fix(realtime-canvas): use runware seedImage-compatible model

app/api/realtime/config/route.ts

@@ -34,7 +34,7 @@ const defaultConfig = {
     jpegQuality: 0.55,
   },
   model: {
-    id: "runware:400@4",
+    id: "runware:101@1",
     defaults: {
       steps: 4,
       cfgScale: 3.5,

app/api/realtime/generate/route.ts

@@ -108,7 +108,10 @@ export async function POST(request: Request) {
     );
   }
 
-  const model = String(config.runwareModel || process.env.RUNWARE_MODEL || "runware:400@4").trim();
+  const fallbackSeedImageModel = "runware:101@1";
+  const model = String(
+    config.runwareModel || process.env.RUNWARE_MODEL || fallbackSeedImageModel
+  ).trim();
   const maxInputResolution = clamp(Number(config.maxInputResolution || 1024), 512, 1536);
   const size = resolveSquareSize(body.imageSize, maxInputResolution);
   const steps = clamp(
@@ -127,56 +130,85 @@ export async function POST(request: Request) {
     1
   );
 
-  const taskUUID = crypto.randomUUID();
+  const positivePrompt =
-  const runwareRequest = [
+    String(body.prompt || "").trim() || "将草图渲染为高质感产品设计图，保持结构和主轮廓一致。";
-    {
+
-      taskType: "imageInference",
+  const requestInference = async (modelId: string) => {
+    const taskUUID = crypto.randomUUID();
+    const runwareRequest = [
+      {
+        taskType: "imageInference",
+        taskUUID,
+        model: modelId,
+        positivePrompt,
+        seedImage: imageUrl,
+        width: size,
+        height: size,
+        strength,
+        CFGScale: cfgScale,
+        steps,
+        numberResults: 1,
+        outputType: "dataURI",
+        outputFormat: "JPG",
+      },
+    ];
+
+    const upstreamResponse = await fetch("https://api.runware.ai/v1", {
+      method: "POST",
+      headers: {
+        Authorization: `Bearer ${runwareApiKey}`,
+        "Content-Type": "application/json",
+        Accept: "application/json",
+      },
+      body: JSON.stringify(runwareRequest),
+      cache: "no-store",
+    });
+
+    const upstreamJson = await upstreamResponse.json().catch(() => null);
+    const upstreamError = parseRunwareError(upstreamJson);
+
+    return {
       taskUUID,
-      model,
+      modelId,
-      positivePrompt: String(body.prompt || "").trim() || "将草图渲染为高质感产品设计图，保持结构和主轮廓一致。",
+      upstreamResponse,
-      seedImage: imageUrl,
+      upstreamJson,
-      width: size,
+      upstreamError,
-      height: size,
+    };
-      strength,
+  };
-      CFGScale: cfgScale,
-      steps,
-      numberResults: 1,
-      outputType: "dataURI",
-      outputFormat: "JPG",
-    },
-  ];
 
-  const upstreamResponse = await fetch("https://api.runware.ai/v1", {
+  let requestResult = await requestInference(model);
-    method: "POST",
+  const shouldRetryWithSeedImageModel =
-    headers: {
+    (requestResult.upstreamError || "")
-      Authorization: `Bearer ${runwareApiKey}`,
+      .toLowerCase()
-      "Content-Type": "application/json",
+      .includes("unsupported use of 'seedimage' parameter") &&
-      Accept: "application/json",
+    model !== fallbackSeedImageModel;
-    },
-    body: JSON.stringify(runwareRequest),
-    cache: "no-store",
-  });
 
-  const upstreamJson = await upstreamResponse.json().catch(() => null);
+  if (shouldRetryWithSeedImageModel) {
-  const upstreamError = parseRunwareError(upstreamJson);
+    requestResult = await requestInference(fallbackSeedImageModel);
+  }
 
-  if (!upstreamResponse.ok || upstreamError) {
+  if (!requestResult.upstreamResponse.ok || requestResult.upstreamError) {
     return Response.json(
       {
         code: "RUNWARE_REQUEST_FAILED",
-        message: upstreamError || `Runware 请求失败（${upstreamResponse.status}）`,
+        message:
+          requestResult.upstreamError ||
+          `Runware 请求失败（${requestResult.upstreamResponse.status}）`,
       },
       { status: 502 }
     );
   }
 
-  const resultList = Array.isArray(upstreamJson)
+  const resultList = Array.isArray(requestResult.upstreamJson)
-    ? upstreamJson
+    ? requestResult.upstreamJson
-    : Array.isArray(upstreamJson?.data)
+    : Array.isArray(requestResult.upstreamJson?.data)
-      ? upstreamJson.data
+      ? requestResult.upstreamJson.data
       : [];
   const imageResult =
-    resultList.find((item: any) => item?.taskUUID === taskUUID && (item?.imageDataURI || item?.imageURL)) ||
+    resultList.find(
+      (item: any) =>
+        item?.taskUUID === requestResult.taskUUID && (item?.imageDataURI || item?.imageURL)
+    ) ||
     resultList.find((item: any) => item?.imageDataURI || item?.imageURL);
 
   const imageDataURI = String(imageResult?.imageDataURI || "").trim();
@@ -194,16 +226,16 @@ export async function POST(request: Request) {
   console.log("[RealtimeRunware] frame success", {
     userId: session.user.id,
     requestId: body.requestId || null,
-    taskUUID,
+    taskUUID: requestResult.taskUUID,
-    model,
+    model: requestResult.modelId,
     cost,
   });
 
   return Response.json({
     ok: true,
     provider: "runware",
-    model,
+    model: requestResult.modelId,
-    taskUUID,
+    taskUUID: requestResult.taskUUID,
     imageDataURI: imageDataURI || undefined,
     imageUrl: imageURL || undefined,
     cost,

components/canvas/RealtimeCanvasDialog.tsx

@@ -89,7 +89,7 @@ const defaultRealtimeConfig: RealtimeConfig = {
     jpegQuality: 0.55,
   },
   model: {
-    id: "runware:400@4",
+    id: "runware:101@1",
     defaults: {
       steps: 4,
       cfgScale: 3.5,