feat: add Visionary image provider

app/(admin)/settings/_lib/types.ts

@@ -89,6 +89,7 @@ export type AdminAiProvider = {
     | "snapgen-image"
     | "openai-image"
     | "bananaimage"
+    | "visionary"
     | "stepfun-image"
     | "midjourney"
     | "fal-video"

app/(admin)/settings/admin-settings-client.tsx

@@ -161,6 +161,7 @@ import { FAL_IMAGE_MODEL_PRESETS } from "@/lib/ai/fal-image-models";
 import { RUXA_IMAGE_MODEL_PRESETS } from "@/lib/ai/ruxa-image-models";
 import { SNAPGEN_IMAGE_MODEL_PRESETS } from "@/lib/ai/snapgen-image-models";
 import { BANANAIMAGE_MODEL_PRESETS } from "@/lib/ai/bananaimage-models";
+import { VISIONARY_MODEL_PRESETS } from "@/lib/ai/visionary-models";
 import {
   formatImageModelCreditDiscountLabel,
   getGenerationCreditCostFromImageGenConfig,
@@ -616,6 +617,7 @@ type AiProvider = {
     | "snapgen-image"
     | "openai-image"
     | "bananaimage"
+    | "visionary"
     | "stepfun-image"
     | "midjourney"
     | "fal-video"
@@ -1574,6 +1576,7 @@ const PROVIDER_TYPES = [
   { value: "snapgen-image", label: "SnapGen 生图" },
   { value: "openai-image", label: "OpenAI 图片兼容" },
   { value: "bananaimage", label: "BananaImage 生图" },
+  { value: "visionary", label: "Visionary 生图" },
   { value: "stepfun-image", label: "阶跃星辰 Step Image Edit" },
   { value: "bltcy-video", label: "柏拉图统一视频" },
   { value: "grsai-gpt-image", label: "Grsai GPT Image" },
@@ -1609,6 +1612,7 @@ const PROVIDER_DEFAULT_BASE_URL: Record<string, string> = {
   "snapgen-image": "https://api.snapgen.ai",
   "openai-image": "https://api.openai.com/v1",
   bananaimage: "https://bananaimage.aigenmedia.art",
+  visionary: "https://api.visionary.beer",
   "stepfun-image": "https://api.stepfun.com",
   "bltcy-video": "https://api.bltcy.ai",
   "grsai-gpt-image": "https://grsai.dakka.com.cn",
@@ -4010,6 +4014,7 @@ export function AdminSettingsClient() {
       | "snapgen-image"
       | "openai-image"
       | "bananaimage"
+      | "visionary"
       | "stepfun-image"
       | "midjourney"
       | "fal-video"
@@ -6247,6 +6252,7 @@ export function AdminSettingsClient() {
       const isRuxaImageProvider = providerForm.type === "ruxa-image";
       const isSnapgenImageProvider = providerForm.type === "snapgen-image";
       const isBananaImageProvider = providerForm.type === "bananaimage";
+      const isVisionaryProvider = providerForm.type === "visionary";
       const isBltcyVideoProvider = providerForm.type === "bltcy-video";
       const isLemonProvider =
         providerForm.type === "openai" &&
@@ -6400,6 +6406,17 @@ export function AdminSettingsClient() {
         }
       }
 
+      if (isNewProvider && isVisionaryProvider && providerId) {
+        try {
+          await handleQuickAddVisionaryModels(providerId, { skipConfirm: true });
+        } catch (modelError) {
+          console.error("[Auto Add Visionary Models] Error:", modelError);
+          toast.warning(
+            'Visionary 预设模型添加失败，请手动点击"快速添加 Visionary 图片预设"按钮'
+          );
+        }
+      }
+
       if (isNewProvider && isBltcyVideoProvider && providerId) {
         try {
           await handleQuickAddBltcyVideoModels(providerId, {
@@ -7410,6 +7427,44 @@ export function AdminSettingsClient() {
     }
   };
 
+  const handleQuickAddVisionaryModels = async (
+    providerId: string,
+    options?: { skipConfirm?: boolean }
+  ) => {
+    if (
+      !options?.skipConfirm &&
+      !confirm(
+        `将同步 ${VISIONARY_MODEL_PRESETS.length} 个 Visionary 生图模型，支持最多 9 张参考图、比例选择、质量档位和 1K/2K/4K。\n\n继续吗？`
+      )
+    ) {
+      return;
+    }
+
+    try {
+      toast.info("正在同步 Visionary 生图预设模型...");
+      const response = await fetch("/api/admin/visionary-models", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({ providerId }),
+      });
+      const data = await response.json();
+      if (!response.ok) throw new Error(data.error || "同步失败");
+
+      const totalSynced =
+        Number(data.addedCount || 0) + Number(data.updatedCount || 0);
+      if (totalSynced > 0) {
+        toast.success(`成功同步 ${totalSynced} 个 Visionary 生图预设模型`);
+        mutateModels();
+      }
+      if (data.errors?.length) {
+        toast.warning(`${data.errors.length} 个 Visionary 模型同步失败`);
+      }
+    } catch (error: any) {
+      console.error("[Quick Add Visionary Models] Error:", error);
+      toast.error(error.message || "同步 Visionary 生图预设模型失败");
+    }
+  };
+
   const handleUseFalImageProviderPreset = () => {
     setProviderForm({
       id: "",
@@ -15604,6 +15659,14 @@ export function AdminSettingsClient() {
                             1K/2K/4K 输出。
                           </p>
                         )}
+                        {providerForm.type === "visionary" && (
+                          <p className="text-muted-foreground text-xs">
+                            Visionary 使用 Bearer API Key 认证，默认地址
+                            https://api.visionary.beer。保存后自动同步 GPT Image 2
+                            与 Nano Banana 全部开放模型，支持最多 9 张参考图、比例选择、
+                            质量档位和 1K/2K/4K 输出。
+                          </p>
+                        )}
                         {providerForm.type === "bfl-image" &&
                           isBltcyBflBaseUrl(providerForm.baseUrl) && (
                             <p className="text-muted-foreground text-xs">
@@ -15737,6 +15800,19 @@ export function AdminSettingsClient() {
                           快速添加 BananaImage 图片预设
                         </Button>
                       )}
+                      {provider.type === "visionary" && (
+                        <Button
+                          className="mt-2"
+                          onClick={() =>
+                            handleQuickAddVisionaryModels(provider.id)
+                          }
+                          size="sm"
+                          variant="secondary"
+                        >
+                          <ImageIcon className="mr-1 h-4 w-4" />
+                          快速添加 Visionary 图片预设
+                        </Button>
+                      )}
                       {provider.type === "bltcy-video" && (
                         <Button
                           className="mt-2"

app/(chat)/api/chat/_lib/image-failover.ts

@@ -16,6 +16,7 @@ export const IMAGE_FAILOVER_PROVIDER_ALLOWLIST = new Set([
   "snapgen-image",
   "openai-image",
   "bananaimage",
+  "visionary",
   "stepfun-image",
   "runway",
   "krea",
@@ -245,6 +246,7 @@ export function getImageFailoverConvertProvider(providerType?: string | null) {
     case "snapgen-image":
     case "openai-image":
     case "bananaimage":
+    case "visionary":
     case "stepfun-image":
     case "midjourney":
     case "runway":

app/(chat)/api/chat/_lib/image-media.ts

@@ -525,6 +525,7 @@ export async function convertMessagesWithImages(
     normalizedProviderType === "snapgen-image" ||
     normalizedProviderType === "openai-image" ||
     normalizedProviderType === "bananaimage" ||
+    normalizedProviderType === "visionary" ||
     normalizedProviderType === "stepfun-image" ||
     normalizedProviderType === "midjourney" ||
     normalizedProviderType === "runway" ||

app/(chat)/api/chat/_lib/stream.ts

@@ -188,6 +188,7 @@ function normalizeImageLoadingProviderType(providerType?: string | null): string
     normalized === "snapgen-image" ||
     normalized === "openai-image" ||
     normalized === "bananaimage" ||
+    normalized === "visionary" ||
     normalized === "stepfun-image" ||
     normalized === "midjourney" ||
     normalized === "runway" ||

