62 lines
3.5 KiB
TypeScript
62 lines
3.5 KiB
TypeScript
import { generateText } from "ai";
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import { createLogger } from "@/lib/observability/logger";
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const logger = createLogger("canvas-prompt-tools");
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import { NextResponse } from "next/server";
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import { auth } from "@/app/(auth)/auth";
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import { getLanguageModelById } from "@/lib/ai/dynamic-provider";
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import { getEnabledAiModelsWithProvider, getSystemSetting } from "@/lib/db/queries";
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import { VIDEO_CANVAS_FUNCTION_CONFIG_KEY, normalizeVideoCanvasFunctionConfig } from "@/lib/video-canvas/config";
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import { promptToolErrorMessage, promptToolFunctionKey, promptToolSchema, selectPromptToolModel } from "@/lib/video-canvas/prompt-tools";
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export const runtime = "nodejs";
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export const maxDuration = 120;
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const running = new Set<string>();
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export async function POST(request: Request) {
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const session = await auth();
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if (!session?.user?.id) return NextResponse.json({ success: false, error: "未登录" }, { status: 401 });
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const parsed = promptToolSchema.safeParse(await request.json().catch(() => null));
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if (!parsed.success) return NextResponse.json({ success: false, error: parsed.error.issues[0]?.message || "参数无效" }, { status: 400 });
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if (running.has(session.user.id)) return NextResponse.json({ success: false, error: "提示词处理中，请稍候" }, { status: 429 });
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running.add(session.user.id);
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try {
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const [setting, available] = await Promise.all([
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getSystemSetting({ key: VIDEO_CANVAS_FUNCTION_CONFIG_KEY }),
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getEnabledAiModelsWithProvider(false),
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]);
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const config = normalizeVideoCanvasFunctionConfig(setting?.value);
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const definition = config.functions[promptToolFunctionKey(parsed.data.mode)];
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if (!config.enabled || !definition?.enabled) return NextResponse.json({ success: false, error: "此提示词功能已停用" }, { status: 403 });
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const requested = parsed.data.model && parsed.data.model !== "auto"
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? parsed.data.model : definition.model && definition.model !== "auto"
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? definition.model : config.defaultMultimodalModel;
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let selected;
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try {
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selected = selectPromptToolModel(available
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.filter(item => item.provider.isEnabled && item.model.isEnabled && !item.model.isSubModel)
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.map(item => ({ ...item.model, providerType: item.provider.type })), requested);
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} catch (error) {
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return NextResponse.json({ success: false, error: (error as Error).message }, { status: 400 });
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}
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const model = await getLanguageModelById(selected.id);
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if (!model) return NextResponse.json({ success: false, error: "提示词模型初始化失败" }, { status: 502 });
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const { text } = await generateText({
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model,
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system: definition.prompt,
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prompt: parsed.data.prompt,
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temperature: parsed.data.mode === "translate" ? 0.1 : 0.4,
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maxOutputTokens: 4000,
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maxRetries: 0,
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abortSignal: AbortSignal.any([request.signal, AbortSignal.timeout(90_000)]),
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});
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if (!text.trim()) throw new Error("empty model output");
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return NextResponse.json({ success: true, data: { text: text.trim(), model: selected.id, modelName: selected.displayName || selected.modelId } });
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} catch (error) {
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const detail = error as { name?: string; statusCode?: number; cause?: { code?: string }; data?: { error?: { code?: string } } };
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logger.warn("Prompt tool request failed", { name: detail?.name, statusCode: detail?.statusCode, code: detail?.data?.error?.code || detail?.cause?.code });
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return NextResponse.json({ success: false, error: promptToolErrorMessage(error) }, { status: 502 });
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} finally {
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running.delete(session.user.id);
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}
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}
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