fix: async canvas image generation queue and stabilize runtime
This commit is contained in:
parent
d8a9e15426
commit
598cdfd736
@ -2584,7 +2584,7 @@ export async function POST(request: Request) {
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// 如果时间检查失败,继续执行(避免因检查逻辑错误导致系统不可用)
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}
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const chat = await getChatById({ id });
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let chat = await getChatById({ id });
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let messagesFromDb: DBMessage[] = [];
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if (chat) {
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@ -2598,13 +2598,40 @@ export async function POST(request: Request) {
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message,
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});
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await saveChat({
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id,
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userId: session.user.id,
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title,
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visibility: selectedVisibilityType,
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});
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// New chat - no need to fetch messages, it's empty
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try {
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await saveChat({
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id,
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userId: session.user.id,
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title,
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visibility: selectedVisibilityType,
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});
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} catch (error) {
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const racedChat = await getChatById({ id });
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if (!racedChat) {
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throw error;
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}
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if (racedChat.userId !== session.user.id) {
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return new ChatSDKError("forbidden:chat").toResponse();
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}
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console.warn("[Chat API] saveChat conflicted, reused existing chat:", {
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chatId: id,
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userId: session.user.id,
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});
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}
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chat = await getChatById({ id });
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if (!chat) {
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throw new ChatSDKError("bad_request:database", "Failed to save chat");
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}
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if (chat.userId !== session.user.id) {
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return new ChatSDKError("forbidden:chat").toResponse();
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}
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// In a race scenario another request may have already written messages.
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messagesFromDb = await getMessagesByChatId({ id });
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}
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const uiMessages = [...convertToUIMessages(messagesFromDb), message];
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@ -1,56 +1,87 @@
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import { NextResponse } from "next/server";
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import { auth } from "@/app/(auth)/auth";
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import { getEnabledAiModelsWithProvider, getAiProviderById } from "@/lib/db/queries";
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import { createGeminiImage } from "@/lib/ai/providers/gemini-image";
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import { createAlibabaImage } from "@/lib/ai/providers/alibaba-image";
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import { createRuxaImage } from "@/lib/ai/providers/ruxa-image";
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import { createFalImage } from "@/lib/ai/providers/fal-image";
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import {
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createCanvasImageTask,
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enqueueCanvasImageTask,
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getCanvasImageTaskForUser,
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} from "@/lib/canvas/image-task-queue";
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import {
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generateCanvasImage,
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type CanvasGenerateImageRequest,
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} from "@/lib/canvas/generate-image";
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export const maxDuration = 120;
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interface GenerateImageRequest {
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prompt: string;
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negativePrompt?: string;
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model?: string; // 模型 ID
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aspectRatio?: string; // 宽高比 "1:1", "16:9" 等
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imageCount?: number; // 生成数量
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referenceImage?: string; // 参考图片(用于图生图)
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referenceImages?: string[]; // 多参考图(用于多角度/细节一致性)
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interface GenerateImageRequest extends CanvasGenerateImageRequest {
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async?: boolean;
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}
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interface ParsedImage {
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thumbnailUrl: string;
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originalUrl: string;
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function toGenerateImagePayload(body: GenerateImageRequest): CanvasGenerateImageRequest {
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return {
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prompt: String(body.prompt || "").trim(),
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negativePrompt:
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typeof body.negativePrompt === "string" ? body.negativePrompt : undefined,
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model: typeof body.model === "string" ? body.model : undefined,
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aspectRatio:
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typeof body.aspectRatio === "string" && body.aspectRatio.trim()
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? body.aspectRatio.trim()
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: "1:1",
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imageCount:
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typeof body.imageCount === "number" && Number.isFinite(body.imageCount)