app/(chat)/api/chat/route.ts

@@ -9104,6 +9104,7 @@ export async function POST(request: Request) {
                   "snapgen-image": 5,
                   "openai-image": 6,
                   bananaimage: 7,
+                  visionary: 7,
                   "stepfun-image": 7,
                   "grsai-gpt-image": 8,
                   runway: 9,
@@ -9496,6 +9497,7 @@ export async function POST(request: Request) {
         "snapgen-image",
         "openai-image",
         "bananaimage",
+        "visionary",
         "stepfun-image",
         "midjourney",
         "runway",
@@ -9720,6 +9722,8 @@ export async function POST(request: Request) {
                       ? "openai-image"
                     : (languageModel as any).provider === "bananaimage"
                       ? "bananaimage"
+                    : (languageModel as any).provider === "visionary"
+                      ? "visionary"
                     : (languageModel as any).provider === "stepfun-image"
                       ? "stepfun-image"
                       : (languageModel as any).provider === "midjourney"
@@ -9824,6 +9828,7 @@ export async function POST(request: Request) {
                   "snapgen-image": 5,
                   "openai-image": 6,
                   bananaimage: 7,
+                  visionary: 7,
                   "stepfun-image": 7,
                   runway: 8,
                   krea: 9,
@@ -9869,6 +9874,8 @@ export async function POST(request: Request) {
                             ? "openai-image"
                           : candidate.provider.type === "bananaimage"
                             ? "bananaimage"
+                          : candidate.provider.type === "visionary"
+                            ? "visionary"
                           : candidate.provider.type === "stepfun-image"
                             ? "stepfun-image"
                             : candidate.provider.type === "midjourney"
@@ -10256,6 +10263,7 @@ export async function POST(request: Request) {
                   "snapgen-image": 4,
                   "openai-image": 5,
                   bananaimage: 6,
+                  visionary: 6,
                   "stepfun-image": 6,
                   runway: 7,
                   krea: 8,
@@ -10302,6 +10310,8 @@ export async function POST(request: Request) {
                             ? "openai-image"
                           : candidate.provider.type === "bananaimage"
                             ? "bananaimage"
+                          : candidate.provider.type === "visionary"
+                            ? "visionary"
                           : candidate.provider.type === "stepfun-image"
                             ? "stepfun-image"
                             : candidate.provider.type === "midjourney"
@@ -11132,6 +11142,7 @@ export async function POST(request: Request) {
                   "snapgen-image": 5,
                   "openai-image": 6,
                   bananaimage: 7,
+                  visionary: 7,
                   "stepfun-image": 7,
                   runway: 8,
                   krea: 9,
@@ -11180,6 +11191,8 @@ export async function POST(request: Request) {
                             ? "openai-image"
                           : candidate.provider.type === "bananaimage"
                             ? "bananaimage"
+                          : candidate.provider.type === "visionary"
+                            ? "visionary"
                           : candidate.provider.type === "stepfun-image"
                             ? "stepfun-image"
                             : candidate.provider.type === "midjourney"

app/(chat)/api/chat/schema.ts

@@ -48,6 +48,7 @@ const imageParamsSchema = z.object({
   aspectRatio: z.string().optional(),
   imageSize: z.preprocess(normalizeImageSizeInput, z.enum(imageSizeValues).optional()),
   imageCount: z.number().min(1).max(10).optional(),
+  quality: z.enum(["auto", "low", "medium", "high"]).optional(),
   // 阿里生图专用参数
   size: z.string().optional(),           // 自定义分辨率，如 "1024*1024"
   negativePrompt: z.string().optional(), // 反向提示词

app/api/admin/ai-providers/route.ts

@@ -33,6 +33,7 @@ const providerTypes = [
   "snapgen-image",
   "openai-image",
   "bananaimage",
+  "visionary",
   "stepfun-image",
   "midjourney",
   "fal-video",
@@ -75,6 +76,7 @@ const RUXA_IMAGE_BASE_URL = "https://api.ruxa.ai";
 const SNAPGEN_IMAGE_BASE_URL = "https://api.snapgen.ai";
 const OPENAI_IMAGE_BASE_URL = "https://api.openai.com/v1";
 const BANANAIMAGE_BASE_URL = "https://bananaimage.aigenmedia.art";
+const VISIONARY_BASE_URL = "https://api.visionary.beer";
 const STEPFUN_IMAGE_BASE_URL = "https://api.stepfun.com";
 const BFL_IMAGE_BASE_URL = "https://api.bfl.ai";
 const MIDJOURNEY_BASE_URL = "https://your-midjourney-api.example.com";
@@ -241,6 +243,8 @@ export async function POST(request: Request) {
               ? data.baseUrl || OPENAI_IMAGE_BASE_URL
             : data.type === "bananaimage"
               ? data.baseUrl || BANANAIMAGE_BASE_URL
+            : data.type === "visionary"
+              ? data.baseUrl || VISIONARY_BASE_URL
             : data.type === "stepfun-image"
               ? data.baseUrl || STEPFUN_IMAGE_BASE_URL
             : data.type === "midjourney"

app/api/admin/visionary-models/route.ts

@@ -0,0 +1,139 @@
+import { and, eq } from "drizzle-orm";
+import { NextResponse } from "next/server";
+import { VISIONARY_MODEL_PRESETS } from "@/lib/ai/visionary-models";
+import { db } from "@/lib/db";
+import { getAiProviderById } from "@/lib/db/queries";
+import { type AiModel, aiModel } from "@/lib/db/schema";
+import { requireAdmin } from "@/lib/middleware/admin";
+
+export async function GET() {
+  try {
+    await requireAdmin();
+    return NextResponse.json({
+      presets: VISIONARY_MODEL_PRESETS,
+      counts: { total: VISIONARY_MODEL_PRESETS.length },
+    });
+  } catch (error: any) {
+    console.error("[Visionary Models API] GET error:", error);
+    return NextResponse.json(
+      { error: error.message || "Failed to fetch Visionary model presets" },
+      { status: 500 }
+    );
+  }
+}
+
+export async function POST(request: Request) {
+  try {
+    await requireAdmin();
+    const body = await request.json();
+    const providerId = String(body?.providerId || "").trim();
+    const modelIds = Array.isArray(body?.modelIds)
+      ? body.modelIds
+          .map((item: unknown) => String(item || "").trim())
+          .filter(Boolean)
+      : null;
+
+    if (!providerId) {
+      return NextResponse.json(
+        { error: "Provider ID is required" },
+        { status: 400 }
+      );
+    }
+
+    const provider = await getAiProviderById({ id: providerId });
+    if (!provider || provider.type !== "visionary") {
+      return NextResponse.json(
+        { error: "Provider must be a Visionary provider" },
+        { status: 400 }
+      );
+    }
+
+    const presets = modelIds
+      ? VISIONARY_MODEL_PRESETS.filter((preset) =>
+          modelIds.includes(preset.modelId)
+        )
+      : VISIONARY_MODEL_PRESETS;
+    const addedModels: AiModel[] = [];
+    const updatedModels: AiModel[] = [];
+    const errors: { modelId: string; error: string }[] = [];
+
+    for (const preset of presets) {
+      try {
+        const existing = await db.query.aiModel.findFirst({
+          where: and(
+            eq(aiModel.providerId, providerId),
+            eq(aiModel.modelId, preset.modelId)
+          ),
+        });
+        const values = {
+          displayName: preset.displayName,
+          description: preset.description,
+          supportsVision: preset.supportsVision,
+          supportsImageGen: preset.supportsImageGen,
+          isEnabled: true,
+          isHidden: false,
+          sortOrder: preset.sortOrder,
+          capabilities: preset.capabilities || null,
+          defaultParams: preset.defaultParams || null,
+          imageGenConfig: preset.imageGenConfig || null,
+        };
+
+        if (existing) {
+          const [updated] = await db
+            .update(aiModel)
+            .set(values)
+            .where(
+              and(
+                eq(aiModel.providerId, providerId),
+                eq(aiModel.modelId, preset.modelId)
+              )
+            )
+            .returning();
+          if (updated) updatedModels.push(updated);
+          continue;
+        }
+
+        const [created] = await db
+          .insert(aiModel)
+          .values({
+            providerId,
+            modelId: preset.modelId,
+            ...values,
+            isDefault: false,
+            isSubModel: false,
+            parentModelId: null,
+          })
+          .returning();
+        if (created) addedModels.push(created);
+      } catch (error: any) {
+        console.error(
+          `[Visionary Models API] Failed to sync ${preset.modelId}:`,
+          error
+        );
+        errors.push({
+          modelId: preset.modelId,
+          error: error.message || "Sync failed",
+        });
+      }
+    }
+
+    return NextResponse.json({
+      success: true,
+      addedCount: addedModels.length,
+      updatedCount: updatedModels.length,
+      addedModels,
+      updatedModels,
+      errors: errors.length > 0 ? errors : undefined,
+      counts: {
+        requested: presets.length,
+        total: VISIONARY_MODEL_PRESETS.length,
+      },
+    });
+  } catch (error: any) {
+    console.error("[Visionary Models API] POST error:", error);
+    return NextResponse.json(
+      { error: error.message || "Failed to sync Visionary models" },
+      { status: 500 }
+    );
+  }
+}

