136 lines
4.8 KiB
TypeScript
136 lines
4.8 KiB
TypeScript
import express from "express";
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import u from "@/utils";
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import { z } from "zod";
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import { v4 as uuidv4 } from "uuid";
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import { success } from "@/lib/responseFormat";
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import { validateFields } from "@/middleware/middleware";
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const router = express.Router();
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export default router.post(
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"/",
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validateFields({
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scriptId: z.number(),
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projectId: z.number(),
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storyboardId: z.number(),
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prompt: z.string(),
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data: z
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.array(
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z.object({
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id: z.number(),
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type: z.string(),
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}),
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)
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.optional(),
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model: z.string(),
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duration: z.number(),
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resolution: z.string(),
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audio: z.boolean().optional(),
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mode: z.string(),
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}),
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async (req, res) => {
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const { scriptId, projectId, storyboardId, prompt, data, model, duration, resolution, audio, mode } = req.body;
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//获取生成视频比例
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const ratio = await u.db("o_project").select("videoRatio").where("id", projectId).first();
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const videoPath = `/${projectId}/video/${uuidv4()}.mp4`; //视频保存路径
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//新增
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const videoData = {
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filePath: videoPath,
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time: Date.now(),
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state: "生成中",
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scriptId,
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storyboardId,
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};
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const [videoId] = await u.db("o_video").insert(videoData);
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//查询分镜是否已有配置
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const config = await u.db("o_videoConfig").where({ storyboardId }).first();
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//保存配置
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if (config) {
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await u
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.db("o_videoConfig")
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.update({ audio, model, mode, data: JSON.stringify(data), resolution, duration, prompt, updateTime: Date.now() })
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.where({ id: config.id });
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} else {
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await u.db("o_videoConfig").insert({
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storyboardId,
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audio,
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model,
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mode,
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data: JSON.stringify(data),
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resolution,
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duration,
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prompt,
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createTime: Date.now(),
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updateTime: Date.now(),
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});
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}
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//查询出图片数据
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const images = await Promise.all(
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data.map(async (item: { id: number; type: string }) => {
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if (item.type === "storyboard") {
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const filePath = await u.db("o_storyboard").where("id", item.id).select("filePath").first();
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return filePath?.filePath;
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}
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if (item.type === "assets") {
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const filePath = await u
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.db("o_assets")
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.where("o_assets.id", item.id)
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.leftJoin("o_image", "o_assets.imageId", "o_image.id")
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.select("o_image.filePath")
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.first();
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return filePath?.filePath;
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}
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}),
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);
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//把images里面的图片转成base64格式
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const base64 = await Promise.all(
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images.map(async (item) => {
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if (!item) return null;
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return await u.oss.getImageBase64(item);
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}),
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);
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res.status(200).send(success(videoId));
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(async () => {
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try {
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const relatedObjects = {
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id: storyboardId,
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projectId,
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type: "视频",
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};
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const systemPrompt = `你是一个专业的视频生成引擎，能够根据用户提供的提示词、图片和参数生成高质量的视频内容。请严格按照用户的需求进行视频创作，确保输出的视频符合以下要求：
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1. 视频内容必须与用户提供的提示词和图片相关联，准确反映用户的创意意图。
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2. 视频质量应达到专业水平，画面清晰、流畅，符合用户指定的分辨率和时长要求。
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3. 视频风格应与用户指定的模式数据相匹配，包括色彩、音乐、特效等元素。
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4. 视频中应包含用户提供的图片，并在视频中适当展示，以增强视频的视觉效果。
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5. 如果用户指定了音频，请确保视频中的音频与视频内容相匹配，符合用户的创意意图。`;
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console.log("%c Line:110 🍑 prompt", "background:#b03734", prompt);
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const aiVideo = u.Ai.Video(model);
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await aiVideo.run({
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projectId,
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prompt,
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imageBase64: base64.filter((item) => item !== null) as string[],
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mode,
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duration,
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aspectRatio: (ratio?.videoRatio as `${number}:${number}`) || "16:9",
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resolution,
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audio,
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taskClass: "视频生成",
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describe: "根据提示词生成视频",
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relatedObjects: JSON.stringify(relatedObjects),
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});
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await aiVideo.save(videoPath);
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await u.db("o_video").where("id", videoId).update({ state: "生成成功" });
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// await u.db("o_videoConfig").where("storyboardId", storyboardId).update({ videoId, updateTime: Date.now() });
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} catch (error: any) {
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await u
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.db("o_video")
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.where("id", videoId)
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.update({
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state: "生成失败",
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errorReason: error instanceof Error ? error.message : "未知错误",
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});
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}
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})();
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},
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);
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