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? body.imageCount
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: 1,
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referenceImage:
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typeof body.referenceImage === "string" ? body.referenceImage : undefined,
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referenceImages: Array.isArray(body.referenceImages)
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? body.referenceImages.map((item) => String(item || "").trim()).filter(Boolean)
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: [],
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};
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}
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function parseImagesFromMarkdown(markdown: string): ParsedImage[] {
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const imageRegex = /!\[([^\]]*)\]\(([^)]+)\)/g;
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const matches = [...markdown.matchAll(imageRegex)];
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const parsed: ParsedImage[] = [];
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for (const match of matches) {
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const altText = match[1] || "";
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const thumbnailUrl = match[2];
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let originalUrl = thumbnailUrl;
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if (altText.includes("thumb|||")) {
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const content = altText.substring(altText.indexOf("thumb|||") + 8);
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const parts = content.split("|||");
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originalUrl = parts[0] || thumbnailUrl;
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} else if (altText.includes("thumb$$")) {
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const content = altText.substring(altText.indexOf("thumb$$") + 7);
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const parts = content.split("$$");
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originalUrl = parts[0] || thumbnailUrl;
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} else if (altText.includes("thumb|")) {
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const content = altText.substring(altText.indexOf("thumb|") + 6);
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const parts = content.split("|");
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originalUrl = parts[0] || thumbnailUrl;
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export async function GET(request: Request) {
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try {
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const session = await auth();
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if (!session?.user?.id) {
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return NextResponse.json({ success: false, error: "未登录" }, { status: 401 });
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}
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parsed.push({ thumbnailUrl, originalUrl });
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}
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const { searchParams } = new URL(request.url);
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const taskId = String(searchParams.get("taskId") || "").trim();
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if (!taskId) {
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return NextResponse.json(
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{ success: false, error: "缺少 taskId 参数" },
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{ status: 400 }
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);
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}
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return parsed;
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const task = await getCanvasImageTaskForUser({ taskId, userId: session.user.id });
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if (!task) {
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return NextResponse.json({ success: false, error: "任务不存在" }, { status: 404 });
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}
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return NextResponse.json({
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success: true,
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task: {
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id: task.id,
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status: task.status,
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attempts: task.attempts,
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error: task.error || null,
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result: task.result || null,
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createdAt: task.createdAt,
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startedAt: task.startedAt,
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completedAt: task.completedAt,
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},
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});
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} catch (error) {
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console.error("[Canvas Generate Image][TaskStatus] Error:", error);
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return NextResponse.json(
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{
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success: false,
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error: error instanceof Error ? error.message : "查询任务失败",
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},
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{ status: 500 }
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);
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}
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}
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export async function POST(request: Request) {
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@ -64,160 +95,33 @@ export async function POST(request: Request) {
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}
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const body: GenerateImageRequest = await request.json();
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const {
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prompt,
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negativePrompt,
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model,
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aspectRatio = "1:1",
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imageCount = 1,
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referenceImage,
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referenceImages,
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} = body;
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if (!prompt) {
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const payload = toGenerateImagePayload(body);
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if (!payload.prompt) {
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return NextResponse.json(
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{ success: false, error: "请输入提示词" },
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{ status: 400 }
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);
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}
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// 获取可用的图片生成模型(筛选 supportsImageGen 的模型)
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const allModels = await getEnabledAiModelsWithProvider();