app/api/canvas/text-edit/route.ts

@@ -12,6 +12,7 @@ import { createFalImage } from "@/lib/ai/providers/fal-image";
 import { createSnapgenImage } from "@/lib/ai/providers/snapgen-image";
 import { createOpenAIImage } from "@/lib/ai/providers/openai-image";
 import { createBananaImage } from "@/lib/ai/providers/bananaimage";
+import { createVisionary } from "@/lib/ai/providers/visionary";
 import { createStepfunImage } from "@/lib/ai/providers/stepfun-image";
 import { createMidjourney } from "@/lib/ai/providers/midjourney";
 import { createRunway } from "@/lib/ai/providers/runway";
@@ -53,6 +54,7 @@ const SUPPORTED_TEXT_EDIT_PROVIDER_TYPES = new Set([
   "snapgen-image",
   "openai-image",
   "bananaimage",
+  "visionary",
   "stepfun-image",
   "midjourney",
   "runway",
@@ -119,6 +121,8 @@ function createTextEditProvider(
       return createOpenAIImage({ baseURL, apiKey });
     case "bananaimage":
       return createBananaImage({ baseURL, apiKey });
+    case "visionary":
+      return createVisionary({ baseURL, apiKey });
     case "stepfun-image":
       return createStepfunImage({ baseURL, apiKey });
     case "midjourney":

app/api/scene-fusion/route.ts

@@ -26,6 +26,7 @@ import { createFalImage } from "@/lib/ai/providers/fal-image";
 import { createSnapgenImage } from "@/lib/ai/providers/snapgen-image";
 import { createOpenAIImage } from "@/lib/ai/providers/openai-image";
 import { createBananaImage } from "@/lib/ai/providers/bananaimage";
+import { createVisionary } from "@/lib/ai/providers/visionary";
 import { callQwen3Vl } from "@/lib/ai/qwen3-vl";
 import {
   canProcessSceneFusionProviderType,
@@ -1539,6 +1540,17 @@ async function processSceneWithProvider(
         imageSize,
       );
 
+    case "visionary":
+      return processWithVisionary(
+        productImageUrl,
+        sceneImageUrl,
+        prompt,
+        provider,
+        runtimeModelId || modelId,
+        aspectRatio,
+        imageSize,
+      );
+
     case "gemini":
     case "gemini-image":
       return processWithGemini(productImageUrl, sceneImageUrl, prompt, provider, modelId, aspectRatio, imageSize);
@@ -1831,6 +1843,43 @@ async function processWithBananaImage(
   return { thumbnail, original, prompt };
 }
 
+async function processWithVisionary(
+  productImageUrl: string,
+  sceneImageUrl: string,
+  prompt: string,
+  provider: { baseUrl: string; apiKey: string },
+  modelId: string,
+  aspectRatio?: string,
+  imageSize?: string
+): Promise<{ thumbnail: string; original: string; prompt: string }> {
+  logger.info("provider_processing", { providerType: "visionary", modelId });
+
+  const visionaryProvider = createVisionary({
+    baseURL: provider.baseUrl,
+    apiKey: provider.apiKey,
+  });
+  const result = await visionaryProvider.chat(modelId).doGenerate({
+    messages: [
+      {
+        role: "user",
+        content: [
+          { type: "image_url", image_url: { url: productImageUrl } },
+          { type: "image_url", image_url: { url: sceneImageUrl } },
+          { type: "text", text: prompt },
+        ],
+      },
+    ],
+    imageParams: {
+      aspectRatio: aspectRatio || "auto",
+      imageSize: imageSize || "2K",
+      imageCount: 1,
+    },
+  });
+
+  const { thumbnail, original } = parseImageFromMarkdown(result.text);
+  return { thumbnail, original, prompt };
+}
+
 /**
  * 使用既梦/火山模型处理
  */

components/image-generation-loading.tsx

@@ -27,6 +27,7 @@ const PROVIDER_MODEL_LABEL: Record<string, string> = {
   "snapgen-image": "SnapGen 图片",
   "openai-image": "OpenAI 图片",
   bananaimage: "BananaImage 图片",
+  visionary: "Visionary 图片",
   "stepfun-image": "StepFun 图片",
   midjourney: "Midjourney",
   "volcano-vision": "即梦 4.5",

components/image-params-bar.tsx

@@ -18,6 +18,7 @@ export interface ImageGenerationParams {
   aspectRatio: string;
   imageSize: string;
   imageCount?: number;           // 生成图片数量
+  quality?: "auto" | "low" | "medium" | "high";
   // 🆕 阿里生图专用参数
   size?: string;                 // 自定义分辨率，如 "1024*1024"
   negativePrompt?: string;       // 反向提示词
@@ -47,6 +48,7 @@ interface ImageParamsBarProps {
     supportsNegativePrompt?: boolean;
     supportsWatermark?: boolean;
     supportsSeed?: boolean;
+    supportsQuality?: boolean;
     supportedAspectRatios?: string[];
     supportedImageSizes?: string[];
   };
@@ -144,6 +146,7 @@ export function ImageParamsBar({
       "aspectRatio",
       "imageSize",
       "imageCount",
+      "quality",
       "size",
       "negativePrompt",
       "promptExtend",
@@ -172,6 +175,7 @@ export function ImageParamsBar({
     if (
       providerType === "openai-image" ||
       providerType === "bananaimage" ||
+      providerType === "visionary" ||
       providerType === "stepfun-image" ||
       providerType === "midjourney"
     ) {
@@ -281,6 +285,7 @@ export function ImageParamsBar({
     a.aspectRatio === b.aspectRatio &&
     a.imageSize === b.imageSize &&
     (a.imageCount || 1) === (b.imageCount || 1) &&
+    (a.quality || "medium") === (b.quality || "medium") &&
     a.size === b.size &&
     a.negativePrompt === b.negativePrompt &&
     a.promptExtend === b.promptExtend &&
@@ -295,6 +300,7 @@ export function ImageParamsBar({
       aspectRatio: inlineTheme === "minimal" ? "1:1" : "auto",
       imageSize: "2K",
       imageCount: 1,
+      quality: "medium",
       promptExtend: true,
       watermark: false,
       ...source,
@@ -308,7 +314,14 @@ export function ImageParamsBar({
     ...buildBaseParams(initialParams),
   });
   const [minimalParamsOpen, setMinimalParamsOpen] = useState(false);
-  const [qualityLabel, setQualityLabel] = useState<"自动" | "高" | "中" | "低">("中");
+  const qualityOptions = [
+    { label: "自动", value: "auto" },
+    { label: "高", value: "high" },
+    { label: "中", value: "medium" },
+    { label: "低", value: "low" },
+  ] as const;
+  const qualityLabel =
+    qualityOptions.find((option) => option.value === params.quality)?.label || "中";
 
   const imageCountOptions = getImageCountOptions();
   const showImageCountSelector = !hideImageCount && imageCountOptions.length > 1;
@@ -499,19 +512,19 @@ export function ImageParamsBar({
               <div>
                 <div className="mb-2 text-[14px] font-medium leading-none">质量</div>
                 <div className="grid h-9 grid-cols-4 rounded-full bg-[#f4f4f5] p-0.5 dark:bg-white/8">
-                  {(["自动", "高", "中", "低"] as const).map((quality) => (
+                  {qualityOptions.map((quality) => (
                     <button
-                      key={quality}
+                      key={quality.value}
                       type="button"
                       className={cn(
                         "rounded-full text-[13px] font-medium transition-colors",
-                        qualityLabel === quality
+                        params.quality === quality.value
                           ? "border border-[#c8cdd5] bg-white shadow-[0_1px_4px_rgba(15,23,42,0.1)] dark:border-white/12 dark:bg-white/16"
                           : "text-[#3d434d] hover:bg-white/55 dark:text-zinc-300 dark:hover:bg-white/10"
                       )}
-                      onClick={() => setQualityLabel(quality)}
+                      onClick={() => updateParam("quality", quality.value)}
                     >
-                      {quality}
+                      {quality.label}
                     </button>
                   ))}
                 </div>

components/image-preview.tsx

@@ -172,6 +172,9 @@ export function ImagePreview({
       } else if (src.includes("bananaimage-thumb-")) {
         originalUrl = src.replace("bananaimage-thumb-", "bananaimage-orig-");
         console.log("[ImagePreview] Inferred original URL from bananaimage-thumb filename");
+      } else if (src.includes("visionary-thumb-")) {
+        originalUrl = src.replace("visionary-thumb-", "visionary-orig-");
+        console.log("[ImagePreview] Inferred original URL from visionary-thumb filename");
       } else if (src.includes("/thumb/") || src.includes("-thumb")) {
         // 尝试从S3 URL中推断原图URL（常见格式：xxx-thumb.jpg -> xxx.jpg 或 xxx/thumb/xxx -> xxx/xxx）
         originalUrl = src.replace(/-thumb\./g, ".").replace(/\/thumb\//g, "/");

lib/ai/dynamic-provider.ts

@@ -25,6 +25,7 @@ import { createFalImage } from "./providers/fal-image";
 import { createSnapgenImage } from "./providers/snapgen-image";
 import { createOpenAIImage } from "./providers/openai-image";
 import { createBananaImage } from "./providers/bananaimage";
+import { createVisionary } from "./providers/visionary";
 import { createStepfunImage } from "./providers/stepfun-image";
 import { createMidjourney } from "./providers/midjourney";
 import { createFalVideo } from "./providers/fal-video";
@@ -304,6 +305,15 @@ function getOrCreateProvider(provider: Pick<AiProvider, "id" | "type" | "baseUrl
       return bananaImageProvider as any;
     }
 
