已存在的条目替换为更新后的数据
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assetsData.forEach((asset) => {
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if (updateAssetsMap[asset.id]) {
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const updatedMap = Object.fromEntries(updateAssetsMap[asset.id].map((d) => [d.id, d]));
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asset.derive = (asset.derive || []).map((d) => updatedMap[d.id] ?? d);
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}
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});
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thinking.updateTitle("保存 衍生资产 数据完成");
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thinking.complete();
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socket.emit("setFlowData", { key: "assets", value: assetsData });
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return true;
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},
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}),
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delete_flowData_assets: tool({
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description: "删除对应衍生资产",
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inputSchema: z.object({ ids: z.array(z.number()).describe("需要删除的 衍生资产id ") }),
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execute: async ({ ids }) => {
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console.log("[tools] delete_flowData delete_flowData_assets", ids);
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const thinking = msg.thinking("正在删除指定 衍生资产 数据...");
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await u.db("o_assets").whereIn("id", ids).delete();
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const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key: "assets" }, (res: any) => resolve(res)));
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const assetsData = flowData.assets;
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assetsData.forEach((i) => {
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i.derive = (i.derive || []).filter((d) => !ids.includes(d.id));
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});
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thinking.updateTitle("删除指定 衍生资产 数据完成");
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thinking.complete();
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// 将 derive 中已存在的条目替换为更新后的数据
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socket.emit("setFlowData", { key: "assets", value: assetsData });
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return true;
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},
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}),
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// set_flowData_assets: tool({
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// description: "保存衍生资产列表到工作区",
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// inputSchema: z.object({ value: flowDataSchema.shape.assets }),
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// execute: async ({ value }) => {
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// console.log("[tools] set_flowData assets", value);
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// resTool.systemMessage("正在保存 衍生资产 数据");
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// if (value && Array.isArray(value) && value.length) {
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// for (const i of value) {
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// if (!i?.id) {
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// const [insertedId] = await u.db("o_assets").insert({
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// assetsId: null,
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// name: i.name,
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// type: i.type,
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// prompt: i.prompt,
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// describe: i.desc,
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// startTime: Date.now(),
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// });
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// i.id = insertedId;
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// }
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// if (i.derive && Array.isArray(i.derive) && i.derive.length) {
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// for (const sub of i.derive) {
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// if (sub.id) continue;
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// const [insertedId] = await u.db("o_assets").insert({
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// assetsId: +i.id || null,
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// projectId: resTool.data.projectId,
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// name: sub.name,
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// type: sub.type,
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// prompt: sub.prompt,
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// describe: sub.desc,
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// startTime: Date.now(),
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// });
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// await u.db("o_scriptAssets").insert({
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// scriptId: resTool.data.scriptId,
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// assetId: insertedId,