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const imageModels = allModels.filter(m => m.model.supportsImageGen);
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if (!imageModels || imageModels.length === 0) {
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return NextResponse.json(
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{ success: false, error: "暂无可用的图片生成模型" },
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{ status: 400 }
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);
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}
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// 选择模型(如果指定了 model,使用指定的;否则使用默认的)
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let selectedModel = model
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? imageModels.find(m => m.model.modelId === model || m.model.id === model)
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: imageModels.find(m => m.model.isDefault) || imageModels[0];
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if (!selectedModel) {
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selectedModel = imageModels[0];
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}
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const provider = await getAiProviderById({ id: selectedModel.model.providerId });
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if (!provider) {
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return NextResponse.json(
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{ success: false, error: "模型提供商配置错误" },
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{ status: 500 }
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);
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}
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const normalizedReferenceImages = Array.from(
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new Set(
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[
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...(Array.isArray(referenceImages) ? referenceImages : []),
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...(referenceImage ? [referenceImage] : []),
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]
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.map((item) => String(item || "").trim())
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.filter((url) => /^https?:\/\//i.test(url))
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)
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).slice(0, 12);
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// 构建消息
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const messages = [{
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role: "user" as const,
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content: normalizedReferenceImages.length > 0
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? [
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{ type: "text" as const, text: prompt },
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...normalizedReferenceImages.map((url) => ({
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type: "image_url" as const,
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image_url: { url },
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})),
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]
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: prompt,
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}];
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// 图片参数
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const imageParams = {
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aspectRatio,
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imageSize: "2K",
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imageCount,
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negativePrompt,
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};
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let imageMarkdown = "";
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// 根据提供商类型调用不同的生成器
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if (provider.type === "gemini") {
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const geminiProvider = createGeminiImage({
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apiKey: provider.apiKey,
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baseURL: provider.baseUrl,
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const asyncMode = body.async === true;
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if (asyncMode) {
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const task = await createCanvasImageTask({
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userId: session.user.id,
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request: payload,
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});
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const model = geminiProvider.chat(selectedModel.model.modelId);
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const result = await model.doGenerate({
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messages,
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imageParams,
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});
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imageMarkdown = result.text || "";
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} else if (provider.type === "alibaba-image") {
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const alibabaProvider = createAlibabaImage({
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apiKey: provider.apiKey,
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baseURL: provider.baseUrl,
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});
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const model = alibabaProvider.chat(selectedModel.model.modelId);
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const result = await model.doGenerate({
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messages,
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imageParams,
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});
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imageMarkdown = result.text || "";
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} else if (provider.type === "ruxa-image") {
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const ruxaProvider = createRuxaImage({
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apiKey: provider.apiKey,
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baseURL: provider.baseUrl,
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});
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const model = ruxaProvider.chat(selectedModel.model.modelId);
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const result = await model.doGenerate({
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messages,
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imageParams,
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});
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imageMarkdown = result.text || "";
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} else if (provider.type === "fal-image") {
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const falProvider = createFalImage({
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apiKey: provider.apiKey,
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baseURL: provider.baseUrl,
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});
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const model = falProvider.chat(selectedModel.model.modelId);
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const result = await model.doGenerate({
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messages,