+    case "visionary": {
+      const visionaryProvider = createVisionary({
+        baseURL: resolvedBaseUrl,
+        apiKey: provider.apiKey,
+      });
+      logProviderCreated("visionary", resolvedBaseUrl);
+      return visionaryProvider as any;
+    }
+
     case "stepfun-image": {
       const stepfunImageProvider = createStepfunImage({
         baseURL: resolvedBaseUrl,
@@ -475,6 +485,9 @@ export async function getDynamicModel(
     } else if (provider.type === "bananaimage") {
       baseModel = providerInstance.chat(resolvedModelId);
       logChatModelResult("bananaimage", baseModel);
+    } else if (provider.type === "visionary") {
+      baseModel = providerInstance.chat(resolvedModelId);
+      logChatModelResult("visionary", baseModel);
     } else if (provider.type === "stepfun-image") {
       baseModel = providerInstance.chat(resolvedModelId);
       logChatModelResult("stepfun-image", baseModel);

lib/ai/model-classification.ts

@@ -20,6 +20,7 @@ const STATIC_IMAGE_PROVIDER_TYPES = new Set([
   "grsai-gpt-image",
   "openai-image",
   "bananaimage",
+  "visionary",
   "stepfun-image",
   "midjourney",
   "volcano-vision",

lib/ai/model-router.ts

@@ -61,6 +61,7 @@ const IMAGE_ONLY_PROVIDER_TYPES = new Set([
   "snapgen-image",
   "openai-image",
   "bananaimage",
+  "visionary",
   "stepfun-image",
   "midjourney",
   "gemini-image",
@@ -173,7 +174,7 @@ const INTENT_MODEL_MAP: Record<
 > = {
   // 图片编辑：优先 alibaba-image（灵魂4.5，支持提示词扩展）
   image_edit: {
-    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "stepfun-image", "runway", "krea", "gemini", "huanke-gemini"],
+    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "visionary", "stepfun-image", "runway", "krea", "gemini", "huanke-gemini"],
     requireVision: true,
     requireImageGen: true,
     description: "图片编辑",
@@ -188,7 +189,7 @@ const INTENT_MODEL_MAP: Record<
 
   // 图片生成：优先灵魂4.5
   image_gen: {
-    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "stepfun-image", "runway", "krea", "gemini", "huanke-gemini", "volcano-vision"],
+    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "visionary", "stepfun-image", "runway", "krea", "gemini", "huanke-gemini", "volcano-vision"],
     requireImageGen: true,
     description: "图片生成",
   },
@@ -216,25 +217,25 @@ const SUB_INTENT_OVERRIDES: Record<
 > = {
   // 抠图：alibaba-image 效果最好
   remove_background: {
-    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "stepfun-image", "runway", "krea", "gemini"],
+    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "visionary", "stepfun-image", "runway", "krea", "gemini"],
     reason: "抠图首选灵魂4.5",
   },
 
   // 换背景：alibaba-image 支持场景生成
   replace_background: {
-    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "stepfun-image", "runway", "krea", "gemini"],
+    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "visionary", "stepfun-image", "runway", "krea", "gemini"],
     reason: "换背景首选灵魂4.5",
   },
 
   // 图片增强
   enhance: {
-    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "stepfun-image", "runway", "krea", "gemini", "volcano-vision"],
+    providerTypes: ["alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "visionary", "stepfun-image", "runway", "krea", "gemini", "volcano-vision"],
     reason: "增强首选灵魂4.5",
   },
 
   // 风格迁移：gemini 可能更有创意
   style_transfer: {
-    providerTypes: ["gemini", "alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "stepfun-image", "runway", "krea"],
+    providerTypes: ["gemini", "alibaba-image", "bfl-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "visionary", "stepfun-image", "runway", "krea"],
     reason: "风格迁移优选Gemini",
   },
 };

lib/ai/provider-defaults.ts

@@ -18,6 +18,7 @@ const PROVIDER_DEFAULT_BASE_URL: Partial<Record<AiProvider["type"], string>> = {
   "snapgen-image": "https://api.snapgen.ai",
   "openai-image": "https://api.openai.com/v1",
   bananaimage: "https://bananaimage.aigenmedia.art",
+  visionary: "https://api.visionary.beer",
   "stepfun-image": "https://api.stepfun.com",
   "bfl-image": "https://api.bfl.ai",
   midjourney: "https://your-midjourney-api.example.com",