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// });
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// sub.id = insertedId;
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// }
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// }
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// }
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// }
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// socket.emit("setFlowData", { key: "assets", value });
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// return true;
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// },
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// }),
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set_flowData_storyboardTable: tool({
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description: "保存分镜表到工作区",
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inputSchema: z.object({ value: flowDataSchema.shape.storyboardTable }),
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execute: async ({ value }) => {
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console.log("[tools] set_flowData storyboardTable", value);
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const thinking = msg.thinking("正在保存 分镜表 数据...");
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socket.emit("setFlowData", { key: "storyboardTable", value });
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thinking.updateTitle("保存 分镜表 数据完成");
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thinking.complete();
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return true;
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},
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}),
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add_flowData_storyboard: tool({
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description: "新增分镜面板到工作区",
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inputSchema: z.object({ value: z.array(storyboardSchema.omit({ id: true })) }),
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execute: async ({ value }) => {
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console.log("[tools] add_flowData storyboard", value);
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const thinking = msg.thinking("正在保存 分镜面板 数据...");
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const setData = [...value] as z.infer<typeof storyboardSchema>[];
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for (const item of setData) {
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item.src = "";
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const [insertedId] = await u.db("o_storyboard").insert({
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title: item.title,
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prompt: item.prompt,
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description: item.description,
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frameMode: item.frameMode,
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duration: String(item.duration),
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camera: item.camera,
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sound: item.sound,
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lines: item.lines,
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state: "未生成",
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scriptId: resTool.data.scriptId,
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createTime: Date.now(),
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});
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if (item.associateAssetsIds.length) {
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await u.db("o_assets2Storyboard").insert(item.associateAssetsIds.map((i) => ({ storyboardId: insertedId, assetId: i })));
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}
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item.id = insertedId;
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}
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//为了防止丢失分镜其他数据，例如：依赖分镜Id、依赖资产idc
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const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key: "storyboard" }, (res: any) => resolve(res)));
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const storyboardData = flowData["storyboard"].concat([...setData]);
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socket.emit("setFlowData", { key: "storyboard", value: storyboardData });
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thinking.updateTitle("保存 分镜面板 数据完成");
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thinking.complete();
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return true;
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},
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}),
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update_flowData_storyboard: tool({
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description: "更新指定分镜面板到工作区",
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inputSchema: z.object({ value: flowDataSchema.shape.storyboard }),
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execute: async ({ value }) => {
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console.log("[tools] update_flowData storyboard", value);
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const thinking = msg.thinking("正在保存 分镜面板 数据...");
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for (const item of value) {
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await u
