src/api/adVideoPlanClient.ts

@@ -108,36 +108,63 @@ interface ChatMessage {
   content: string;
 }
 
+const MAX_RETRIES = 3;
+const RETRY_BASE_MS = 2000;
+const CHAT_TIMEOUT_MS = 120_000; // 2 minutes per AI call
+
+function isTransientError(err: unknown): boolean {
+  if (!(err instanceof Error)) return false;
+  const msg = err.message.toLowerCase();
+  return /\b429\b/.test(msg) || msg.includes("signal timed out") || msg.includes("aborted") || msg.includes("timeout");
+}
+
+async function retryOnTransient<T>(fn: () => Promise<T>, signal?: AbortSignal): Promise<T> {
+  for (let attempt = 0; attempt <= MAX_RETRIES; attempt++) {
+    try {
+      return await fn();
+    } catch (err) {
+      if (signal?.aborted) throw err;
+      if (attempt === MAX_RETRIES) throw err;
+      if (!isTransientError(err)) throw err;
+      const delay = RETRY_BASE_MS * 2 ** attempt + Math.random() * 1000;
+      await new Promise((r) => setTimeout(r, delay));
+    }
+  }
+  throw new Error("unreachable");
+}
+
 async function chat(
   systemPrompt: string,
   userContent: string,
   options?: { model?: string; signal?: AbortSignal },
 ): Promise<string> {
-  const messages: ChatMessage[] = [
-    { role: "system", content: systemPrompt },
-    { role: "user", content: userContent },
-  ];
-  const timeoutSignal = AbortSignal.timeout(60000);
-  const combinedSignal = options?.signal
-    ? AbortSignal.any([options.signal, timeoutSignal])
-    : timeoutSignal;
-  const res = await fetch(buildApiUrl("ai/chat"), {
-    method: "POST",
-    headers: buildAuthHeaders(),
-    body: JSON.stringify({
-      model: options?.model ?? TEXT_MODEL,
-      messages,
-      stream: false,
-      temperature: 0.4,
-    }),
-    signal: combinedSignal,
-  });
-  if (!res.ok) throw new Error(`AI 调用失败 (${res.status})`);
-  const payload = await res.json();
-  const content: string =
-    payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
-  if (!content) throw new Error("模型未返回有效内容");
-  return content;
+  return retryOnTransient(async () => {
+    const messages: ChatMessage[] = [
+      { role: "system", content: systemPrompt },
+      { role: "user", content: userContent },
+    ];
+    const timeoutSignal = AbortSignal.timeout(CHAT_TIMEOUT_MS);
+    const combinedSignal = options?.signal
+      ? AbortSignal.any([options.signal, timeoutSignal])
+      : timeoutSignal;
+    const res = await fetch(buildApiUrl("ai/chat"), {
+      method: "POST",
+      headers: buildAuthHeaders(),
+      body: JSON.stringify({
+        model: options?.model ?? TEXT_MODEL,
+        messages,
+        stream: false,
+        temperature: 0.4,
+      }),
+      signal: combinedSignal,
+    });
+    if (!res.ok) throw new Error(`AI 调用失败 (${res.status})`);
+    const payload = await res.json();
+    const content: string =
+      payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
+    if (!content) throw new Error("模型未返回有效内容");
+    return content;
+  }, options?.signal);
 }
 
 async function visionChat(
@@ -156,28 +183,32 @@ async function visionChat(
   ];
 
   for (const model of [VISION_MODEL, VISION_FALLBACK_MODEL]) {
-    const timeoutSignal = AbortSignal.timeout(60000);
+    const timeoutSignal = AbortSignal.timeout(CHAT_TIMEOUT_MS);
     const combinedSignal = signal
       ? AbortSignal.any([signal, timeoutSignal])
       : timeoutSignal;
     try {
-      const res = await fetch(buildApiUrl("ai/chat"), {
-        method: "POST",
-        headers: buildAuthHeaders(),
-        body: JSON.stringify({ model, messages, stream: false, temperature: 0.3 }),
-        signal: combinedSignal,
-      });
-      if (!res.ok) {
-        const errBody = await res.text().catch(() => "");
-        if (model === VISION_MODEL && errBody.includes("image format")) continue;
-        throw new Error(`图片理解调用失败 (${res.status})`);
-      }
-      const payload = await res.json();
-      const out: string =
-        payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
-      if (!out) throw new Error("图片理解未返回有效内容");
+      const out = await retryOnTransient(async () => {
+        const res = await fetch(buildApiUrl("ai/chat"), {
+          method: "POST",
+          headers: buildAuthHeaders(),
+          body: JSON.stringify({ model, messages, stream: false, temperature: 0.3 }),
+          signal: combinedSignal,
+        });
+        if (!res.ok) {
+          const errBody = await res.text().catch(() => "");
+          if (model === VISION_MODEL && errBody.includes("image format")) throw new Error("IMAGE_FORMAT_FALLBACK");
+          throw new Error(`图片理解调用失败 (${res.status})`);
+        }
+        const payload = await res.json();
+        const result: string =
+          payload?.content ?? payload?.choices?.[0]?.message?.content ?? payload?.text ?? "";
+        if (!result) throw new Error("图片理解未返回有效内容");
+        return result;
+      }, signal);
       return out;
     } catch (err) {
+      if (err instanceof Error && err.message === "IMAGE_FORMAT_FALLBACK") continue;
       if (model === VISION_MODEL && err instanceof Error && err.message?.includes("图片理解调用失败")) continue;
       throw err;
     }

src/api/aiGenerationClient.ts

@@ -408,9 +408,11 @@ export const aiGenerationClient = {
     form.append("file", blob, options?.name || "upload.png");
     if (options?.scope) form.append("scope", options.scope);
     if (options?.mimeType) form.append("mimeType", options.mimeType);
+    // Exclude Content-Type so browser auto-sets multipart/form-data with boundary
+    const { "Content-Type": _ct, ...authHeaders } = buildAuthHeaders();
     const res = await fetch(buildApiUrl("oss/upload-binary"), {
       method: "POST",
-      headers: { ...buildAuthHeaders() },
+      headers: authHeaders,
       body: form,
     });
     if (!res.ok) {