lib/ai/providers/visionary.ts

@@ -0,0 +1,532 @@
+import "server-only";
+
+import { randomUUID } from "node:crypto";
+import sharp from "sharp";
+import {
+  getVisionaryModelPresetById,
+  VISIONARY_BASE_URL,
+} from "@/lib/ai/visionary-models";
+import { createDeferredUploadedImage } from "@/lib/storage/image-archive";
+import { uploadFile } from "@/lib/storage/service";
+
+interface VisionaryConfig {
+  apiKey: string;
+  baseURL?: string;
+}
+
+interface VisionaryImageParams {
+  aspectRatio?: string;
+  imageSize?: string;
+  imageCount?: number;
+  promptExtend?: boolean;
+  quality?: "auto" | "low" | "medium" | "high" | string;
+}
+
+interface VisionaryModelConfig {
+  maxReferenceImages?: number;
+  supportedAspectRatios?: string[];
+  supportedImageSizes?: string[];
+  supportsPromptExtend?: boolean;
+  supportsQuality?: boolean;
+}
+
+interface ReferenceImage {
+  apiValue: string;
+  height?: number;
+  width?: number;
+}
+
+interface UploadedImage {
+  thumbnail: string;
+  original: string;
+}
+
+const POLL_INTERVAL_MS = 3000;
+const MAX_POLL_INTERVAL_MS = 15_000;
+const POLL_TIMEOUT_MS = 18 * 60 * 1000;
+const MAX_TRANSIENT_POLL_FAILURES = 8;
+const IMAGE_DOWNLOAD_TIMEOUT_MS = 120_000;
+
+function joinApiPath(baseURL: string, path: string) {
+  const cleanBase = String(baseURL || VISIONARY_BASE_URL).replace(/\/+$/, "");
+  const cleanPath = path.startsWith("/") ? path : `/${path}`;
+  return `${cleanBase}${cleanPath}`;
+}
+
+function delay(ms: number) {
+  return new Promise((resolve) => setTimeout(resolve, ms));
+}
+
+function normalizeModelId(modelId?: string) {
+  const normalized = String(modelId || "").trim();
+  if (!normalized) throw new Error("Visionary 模型 ID 未配置");
+  return normalized;
+}
+
+function normalizeAspectRatio(value?: string) {
+  const normalized = String(value || "auto").trim().toLowerCase();
+  if (normalized === "auto") return "auto";
+  const match = normalized.match(/^(\d+)\s*:\s*(\d+)$/);
+  if (!match) return "auto";
+  return `${Number(match[1])}:${Number(match[2])}`;
+}
+
+function getSupportedAspectRatios(
+  modelId: string,
+  modelConfig?: VisionaryModelConfig | null
+) {
+  const preset = getVisionaryModelPresetById(modelId);
+  const configured = modelConfig?.supportedAspectRatios;
+  const values = Array.isArray(configured)
+    ? configured
+    : (preset?.imageGenConfig?.supportedAspectRatios as string[] | undefined);
+  return Array.from(
+    new Set((values || ["auto", "1:1"]).map(normalizeAspectRatio))
+  );
+}
+
+function resolveAspectRatio(
+  requested: string | undefined,
+  modelId: string,
+  modelConfig?: VisionaryModelConfig | null
+) {
+  const supported = getSupportedAspectRatios(modelId, modelConfig);
+  const normalized = normalizeAspectRatio(requested);
+  if (supported.includes(normalized)) return normalized;
+  return supported.includes("auto") ? "auto" : supported[0] || "1:1";
+}
+
+function normalizeImageSize(
+  requested: string | undefined,
+  modelId: string,
+  modelConfig?: VisionaryModelConfig | null
+) {
+  const preset = getVisionaryModelPresetById(modelId);
+  const configured = modelConfig?.supportedImageSizes;
+  const supported = (Array.isArray(configured)
+    ? configured
+    : (preset?.imageGenConfig?.supportedImageSizes as string[] | undefined) || ["1K"]
+  )
+    .map((size) => String(size).trim().toUpperCase())
+    .filter((size) => ["1K", "2K", "4K"].includes(size));
+  const defaultSize = String(preset?.defaultParams?.imageSize || supported[0] || "1K")
+    .trim()
+    .toUpperCase();
+  const normalized = String(requested || defaultSize).trim().toUpperCase();
+  if (supported.includes(normalized)) return normalized;
+  return supported.includes(defaultSize) ? defaultSize : supported[0] || "1K";
+}
+
+function normalizeQuality(value?: string) {
+  const normalized = String(value || "auto").trim().toLowerCase();
+  return ["auto", "low", "medium", "high"].includes(normalized)
+    ? normalized
+    : "auto";
+}
+
+function extractPromptAndImages(
+  messages: Array<{ role: string; content?: any; parts?: any[] }>
+) {
+  const lastUserMessage = messages.filter((message) => message.role === "user").pop();
+  if (!lastUserMessage) throw new Error("未找到用户消息");
+
+  const texts: string[] = [];
+  const imageUrls: string[] = [];
+  const seenImages = new Set<string>();
+  const pushText = (value: unknown) => {
+    if (typeof value === "string" && value.trim()) texts.push(value.trim());
+  };
+  const pushImage = (value: unknown) => {
+    let url = "";
+    if (typeof value === "string") url = value;
+    else if (value instanceof URL) url = value.toString();
+    else if (value && typeof value === "object") {
+      url = String(
+        (value as any).url ||
+          (value as any).imageUrl ||
+          (value as any).fileUrl ||
+          (value as any).src ||
+          ""
+      );
+    }
+    url = url.trim();
+    if (!url || seenImages.has(url)) return;
+    if (!url.startsWith("data:image/") && !/^https?:\/\//i.test(url)) return;
+    seenImages.add(url);
+    imageUrls.push(url);
+  };
+  const visitPart = (part: any) => {
+    if (!part) return;
+    if (typeof part === "string") {
+      pushText(part);
+      return;
+    }
+    if (part.type === "text" || typeof part.text === "string") pushText(part.text);
+    if (part.type === "image_url") pushImage(part.image_url);
+    if (part.type === "image") pushImage(part.image || part.url);
+    if (part.type === "file") pushImage(part.url || part.file || part.data);
+    if (part.inlineData?.data) {
+      pushImage(
+        `data:${part.inlineData.mimeType || "image/png"};base64,${part.inlineData.data}`
+      );
+    }
+  };
+
+  const content = lastUserMessage.content;
+  if (typeof content === "string") pushText(content);
+  else if (Array.isArray(content)) content.forEach(visitPart);
+  if (Array.isArray(lastUserMessage.parts)) lastUserMessage.parts.forEach(visitPart);
+
+  const prompt = texts.join("\n").trim();
+  if (!prompt) throw new Error("请输入图片生成或编辑要求");
+  return { prompt, imageUrls };
+}
+
+function parseDataUrl(dataUrl: string) {
+  const match = dataUrl.match(/^data:(image\/(?:jpeg|png|webp));base64,(.+)$/s);
+  if (!match) throw new Error("Visionary 参考图仅支持 JPEG、PNG 或 WebP Data URI");
+  const mimeType = match[1] || "image/png";
+  const buffer = Buffer.from(match[2] || "", "base64");
+  return { mimeType, buffer, dataUrl };
+}
+
+async function loadReferenceImage(imageUrl: string): Promise<ReferenceImage> {
+  if (imageUrl.startsWith("data:")) {
+    const parsed = parseDataUrl(imageUrl);
+    const metadata = await sharp(parsed.buffer, { failOn: "none" })
+      .metadata()
+      .catch(() => null);
+    return {
+      apiValue: parsed.dataUrl,
+      width: metadata?.width,
+      height: metadata?.height,
+    };
+  }
+
+  const response = await fetch(imageUrl, {
+    cache: "no-store",
+    redirect: "follow",
+    signal: AbortSignal.timeout(IMAGE_DOWNLOAD_TIMEOUT_MS),
+    headers: {
+      Accept: "image/avif,image/webp,image/png,image/jpeg,image/*,*/*;q=0.8",
+      "User-Agent": "yedir-ai-visionary/1.0",
+    },
+  });
+  if (!response.ok) {
+    throw new Error(`Visionary 参考图下载失败（HTTP ${response.status}）`);
+  }
+  const mimeType = response.headers.get("content-type")?.split(";")[0] || "";
+  if (!/^image\/(?:jpeg|png|webp)$/i.test(mimeType)) {
+    throw new Error(`Visionary 不支持此参考图格式：${mimeType || "unknown"}`);
+  }
+  const buffer = Buffer.from(await response.arrayBuffer());
+  const metadata = await sharp(buffer, { failOn: "none" })
+    .metadata()
+    .catch(() => null);
+  return {
+    apiValue: /^https:\/\//i.test(imageUrl)
+      ? imageUrl
+      : `data:${mimeType};base64,${buffer.toString("base64")}`,
+    width: metadata?.width,
+    height: metadata?.height,
+  };
+}
+
+function detectImageExtension(mimeType?: string | null) {
+  const normalized = String(mimeType || "").toLowerCase();
+  if (normalized.includes("jpeg") || normalized.includes("jpg")) return "jpg";
+  if (normalized.includes("webp")) return "webp";
+  if (normalized.includes("gif")) return "gif";
+  return "png";
+}
+
+function generateFilename(prefix: string, extension: string) {
+  return `${prefix}-${Date.now()}-${Math.random().toString(36).slice(2, 8)}.${extension}`;
+}
+
+function toArrayBuffer(buffer: Buffer) {
+  return buffer.buffer.slice(
+    buffer.byteOffset,
+    buffer.byteOffset + buffer.byteLength
+  ) as ArrayBuffer;
+}
+
+async function uploadImageBuffer(
+  buffer: Buffer,
+  mimeType?: string | null
+): Promise<UploadedImage> {
+  const extension = detectImageExtension(mimeType);
+  const thumbnailBuffer = await sharp(buffer, { failOn: "none" })
+    .resize(400, 400, { fit: "inside", withoutEnlargement: true })
+    .jpeg({ quality: 82 })
+    .toBuffer()
+    .catch(() => buffer);
+  const [original, thumbnail] = await Promise.all([
+    uploadFile(generateFilename("visionary-orig", extension), toArrayBuffer(buffer)),
