forked from 77media/video-flow
67 lines
1.9 KiB
TypeScript
67 lines
1.9 KiB
TypeScript
import { generateCharacterBrief } from "@/api/video_flow";
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import { StoryTemplateEntity } from "../domain/Entities";
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import { getTemplateStoryList } from "@/api/movie_start";
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/**
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* 模板故事用例
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* 负责管理故事模板的获取与操作
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*/
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export class TemplateStoryUseCase {
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/** 故事模板列表 */
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templateStoryList: StoryTemplateEntity[] = [];
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/** 当前选中的故事模板 */
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selectedTemplate: StoryTemplateEntity | null = null;
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constructor() {}
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/**
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* 获取故事模板列表
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* @returns {Promise<StoryTemplateEntity[]>} - 故事模板实体数组
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*/
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async getTemplateStoryList(): Promise<StoryTemplateEntity[]> {
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try {
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const response = await getTemplateStoryList();
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if (response.successful && response.data) {
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this.templateStoryList = response.data.items;
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return response.data.items;
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}
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throw new Error(response.message || "获取故事模板列表失败");
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} catch (error) {
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console.error("获取故事模板列表失败:", error);
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throw error;
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}
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}
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/**
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* 上传人物头像并分析特征，
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* @returns {Promise<{crop_url: string, whisk_caption: string}>} 返回新的头像URL和特征描述
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*/
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async AvatarAndAnalyzeFeatures(
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imageUrl: string
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): Promise<{ crop_url: string; whisk_caption: string }> {
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// 直接在这里处理上传和分析逻辑
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try {
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// 2. 调用AI分析接口获取人物特征描述
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const analysisResult = await generateCharacterBrief({
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image_url: imageUrl,
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});
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if (!analysisResult.successful || !analysisResult.data) {
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throw new Error("人物特征分析失败");
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}
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// 3. 返回新的头像URL和特征描述，用于替换旧数据
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const result = {
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crop_url: imageUrl,
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whisk_caption: JSON.stringify(analysisResult.data.character_brief),
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};
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return result;
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} catch (error) {
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throw error;
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}
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}
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}
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