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.db("o_storyboard")
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.where("id", item.id)
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.update({
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title: item.title,
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prompt: item.prompt,
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description: item.description,
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frameMode: item.frameMode,
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duration: String(item.duration),
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camera: item.camera,
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sound: item.sound,
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lines: item.lines,
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});
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}
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//直接拉取前端数据，为了防止丢失分镜其他数据，例如：依赖分镜Id、依赖资产idc
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const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key: "storyboard" }, (res: any) => resolve(res)));
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const storyboardData = flowData["storyboard"].map((existing) => {
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const updated = value.find((v) => v.id === existing.id);
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if (!updated) return existing;
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return {
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...existing,
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title: updated.title,
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prompt: updated.prompt,
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description: updated.description,
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frameMode: updated.frameMode,
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duration: updated.duration,
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camera: updated.camera,
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sound: updated.sound,
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lines: updated.lines,
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};
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});
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socket.emit("setFlowData", { key: "storyboard", value: storyboardData });
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thinking.updateTitle("保存 分镜面板 数据完成");
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thinking.complete();
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return true;
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},
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}),
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delete_flowData_storyboard: tool({
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description: "删除指定分镜面板并更新工作区",
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inputSchema: z.object({ ids: z.array(z.number()).describe("需要删除的 分镜id ") }),
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execute: async ({ ids }) => {
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console.log("[tools] delete_flowData storyboard", ids);
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const thinking = msg.thinking("正在删除指定 分镜面板 数据...");
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await u.db("o_storyboard").whereIn("id", ids).delete();
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await u.db("o_assets2Storyboard").whereIn("storyboardId", ids).delete();
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await u.db("o_storyboardFlow").whereIn("storyboardId", ids).delete();
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const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key: "storyboard" }, (res: any) => resolve(res)));
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const storyboardData = flowData["storyboard"].filter((item) => !ids.includes(item.id));
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socket.emit("setFlowData", { key: "storyboard", value: storyboardData });
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thinking.updateTitle("删除指定 分镜面板 数据完成");
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thinking.complete();
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return true;
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},
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}),
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// set_flowData_storyboard: tool({
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// description: "保存分镜面板到工作区",
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// inputSchema: z.object({ value: flowDataSchema.shape.storyboard }),
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// execute: async ({ value }) => {
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// console.log("[tools] set_flowData storyboard", value);
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// resTool.systemMessage("正在保存 分镜面板 数据...");
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// for (const item of value) {
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// if (!item.id) {
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// const [insertedId] = await u.db("o_storyboard").insert({
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// title: item.title,
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// prompt: item.prompt,