+    uploadFile(generateFilename("visionary-thumb", "jpg"), toArrayBuffer(thumbnailBuffer)),
+  ]);
+  return { original: original.url, thumbnail: thumbnail.url };
+}
+
+async function archiveOutputImage(imageUrl: string): Promise<UploadedImage> {
+  if (imageUrl.startsWith("data:")) {
+    const parsed = parseDataUrl(imageUrl);
+    return uploadImageBuffer(parsed.buffer, parsed.mimeType);
+  }
+
+  const deferred = await createDeferredUploadedImage(imageUrl, {
+    providerType: "visionary",
+  });
+  if (deferred) return deferred;
+
+  const response = await fetch(imageUrl, {
+    cache: "no-store",
+    redirect: "follow",
+    signal: AbortSignal.timeout(IMAGE_DOWNLOAD_TIMEOUT_MS),
+    headers: { "User-Agent": "yedir-ai-visionary/1.0" },
+  });
+  if (!response.ok) {
+    throw new Error(`Visionary 结果图片下载失败（HTTP ${response.status}）`);
+  }
+  return uploadImageBuffer(
+    Buffer.from(await response.arrayBuffer()),
+    response.headers.get("content-type")
+  );
+}
+
+async function parseJsonResponse(response: Response) {
+  const rawText = await response.text();
+  if (!rawText.trim()) return null;
+  try {
+    return JSON.parse(rawText);
+  } catch {
+    return rawText;
+  }
+}
+
+function extractErrorMessage(payload: any, fallback = "Visionary 请求失败") {
+  if (typeof payload === "string" && payload.trim()) return payload.trim();
+  const value =
+    payload?.error?.message ||
+    payload?.data?.error?.message ||
+    payload?.data?.error ||
+    payload?.error ||
+    payload?.message ||
+    fallback;
+  return typeof value === "string" ? value : fallback;
+}
+
+function extractSubmittedTask(payload: any) {
+  const task = Array.isArray(payload?.data) ? payload.data[0] : payload?.data || payload;
+  const taskId = String(task?.task_id || task?.taskId || task?.id || "").trim();
+  const retryAfter = Number(task?.retry_after || task?.retryAfter || 3);
+  return { taskId, retryAfter };
+}
+
+function extractTaskImages(payload: any) {
+  const task = payload?.data || payload;
+  const images = task?.result?.images;
+  if (!Array.isArray(images)) return [] as string[];
+  return Array.from(
+    new Set(
+      images.flatMap((image: any) => {
+        const value = image?.url;
+        if (Array.isArray(value)) return value;
+        return value ? [value] : [];
+      })
+    )
+  )
+    .map((value) => String(value || "").trim())
+    .filter((value) => /^https?:\/\//i.test(value) || value.startsWith("data:image/"));
+}
+
+async function submitTask(params: {
+  apiKey: string;
+  aspectRatio: string;
+  baseURL: string;
+  imageSize: string;
+  modelId: string;
+  prompt: string;
+  promptExtend?: boolean;
+  quality?: string;
+  referenceImages: ReferenceImage[];
+}) {
+  const clientRequestId = `yedir-${randomUUID()}`;
+  const body: Record<string, unknown> = {
+    model: params.modelId,
+    prompt: params.prompt,
+    images: params.referenceImages.map((image) => image.apiValue),
+    size: params.aspectRatio,
+    resolution: params.imageSize,
+    client_request_id: clientRequestId,
+  };
+  if (params.modelId === "gpt-image-2") {
+    body.quality = normalizeQuality(params.quality);
+  }
+  if (params.modelId === "nano-banana-pro") {
+    body.optimizeChineseText = Boolean(params.promptExtend);
+  }
+
+  const response = await fetch(joinApiPath(params.baseURL, "/v1/images/generations"), {
+    method: "POST",
+    headers: {
+      Authorization: `Bearer ${params.apiKey}`,
+      "Content-Type": "application/json",
+      "Idempotency-Key": clientRequestId,
+      "User-Agent": "yedir-ai-visionary/1.0",
+    },
+    body: JSON.stringify(body),
+    signal: AbortSignal.timeout(30_000),
+  });
+  const payload = await parseJsonResponse(response);
+  if (!response.ok) {
+    throw new Error(`${extractErrorMessage(payload)}（HTTP ${response.status}）`);
+  }
+  const task = extractSubmittedTask(payload);
+  if (!task.taskId) throw new Error("Visionary 未返回 task_id");
+  return task;
+}
+
+async function waitForTask(params: {
+  apiKey: string;
+  baseURL: string;
+  initialRetryAfter: number;
+  taskId: string;
+}) {
+  const startedAt = Date.now();
+  let retryAfter = params.initialRetryAfter;
+  let transientFailures = 0;
+
+  while (Date.now() - startedAt < POLL_TIMEOUT_MS) {
+    const waitMs = Math.min(
+      MAX_POLL_INTERVAL_MS,
+      Math.max(POLL_INTERVAL_MS, Math.round(retryAfter * 1000))
+    );
+    await delay(waitMs);
+
+    try {
+      const response = await fetch(
+        joinApiPath(params.baseURL, `/v1/tasks/${encodeURIComponent(params.taskId)}`),
+        {
+          cache: "no-store",
+          headers: {
+            Authorization: `Bearer ${params.apiKey}`,
+            "User-Agent": "yedir-ai-visionary/1.0",
+          },
+          signal: AbortSignal.timeout(30_000),
+        }
+      );
+      const payload = await parseJsonResponse(response);
+      if (!response.ok) {
+        if (response.status >= 500 || response.status === 429) {
+          throw new Error(`HTTP ${response.status}`);
+        }
+        throw new Error(extractErrorMessage(payload));
+      }
+
+      transientFailures = 0;
+      const task = payload?.data || payload;
+      const status = String(task?.status || "").trim().toLowerCase();
+      retryAfter = Number(task?.retry_after || retryAfter || 3);
+      if (status === "completed") {
+        const images = extractTaskImages(payload);
+        if (images.length === 0) throw new Error("Visionary 任务完成但未返回图片");
+        return images;
+      }
+      if (["failed", "error", "cancelled", "canceled"].includes(status)) {
+        throw new Error(extractErrorMessage(payload, "Visionary 图片生成失败"));
+      }
+    } catch (error) {
+      const message = error instanceof Error ? error.message : String(error);
+      if (!/^HTTP (?:429|5\d\d)$/.test(message) && !/fetch|network|abort/i.test(message)) {
+        throw error;
+      }
+      transientFailures += 1;
+      if (transientFailures >= MAX_TRANSIENT_POLL_FAILURES) throw error;
+    }
+  }
+
+  throw new Error("Visionary 生成超时，任务可能仍在处理，请稍后重试");
+}
+
+function formatMarkdown(images: UploadedImage[], imageSize: string) {
+  return images
+    .map((image) => `![thumb|||${image.original}|||${imageSize}](${image.thumbnail})`)
+    .join("\n\n");
+}
+
+export function createVisionary({ apiKey, baseURL = VISIONARY_BASE_URL }: VisionaryConfig) {
+  return {
+    provider: "visionary",
+    chat: (modelId: string) => ({
+      provider: "visionary",
+      doGenerate: async (options: {
+        messages: Array<{ role: string; content?: any; parts?: any[] }>;
+        imageParams?: VisionaryImageParams;
+        imageGenConfig?: VisionaryModelConfig | null;
+        overrideModelId?: string;
+      }) => {
+        const requestedModelId = normalizeModelId(options.overrideModelId || modelId);
+        const preset = getVisionaryModelPresetById(requestedModelId);
+        if (!preset) throw new Error(`Visionary 暂不支持模型：${requestedModelId}`);
+
+        const { prompt, imageUrls } = extractPromptAndImages(options.messages);
+        const maxReferenceImages = Math.max(
+          0,
+          Math.min(9, options.imageGenConfig?.maxReferenceImages || 9)
+        );
+        const referenceImages = await Promise.all(
+          imageUrls.slice(0, maxReferenceImages).map(loadReferenceImage)
+        );
+        const aspectRatio = resolveAspectRatio(
+          options.imageParams?.aspectRatio,
+          requestedModelId,
+          options.imageGenConfig
+        );
+        const imageSize = normalizeImageSize(
+          options.imageParams?.imageSize,
+          requestedModelId,
+          options.imageGenConfig
+        );
+
+        const submitted = await submitTask({
+          apiKey,
+          aspectRatio,
+          baseURL,
+          imageSize,
+          modelId: requestedModelId,
+          prompt,
+          promptExtend: options.imageParams?.promptExtend,
+          quality: options.imageParams?.quality,
+          referenceImages,
+        });
+        const outputUrls = await waitForTask({
+          apiKey,
+          baseURL,
+          initialRetryAfter: submitted.retryAfter,
+          taskId: submitted.taskId,
+        });
+        const uploadedImages = await Promise.all(
+          outputUrls
+            .slice(0, Math.max(1, options.imageParams?.imageCount || 1))
+            .map(archiveOutputImage)
+        );
+        const text = formatMarkdown(uploadedImages, imageSize);
+        return {
+          text,
+          finishReason: "stop" as const,
+          usage: { promptTokens: 0, completionTokens: text.length },
+        };
+      },
+      doStream: async function* (options: {
+        messages: Array<{ role: string; content?: any; parts?: any[] }>;
+        imageParams?: VisionaryImageParams;
+        imageGenConfig?: VisionaryModelConfig | null;
+        overrideModelId?: string;
+      }) {
+        const result = await this.doGenerate(options);
+        yield { type: "text-delta", textDelta: result.text };
+      },
+    }),
+  };
+}