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imageParams,
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});
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imageMarkdown = result.text || "";
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} else {
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return NextResponse.json(
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{ success: false, error: "不支持的图片生成模型类型" },
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{ status: 400 }
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);
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}
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const parsedImages = parseImagesFromMarkdown(imageMarkdown);
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if (parsedImages.length > 0) {
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await enqueueCanvasImageTask(task.id);
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return NextResponse.json({
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success: true,
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data: {
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images: parsedImages,
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model: selectedModel.model.displayName,
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prompt,
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}
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taskId: task.id,
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status: task.status,
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});
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} else {
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return NextResponse.json(
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{ success: false, error: "图片生成失败" },
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{ status: 500 }
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);
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}
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const result = await generateCanvasImage(payload);
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return NextResponse.json({
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success: true,
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data: result,
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});
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} catch (error) {
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console.error("[Canvas Generate Image] Error:", error);
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return NextResponse.json(
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@ -6,13 +6,30 @@ const ALLOWED_FAL_HOSTS = new Set(["rest.alpha.fal.ai", "rest.fal.ai"]);
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type FalRealtimeConfig = {
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enabled?: boolean;
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falApiKey?: string;
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apiKey?: string;
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};
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type AngleEditConfig = {
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falApiKey?: string;
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};
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async function getRealtimeCanvasConfig() {
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const realtimeSetting = await getSystemSetting({ key: "realtime_canvas_config" }).catch(
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() => null
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);
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return (realtimeSetting?.value || {}) as FalRealtimeConfig;
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const [realtimeSetting, angleEditSetting] = await Promise.all([
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getSystemSetting({ key: "realtime_canvas_config" }).catch(() => null),
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getSystemSetting({ key: "angle_edit_config" }).catch(() => null),
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]);
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const realtimeConfig = (realtimeSetting?.value || {}) as FalRealtimeConfig;
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const angleEditConfig = (angleEditSetting?.value || {}) as AngleEditConfig;
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const fallbackKey = String(
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angleEditConfig.falApiKey || process.env.FAL_KEY || process.env.FAL_API_KEY || ""
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).trim();
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return {
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...realtimeConfig,
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falApiKey:
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String(realtimeConfig.falApiKey || realtimeConfig.apiKey || "").trim() || fallbackKey,
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} as FalRealtimeConfig;
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}
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async function handleProxy(request: Request) {
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@ -4,6 +4,7 @@ import { getSystemSetting } from "@/lib/db/queries";
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type RealtimeCanvasConfig = {
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enabled?: boolean;
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falApiKey?: string;
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apiKey?: string;
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throttleInterval?: number;
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maxBuffering?: number;
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maxInputResolution?: number;
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@ -16,6 +17,10 @@ type RealtimeCanvasConfig = {
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};
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};
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type AngleEditConfig = {
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falApiKey?: string;
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};
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const defaultConfig = {
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session: {
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idleTimeoutMs: 120000,
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@ -57,8 +62,12 @@ export async function GET() {
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return Response.json({ code: "UNAUTHORIZED", message: "请先登录" }, { status: 401 });
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}
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const setting = await getSystemSetting({ key: "realtime_canvas_config" }).catch(() => null);
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const [setting, angleEditSetting] = await Promise.all([
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getSystemSetting({ key: "realtime_canvas_config" }).catch(() => null),
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getSystemSetting({ key: "angle_edit_config" }).catch(() => null),
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]);
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const config = (setting?.value || {}) as RealtimeCanvasConfig;
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const angleEditConfig = (angleEditSetting?.value || {}) as AngleEditConfig;
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if (config.enabled === false) {
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return Response.json(
