feat: v0.7.4 时序语义修正 · 防线实效补漏 · 全量测试翻倍 — 2406 用例 + jsdom 组件测试全量回归

P1 修复面收口:
- 超时三态区分（aborted→USER_INTERRUPT / ETIMEDOUT→TIMEOUT / 其余→ERROR），
  根治"真实网络超时被误报为用户中断"
- 流空闲超时统一（SSE/Ollama/Anthropic 读循环 60s 无数据抛 504 进重试通道）
- 同会话并发 sendMessage 防重入（isRunning 守卫）+ 会话存在性预检 +
  前置调用移入 try（ERROR+DONE 双事件保证，根治 isStreaming 假死）
- 清空审计后 resetChainCache（根治 verifyChain 误报 TAMPERED）
- DONE 不再提前清理 TRACE（TERMINATED 统一收尾，补全最终迭代录制）
- IME 合成回车不发送（普通 Enter + Cmd/Ctrl+Enter 双分支）+ handleSend 闭包修复

P2 安全纵深:
- preload 移除原始 electronAPI 暴露（渲染层零使用，关掉 XSS invoke 任意通道单点风险）
- CORS 同源回显根治（仅当前浏览页面 Origin，did-navigate 同步）
- MEMORY.md 命令保护正则扩展（括号/$/反引号/< 重定向边界 + 前导路径）
- write_file append TOCTOU 统一（open 后 realpath 校验，新文件分支补漏）
- 敏感键归一化（authKey 驼峰/连字符命中）+ MCP headers 鉴权值加密落库
- ReDoS 检测共享化（search_files/file_editor 统一拦截）
- run_tests/lint_code 升风险 + 需确认 + npx --no-install（执行边界对齐 run_command）
- MCP/SearXNG/llm.baseURL/updateFeedUrl 配置类 URL 高危目标校验（IPv6 去括号 +
  十六进制映射解析 + 尾点剥离）

P3 架构还债:
- temperature/maxTokens 热生效（引擎/编排器/SubAgent 三处接线）+ setBatch 单事务落盘
- SessionRecorder flush 竞态根治（flushPromise 等待 + 超限内联落盘 + stopRecording async）
- 内存收口（lastConsolidationBySession LRU / subTraces 清理 / 会话删除 disposeEngine）
- i18n 全量收口（28 组件 + 353 key 双字典，状态标签改渲染时函数）
- 死代码清理（updateTraceStep/HEADER_HEIGHT/void preA/失实注释）
- 斜杠菜单 MUI 化 + 删除逻辑收敛 resetSessionState + Blob URL 统一释放 +
  用户消息"仅保存"落库（saveMessage 透传前端 id 修复 id 错位）

P4 能力演进:
- 死循环检测拆分（驻留前置 + 乒乓后置带进度信号，合法交替不误报）
- run-lock 30s 超时强制 abort（旧 run 卡死不无限排队）
- RETRY 双通道 stream_reset（前端按 run 归属精确清空，根治重试文本重复）
- FTS5 trigram 中文子串搜索（迁移 9 版本化 SCHEMA_VERSION=2，≤2 字符 LIKE 回退）
- getContextWindow 兜底 1M→128K（未知模型防 413）

测试:
- 855 → 2406 用例（+1551，2.8 倍）：服务层 +325（含 MemoryManager 51 新用例）、
  工具实体 +483、IPC/适配器 +390（含 OpenAI/Anthropic/Ollama 独立套件）、
  纯函数表格化 +330；引入 jsdom + @testing-library（14 组件测试文件 249 用例）
- 修复 R1（saveMessage id 透传）/ R2（stream_reset 精确归属）两个回归缺陷
- 遗留低危项清零：git-tools 顺序耦合 / web-fetch 真实时间退避 / slo 内存断言 /
  mcp-security 多余 skipIf / deepseek-balance 命名误导 / 组件 mock 注入脆弱性

版本: 0.7.4; README 同步（工具风险表/版本徽章）; 依赖: 移除 @electron-toolkit/preload，
新增 jsdom/@testing-library（devDependencies 不打包）

回归: typecheck 双端 0 错误; ESLint 0/0; Electron ABI 全量 2406/2406 零跳过;
系统 Node 2110 通过 296 跳过（better-sqlite3 ABI）

electron/harness/adapters/__tests__/deepseek-vision.test.ts

@@ -16,7 +16,7 @@ vi.mock('electron-log', () => ({
 }));
 
 import { DeepSeekAdapter } from '../deepseek.adapter';
-import type { MetonaRequest } from '../../types';
+import type { MetonaRequest, MetonaImageContent } from '../../types';
 
 const mockFetch = vi.fn();
 vi.stubGlobal('fetch', mockFetch);
@@ -37,7 +37,7 @@ function makeAdapter(model: string): DeepSeekAdapter {
   });
 }
 
