fix: recognize BFL reference image support

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

@@ -1,6 +1,7 @@
 import { createLogger } from "@/lib/observability/logger";
 import { isFalGptImage2EditModelId } from "@/lib/ai/providers/fal-image";
 import { getLanguageModelById } from "@/lib/ai/dynamic-provider";
+import { modelLacksReferenceImageInputSupport } from "@/lib/ai/reference-image-capability";
 import type { ChatMessage } from "@/lib/types";
 import { convertMessagesWithImages } from "./image-media";
 
@@ -370,7 +371,10 @@ export async function generateImageWithFailoverCandidate(params: {
   const { candidate, messages, imageParams, fallbackImageParams } = params;
   const providerType = String(candidate.provider?.type || "");
   const candidateRuntimeModelId = resolveImageModelRuntimeId(candidate.model);
-  if (chatMessagesHaveImageInput(messages) && candidate.model?.supportsVision === false) {
+  if (
+    chatMessagesHaveImageInput(messages) &&
+    modelLacksReferenceImageInputSupport(candidate.model, candidate.provider)
+  ) {
     throw new Error(
       `备用模型不支持参考图/图生图输入：${candidate.model.displayName || candidate.model.id}`
     );

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

@@ -14,6 +14,10 @@ import {
   getPointsSystemConfig,
   getSiteSettings,
 } from "@/lib/db/queries";
+import {
+  modelLacksReferenceImageInputSupport,
+  modelSupportsReferenceImageInput,
+} from "@/lib/ai/reference-image-capability";
 import { getImageToolCreditCost } from "@/lib/points/config";
 import { prepareFeaturePointsCharge } from "@/lib/points/feature-charge";
 import { uploadFile } from "@/lib/storage/service";
@@ -217,7 +221,10 @@ function findModelSelectionEntry(
 function isScaleAdjustDedicatedDetailModel(
   entry: AiModelWithProviderForSelection | null | undefined
 ) {
-  if (!entry?.model?.supportsImageGen || entry.model.supportsVision === false) {
+  if (
+    !entry?.model?.supportsImageGen ||
+    modelLacksReferenceImageInputSupport(entry.model, entry.provider)
+  ) {
     return false;
   }
   const label = `${entry.model.displayName || ""} ${entry.model.modelId || ""}`
@@ -237,7 +244,7 @@ function isHealthyImageModelEntry(
 ) {
   return (
     Boolean(entry?.model?.supportsImageGen) &&
-    entry?.model?.supportsVision !== false &&
+    modelSupportsReferenceImageInput(entry?.model, entry?.provider) &&
     entry?.model?.healthStatus === "healthy"
   );
 }

app/api/scene-fusion/route.ts

@@ -35,6 +35,7 @@ import {
 import { acquireCanvasImageModelSlot } from "@/lib/canvas/image-concurrency";
 import { createLogger } from "@/lib/observability/logger";
 import { resolveModelRuntimeId } from "@/lib/ai/model-runtime";
+import { modelSupportsReferenceImageInput } from "@/lib/ai/reference-image-capability";
 import { resolveLongestEdgeDimensions } from "@/lib/ai/image-size-constraints";
 
 // 请求体 Schema
@@ -905,7 +906,7 @@ function buildSceneFusionCandidatePool(
         id: String(entry.model.id),
         modelId: String(entry.model.modelId || ""),
         displayName: String(entry.model.displayName || entry.model.modelId || entry.model.id),
-        supportsVision: Boolean(entry.model.supportsVision),
+        supportsVision: modelSupportsReferenceImageInput(entry.model, entry.provider),
         imageGenConfig: (entry.model.imageGenConfig || null) as SceneFusionImageGenConfig | null,
         excludeFromFailover: Boolean(entry.model.excludeFromFailover),
         defaultParams: (entry.model.defaultParams as Record<string, any> | null) || null,

lib/ai/model-router.ts

@@ -10,6 +10,7 @@ import {
   isImageGenerationModelDescriptor,
   isVideoModelDescriptor,
 } from "@/lib/ai/model-classification";
+import { isKnownReferenceImageModel } from "@/lib/ai/reference-image-capability";
 