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@ -67,7 +76,16 @@ export async function GET() {
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);
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}
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if (!String(config.falApiKey || "").trim()) {
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const falApiKey = String(
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config.falApiKey ||
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config.apiKey ||
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angleEditConfig.falApiKey ||
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process.env.FAL_KEY ||
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process.env.FAL_API_KEY ||
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""
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).trim();
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if (!falApiKey) {
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return Response.json(
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{
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code: "FAL_KEY_MISSING",
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@ -336,6 +336,85 @@ const CANVAS_AGENT_SECTION_TITLES = new Set([
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"执行计划",
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"输出设置",
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]);
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const CANVAS_IMAGE_TASK_POLL_INTERVAL_MS = 1600;
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const CANVAS_IMAGE_TASK_TIMEOUT_MS = 4 * 60 * 1000;
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type CanvasImageGenerationRequest = {
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prompt: string;
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model?: string;
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aspectRatio?: string;
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imageCount?: number;
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negativePrompt?: string;
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referenceImage?: string;
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referenceImages?: string[];
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};
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function sleep(ms: number) {
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return new Promise((resolve) => window.setTimeout(resolve, ms));
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}
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async function requestCanvasImageGeneration(
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payload: CanvasImageGenerationRequest
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): Promise<{ images: Array<{ originalUrl?: string; thumbnailUrl?: string }> }> {
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const createResponse = await fetch("/api/canvas/generate/image", {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({
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...payload,
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async: true,
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}),
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});
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const createResult = await createResponse.json().catch(() => ({}));
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if (!createResponse.ok || !createResult?.success) {
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throw new Error(createResult?.error || "创建生图任务失败");
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}
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if (Array.isArray(createResult?.data?.images) && createResult.data.images.length > 0) {
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return { images: createResult.data.images };
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}
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const taskId = String(createResult?.taskId || "").trim();
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||||
if (!taskId) {
|
||||
throw new Error("创建生图任务失败:未返回任务ID");
|
||||
}
|
||||
|
||||
const deadline = Date.now() + CANVAS_IMAGE_TASK_TIMEOUT_MS;
|
||||
let lastError = "";
|
||||
|
||||
while (Date.now() < deadline) {
|
||||
await sleep(CANVAS_IMAGE_TASK_POLL_INTERVAL_MS);
|
||||
|
||||
const statusResponse = await fetch(
|
||||
`/api/canvas/generate/image?taskId=${encodeURIComponent(taskId)}`,
|
||||
{ cache: "no-store" }
|
||||
);
|
||||
const statusResult = await statusResponse.json().catch(() => ({}));
|
||||
|
||||
if (!statusResponse.ok || !statusResult?.success) {
|
||||
lastError = statusResult?.error || `查询任务失败(${statusResponse.status})`;
|
||||
continue;
|
||||
}
|
||||
|
||||
const task = statusResult?.task;
|
||||
const status = String(task?.status || "").trim();
|
||||
|
||||
if (status === "succeeded") {
|
||||
const result = task?.result || {};
|
||||
const images = Array.isArray(result?.images) ? result.images : [];
|
||||
if (images.length === 0) {
|
||||
throw new Error("任务完成但未返回图片");
|
||||
}
|
||||
return { images };
|
||||
}
|
||||
|
||||
if (status === "failed") {
|
||||
throw new Error(String(task?.error || "图片生成失败"));
|
||||
}
|
||||
}
|
||||
|
||||
throw new Error(lastError || "图片生成超时,请稍后重试");
|
||||
}
|
||||
|
||||
type CanvasAnalysisSection = {
|
||||
before: string;
|
||||
@ -3897,24 +3976,19 @@ export function CanvasChatPanel({ chatId, initialMessages = [], onClose, onOpenF
|
||||
...generationReferenceImagesBase,
|
||||
...extraReferenceImages,
|
||||
].filter(Boolean);
|
||||
const response = await fetch("/api/canvas/generate/image", {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({
|
||||
prompt: promptOverride,
|
||||
model: modelForGeneration,
|
||||
aspectRatio: "9:16",
|
||||
imageCount: 1,
|
||||
negativePrompt: imageParams.negativePrompt,
|
||||
referenceImage: productAttachments[0]?.url,
|
||||
referenceImages: generationReferenceImages,
|
||||
}),
|
||||
const result = await requestCanvasImageGeneration({
|
||||
prompt: promptOverride,
|
||||
model: modelForGeneration,
|
||||
aspectRatio: "9:16",
|
||||
imageCount: 1,
|
||||
negativePrompt: imageParams.negativePrompt,
|
||||
referenceImage: productAttachments[0]?.url,
|
||||
referenceImages: generationReferenceImages,
|
||||
});
|
||||
const result = await response.json();
|
||||
if (!response.ok || !result?.success || !Array.isArray(result?.data?.images) || result.data.images.length === 0) {
|
||||
throw new Error(result?.error || `第 ${index + 1} 张生成失败`);
|
||||
if (!Array.isArray(result?.images) || result.images.length === 0) {
|
||||
throw new Error(`第 ${index + 1} 张生成失败`);
|
||||
}
|
||||
const generatedImage = result.data.images[0];
|
||||
const generatedImage = result.images[0];
|
||||
return {
|
||||
originalUrl: String(generatedImage?.originalUrl || generatedImage?.thumbnailUrl || "").trim(),
|
||||
thumbnailUrl: String(generatedImage?.thumbnailUrl || generatedImage?.originalUrl || "").trim(),
|
||||
@ -4148,24 +4222,17 @@ export function CanvasChatPanel({ chatId, initialMessages = [], onClose, onOpenF
|
||||
...(bundleAttachments.length ? bundleAttachments.map((item) => item.url) : []),
|
||||
].filter(Boolean);
|
||||
|
||||
const reviewResponse = await fetch("/api/canvas/generate/image", {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({
|
||||
prompt: reviewPrompt,
|
||||
model: modelForGeneration,
|
||||
aspectRatio: "1:1",
|
||||
imageCount: DETAIL_REVIEW_IMAGE_COUNT,
|
||||
negativePrompt: imageParams.negativePrompt,
|
||||
referenceImage: productAttachments[0]?.url,
|
||||
referenceImages: reviewReferenceImages,
|
||||
}),
|
||||
const reviewResult = await requestCanvasImageGeneration({