-function makeRequest(images?: Array<{ url: string }>): MetonaRequest {
+function makeRequest(images?: MetonaImageContent[]): MetonaRequest {
   return {
     meta: {
       sessionId: 's',
@@ -60,7 +60,12 @@ function okResponse(): Response {
   } as unknown as Response;
 }
 
-function requestBody(): { model: string; messages: Array<Record<string, unknown>> } {
+// toNativeRequest 返回 Record<string, unknown>；这里收敛为「已知字段 + 任意扩展字段」
+// 的交叉类型，测试可直接断言 max_tokens/thinking/temperature/stop/stream 等协议字段。
+function requestBody(): { model: string; messages: Array<Record<string, unknown>> } & Record<
+  string,
+  unknown
+> {
   const [, init] = mockFetch.mock.calls[0] as [string, RequestInit];
   return JSON.parse(init.body as string);
 }
@@ -122,4 +127,275 @@ describe('DeepSeek vision 模型多模态请求格式（v0.5.4）', () => {
     const userMsg = body.messages[1];
     expect(userMsg.content).toBe('这张图片里有什么？');
   });
+
+  it('vision 模型：多张图片全部转为 image_url parts（保持顺序）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send(
+      makeRequest([
+        { url: 'data:image/png;base64,AAA' },
+        { url: 'data:image/png;base64,BBB' },
+        { url: 'data:image/jpeg;base64,CCC' },
+      ]),
+    );
+
+    const body = requestBody();
+    const parts = body.messages[1].content as Array<Record<string, unknown>>;
+    expect(parts).toHaveLength(4); // 1 text + 3 image
+    expect(parts[1]).toMatchObject({
+      type: 'image_url',
+      image_url: { url: 'data:image/png;base64,AAA' },
+    });
+    expect(parts[2]).toMatchObject({
+      type: 'image_url',
+      image_url: { url: 'data:image/png;base64,BBB' },
+    });
+    expect(parts[3]).toMatchObject({
+      type: 'image_url',
+      image_url: { url: 'data:image/jpeg;base64,CCC' },
+    });
+  });
+
+  it('vision 模型：无文本消息时仍生成 image parts（不丢弃图片）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest([{ url: 'data:image/png;base64,AAA' }]),
+      messages: [
+        {
+          role: 'user',
+          content: null,
+          images: [{ url: 'data:image/png;base64,AAA' }],
+          timestamp: Date.now(),
+        },
+      ],
+    } as MetonaRequest);
+
+    const body = requestBody();
+    const parts = body.messages[1].content as Array<Record<string, unknown>>;
+    // 无文本 → 只有 image_url part（text part 不生成）
+    expect(parts).toHaveLength(1);
+    expect(parts[0].type).toBe('image_url');
+  });
+
+  it('非 vision 模型：即使 content 为 null 也不转换图片（纯 null content）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-pro');
+
+    await adapter.send({
+      ...makeRequest([{ url: 'data:image/png;base64,AAA' }]),
+      messages: [
+        {
+          role: 'user',
+          content: null,
+          images: [{ url: 'data:image/png;base64,AAA' }],
+          timestamp: Date.now(),
+        },
+      ],
+    } as MetonaRequest);
+
+    const body = requestBody();
+    const userMsg = body.messages[1];
+    expect(userMsg.content).toBeNull();
+  });
+
+  it('vision 模型 detail 字段被丢弃（image_url 仅保留 url）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send(makeRequest([{ url: 'data:image/png;base64,AAA', detail: 'high' }]));
+
+    const body = requestBody();
+    const parts = body.messages[1].content as Array<Record<string, unknown>>;
+    expect(parts[1]).toEqual({
+      type: 'image_url',
+      image_url: { url: 'data:image/png;base64,AAA' },
+    });
+  });
+
+  it('vision 模型 max_tokens 未配置 → 默认 8192（MODEL_INFO 上限）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest(),
+      params: { temperature: 0, stream: false },
+    } as MetonaRequest);
+
+    const body = requestBody();
+    expect(body.max_tokens).toBe(8_192);
+  });
+
+  it('vision 模型 thinking 参数显式映射（thinkingEnabled 兼容）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest([{ url: 'data:image/png;base64,AAA' }]),
+      params: { maxTokens: 4096, temperature: 0, stream: false, thinkingEnabled: true },
+    } as MetonaRequest);
+
+    const body = requestBody();
+    // vision 模型 supportsThinking=false，但参数仍透传 thinking enabled（引擎决定）
+    expect(body.thinking).toEqual({ type: 'enabled' });
+  });
+
+  it('vision 模型 messages 数组首位始终为 system 消息', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send(makeRequest([{ url: 'data:image/png;base64,AAA' }]));
+    const body = requestBody();