 type EnabledModelWithProvider = Awaited<
   ReturnType<typeof import("@/lib/db/queries")["getEnabledAiModelsWithProvider"]>
@@ -31,8 +32,13 @@ function hasVisionCapability(model: {
   supportsVision?: boolean | null;
   capabilities?: unknown;
   defaultParams?: unknown;
-}) {
-  return Boolean(model.supportsVision) || isAiModelMultimodal(model);
+  modelId?: unknown;
+}, providerType?: string | null) {
+  return (
+    Boolean(model.supportsVision) ||
+    isKnownReferenceImageModel(model, { type: providerType }) ||
+    isAiModelMultimodal(model)
+  );
 }
 
 const CHAT_PROVIDER_TYPES = [
@@ -86,7 +92,7 @@ function isConversationalCandidate(
   const matchesPreferredProvider = CHAT_PROVIDER_TYPES.includes(
     providerType as (typeof CHAT_PROVIDER_TYPES)[number],
   );
-  const hasVision = hasVisionCapability(item.model);
+  const hasVision = hasVisionCapability(item.model, providerType);
 
   if (matchesPreferredProvider) {
     return requireVision ? hasVision : true;
@@ -120,7 +126,7 @@ function matchesIntentRequirements(
   if (params.intent === "vision") {
     return (
       !isVideoProviderType(String(item.provider.type || ""), item.model) &&
-      hasVisionCapability(item.model)
+      hasVisionCapability(item.model, item.provider.type)
     );
   }
 
@@ -128,7 +134,7 @@ function matchesIntentRequirements(
     return isVideoProviderType(String(item.provider.type || ""), item.model);
   }
 
-  if (params.requireVision && !hasVisionCapability(item.model)) return false;
+  if (params.requireVision && !hasVisionCapability(item.model, item.provider.type)) return false;
   if (
     params.requireImageGen &&
     !isImageGenerationModelDescriptor({
@@ -271,7 +277,9 @@ export async function routeToModel(params: {
 
     if (configuredModel) {
       const isImageIntent = intent === "image_edit" || intent === "image_gen";
-      const matchesVision = !config.requireVision || hasVisionCapability(configuredModel.model);
+      const matchesVision =
+        !config.requireVision ||
+        hasVisionCapability(configuredModel.model, configuredModel.provider.type);
       const matchesImageGen = !config.requireImageGen || configuredModel.model.supportsImageGen;
       const allowImageIntentWithImageGenOnly =
         isImageIntent && configuredModel.model.supportsImageGen;
@@ -347,7 +355,8 @@ export async function routeToModel(params: {
       !item.model.isSubModel &&
       item.model.isEnabled &&
       !isVideoProviderType(String(item.provider.type || ""), item.model) &&
-      (item.model.supportsImageGen || hasVisionCapability(item.model))
+      (item.model.supportsImageGen ||
+        hasVisionCapability(item.model, item.provider.type))
     );
   });
 