|
||||
prompt: reviewPrompt,
|
||||
model: modelForGeneration,
|
||||
aspectRatio: "1:1",
|
||||
imageCount: DETAIL_REVIEW_IMAGE_COUNT,
|
||||
negativePrompt: imageParams.negativePrompt,
|
||||
referenceImage: productAttachments[0]?.url,
|
||||
referenceImages: reviewReferenceImages,
|
||||
});
|
||||
const reviewResult = await reviewResponse.json();
|
||||
const reviewImagesRaw = Array.isArray(reviewResult?.data?.images)
|
||||
? reviewResult.data.images
|
||||
: [];
|
||||
if (!reviewResponse.ok || !reviewResult?.success || reviewImagesRaw.length === 0) {
|
||||
const reviewImagesRaw = Array.isArray(reviewResult?.images) ? reviewResult.images : [];
|
||||
if (reviewImagesRaw.length === 0) {
|
||||
reviewFailures.push(`评价${reviewIndex + 1}生成失败`);
|
||||
continue;
|
||||
}
|
||||
@ -4501,24 +4568,17 @@ export function CanvasChatPanel({ chatId, initialMessages = [], onClose, onOpenF
|
||||
...(bundleAttachments.length ? bundleAttachments.map((item) => item.url) : []),
|
||||
].filter(Boolean);
|
||||
|
||||
const reviewResponse = await fetch("/api/canvas/generate/image", {
|
||||
method: "POST",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({
|
||||
prompt: reviewPrompt,
|
||||
model: modelForGeneration,
|
||||
aspectRatio: "1:1",
|
||||
imageCount: DETAIL_REVIEW_IMAGE_COUNT,
|
||||
negativePrompt: imageParams.negativePrompt,
|
||||
referenceImage: productAttachments[0]?.url,
|
||||
referenceImages: reviewReferenceImages,
|
||||
}),
|
||||
const reviewResult = await requestCanvasImageGeneration({
|
||||
prompt: reviewPrompt,
|
||||
model: modelForGeneration,
|
||||
aspectRatio: "1:1",
|
||||
imageCount: DETAIL_REVIEW_IMAGE_COUNT,
|
||||
negativePrompt: imageParams.negativePrompt,
|
||||
referenceImage: productAttachments[0]?.url,
|
||||
referenceImages: reviewReferenceImages,
|
||||
});
|
||||
const reviewResult = await reviewResponse.json();
|
||||
const reviewImagesRaw = Array.isArray(reviewResult?.data?.images)
|
||||
? reviewResult.data.images
|
||||
: [];
|
||||
if (!reviewResponse.ok || !reviewResult?.success || reviewImagesRaw.length === 0) {
|
||||
const reviewImagesRaw = Array.isArray(reviewResult?.images) ? reviewResult.images : [];
|
||||
if (reviewImagesRaw.length === 0) {
|
||||
reviewFailures.push(`第${reviewIndex + 1}条生成失败`);
|
||||
continue;
|
||||
}
|
||||
|
||||
@ -35,6 +35,7 @@ import {
|
||||
Download,
|
||||
Undo2,
|
||||
Redo2,
|
||||
Send,
|
||||
} from "lucide-react";
|
||||
import { toast } from "sonner";
|
||||
|
||||
@ -101,9 +102,15 @@ const defaultRealtimeConfig: RealtimeConfig = {
|
||||
|
||||
function buildImageDataUrl(image: any) {
|
||||
if (!image) return "";
|
||||
if (typeof image === "string" && image.trim()) {
|
||||
return image;
|
||||
}
|
||||
if (typeof image.url === "string" && image.url.trim()) {
|
||||
return image.url;
|
||||
}
|
||||
if (typeof image.image_url === "string" && image.image_url.trim()) {
|
||||
return image.image_url;
|
||||
}
|
||||
if (typeof image.content === "string" && image.content.trim()) {
|
||||
if (image.content.startsWith("data:")) {
|
||||
return image.content;
|
||||
@ -162,6 +169,7 @@ export function RealtimeCanvasDialog({
|
||||
open,
|
||||
onOpenChange,
|
||||
initialImageUrl,
|
||||
onApplyResult,
|
||||
}: RealtimeCanvasDialogProps) {
|
||||
const canvasRef = useRef<HTMLCanvasElement | null>(null);
|
||||
const previewCanvasRef = useRef<HTMLCanvasElement | null>(null);
|
||||
@ -402,11 +410,11 @@ export function RealtimeCanvasDialog({
|
||||
}, [saveHistory]);
|
||||
|
||||
const drawInitialImage = useCallback(async () => {
|
||||
if (!open || !initialImageUrl || hasLoadedInitialImageRef.current) return;
|
||||
if (!open || !initialImageUrl || hasLoadedInitialImageRef.current) return false;
|
||||
const canvas = canvasRef.current;
|
||||
if (!canvas) return;
|
||||
if (!canvas) return false;
|
||||
const ctx = canvas.getContext("2d");
|
||||
if (!ctx) return;
|
||||
if (!ctx) return false;
|
||||
|
||||
const image = new Image();
|
||||
image.crossOrigin = "anonymous";
|
||||
@ -426,6 +434,7 @@ export function RealtimeCanvasDialog({
|
||||
hasLoadedInitialImageRef.current = true;
|
||||
dirtyRef.current = true;
|
||||
saveHistory(); // Save initial image state
|
||||
return true;
|
||||
}, [initialImageUrl, open, saveHistory]);
|
||||
|
||||
const initializeCanvas = useCallback(() => {
|
||||
@ -666,8 +675,10 @@ export function RealtimeCanvasDialog({
|
||||
useEffect(() => {
|
||||
if (!open) return;
|
||||
initializeCanvas();
|
||||
void drawInitialImage().then(() => {
|
||||
scheduleFlush(true, false);
|
||||
void drawInitialImage().then((hasInitialImage) => {
|
||||
if (hasInitialImage) {
|
||||
scheduleFlush(true, false);
|
||||
}
|
||||
});
|
||||
const onResize = () => initializeCanvas();
|
||||
window.addEventListener("resize", onResize);
|
||||
@ -760,9 +771,14 @@ export function RealtimeCanvasDialog({
|
||||
return;
|
||||
}
|
||||
|
||||
const latestImage = Array.isArray(result?.images)
|
||||
? result.images[result.images.length - 1]
|
||||
: null;
|
||||
const imageGroups = [result?.images, result?.output?.images, result?.data?.images];
|
||||
const firstImageGroup = imageGroups.find((group) => Array.isArray(group)) as any[] | undefined;
|
||||
const latestImage =
|
||||
(firstImageGroup && firstImageGroup[firstImageGroup.length - 1]) ||
|
||||
result?.image ||
|
||||
result?.output?.image ||
|
||||
result?.data?.image ||
|
||||
null;
|
||||
const nextPreviewUrl = buildImageDataUrl(latestImage);
|
||||
if (!nextPreviewUrl) return;
|
||||
|
||||
@ -947,6 +963,19 @@ export function RealtimeCanvasDialog({
|
||||
}
|
||||
}, []);
|
||||
|
||||
const handleApplyToCanvas = useCallback(() => {
|
||||
if (!previewUrl) {
|
||||
toast.error("请先生成预览结果");
|
||||
return;
|
||||
}
|
||||
|
||||
onApplyResult({
|
||||
imageUrl: previewUrl,
|
||||
prompt: prompt.trim() || FALLBACK_PROMPT,
|
||||
});
|
||||
onOpenChange(false);
|
||||
}, [onApplyResult, onOpenChange, previewUrl, prompt]);
|
||||
|
||||
return (
|
||||
<Dialog open={open} onOpenChange={onOpenChange}>
|
||||
<DialogContent className="h-[95vh] w-[98vw] max-w-[1800px] overflow-hidden rounded-[20px] border-0 bg-background p-0 shadow-2xl sm:rounded-[20px] md:rounded-[24px]">
|
||||
@ -1259,6 +1288,16 @@ export function RealtimeCanvasDialog({
|
||||
>
|
||||
{status === 'connecting' ? <Loader2 className="h-4 w-4 animate-spin" /> : 'Generate'}
|
||||
</Button>
|
||||
<Button
|
||||
size="sm"
|
||||
variant="outline"
|
||||
className="h-9 rounded-xl px-4 font-medium"
|
||||
onClick={handleApplyToCanvas}
|
||||
disabled={!previewUrl}
|
||||
>
|
||||
<Send className="h-4 w-4 mr-1.5" />
|
||||
发送到画布
|
||||
</Button>
|
||||
</div>
|
||||
</div>
|
||||
<div className="text-center mt-2">
|
||||
|
||||
@ -16,10 +16,9 @@ module.exports = {
|
||||
log_date_format: "YYYY-MM-DD HH:mm:ss Z",
|
||||
merge_logs: true,
|
||||
autorestart: true,
|
||||
max_memory_restart: "1G",
|
||||
max_memory_restart: "3G",
|
||||
watch: false,
|
||||
ignore_watch: ["node_modules", ".next", ".git"],
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
|
||||
187
lib/canvas/generate-image.ts
Normal file
187
lib/canvas/generate-image.ts
Normal file
@ -0,0 +1,187 @@
|
||||
import "server-only";
|
||||
|
||||
import { getEnabledAiModelsWithProvider, getAiProviderById } from "@/lib/db/queries";
|
||||
import { createGeminiImage } from "@/lib/ai/providers/gemini-image";
|
||||
import { createAlibabaImage } from "@/lib/ai/providers/alibaba-image";
|
||||
import { createRuxaImage } from "@/lib/ai/providers/ruxa-image";
|
||||
import { createFalImage } from "@/lib/ai/providers/fal-image";
|
||||
|
||||
export interface CanvasGenerateImageRequest {
|
||||
prompt: string;
|
||||
negativePrompt?: string;
|
||||
model?: string;
|
||||
aspectRatio?: string;
|
||||
imageCount?: number;
|
||||
referenceImage?: string;
|
||||