+    expect(body.messages[0].role).toBe('system');
+    expect(body.messages[0].content as string).toContain('sys');
+  });
+
+  it('tool 结果消息不被 images 转换影响（role=tool 保留 tool_call_id）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest([{ url: 'data:image/png;base64,AAA' }]),
+      messages: [
+        {
+          role: 'user',
+          content: '请读图',
+          images: [{ url: 'data:image/png;base64,AAA' }],
+          timestamp: Date.now(),
+        },
+        {
+          role: 'assistant',
+          content: null,
+          toolCalls: [
+            {
+              id: 'tc1',
+              name: 'view_image',
+              args: { path: 'a.png' },
+              iteration: 1,
+              timestamp: Date.now(),
+            },
+          ],
+          timestamp: Date.now(),
+        },
+        {
+          role: 'tool',
+          content: null,
+          toolResult: {
+            toolCallId: 'tc1',
+            toolName: 'view_image',
+            result: { path: 'a.png' },
+            success: true,
+            durationMs: 1,
+            timestamp: Date.now(),
+          },
+          timestamp: Date.now(),
+        },
+      ],
+    } as MetonaRequest);
+
+    const body = requestBody();
+    const toolMsg = body.messages[3];
+    expect(toolMsg.role).toBe('tool');
+    expect(toolMsg.tool_call_id).toBe('tc1');
+    expect(toolMsg.content).toBe('{"path":"a.png"}');
+  });
+
+  it('孤立 tool 消息被过滤（无前置 tool_calls）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest(),
+      messages: [
+        { role: 'user', content: 'hi', timestamp: Date.now() },
+        {
+          role: 'tool',
+          content: null,
+          toolResult: {
+            toolCallId: 'tc_orphan',
+            toolName: 'x',
+            result: 'r',
+            success: true,
+            durationMs: 1,
+            timestamp: Date.now(),
+          },
+          timestamp: Date.now(),
+        },
+      ],
+    } as MetonaRequest);
+
+    const body = requestBody();
+    // system + user，孤立 tool 被剔除
+    expect(body.messages).toHaveLength(2);
+  });
+
+  it('temperature 与 stop 序列透传', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest(),
+      params: { maxTokens: 4096, temperature: 0.4, stream: false, stopSequences: ['<END>'] },
+    } as MetonaRequest);
+
+    const body = requestBody();
+    expect(body.temperature).toBe(0.4);
+    expect(body.stop).toEqual(['<END>']);
+  });
+
+  it('send（非流式路径）强制 stream=false 且不附加 stream_options', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest([{ url: 'data:image/png;base64,AAA' }]),
+      params: { maxTokens: 4096, temperature: 0, stream: true },
+    } as MetonaRequest);
+
+    const body = requestBody();
+    // send() 契约：无论请求参数如何，非流式路径强制 stream=false，stream_options 仅流式路径注入
+    expect(body.stream).toBe(false);
+    expect(body.stream_options).toBeUndefined();
+  });
+
+  it('非 vision 模型带图片不产生 image_url（content 保持字符串）', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash');
+
+    await adapter.send(makeRequest([{ url: 'data:image/png;base64,AAA' }]));
+    const body = requestBody();
+    const userMsg = body.messages[1];
+    expect(typeof userMsg.content).toBe('string');
+    expect(userMsg.content).not.toContain('image_url');
+  });
+
+  it('vision 模型 base64 data URI 原样保留在 image_url 中', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    const dataUri = 'data:image/png;base64,' + 'Z'.repeat(50);
+    await adapter.send(makeRequest([{ url: dataUri }]));
+    const body = requestBody();
+    const parts = body.messages[1].content as Array<Record<string, unknown>>;
+    expect(parts[1]).toMatchObject({ image_url: { url: dataUri } });
+  });
+
+  it('vision 模型 reasoning_content 在 assistant 历史中保留', async () => {
+    mockFetch.mockResolvedValue(okResponse());
+    const adapter = makeAdapter('deepseek-v4-flash-vision-exp');
+
+    await adapter.send({
+      ...makeRequest(),
+      messages: [
+        { role: 'user', content: 'hi', timestamp: Date.now() },
+        { role: 'assistant', content: 'answer', reasoningContent: 'trace', timestamp: Date.now() },
+      ],
+    } as MetonaRequest);
+
+    const body = requestBody();
+    const assistantMsg = body.messages[2] as Record<string, unknown>;
+    expect(assistantMsg.reasoning_content).toBe('trace');
+  });
 });