lib/ai/runtime/generated-image-persistence.ts

@@ -61,6 +61,8 @@ export function parseImageAltMetadata(altText: string, thumbnailUrl: string): {
       originalUrl = thumbnailUrl.replace("snapgen-image-thumb-", "snapgen-image-orig-");
     } else if (thumbnailUrl.includes("bananaimage-thumb-")) {
       originalUrl = thumbnailUrl.replace("bananaimage-thumb-", "bananaimage-orig-");
+    } else if (thumbnailUrl.includes("visionary-thumb-")) {
+      originalUrl = thumbnailUrl.replace("visionary-thumb-", "visionary-orig-");
     }
   }
 

lib/ai/visionary-models.ts

@@ -0,0 +1,161 @@
+export interface VisionaryModelPreset {
+  modelId: string;
+  displayName: string;
+  description: string;
+  supportsVision: boolean;
+  supportsImageGen: boolean;
+  capabilities?: Record<string, any>;
+  defaultParams?: Record<string, any>;
+  imageGenConfig?: Record<string, any>;
+  sortOrder: number;
+}
+
+export const VISIONARY_BASE_URL = "https://api.visionary.beer";
+
+const VISIONARY_GPT_IMAGE_RATIOS = [
+  "auto",
+  "1:1",
+  "3:2",
+  "2:3",
+  "4:3",
+  "3:4",
+  "16:9",
+  "9:16",
+  "21:9",
+  "9:21",
+  "2:1",
+  "1:2",
+  "5:4",
+  "4:5",
+  "3:1",
+  "1:3",
+];
+
+const VISIONARY_NANO_BANANA_RATIOS = [
+  "auto",
+  "1:1",
+  "4:3",
+  "3:4",
+  "3:2",
+  "2:3",
+  "16:9",
+  "9:16",
+  "21:9",
+  "5:4",
+  "4:5",
+  "1:4",
+  "4:1",
+  "1:8",
+  "8:1",
+];
+
+function buildVisionaryPreset(params: {
+  modelId: string;
+  displayName: string;
+  description: string;
+  supportedAspectRatios: string[];
+  supportedImageSizes: string[];
+  defaultImageSize: string;
+  supportsQuality?: boolean;
+  supportsPromptExtend?: boolean;
+  sortOrder: number;
+}) {
+  const supportedModes = ["text-to-image", "image-to-image", "reference-images"];
+
+  return {
+    modelId: params.modelId,
+    displayName: params.displayName,
+    description: params.description,
+    supportsVision: true,
+    supportsImageGen: true,
+    capabilities: {
+      provider: "visionary",
+      apiFormat: "visionary-task",
+      supportedModes,
+      supportedAspectRatios: params.supportedAspectRatios,
+      supportedImageSizes: params.supportedImageSizes,
+      supportsMultiImageReference: true,
+      maxReferenceImages: 9,
+      supportsQuality: Boolean(params.supportsQuality),
+    },
+    defaultParams: {
+      provider: "visionary",
+      apiFormat: "visionary-task",
+      endpoint: params.modelId,
+      imageSize: params.defaultImageSize,
+      aspectRatio: "auto",
+      quality: "auto",
+      supportedModes,
+    },
+    imageGenConfig: {
+      apiFormat: "visionary-task",
+      maxImages: 1,
+      supportsSize: true,
+      supports1K: params.supportedImageSizes.includes("1K"),
+      supports2K: params.supportedImageSizes.includes("2K"),
+      supports4K: params.supportedImageSizes.includes("4K"),
+      supportsPromptExtend: Boolean(params.supportsPromptExtend),
+      supportsNegativePrompt: false,
+      supportsWatermark: false,
+      supportsSeed: false,
+      supportsQuality: Boolean(params.supportsQuality),
+      maxReferenceImages: 9,
+      supportedImageSizes: params.supportedImageSizes,
+      supportedAspectRatios: params.supportedAspectRatios,
+      enableLoadingPlaceholder: true,
+      loadingColor: "yellow",
+    },
+    sortOrder: params.sortOrder,
+  } satisfies VisionaryModelPreset;
+}
+
+export const VISIONARY_MODEL_PRESETS: VisionaryModelPreset[] = [
+  buildVisionaryPreset({
+    modelId: "gpt-image-2",
+    displayName: "Visionary GPT Image 2",
+    description:
+      "Visionary GPT Image 2。支持文生图、最多 9 张参考图、完整比例选择、质量档位和 1K/2K/4K 输出。",
+    supportedAspectRatios: VISIONARY_GPT_IMAGE_RATIOS,
+    supportedImageSizes: ["1K", "2K", "4K"],
+    defaultImageSize: "1K",
+    supportsQuality: true,
+    sortOrder: 10,
+  }),
+  buildVisionaryPreset({
+    modelId: "nano-banana-pro",
+    displayName: "Visionary Nano Banana Pro",
+    description:
+      "Visionary Nano Banana Pro。支持文生图、多图编辑、中文文字增强、极端比例和 2K/4K 输出。",
+    supportedAspectRatios: VISIONARY_NANO_BANANA_RATIOS,
+    supportedImageSizes: ["2K", "4K"],
+    defaultImageSize: "2K",
+    supportsPromptExtend: true,
+    sortOrder: 20,
+  }),
+  buildVisionaryPreset({
+    modelId: "nano-banana-pro-cl",
+    displayName: "Visionary Nano Banana Pro CL",
+    description:
+      "Visionary Nano Banana Pro CL 开放 API 高质量线路。支持文生图、多图编辑、极端比例和 2K/4K 输出。",
+    supportedAspectRatios: VISIONARY_NANO_BANANA_RATIOS,
+    supportedImageSizes: ["2K", "4K"],
+    defaultImageSize: "2K",
+    sortOrder: 30,
+  }),
+  buildVisionaryPreset({
+    modelId: "nano-banana-2-lite",
+    displayName: "Visionary Nano Banana 2 Lite",
+    description:
+      "Visionary Nano Banana 2 Lite 低延迟线路。支持文生图、多图编辑和极端比例，固定输出 1K。",
+    supportedAspectRatios: VISIONARY_NANO_BANANA_RATIOS,
+    supportedImageSizes: ["1K"],
+    defaultImageSize: "1K",
+    sortOrder: 40,
+  }),
+];
+
+export function getVisionaryModelPresetById(modelId: string) {
+  return VISIONARY_MODEL_PRESETS.find(
+    (preset) => preset.modelId === String(modelId || "").trim()
+  );
+}

lib/canvas/generate-image.ts

@@ -11,6 +11,7 @@ import { createFalImage } from "@/lib/ai/providers/fal-image";
 import { createSnapgenImage } from "@/lib/ai/providers/snapgen-image";
 import { createOpenAIImage } from "@/lib/ai/providers/openai-image";
 import { createBananaImage } from "@/lib/ai/providers/bananaimage";
+import { createVisionary } from "@/lib/ai/providers/visionary";
 import { createStepfunImage } from "@/lib/ai/providers/stepfun-image";
 import { createMidjourney } from "@/lib/ai/providers/midjourney";
 import { createRunway } from "@/lib/ai/providers/runway";
@@ -233,6 +234,7 @@ const SUPPORTED_CANVAS_PROVIDER_TYPES = new Set([
   "snapgen-image",
   "openai-image",
   "bananaimage",
+  "visionary",
   "stepfun-image",
   "midjourney",
   "runway",
@@ -3158,6 +3160,7 @@ function getProviderBatchLimit(providerType: string) {
     case "bfl-image":
     case "openai-image":
     case "bananaimage":
+    case "visionary":
     case "stepfun-image":
     case "midjourney":
     case "runway":
@@ -3191,6 +3194,7 @@ function getCanvasScaleAdjustProviderFailoverPriority(providerType: string) {
     case "snapgen-image":
       return 20;
     case "bananaimage":
+    case "visionary":
       return 25;
     case "krea":
       return 30;
@@ -3770,7 +3774,7 @@ export async function generateCanvasImage(
   if (!SUPPORTED_CANVAS_PROVIDER_TYPES.has(provider.type)) {
     if (request.allowFailover === false) {
       throw new Error(
-        "当前图片模型类型暂不支持画布生成，请在后台选择 Gemini/Grsai GPT Image/火山 Seedream/阿里/BFL/RUXA/FAL/SnapGen/OpenAI/BananaImage/StepFun/Runway/Krea 图片模型。"
+        "当前图片模型类型暂不支持画布生成，请在后台选择 Gemini/Grsai GPT Image/火山 Seedream/阿里/BFL/RUXA/FAL/SnapGen/OpenAI/BananaImage/Visionary/StepFun/Runway/Krea 图片模型。"
       );
     }
 
@@ -3803,7 +3807,7 @@ export async function generateCanvasImage(
     }
     if (!SUPPORTED_CANVAS_PROVIDER_TYPES.has(fallbackProvider.type)) {
       throw new Error(
-        "当前图片模型类型暂不支持画布生成，请在后台选择 Gemini/Grsai GPT Image/火山 Seedream/阿里/BFL/RUXA/FAL/SnapGen/OpenAI/BananaImage/StepFun/Runway/Krea 图片模型。"
+        "当前图片模型类型暂不支持画布生成，请在后台选择 Gemini/Grsai GPT Image/火山 Seedream/阿里/BFL/RUXA/FAL/SnapGen/OpenAI/BananaImage/Visionary/StepFun/Runway/Krea 图片模型。"
       );
     }
     if (fallbackModel.model.id !== selectedModel.model.id) {
@@ -4065,6 +4069,26 @@ export async function generateCanvasImage(
       });
       return result.text || "";
     };
+  } else if (provider.type === "visionary") {
+    const visionaryProvider = createVisionary({
+      apiKey: provider.apiKey,
+      baseURL: provider.baseUrl,
+    });
+    const runtimeModelId = resolveModelRuntimeId(selectedModel.model, {
+      providerType: provider.type,
+    });
+    const modelInstance = visionaryProvider.chat(runtimeModelId);
+    executeGenerateBatch = async (batchImageCount) => {
+      const result = await modelInstance.doGenerate({
+        messages,
+        imageParams: {
+          ...imageParams,
+          imageCount: batchImageCount,
+        },
+        imageGenConfig: selectedModel.model.imageGenConfig || null,
+      });
+      return result.text || "";
+    };
   } else if (provider.type === "stepfun-image") {
     const stepfunProvider = createStepfunImage({
       apiKey: provider.apiKey,

lib/db/migrate.ts

@@ -34,6 +34,7 @@ const providerBaseUrlDefaults = [
   { type: "snapgen-image", baseUrl: "https://api.snapgen.ai" },
   { type: "openai-image", baseUrl: "https://api.openai.com/v1" },
   { type: "bananaimage", baseUrl: "https://bananaimage.aigenmedia.art" },
+  { type: "visionary", baseUrl: "https://api.visionary.beer" },
   { type: "stepfun-image", baseUrl: "https://api.stepfun.com" },
   { type: "midjourney", baseUrl: "https://your-midjourney-api.example.com" },
   { type: "fal-video", baseUrl: "https://fal.run" },
@@ -151,7 +152,7 @@ async function runMigrationStatements(db: ReturnType<typeof drizzle>) {
       ADD CONSTRAINT "AiProvider_type_check"
       CHECK (type IN (
         'alibaba', 'openai', 'custom', 'local', 'gemini',
-        'grsai-gpt-image', 'grsai-video', 'huanke-gemini', 'qianwen-video', 'doubao-video', 'ruxa-video', 'volcano-vision', 'volcano-video', 'alibaba-image', 'bfl-image', 'ruxa-image', 'fal-image', 'snapgen-image', 'openai-image', 'bananaimage', 'stepfun-image', 'midjourney', 'fal-video', 'zhipu', 'tripo-3d', 'worldlabs-3d', 'kittycad-cad', 'runway', 'krea'
+        'grsai-gpt-image', 'grsai-video', 'huanke-gemini', 'qianwen-video', 'doubao-video', 'ruxa-video', 'volcano-vision', 'volcano-video', 'alibaba-image', 'bfl-image', 'ruxa-image', 'fal-image', 'snapgen-image', 'openai-image', 'bananaimage', 'visionary', 'stepfun-image', 'midjourney', 'fal-video', 'zhipu', 'tripo-3d', 'worldlabs-3d', 'kittycad-cad', 'runway', 'krea'
       ));
     `);
   await db.execute(sql`