referenceImages?: string[];
|
||||
}
|
||||
|
||||
export interface ParsedImage {
|
||||
thumbnailUrl: string;
|
||||
originalUrl: string;
|
||||
}
|
||||
|
||||
export interface CanvasGenerateImageResult {
|
||||
images: ParsedImage[];
|
||||
model: string;
|
||||
prompt: string;
|
||||
}
|
||||
|
||||
function parseImagesFromMarkdown(markdown: string): ParsedImage[] {
|
||||
const imageRegex = /!\[([^\]]*)\]\(([^)]+)\)/g;
|
||||
const matches = [...markdown.matchAll(imageRegex)];
|
||||
const parsed: ParsedImage[] = [];
|
||||
|
||||
for (const match of matches) {
|
||||
const altText = match[1] || "";
|
||||
const thumbnailUrl = match[2];
|
||||
let originalUrl = thumbnailUrl;
|
||||
|
||||
if (altText.includes("thumb|||")) {
|
||||
const content = altText.substring(altText.indexOf("thumb|||") + 8);
|
||||
const parts = content.split("|||");
|
||||
originalUrl = parts[0] || thumbnailUrl;
|
||||
} else if (altText.includes("thumb$$")) {
|
||||
const content = altText.substring(altText.indexOf("thumb$$") + 7);
|
||||
const parts = content.split("$$");
|
||||
originalUrl = parts[0] || thumbnailUrl;
|
||||
} else if (altText.includes("thumb|")) {
|
||||
const content = altText.substring(altText.indexOf("thumb|") + 6);
|
||||
const parts = content.split("|");
|
||||
originalUrl = parts[0] || thumbnailUrl;
|
||||
}
|
||||
|
||||
parsed.push({ thumbnailUrl, originalUrl });
|
||||
}
|
||||
|
||||
return parsed;
|
||||
}
|
||||
|
||||
export async function generateCanvasImage(
|
||||
request: CanvasGenerateImageRequest
|
||||
): Promise<CanvasGenerateImageResult> {
|
||||
const prompt = String(request.prompt || "").trim();
|
||||
if (!prompt) {
|
||||
throw new Error("请输入提示词");
|
||||
}
|
||||
|
||||
const negativePrompt =
|
||||
typeof request.negativePrompt === "string" ? request.negativePrompt : undefined;
|
||||
const model = typeof request.model === "string" ? request.model : undefined;
|
||||
const aspectRatio =
|
||||
typeof request.aspectRatio === "string" && request.aspectRatio.trim()
|
||||
? request.aspectRatio.trim()
|
||||
: "1:1";
|
||||
const imageCount =
|
||||
typeof request.imageCount === "number" && Number.isFinite(request.imageCount)
|
||||
? Math.max(1, Math.min(8, Math.floor(request.imageCount)))
|
||||
: 1;
|
||||
const referenceImage =
|
||||
typeof request.referenceImage === "string" ? request.referenceImage : undefined;
|
||||
const referenceImages = Array.isArray(request.referenceImages)
|
||||
? request.referenceImages
|
||||
: [];
|
||||
|
||||
const allModels = await getEnabledAiModelsWithProvider();
|
||||
const imageModels = allModels.filter((m) => m.model.supportsImageGen);
|
||||
|
||||
if (!imageModels || imageModels.length === 0) {
|
||||
throw new Error("暂无可用的图片生成模型");
|
||||
}
|
||||
|
||||
let selectedModel = model
|
||||
? imageModels.find((m) => m.model.modelId === model || m.model.id === model)
|
||||
: imageModels.find((m) => m.model.isDefault) || imageModels[0];
|
||||
|
||||
if (!selectedModel) {
|
||||
selectedModel = imageModels[0];
|
||||
}
|
||||
|
||||
const provider = await getAiProviderById({ id: selectedModel.model.providerId });
|
||||
if (!provider) {
|
||||
throw new Error("模型提供商配置错误");
|
||||
}
|
||||
|
||||
const normalizedReferenceImages = Array.from(
|
||||
new Set(
|
||||
[
|
||||
...referenceImages,
|
||||
...(referenceImage ? [referenceImage] : []),
|
||||
]
|
||||
.map((item) => String(item || "").trim())
|
||||
.filter((url) => /^https?:\/\//i.test(url))
|
||||
)
|
||||
).slice(0, 12);
|
||||
|
||||
const messages = [
|
||||
{
|
||||
role: "user" as const,
|
||||
content:
|
||||
normalizedReferenceImages.length > 0
|
||||
? [
|
||||
{ type: "text" as const, text: prompt },
|
||||
...normalizedReferenceImages.map((url) => ({
|
||||
type: "image_url" as const,
|
||||
image_url: { url },
|
||||
})),
|
||||
]
|
||||
: prompt,
|
||||
},
|
||||
];
|
||||
|
||||
const imageParams = {
|
||||
aspectRatio,
|
||||
imageSize: "2K",
|
||||
imageCount,
|
||||
negativePrompt,
|
||||
};
|
||||
|
||||
let imageMarkdown = "";
|
||||
|
||||
if (provider.type === "gemini") {
|
||||
const geminiProvider = createGeminiImage({
|
||||
apiKey: provider.apiKey,
|
||||
baseURL: provider.baseUrl,
|
||||
});
|
||||
const modelInstance = geminiProvider.chat(selectedModel.model.modelId);
|
||||
const result = await modelInstance.doGenerate({ messages, imageParams });
|
||||
imageMarkdown = result.text || "";
|
||||
} else if (provider.type === "alibaba-image") {
|
||||
const alibabaProvider = createAlibabaImage({
|
||||
apiKey: provider.apiKey,
|
||||
baseURL: provider.baseUrl,
|
||||
});
|
||||
const modelInstance = alibabaProvider.chat(selectedModel.model.modelId);
|
||||
const result = await modelInstance.doGenerate({ messages, imageParams });
|
||||
imageMarkdown = result.text || "";
|
||||
} else if (provider.type === "ruxa-image") {
|
||||
const ruxaProvider = createRuxaImage({
|
||||
apiKey: provider.apiKey,
|
||||
baseURL: provider.baseUrl,
|
||||
});
|
||||
const modelInstance = ruxaProvider.chat(selectedModel.model.modelId);
|
||||
const result = await modelInstance.doGenerate({ messages, imageParams });
|
||||
imageMarkdown = result.text || "";
|
||||
} else if (provider.type === "fal-image") {
|
||||
const falProvider = createFalImage({
|
||||
apiKey: provider.apiKey,
|
||||
baseURL: provider.baseUrl,
|
||||
});
|
||||
const modelInstance = falProvider.chat(selectedModel.model.modelId);
|
||||
const result = await modelInstance.doGenerate({ messages, imageParams });
|
||||
imageMarkdown = result.text || "";
|
||||
} else {
|
||||
throw new Error("不支持的图片生成模型类型");
|
||||
}
|
||||
|
||||
const parsedImages = parseImagesFromMarkdown(imageMarkdown);
|
||||
if (parsedImages.length === 0) {
|
||||
throw new Error("图片生成失败");
|
||||
}
|
||||
|
||||
return {
|
||||
images: parsedImages,
|
||||
model: selectedModel.model.displayName,
|
||||
prompt,
|
||||
};
|
||||
}
|
||||
238
lib/canvas/image-task-queue.ts
Normal file
238
lib/canvas/image-task-queue.ts
Normal file
@ -0,0 +1,238 @@
|
||||
import "server-only";
|
||||
|
||||
import { and, asc, eq, lt, notInArray, sql } from "drizzle-orm";
|
||||
import { db } from "@/lib/db";
|
||||
import { canvasImageTask } from "@/lib/db/schema";
|
||||
import {
|
||||
generateCanvasImage,
|
||||
type CanvasGenerateImageRequest,
|
||||
type CanvasGenerateImageResult,
|
||||
} from "./generate-image";
|
||||
|
||||
type CanvasImageTaskStatus = "pending" | "running" | "succeeded" | "failed";
|
||||
|
||||
interface QueueState {
|
||||
pending: string[];
|
||||
pendingSet: Set<string>;
|
||||
running: Set<string>;
|
||||
draining: boolean;
|
||||
}
|
||||
|
||||
const DEFAULT_CONCURRENCY = 1;
|
||||
const STALE_RUNNING_MS = 5 * 60 * 1000;
|
||||
const queueStateKey = "__canvas_image_task_queue_state__";
|
||||
|
||||
function getQueueConcurrency(): number {
|
||||
const raw = Number.parseInt(process.env.CANVAS_IMAGE_TASK_CONCURRENCY || "", 10);
|
||||
if (Number.isFinite(raw) && raw > 0) {
|
||||
return Math.min(raw, 4);
|
||||
}
|
||||
return DEFAULT_CONCURRENCY;
|
||||
}
|
||||
|
||||
function getQueueState(): QueueState {
|
||||
const globalObj = globalThis as typeof globalThis & {
|
||||
[queueStateKey]?: QueueState;
|
||||
};
|
||||
if (!globalObj[queueStateKey]) {
|
||||
globalObj[queueStateKey] = {
|
||||
pending: [],
|
||||
pendingSet: new Set<string>(),
|
||||
running: new Set<string>(),
|
||||
draining: false,
|
||||
};
|
||||
}
|
||||
return globalObj[queueStateKey] as QueueState;
|
||||
}
|
||||
|
||||
function enqueueLocalTask(taskId: string) {
|
||||
const state = getQueueState();
|
||||
if (!taskId || state.running.has(taskId) || state.pendingSet.has(taskId)) {
|
||||
return;
|
||||
}
|
||||
state.pending.push(taskId);
|
||||
state.pendingSet.add(taskId);
|
||||
}
|
||||
|
||||
async function claimNextPendingTask(): Promise<string | null> {
|
||||