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// description: item.description,
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// filePath: item.src,
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// frameMode: item.frameMode,
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// duration: String(item.duration),
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// camera: item.camera,
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// sound: item.sound,
|
||
// lines: item.lines,
|
||
// state: "未生成",
|
||
// scriptId: resTool.data.scriptId,
|
||
// });
|
||
// console.log("%c Line:216 🥥 item.associateAssetsIds", "background:#6ec1c2", item.associateAssetsIds);
|
||
|
||
// if (item.associateAssetsIds.length) {
|
||
// await u.db("o_assets2Storyboard").insert(item.associateAssetsIds.map((i) => ({ storyboardId: insertedId, assetId: i })));
|
||
// }
|
||
// item.id = insertedId;
|
||
// }
|
||
// }
|
||
// socket.emit("setFlowData", { key: "storyboard", value });
|
||
// return true;
|
||
// },
|
||
// }),
|
||
set_flowData_workbench: tool({
|
||
description: "保存工作台配置数据到工作区",
|
||
inputSchema: z.object({ value: flowDataSchema.shape.workbench }),
|
||
execute: async ({ value }) => {
|
||
console.log("[tools] set_flowData workbench", value);
|
||
const thinking = msg.thinking("正在保存 工作台配置 数据...");
|
||
socket.emit("setFlowData", { key: "workbench", value });
|
||
thinking.updateTitle("保存 工作台配置 数据完成");
|
||
thinking.complete();
|
||
return true;
|
||
},
|
||
}),
|
||
set_flowData_poster: tool({
|
||
description: "保存海报配置到工作区",
|
||
inputSchema: z.object({ value: flowDataSchema.shape.poster }),
|
||
execute: async ({ value }) => {
|
||
console.log("[tools] set_flowData poster", value);
|
||
const thinking = msg.thinking("正在保存 海报配置 数据...");
|
||
thinking.updateTitle("保存 海报配置 数据完成");
|
||
thinking.complete();
|
||
socket.emit("setFlowData", { key: "poster", value });
|
||
return true;
|
||
},
|
||
}),
|
||
// todo 提示词待调
|
||
generate_storyboard_images: tool({
|
||
description: `生成一组图片任务，支持图片间的依赖关系（以图生图），基于有向无环图(DAG)拓扑排序执行。
|
||
|
||
参数说明：
|
||
- images: 图片任务数组
|
||
- id: 图片唯一标识符（分镜id）
|
||
- prompt: 图片生成提示词
|
||
- referenceIds: 依赖的参考图id数组，无依赖填空数组[]
|
||
- assetIds: 参考的资产图id数组（可选）
|
||
|
||
依赖规则：
|
||
1. referenceIds中的id必须存在于images数组中
|
||
2. 禁止循环依赖（如A依赖B，B依赖A）
|
||
3. 被依赖的图片会先生成，其结果作为参考图传入
|
||
|
||
示例：生成猫图，再以猫图为参考生成狗图
|
||
images: [
|
||
{id: 1, prompt: "一只橘猫", referenceIds: [], assetIds: []},
|
||
{id: 2, prompt: "风格相同的金毛犬", referenceIds: [1], assetIds: []}
|
||
]`,
|
||
inputSchema: z.object({
|
||
images: z.array(
|
||
z.object({
|
||
id: z.number().describe("从工作区获取到的分镜id"),
|
||
prompt: z.string().describe("图片生成提示词"),
|
||
referenceIds: z.array(z.number()).describe("依赖的参考 分镜图id数组，无依赖填空数组[]"),
|
||
assetIds: z.array(z.number()).describe("参考的资产图"),
|
||
}),
|
||
),
|
||
}),
|
||
execute: async ({ images }) => {
|
||
console.log("[tools] generate_storyboard_images", images);
|
||
const thinking = msg.thinking("正在生成 分镜图片 数据...");
|
||
// --- 构建任务id集合 ---
|
||
const taskIds = new Set(images.map((item) => item.id));
|
||
const imageMap = new Map(images.map((item) => [item.id, item]));
|
||
|
||
// --- 检测循环依赖 (Kahn算法拓扑排序) ---
|
||
// 将 referenceIds 分为：本批次内依赖 vs 外部已有依赖
|
||
// 只有本批次内的依赖才参与 DAG 调度，外部依赖直接从数据库获取
|
||
const inDegree = new Map<number, number>();
|
||
// adjacency: 被依赖者 -> 依赖它的节点列表
|
||
const adjacency = new Map<number, number[]>();
|
||
|
||
for (const item of images) {
|
||
// 只统计本批次内的依赖作为入度
|
||
const internalDeps = item.referenceIds.filter((refId) => taskIds.has(refId));
|
||
inDegree.set(item.id, internalDeps.length);
|
||
for (const depId of internalDeps) {
|
||
if (!adjacency.has(depId)) adjacency.set(depId, []);
|
||
adjacency.get(depId)!.push(item.id);
|
||
}
|
||
}
|
||
|
||
// 拓扑排序，按层级分组（同层可并行）
|
||
const levels: number[][] = [];
|
||
let queue = images.filter((item) => (inDegree.get(item.id) ?? 0) === 0).map((item) => item.id);
|
||
|
||
const visited = new Set<number>();
|
||
while (queue.length > 0) {
|
||
levels.push([...queue]);
|
||
const nextQueue: number[] = [];
|
||
for (const nodeId of queue) {
|
||
visited.add(nodeId);
|
||
for (const childId of adjacency.get(nodeId) ?? []) {
|
||
inDegree.set(childId, (inDegree.get(childId) ?? 1) - 1);
|
||
if (inDegree.get(childId) === 0) {
|
||
nextQueue.push(childId);
|
||
}
|
||
}
|
||
}
|
||
queue = nextQueue;
|
||
}
|
||
// 循环依赖检测
|
||
if (visited.size !== images.length) {
|
||
const cyclicIds = images.filter((item) => !visited.has(item.id)).map((item) => item.id);
|
||
thinking.appendText(`检测到循环依赖，涉及分镜id: ${cyclicIds.join(", ")}，请修正后重试`);
|
||
thinking.updateTitle("循环依赖错误");
|
||
thinking.error();
|
||
return `错误：检测到循环依赖，涉及分镜id: ${cyclicIds.join(", ")}`;
|
||
}
|
||
|
||
thinking.appendText(`图片生成调度计划：共 ${levels.length} 层，${images.length} 张图片`);
|
||
|
||
// --- 准备公共数据 ---
|
||
const projectData = await u.db("o_project").where("id", resTool.data.projectId).select("videoRatio").first();
|
||
const imageModelData = await u.db("o_project").where("id", resTool.data.projectId).select("imageModel", "imageQuality").first();
|
||
|
||
// 生成单张图片的函数
|
||
const generateOneImage = async (item: (typeof images)[0]) => {
|
||
const thinking = msg.thinking(`正在生成分镜 id:${item.id} 图片`);
|
||
// 更新数据库状态为生成中
|
||
await u.db("o_storyboard").where("id", item.id).update({ state: "生成中" });
|
||
// 更新前端为生成中
|
||
socket.emit("setFlowData", {
|
||
key: "setStoryboardImage",
|
||
value: { ...item, id: item.id, src: "", state: "生成中", referenceIds: item.referenceIds },
|
||
});
|
||
|
||
// 获取参考图base64（包括资产图和已生成的分镜参考图）
|
||
const [assetsBase64, referenceBase64] = await Promise.all([
|
||
