fix(llm): handle non-object json responses

Author: MouseWW

RELEASE_NOTES.md

@@ -1,16 +1,16 @@
-# Anything Analyzer v3.6.28
+# Anything Analyzer v3.6.29
 
 ## 修复
 
-- **OpenAI Chat 非流式响应格式校验** — 避免兼容服务缺少 `message.content` 时被误判为空成功结果
-  - 普通 Chat Completions 请求现在会明确拒绝缺少 `message.content` 的 malformed choice
-  - 工具调用最终文本轮次复用同一校验，保留工具调用中 `content` 为空的合法场景
+- **LLM 非对象 JSON 响应诊断** — 避免兼容服务返回 `null` 等合法但非对象 JSON 时抛出内部属性访问错误
+  - `safeParseJson` 现在会将非对象 JSON 归一为空对象，由各调用路径继续给出明确格式错误
+  - OpenAI Chat Completions 回归测试覆盖 `null` 响应，确保诊断保持为缺少 `choices` 字段
 
 ## 下载
 
 | 平台 | 文件 |
 |------|------|
-| Windows | Anything-Analyzer-Setup-3.6.28.exe |
-| macOS (Apple Silicon) | Anything-Analyzer-3.6.28-arm64.dmg |
-| macOS (Intel) | Anything-Analyzer-3.6.28-x64.dmg |
-| Linux | Anything-Analyzer-3.6.28.AppImage |
+| Windows | Anything-Analyzer-Setup-3.6.29.exe |
+| macOS (Apple Silicon) | Anything-Analyzer-3.6.29-arm64.dmg |
+| macOS (Intel) | Anything-Analyzer-3.6.29-x64.dmg |
+| Linux | Anything-Analyzer-3.6.29.AppImage |

package.json

@@ -1,6 +1,6 @@
 {
   "name": "anything-analyzer",
-  "version": "3.6.28",
+  "version": "3.6.29",
   "description": "Universal web protocol analyzer with embedded browser and AI-powered analysis",
   "packageManager": "pnpm@10.24.0",
   "main": "./out/main/index.js",

src/main/ai/llm-router.ts

@@ -135,8 +135,10 @@ export class LLMRouter {
       throw new Error(`LLM 返回了非 JSON 响应 (${response.status}): ${preview}`);
     }
 
-    // Anthropic error format: { type: "error", error: { type, message } }
-    const obj = data as Record<string, unknown>;
+    // Anthropic error format: { type: "error", error: { type, message } }
+    const obj = data !== null && typeof data === "object"
+      ? data as Record<string, unknown>
+      : {};
     if (obj.type === 'error' && typeof obj.error === 'object' && obj.error !== null) {
       const err = obj.error as Record<string, unknown>;
       throw new Error(`LLM API 错误: ${err.type ?? 'unknown'} — ${err.message ?? JSON.stringify(err)}`);
@@ -153,8 +155,8 @@ export class LLMRouter {
       throw new Error(`LLM API 错误: ${err.message ?? JSON.stringify(err)}`);
     }
 
-    return data as T;
-  }
+    return obj as T;
+  }
 
   async complete(
     messages: ChatMessage[],

tests/main/ai/llm-router.test.ts

@@ -46,10 +46,10 @@ function createRawSSEResponse(body: string): Response {
 // Helper: create a mock JSON Response
 function createJSONResponse(body: unknown): Response {
   return new Response(JSON.stringify(body), {
-    status: 200,
-    headers: { "content-type": "application/json" },
-  });
-}
+    status: 200,
+    headers: { "content-type": "application/json" },
+  });
+}
 
 const baseConfig: LLMProviderConfig = {
   name: "openai",
@@ -261,6 +261,16 @@ describe("LLMRouter", () => {
       ).rejects.toThrow("LLM 响应格式异常: 缺少 choices 字段");
     });
 
+    it("should reject non-object OpenAI completion JSON with a clear format error", async () => {
+      fetchSpy.mockResolvedValueOnce(createJSONResponse(null));
+
+      const router = new LLMRouter(baseConfig);
+
+      await expect(
+        router.complete([{ role: "user", content: "test" }]),
+      ).rejects.toThrow("LLM 响应格式异常: 缺少 choices 字段");
+    });
+
     it("should reject OpenAI completion choices without message content", async () => {
       fetchSpy.mockResolvedValueOnce(
         createJSONResponse({