From 2b6342bc7fa47e8385f72da84528fe110b7145e6 Mon Sep 17 00:00:00 2001
From: Your Name <your.email@example.com>
Date: Sat, 7 Mar 2026 22:09:06 +0800
Subject: [PATCH] fix: prioritize bfl input image editing

---
 app/api/realtime/generate/route.ts | 14 +++++++------
 lib/realtime/bfl-capability.ts     | 33 +++++++++++++++++++++++++++---
 2 files changed, 38 insertions(+), 9 deletions(-)

diff --git a/app/api/realtime/generate/route.ts b/app/api/realtime/generate/route.ts
index b0d095ea9..808f0eb65 100644
--- a/app/api/realtime/generate/route.ts
+++ b/app/api/realtime/generate/route.ts
@@ -154,6 +154,12 @@ function toImagePromptValue(imageUrl: string) {
   return trimmed;
 }
 
+function getBflImageFieldCandidates() {
+  // BFL's current FLUX/Kontext editing APIs use `input_image` as the canonical field.
+  // Keep `image_prompt` only as a legacy fallback in case an older compatible endpoint is used.
+  return ["input_image", "image_prompt"] as const;
+}
+
 type SubmitTaskResult = {
   taskId: string;
   pollingUrl: string;
@@ -367,13 +373,9 @@ export async function POST(request: Request) {
     );
   }
 
-  const preferredImageField =
-    model.toLowerCase().includes("kontext") || model.toLowerCase().includes("edit")
-      ? "input_image"
-      : "image_prompt";
-  const imageFieldCandidates = [preferredImageField, preferredImageField === "input_image" ? "image_prompt" : "input_image"];
+  const imageFieldCandidates = getBflImageFieldCandidates();
 
-  let selectedImageField = imageFieldCandidates[0];
+  let selectedImageField: "input_image" | "image_prompt" = imageFieldCandidates[0];
   let submitResult: SubmitTaskResult | null = null;
   let fallbackWarning = "";
 
diff --git a/lib/realtime/bfl-capability.ts b/lib/realtime/bfl-capability.ts
index 79a703627..f6ba8f44c 100644
--- a/lib/realtime/bfl-capability.ts
+++ b/lib/realtime/bfl-capability.ts
@@ -1,6 +1,9 @@
+import sharp from "sharp";
+
 const DEFAULT_BFL_BASE_URL = "https://api.bfl.ai";
 const DEFAULT_BFL_MODEL_ID = "flux-2-klein-4b";
 const DEFAULT_TIMEOUT_MS = 15_000;
+const PROBE_IMAGE_SIZE = 64;
 
 export type BflCapabilityCode =
   | "SUPPORTED"
@@ -68,6 +71,28 @@ function hasTaskIdentity(payload: any) {
   );
 }
 
+let cachedProbeImageBase64: string | null = null;
+
+async function getProbeImageBase64() {
+  if (cachedProbeImageBase64) {
+    return cachedProbeImageBase64;
+  }
+
+  const buffer = await sharp({
+    create: {
+      width: PROBE_IMAGE_SIZE,
+      height: PROBE_IMAGE_SIZE,
+      channels: 3,
+      background: { r: 255, g: 255, b: 255 },
+    },
+  })
+    .png()
+    .toBuffer();
+
+  cachedProbeImageBase64 = buffer.toString("base64");
+  return cachedProbeImageBase64;
+}
+
 export async function probeBflModelSupport(params: BflProbeParams): Promise<BflModelProbeResult> {
   const apiKey = String(params.apiKey || "").trim();
   const modelId = String(params.modelId || DEFAULT_BFL_MODEL_ID).trim() || DEFAULT_BFL_MODEL_ID;
@@ -87,6 +112,7 @@ export async function probeBflModelSupport(params: BflProbeParams): Promise<BflM
 
   try {
     const endpoint = `${baseUrl}/v1/${encodeModelPath(modelId)}`;
+    const inputImage = await getProbeImageBase64();
     const response = await fetch(endpoint, {
       method: "POST",
       headers: {
@@ -95,9 +121,10 @@ export async function probeBflModelSupport(params: BflProbeParams): Promise<BflM
         Accept: "application/json",
       },
       body: JSON.stringify({
-        prompt: "probe image generation capability",
-        width: 512,
-        height: 512,
+        prompt: "probe image editing capability; preserve the input image composition",
+        input_image: inputImage,
+        width: PROBE_IMAGE_SIZE,
+        height: PROBE_IMAGE_SIZE,
         safety_tolerance: 2,
       }),
       cache: "no-store",