const state = getQueueState();
|
||||
while (state.pending.length > 0) {
|
||||
const taskId = state.pending.shift();
|
||||
if (!taskId) continue;
|
||||
state.pendingSet.delete(taskId);
|
||||
if (!state.running.has(taskId)) {
|
||||
return taskId;
|
||||
}
|
||||
}
|
||||
|
||||
const runningIds = Array.from(state.running);
|
||||
const whereCondition =
|
||||
runningIds.length > 0
|
||||
? and(eq(canvasImageTask.status, "pending"), notInArray(canvasImageTask.id, runningIds))
|
||||
: eq(canvasImageTask.status, "pending");
|
||||
|
||||
const rows = await db
|
||||
.select({ id: canvasImageTask.id })
|
||||
.from(canvasImageTask)
|
||||
.where(whereCondition)
|
||||
.orderBy(asc(canvasImageTask.createdAt))
|
||||
.limit(1);
|
||||
|
||||
return rows[0]?.id ?? null;
|
||||
}
|
||||
|
||||
async function runSingleTask(taskId: string) {
|
||||
const state = getQueueState();
|
||||
state.running.add(taskId);
|
||||
|
||||
try {
|
||||
const [task] = await db
|
||||
.update(canvasImageTask)
|
||||
.set({
|
||||
status: "running",
|
||||
startedAt: new Date(),
|
||||
updatedAt: new Date(),
|
||||
completedAt: null,
|
||||
error: null,
|
||||
attempts: sql`${canvasImageTask.attempts} + 1`,
|
||||
})
|
||||
.where(and(eq(canvasImageTask.id, taskId), eq(canvasImageTask.status, "pending")))
|
||||
.returning({
|
||||
id: canvasImageTask.id,
|
||||
request: canvasImageTask.request,
|
||||
});
|
||||
|
||||
if (!task) {
|
||||
return;
|
||||
}
|
||||
|
||||
const result = await generateCanvasImage(task.request as CanvasGenerateImageRequest);
|
||||
await db
|
||||
.update(canvasImageTask)
|
||||
.set({
|
||||
status: "succeeded",
|
||||
result: result as CanvasGenerateImageResult,
|
||||
error: null,
|
||||
completedAt: new Date(),
|
||||
updatedAt: new Date(),
|
||||
})
|
||||
.where(eq(canvasImageTask.id, taskId));
|
||||
} catch (error) {
|
||||
await db
|
||||
.update(canvasImageTask)
|
||||
.set({
|
||||
status: "failed",
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
completedAt: new Date(),
|
||||
updatedAt: new Date(),
|
||||
})
|
||||
.where(eq(canvasImageTask.id, taskId));
|
||||
} finally {
|
||||
state.running.delete(taskId);
|
||||
void drainCanvasImageTaskQueue();
|
||||
}
|
||||
}
|
||||
|
||||
export async function drainCanvasImageTaskQueue() {
|
||||
const state = getQueueState();
|
||||
if (state.draining) return;
|
||||
|
||||
state.draining = true;
|
||||
try {
|
||||
const maxConcurrent = getQueueConcurrency();
|
||||
while (state.running.size < maxConcurrent) {
|
||||
const taskId = await claimNextPendingTask();
|
||||
if (!taskId) break;
|
||||
if (state.running.has(taskId)) continue;
|
||||
void runSingleTask(taskId);
|
||||
}
|
||||
} finally {
|
||||
state.draining = false;
|
||||
}
|
||||
}
|
||||
|
||||
export async function enqueueCanvasImageTask(taskId: string) {
|
||||
enqueueLocalTask(taskId);
|
||||
await drainCanvasImageTaskQueue();
|
||||
}
|
||||
|
||||
export async function createCanvasImageTask(params: {
|
||||
userId: string;
|
||||
request: CanvasGenerateImageRequest;
|
||||
}) {
|
||||
const [task] = await db
|
||||
.insert(canvasImageTask)
|
||||
.values({
|
||||
userId: params.userId,
|
||||
status: "pending",
|
||||
request: params.request as unknown as Record<string, unknown>,
|
||||
attempts: 0,
|
||||
createdAt: new Date(),
|
||||
updatedAt: new Date(),
|
||||
})
|
||||
.returning({
|
||||
id: canvasImageTask.id,
|
||||
status: canvasImageTask.status,
|
||||
createdAt: canvasImageTask.createdAt,
|
||||
});
|
||||
|
||||
return task;
|
||||
}
|
||||
|
||||
export async function getCanvasImageTaskForUser(params: {
|
||||
taskId: string;
|
||||
userId: string;
|
||||
}) {
|
||||
const rows = await db
|
||||
.select({
|
||||
id: canvasImageTask.id,
|
||||
status: canvasImageTask.status,
|
||||
request: canvasImageTask.request,
|
||||
result: canvasImageTask.result,
|
||||
error: canvasImageTask.error,
|
||||
attempts: canvasImageTask.attempts,
|
||||
startedAt: canvasImageTask.startedAt,
|
||||
completedAt: canvasImageTask.completedAt,
|
||||
createdAt: canvasImageTask.createdAt,
|
||||
updatedAt: canvasImageTask.updatedAt,
|
||||
})
|
||||
.from(canvasImageTask)
|
||||
.where(and(eq(canvasImageTask.id, params.taskId), eq(canvasImageTask.userId, params.userId)))
|
||||
.limit(1);
|
||||
|
||||
const task = rows[0];
|
||||
if (!task) return null;
|
||||
|
||||
if (task.status === "running" && task.startedAt) {
|
||||
const staleBefore = new Date(Date.now() - STALE_RUNNING_MS);
|
||||
if (task.startedAt < staleBefore) {
|
||||
await db
|
||||
.update(canvasImageTask)
|
||||
.set({
|
||||
status: "pending",
|
||||
startedAt: null,
|
||||
completedAt: null,
|
||||
updatedAt: new Date(),
|
||||
})
|
||||
.where(
|
||||
and(
|
||||
eq(canvasImageTask.id, task.id),
|
||||
eq(canvasImageTask.status, "running"),
|
||||
lt(canvasImageTask.startedAt, staleBefore)
|
||||
)
|
||||
);
|
||||
enqueueLocalTask(task.id);
|
||||
await drainCanvasImageTaskQueue();
|
||||
task.status = "pending" as CanvasImageTaskStatus;
|
||||
task.startedAt = null;
|
||||
task.completedAt = null;
|
||||
}
|
||||
}
|
||||
|
||||
if (task.status === "pending") {
|
||||
enqueueLocalTask(task.id);
|
||||
await drainCanvasImageTaskQueue();
|
||||
}
|
||||
|
||||
return task;
|
||||
}
|
||||
19
lib/db/migrations/0045_add_canvas_image_tasks.sql
Normal file
19
lib/db/migrations/0045_add_canvas_image_tasks.sql
Normal file
@ -0,0 +1,19 @@
|
||||
CREATE TABLE IF NOT EXISTS "CanvasImageTask" (
|
||||
"id" uuid PRIMARY KEY DEFAULT gen_random_uuid() NOT NULL,
|
||||
"userId" uuid NOT NULL REFERENCES "User"("id") ON DELETE cascade,
|
||||
"status" varchar(16) NOT NULL DEFAULT 'pending',
|
||||
"request" jsonb NOT NULL,
|
||||
"result" jsonb,
|
||||
"error" text,
|
||||
"attempts" integer NOT NULL DEFAULT 0,
|
||||
"startedAt" timestamp,
|
||||
"completedAt" timestamp,
|
||||
"createdAt" timestamp NOT NULL DEFAULT now(),
|
||||
"updatedAt" timestamp NOT NULL DEFAULT now()
|
||||
);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS "CanvasImageTask_user_status_created_idx"
|
||||
ON "CanvasImageTask"("userId", "status", "createdAt");
|
||||
|
||||
CREATE INDEX IF NOT EXISTS "CanvasImageTask_status_created_idx"
|
||||
ON "CanvasImageTask"("status", "createdAt");
|
||||
@ -218,6 +218,13 @@
|
||||
"when": 1772366460000,
|
||||
"tag": "0044_add_resend_config",
|
||||
"breakpoints": true
|
||||
},
|
||||
{
|
||||
"idx": 31,
|
||||
"version": "7",
|
||||
"when": 1772500000000,
|
||||
"tag": "0045_add_canvas_image_tasks",
|
||||
"breakpoints": true
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
@ -521,6 +521,27 @@ export const canvasDetailArchive = pgTable("CanvasDetailArchive", {
|
||||
|
||||
export type CanvasDetailArchive = InferSelectModel<typeof canvasDetailArchive>;
|
||||
|
||||
// 画布图片生成任务表(异步队列)
|
||||
export const canvasImageTask = pgTable("CanvasImageTask", {
|
||||
id: uuid("id").primaryKey().notNull().defaultRandom(),
|
||||
userId: uuid("userId")
|
||||
.notNull()
|
||||
.references(() => user.id, { onDelete: "cascade" }),
|
||||
status: varchar("status", { length: 16 })
|
||||
.notNull()
|
||||
.default("pending"), // pending | running | succeeded | failed
|
||||
request: jsonb("request").notNull(),
|
||||
result: jsonb("result"),
|
||||
error: text("error"),
|
||||
attempts: integer("attempts").notNull().default(0),
|
||||
startedAt: timestamp("startedAt"),
|
||||
completedAt: timestamp("completedAt"),
|
||||
createdAt: timestamp("createdAt").notNull().defaultNow(),
|
||||
updatedAt: timestamp("updatedAt").notNull().defaultNow(),
|
||||
});
|
||||
|
||||
export type CanvasImageTask = InferSelectModel<typeof canvasImageTask>;
|
||||
|
||||
// 画布节点表(可选,用于更细粒度的查询)
|
||||
export const canvasNode = pgTable("CanvasNode", {
|
||||
id: uuid("id").primaryKey().notNull().defaultRandom(),
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user