getAssetsImageBase64(item.assetIds ?? []),
|
||
getStoryboardImageBase64(item.referenceIds),
|
||
]);
|
||
|
||
const imageCls = await u.Ai.Image(imageModelData.imageModel).run({
|
||
prompt: item.prompt,
|
||
imageBase64: [...assetsBase64, ...referenceBase64],
|
||
size: imageModelData.imageQuality,
|
||
aspectRatio: (projectData?.videoRatio as `${number}:${number}`) ?? "16:9",
|
||
taskClass: "生成图片",
|
||
describe: "分镜图片生成",
|
||
relatedObjects: "hhhh",
|
||
projectId: resTool.data.projectId,
|
||
});
|
||
|
||
const savePath = `/${resTool.data.projectId}/storyboard/${u.uuid()}.jpg`;
|
||
await imageCls.save(savePath);
|
||
|
||
// 更新数据库状态为已完成
|
||
await u.db("o_storyboard").where("id", item.id).update({ state: "已完成", filePath: savePath });
|
||
|
||
const obj = {
|
||
...item,
|
||
id: item.id,
|
||
src: await u.oss.getFileUrl(savePath),
|
||
state: "已完成",
|
||
referenceIds: item.referenceIds,
|
||
};
|
||
// 前端对话框提示
|
||
thinking.appendText(`分镜 id:${item.id} 图片生成完成`);
|
||
thinking.complete();
|
||
// 更新前端界面展示
|
||
socket.emit("setFlowData", { key: "setStoryboardImage", value: obj });
|
||
};
|
||
|
||
// --- 按层级顺序执行：同层并行，层间串行 ---
|
||
for (let levelIndex = 0; levelIndex < levels.length; levelIndex++) {
|
||
const levelIds = levels[levelIndex];
|
||
const levelItems = levelIds.map((id) => imageMap.get(id)!);
|
||
const thinking = msg.thinking(
|
||
`开始生成第 ${levelIndex + 1}/${levels.length} 层，共 ${levelItems.length} 张图片 (ids: ${levelIds.join(", ")})`,
|
||
);
|
||
|
||
// 同层内所有图片并行生成，使用 allSettled 确保不会因单张失败中断整层
|
||
const results = await Promise.allSettled(levelItems.map((item) => generateOneImage(item)));
|
||
|
||
// 处理失败的任务
|
||
for (let i = 0; i < results.length; i++) {
|
||
if (results[i].status === "rejected") {
|
||
const failedId = levelIds[i];
|
||
const reason = (results[i] as PromiseRejectedResult).reason;
|
||
console.error(`[tools] 分镜 id:${failedId} 图片生成失败`, reason);
|
||
thinking.appendText(`分镜 id:${failedId} 图片生成失败: ${reason?.message || reason}`);
|
||
await u.db("o_storyboard").where("id", failedId).update({ state: "生成失败" });
|
||
socket.emit("setFlowData", {
|
||
key: "setStoryboardImage",
|
||
value: { id: failedId, src: "", state: "生成失败" },
|
||
});
|
||
}
|
||
}
|
||
thinking.appendText(`第 ${levelIndex + 1}/${levels.length} 层图片生成完成`);
|
||
thinking.complete();
|
||
}
|
||
thinking.appendText("所有分镜图片生成完成");
|
||
thinking.updateTitle("分镜图片生成完成");
|
||
thinking.complete();
|
||
|
||
return "分镜图片生成完成";
|
||
},
|
||
}),
|
||
|
||
//todo 提示词待调
|
||
generate_assets_images: tool({
|
||
description: `
|
||
生成 资产图片 不区分原资产于衍生资产
|
||
参数说明：
|
||
- images: 图片任务数组
|
||
- assetId: 资产id
|
||
- prompt: 图片生成提示词
|
||
示例：
|
||
images:[
|
||
{assetId: 1, prompt: "一张猫的图片"}
|
||
]
|
||
`,
|
||
inputSchema: z.object({
|
||
images: z.array(
|
||
z.object({
|
||
assetId: z.number().describe("衍生资产id"),
|
||
prompt: z.string().describe("提示词"),
|
||
}),
|
||
),
|
||
}),
|
||
execute: async ({ images }) => {
|
||
console.log("[tools] generate_assets_images", images);
|
||
//先获取到前端资产数据
|
||
const flowData: FlowData = await new Promise((resolve) => socket.emit("getFlowData", { key: "assets" }, (res: any) => resolve(res)));
|
||
const assetsData = flowData["assets"];
|
||
const assetsImage: { assetId: number; prompt: string; id?: number }[] = [...images];
|
||
//获取对应的 原资产id
|
||
assetsImage.forEach((item) => {
|
||
for (const i of assetsData) {
|
||
const findData = i.derive.find((m) => m.id == item.assetId);
|
||
if (findData) {
|
||
item.id = findData.id;
|
||
break;
|
||
}
|
||
}
|
||
});
|
||
//获取所设置模型
|
||
const imageModelData = await u.db("o_project").where("id", resTool.data.projectId).select("imageModel", "imageQuality").first();
|
||
for (const item of assetsImage) {
|
||
const [imageId] = await u.db("o_image").insert({
|
||
// 数据库插入图片记录
|
||
assetsId: item.assetId,
|
||
model: imageModelData?.imageModel,
|
||
state: "生成中",
|
||
resolution: imageModelData?.imageQuality,
|
||
});
|
||
u.Ai.Image(imageModelData?.imageModel)
|
||
.run({
|
||
prompt: item.prompt,
|
||
imageBase64: await getAssetsImageBase64(item.id ? [item.id] : []),
|
||
size: imageModelData?.imageQuality,
|
||
aspectRatio: "16:9",
|
||
taskClass: "生成图片",
|
||
describe: "资产图片生成",
|
||
relatedObjects: "hhhh",
|
||
projectId: resTool.data.projectId,
|
||
})
|
||
.then(async (imageCls) => {
|
||
const savePath = `/${resTool.data.projectId}/assets/${u.uuid()}.jpg`;
|
||
await imageCls.save(savePath);
|
||
const obj = {
|
||
...item,
|
||
id: item.assetId,
|
||
src: await u.oss.getFileUrl(savePath),
|
||
state: "已完成",
|
||
};
|
||
//更新对应数据库
|
||
await u.db("o_assets").where("id", item.assetId).update({ imageId: imageId });
|
||
await u.db("o_image").where({ id: imageId }).update({ state: "已完成", filePath: savePath });
|
||
//通知前端更新
|
||
socket.emit("setFlowData", { key: "setAssetsImage", value: obj });
|
||
});
|
||
//通知前端更新状态
|
||
socket.emit("setFlowData", { key: "setAssetsImage", value: { ...item, id: item.assetId, src: "", state: "生成中" } });
|
||
}
|
||
return "资产生成中";
|
||
},
|
||
}),
|
||
};
|
||
|
||
return toolsNames ? Object.fromEntries(Object.entries(tools).filter(([n]) => toolsNames.includes(n))) : tools;
|
||
};
|
||
|
||
// 获取资产图片base64
|
||
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[];
|
||
}
|
||
|
||
//获取分镜图片base64
|
||
async function getStoryboardImageBase64(imageIds: number[]) {
|
||
if (!imageIds.length) return [];
|
||
const storayboardData = await u.db("o_storyboard").whereIn("id", imageIds).select("id", "filePath");
|
||
const imageUrls = await Promise.all(
|
||
storayboardData.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[];
|
||
}
|