lib/ai/reference-image-capability.ts

@@ -0,0 +1,72 @@
+type ModelDescriptor = {
+  modelId?: unknown;
+  supportsVision?: boolean | null;
+  capabilities?: unknown;
+  defaultParams?: unknown;
+};
+
+type ProviderDescriptor = {
+  type?: unknown;
+};
+
+const BFL_REFERENCE_IMAGE_MODEL_REGEX =
+  /^(?:bfl\/)?(?:flux-2-(?:max|flex|pro(?:-preview)?|klein-(?:4b|9b)(?:-preview)?)|flux-kontext-(?:pro|max))$/i;
+
+function readStringField(source: unknown, key: string) {
+  if (!source || typeof source !== "object" || !(key in source)) return "";
+  return String((source as Record<string, unknown>)[key] || "").trim();
+}
+
+function normalizeBflModelId(value: unknown) {
+  const trimmed = String(value || "").trim();
+  if (!trimmed) return "";
+
+  return trimmed
+    .replace(/^https?:\/\/[^/]+/i, "")
+    .replace(/^\/?(?:bfl\/)?v1\//i, "")
+    .replace(/^\/+/, "")
+    .replace(/[?#].*$/, "");
+}
+
+export function isKnownReferenceImageModel(
+  model: ModelDescriptor | null | undefined,
+  provider?: ProviderDescriptor | null
+) {
+  const providerType = String(provider?.type || "").trim();
+  if (providerType !== "bfl-image") return false;
+
+  const candidates = [
+    model?.modelId,
+    readStringField(model?.defaultParams, "endpoint"),
+    readStringField(model?.defaultParams, "submitEndpoint"),
+    readStringField(model?.capabilities, "endpoint"),
+  ];
+
+  const capabilitiesEndpoints =
+    model?.capabilities &&
+    typeof model.capabilities === "object" &&
+    "endpoints" in model.capabilities
+      ? (model.capabilities as { endpoints?: unknown }).endpoints
+      : undefined;
+
+  candidates.push(readStringField(capabilitiesEndpoints, "submit"));
+
+  return candidates
+    .map(normalizeBflModelId)
+    .some((modelId) => BFL_REFERENCE_IMAGE_MODEL_REGEX.test(modelId));
+}
+
+export function modelLacksReferenceImageInputSupport(
+  model: ModelDescriptor | null | undefined,
+  provider?: ProviderDescriptor | null
+) {
+  if (isKnownReferenceImageModel(model, provider)) return false;
+  return model?.supportsVision === false;
+}
+
+export function modelSupportsReferenceImageInput(
+  model: ModelDescriptor | null | undefined,
+  provider?: ProviderDescriptor | null
+) {
+  return !modelLacksReferenceImageInputSupport(model, provider);
+}

lib/canvas/generate-image.ts

@@ -16,6 +16,7 @@ import { createRunway } from "@/lib/ai/providers/runway";
 import { createKrea } from "@/lib/ai/providers/krea";
 import { createVolcanoVision } from "@/lib/ai/providers/volcano-vision";
 import { resolveModelRuntimeId } from "@/lib/ai/model-runtime";
+import { modelLacksReferenceImageInputSupport } from "@/lib/ai/reference-image-capability";
 import { filterReachableRemoteUrls } from "@/lib/net/url-access";
 import {
   acquireCanvasImageModelSlot,
@@ -1766,7 +1767,10 @@ function findCanvasFailoverModel(params: {
       return false;
     }
     if (!item.model.supportsImageGen) return false;
-    if (params.requiresImageInput && item.model.supportsVision === false) {
+    if (
+      params.requiresImageInput &&
+      modelLacksReferenceImageInputSupport(item.model, item.provider)
+    ) {
       return false;
     }
     if (!SUPPORTED_CANVAS_PROVIDER_TYPES.has(item.provider.type)) return false;
@@ -1884,7 +1888,10 @@ export async function generateCanvasImage(
 
   let provider = selectedModel.provider;
 
-  if (requiresImageInput && selectedModel.model.supportsVision === false) {
+  if (
+    requiresImageInput &&
+    modelLacksReferenceImageInputSupport(selectedModel.model, selectedModel.provider)
+  ) {
     if (request.allowFailover === false) {
       throw new Error("当前图片模型不支持参考图/图生图，请选择支持图像输入的生图模型。");
     }
@@ -1925,7 +1932,12 @@ export async function generateCanvasImage(
     for (const candidate of imageModels) {
       const candidateProvider = candidate.provider;
       if (!SUPPORTED_CANVAS_PROVIDER_TYPES.has(candidateProvider.type)) continue;
-      if (requiresImageInput && candidate.model.supportsVision === false) continue;
+      if (
+        requiresImageInput &&
+        modelLacksReferenceImageInputSupport(candidate.model, candidate.provider)
+      ) {
+        continue;
+      }
       fallbackModel = candidate;
       fallbackProvider = candidateProvider;
       break;