lib/db/migrations/0091_add_visionary_provider_type.sql

@@ -0,0 +1,39 @@
+ALTER TABLE "AiProvider"
+  DROP CONSTRAINT IF EXISTS "AiProvider_type_check";
+
+ALTER TABLE "AiProvider"
+  ADD CONSTRAINT "AiProvider_type_check"
+  CHECK (
+    "type" IN (
+      'alibaba',
+      'openai',
+      'custom',
+      'local',
+      'gemini',
+      'grsai-gpt-image',
+      'grsai-video',
+      'huanke-gemini',
+      'qianwen-video',
+      'doubao-video',
+      'ruxa-video',
+      'volcano-vision',
+      'volcano-video',
+      'alibaba-image',
+      'bfl-image',
+      'ruxa-image',
+      'fal-image',
+      'snapgen-image',
+      'openai-image',
+      'bananaimage',
+      'visionary',
+      'stepfun-image',
+      'midjourney',
+      'fal-video',
+      'zhipu',
+      'tripo-3d',
+      'worldlabs-3d',
+      'kittycad-cad',
+      'runway',
+      'krea'
+    )
+  );

lib/db/migrations/meta/_journal.json

@@ -526,6 +526,13 @@
       "when": 1783946203000,
       "tag": "0088_add_bananaimage_provider_type",
       "breakpoints": true
+    },
+    {
+      "idx": 75,
+      "version": "7",
+      "when": 1784025600000,
+      "tag": "0091_add_visionary_provider_type",
+      "breakpoints": true
     }
   ]
 }

lib/db/queries.ts

@@ -3914,7 +3914,7 @@ export async function createAiProvider({
   updatedBy,
 }: {
   name: string;
-  type: "alibaba" | "openai" | "custom" | "local" | "gemini" | "grsai-gpt-image" | "grsai-video" | "huanke-gemini" | "qianwen-video" | "doubao-video" | "ruxa-video" | "volcano-vision" | "volcano-video" | "alibaba-image" | "bfl-image" | "ruxa-image" | "fal-image" | "snapgen-image" | "openai-image" | "bananaimage" | "stepfun-image" | "midjourney" | "fal-video" | "zhipu" | "tripo-3d" | "worldlabs-3d" | "kittycad-cad" | "runway" | "krea";
+  type: "alibaba" | "openai" | "custom" | "local" | "gemini" | "grsai-gpt-image" | "grsai-video" | "huanke-gemini" | "qianwen-video" | "doubao-video" | "ruxa-video" | "volcano-vision" | "volcano-video" | "alibaba-image" | "bfl-image" | "ruxa-image" | "fal-image" | "snapgen-image" | "openai-image" | "bananaimage" | "visionary" | "stepfun-image" | "midjourney" | "fal-video" | "zhipu" | "tripo-3d" | "worldlabs-3d" | "kittycad-cad" | "runway" | "krea";
   baseUrl: string;
   apiKey: string;
   isEnabled?: boolean;
@@ -3952,7 +3952,7 @@ export async function updateAiProvider({
 }: {
   id: string;
   name?: string;
-  type?: "alibaba" | "openai" | "custom" | "local" | "gemini" | "grsai-gpt-image" | "grsai-video" | "huanke-gemini" | "qianwen-video" | "doubao-video" | "ruxa-video" | "volcano-vision" | "volcano-video" | "alibaba-image" | "bfl-image" | "ruxa-image" | "fal-image" | "snapgen-image" | "openai-image" | "bananaimage" | "stepfun-image" | "midjourney" | "fal-video" | "zhipu" | "tripo-3d" | "worldlabs-3d" | "kittycad-cad" | "runway" | "krea";
+  type?: "alibaba" | "openai" | "custom" | "local" | "gemini" | "grsai-gpt-image" | "grsai-video" | "huanke-gemini" | "qianwen-video" | "doubao-video" | "ruxa-video" | "volcano-vision" | "volcano-video" | "alibaba-image" | "bfl-image" | "ruxa-image" | "fal-image" | "snapgen-image" | "openai-image" | "bananaimage" | "visionary" | "stepfun-image" | "midjourney" | "fal-video" | "zhipu" | "tripo-3d" | "worldlabs-3d" | "kittycad-cad" | "runway" | "krea";
   baseUrl?: string;
   apiKey?: string;
   isEnabled?: boolean;

lib/db/schema.ts

@@ -308,7 +308,7 @@ export type ToolConfig = InferSelectModel<typeof toolConfig>;
 export const aiProvider = pgTable("AiProvider", {
   id: uuid("id").primaryKey().notNull().defaultRandom(),
   name: varchar("name", { length: 128 }).notNull(), // 提供商名称，如 "阿里云通义千问"
-  type: varchar("type", { enum: ["alibaba", "openai", "custom", "local", "gemini", "grsai-gpt-image", "grsai-video", "huanke-gemini", "qianwen-video", "doubao-video", "ruxa-video", "volcano-vision", "volcano-video", "alibaba-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "stepfun-image", "midjourney", "fal-video", "zhipu", "tripo-3d", "worldlabs-3d", "kittycad-cad", "runway", "krea", "bfl-image"] })
+  type: varchar("type", { enum: ["alibaba", "openai", "custom", "local", "gemini", "grsai-gpt-image", "grsai-video", "huanke-gemini", "qianwen-video", "doubao-video", "ruxa-video", "volcano-vision", "volcano-video", "alibaba-image", "ruxa-image", "fal-image", "snapgen-image", "openai-image", "bananaimage", "visionary", "stepfun-image", "midjourney", "fal-video", "zhipu", "tripo-3d", "worldlabs-3d", "kittycad-cad", "runway", "krea", "bfl-image"] })
     .notNull()
     .default("custom"), // 提供商类型
   baseUrl: text("baseUrl").notNull(), // API 基础 URL

lib/external-image-api/service.ts

@@ -346,6 +346,7 @@ function supportsImageEditForReferenceCount(
   const providerImpliesReferenceEdit =
     providerType === "openai-image" ||
     providerType === "bananaimage" ||
+    providerType === "visionary" ||
     providerType === "grsai-gpt-image" ||
     providerType === "ruxa-image" ||
     providerType === "snapgen-image";
@@ -422,6 +423,10 @@ function getExternalImageApiPriority(entry: ImageModelEntry) {
     return 380;
   }
 
+  if (isGptImage2 && providerType === "visionary") {
+    return 370;
+  }
+
   if (isGptImage2 && providerType === "grsai-gpt-image") {
     return isVip ? 350 : 340;
   }

lib/image-url.ts

@@ -54,7 +54,8 @@ export function isLikelyThumbnailUrl(url: string): boolean {
     lowerUrl.includes("stepfun-image-thumb-") ||
     lowerUrl.includes("fal-image-thumb-") ||
     lowerUrl.includes("snapgen-image-thumb-") ||
-    lowerUrl.includes("bananaimage-thumb-")
+    lowerUrl.includes("bananaimage-thumb-") ||
+    lowerUrl.includes("visionary-thumb-")
   ) {
     return true;
   }
@@ -100,6 +101,9 @@ export function inferOriginalImageUrl(url: string): string {
   if (url.includes("bananaimage-thumb-")) {
     return url.replace("bananaimage-thumb-", "bananaimage-orig-");
   }
+  if (url.includes("visionary-thumb-")) {
+    return url.replace("visionary-thumb-", "visionary-orig-");
+  }
 
   if (url.includes("/thumb/")) {
     return url.replace("/thumb/", "/");

lib/scene-fusion/output-capabilities.ts

@@ -78,6 +78,7 @@ export function canProcessSceneFusionProviderType(providerType: string): boolean
     case "snapgen-image":
     case "openai-image":
     case "bananaimage":
+    case "visionary":
     case "gemini":
     case "volcano-vision":
       return true;
@@ -133,6 +134,7 @@ function getSupportedAspectRatiosByProvider(
     case "fal-image":
     case "openai-image":
     case "bananaimage":
+    case "visionary":
     case "gemini":
     default:
       return [...ALL_ASPECT_RATIO_VALUES];