Prevent chat models from entering media generation

NewApiWG model discovery was allowing Doubao text models to appear in media-generation contexts, which made image nodes call a model with no generation channel. The change filters Doubao chat/vision model names out of generation capability inference, bumps model caches, and guards execution for stale saved workflows.

Constraint: NewApiWG /models may return chat models without explicit capability metadata

Rejected: Keep all unknown models visible | it lets text-only models fail inside media nodes

Confidence: high

Scope-risk: narrow

Directive: Do not classify chat/VLM models as media generators without explicit generation capability metadata

Tested: npm test -- src/app/api/generate/providers/__tests__/newapiwg.test.ts

Tested: npm test -- src/components/__tests__/ModelSearchDialog.test.tsx

Not-tested: Full tsc remains blocked by existing unrelated test type errors

src/app/api/generate/providers/__tests__/newapiwg.test.ts

@@ -57,6 +57,19 @@ describe("NewApiWG model capability inference", () => {
       supported_endpoint_types: ["openai"],
     })).toEqual(["text-to-video", "image-to-video"]);
 
+    expect(inferNewApiWGCapabilities({
+      id: "doubao-seed-2-0-pro-260215",
+      name: "Doubao Seed 2.0 Pro",
+      owned_by: "doubao",
+      supported_endpoint_types: ["openai"],
+    })).toEqual([]);
+
+    expect(inferNewApiWGCapabilities({
+      id: "doubao-1-5-vision-pro",
+      owned_by: "doubao",
+      supported_endpoint_types: ["openai"],
+    })).toEqual([]);
+
     expect(inferNewApiWGCapabilities({
       id: "speech-2.8-hd",
       owned_by: "minimax",
@@ -89,6 +102,7 @@ describe("NewApiWG model capability inference", () => {
     vi.stubGlobal("fetch", vi.fn(async () => new Response(JSON.stringify({
       data: [
         { id: "kimi-k2.6", owned_by: "moonshot", supported_endpoint_types: ["openai"] },
+        { id: "doubao-seed-2-0-pro-260215", owned_by: "doubao", supported_endpoint_types: ["openai"] },
         { id: "doubao-seedance-2-0-260128", owned_by: "doubao-video", supported_endpoint_types: ["openai"] },
         { id: "apiyi_sora_image", owned_by: "custom", supported_endpoint_types: ["openai"] },
       ],
@@ -361,6 +375,25 @@ describe("NewApiWG generation payloads", () => {
     expect(capturedBody!.image).toBe("data:image/png;base64,input");
   });
 
+  it("blocks cached Doubao chat models before calling media generation endpoints", async () => {
+    const result = await generateWithNewApiWG("test-key", "https://newapi.example/v1", makeInput({
+      model: {
+        id: "doubao-seed-2-0-pro-260215",
+        name: "Doubao Seed 2.0 Pro",
+        description: null,
+        provider: "newapiwg",
+        capabilities: ["text-to-image", "image-to-image"],
+      },
+      prompt: "draw a banana",
+    }));
+
+    expect(result.success).toBe(false);
+    expect(result.error).toBe(
+      "Doubao Seed 2.0 Pro: this is a text/chat model, not an image, video, audio, or 3D generation model. Choose a generation model such as PopiArt Nano Pro, Seedream, or Seedance."
+    );
+    expect(capturedBody).toBeNull();
+  });
+
   it("normalizes transient provider overload errors", () => {
     expect(normalizeNewApiWGError("system disk overloaded", "Nano Banana")).toBe(
       "Nano Banana: provider is temporarily overloaded. Please retry in a moment or switch models."

src/app/api/generate/providers/newapiwg.ts

@@ -71,6 +71,10 @@ export function normalizeNewApiWGBaseUrl(baseUrl?: string | null): string {
   return (baseUrl || process.env.NEWAPIWG_BASE_URL || DEFAULT_NEWAPIWG_BASE_URL).replace(/\/+$/, "");
 }
 
+function isDoubaoChatModelName(text: string): boolean {
+  return /(^|[\s_\-/])doubao[\s_\-/](?!seedance|seedream)(?:seed|lite|pro|vision|flash|thinking|1|[0-9])/i.test(text);
+}
+
 function flattenTags(value: unknown): string[] {
   if (!value) return [];
   if (Array.isArray(value)) return value.flatMap(flattenTags);
@@ -119,6 +123,9 @@ export function inferNewApiWGCapabilities(model: NewApiWGModelObject): ModelCapa
     ...flattenTags(model.supported_endpoint_types),
     ...rawTags,
   ].filter(Boolean).join(" ").toLowerCase();
+  const modelNameText = [model.id, model.name].filter(Boolean).join(" ").toLowerCase();
+  const isDoubaoChatOnly = isDoubaoChatModelName(modelNameText);
+  if (isDoubaoChatOnly) return [];
 
   const isImageNamedSora = /(^|[\s_\-/])sora[_\-/]?image(?=$|[\s_\-/])/.test(text);
   const hasImage = /image|img|vision|picture|photo|flux|sdxl|stable-diffusion|midjourney|dall-e|gpt-image|imagen|seedream|banana|ernie-image/.test(text);
@@ -738,6 +745,13 @@ export async function generateWithNewApiWG(
   input: GenerationInput
 ): Promise<GenerationOutput> {
   const normalizedBaseUrl = normalizeNewApiWGBaseUrl(baseUrl);
+  if (isDoubaoChatModelName(`${input.model.id} ${input.model.name}`)) {
+    return {
+      success: false,
+      error: `${input.model.name}: this is a text/chat model, not an image, video, audio, or 3D generation model. Choose a generation model such as PopiArt Nano Pro, Seedream, or Seedance.`,
+    };
+  }
+
   const isVideo = input.model.capabilities.some((cap) => cap.includes("video"));
   const isAudio = !isVideo && input.model.capabilities.includes("text-to-audio");
   const prompt = promptFromInput(input);

src/app/api/models/route.ts

@@ -1241,7 +1241,7 @@ export async function GET(
     // For fal.ai, include search in cache key since their API supports search
     const cacheKey =
       provider === "newapiwg"
-        ? `${getCacheKey(provider)}:${newApiWGBaseUrl}:${newApiWGKey?.slice(-8) ?? "no-key"}`
+        ? `${getCacheKey(provider)}:cap-v2:${newApiWGBaseUrl}:${newApiWGKey?.slice(-8) ?? "no-key"}`
         : provider === "replicate" || provider === "wavespeed"
         ? getCacheKey(provider)
         : getCacheKey(provider, searchQuery);

src/components/modals/ModelSearchDialog.tsx

@@ -10,7 +10,7 @@ import { ProviderModel, ModelCapability } from "@/lib/providers/types";
 import { useI18n } from "@/i18n";
 
 // localStorage cache for models (persists across dev server restarts)
-const MODELS_CACHE_KEY = "node-banana-models-cache";
+const MODELS_CACHE_KEY = "node-banana-models-cache-v2";
 const MODELS_CACHE_TTL = 48 * 60 * 60 * 1000; // 48 hours
 
 interface ModelsCacheEntry {