pingp76 · pingp76 · Jun 26, 2026 · Jun 26, 2026
diff --git a/doc/summary.md b/doc/summary.md
@@ -90,8 +90,8 @@ src/
 ├── recovery.ts         # LLM 错误分类与恢复决策：backoff/compact/continue/fail
 ├── terminal.ts         # 终端输入输出封装：共享 readline（REPL + 权限确认共用）
 ├── debug-e2e.ts        # 端到端调试脚本（Skill+TODO+SubAgent 协作验证）
-├── foundation-models.test.ts # Profile 注册表、匹配、fallback 测试（14 个测试用例）
-├── runtime-policy.test.ts # Policy 解析、env 覆盖、非法值报错测试（19 个测试用例）
+├── foundation-models.test.ts # Profile 注册表、匹配、fallback 测试（17 个测试用例）
+├── runtime-policy.test.ts # Policy 解析、env 覆盖、非法值报错测试（20 个测试用例）
 ├── runtime-policy-store.test.ts # Override 合并、reset、snapshot 测试（15 个测试用例）
 ├── context-budget.test.ts # 预算分配公式、总和约束、override 裁剪测试（9 个测试用例）
 ├── llm-adapter.test.ts # Adapter 请求构建、reasoning 回放、streaming 聚合测试（15 个测试用例）
@@ -437,7 +437,7 @@ skills/
 ### Foundation Model Profile 基座模型画像 (`foundation-models.ts`)
 
 - **能力驱动而非模型名驱动**：`agent.ts` 不出现 `kimi`/`deepseek` 等具体模型分支，业务层只看 `RuntimePolicy` 中的策略字段
-- **Profile Registry**：含 `generic-openai-compatible`、`kimi-k2.6`、`kimi-code`、`deepseek-v4`、`minimax-m2.7`、`minimax-m3`、`mimo-v2.5-pro`、`qwen3.7-max`、`glm-5.1` 等画像
+- **Profile Registry**：含 `generic-openai-compatible`、`kimi-k2.6`、`kimi-code`、`deepseek-v4`、`minimax-m2.7`、`minimax-m3`、`mimo-v2.5-pro`、`qwen3.7-max`、`glm-5.2`、`glm-5.1` 等画像
 - **匹配优先级**：`LLM_MODEL_PROFILE` 显式指定 > exact model id > prefix > provider default > generic fallback
 - **硬协议字段 vs 优化提示分离**：maxTokensField、thinking requestShape、reasoning responseFields 等硬字段必须保守；context budget、compression mode 等优化提示允许合理默认
 - **Profile 分级**：`verified` / `experimental` / `needs_review`，stale/high-risk profile 启动时产生 warning 但不阻断
@@ -508,7 +508,7 @@ skills/
 
 ### LLM Provider Profile 抽象层 (`llm-providers.ts`)
 
-- **集中 profile 表**：声明 4 个 provider（`openai_compatible`、`minimax_cn`、`kimi_platform_cn`、`kimi_code_cn`）的默认 endpoint、默认模型、key 环境变量和能力标记
+- **集中 profile 表**：声明 5 个 provider（`openai_compatible`、`minimax_cn`、`kimi_platform_cn`、`kimi_code_cn`、`zhipuai_cn`）的默认 endpoint、默认模型、key 环境变量和能力标记
 - **解析优先级**：`LLM_API_KEY` / `LLM_BASE_URL` / `LLM_MODEL` 优先于 provider 默认值，兼容现有使用方式
 - **启动时解析**：`resolveLLMProviderConfig()` 只读 env，不做网络请求，返回 `ResolvedLLMConfig`
 - **厂商差异不泄漏到 Agent 循环**：Agent、SubAgent、Async Run 只依赖 `LLMClient.chat()`
@@ -725,6 +725,8 @@ skills/
 | `KIMI_CODE_API_KEY`        | Kimi Code CN 专用 key               | `sk-kimi-...`                 |
 | `MOONSHOT_API_KEY`         | Kimi Platform CN 专用 key           | `sk-moonshot-...`             |
 | `MINIMAX_CN_API_KEY`       | MiniMax CN 专用 key                 | `sk-minimax-...`              |
+| `ZHIPUAI_API_KEY`          | ZhipuAI CN 专用 key                 | `sk-zhipu-...`                |
+| `BIGMODEL_API_KEY`         | ZhipuAI CN 备用 key                 | `sk-bigmodel-...`             |
 | `LOG_LEVEL`                | 日志级别                            | `info`                        |
 | `COMPRESS_TOOL_OUTPUT`     | 即时压缩 token 阈值                 | `2000`                        |
 | `COMPRESS_DECAY_THRESHOLD` | 衰减压缩轮次阈值                    | `3`                           |
@@ -789,11 +791,11 @@ skills/
 | `src/session-events.test.ts`                                   | 5                             | drain 清空、peek 不清空、顺序保持                                                                                                                                                                                          |
 | `src/transcript.test.ts`                                       | 6                             | 消息分类、事件 sequence、historySequence、timing 元信息、搜索                                                                                                                                                              |
 | `src/cache-debug.test.ts`                                      | 7                             | inspect 变化检测、system prompt 不变性、formatCacheDebugLog                                                                                                                                                                |
-| `src/llm-providers.test.ts`                                    | 26                            | provider 解析、默认值、覆盖优先级、错误提示、能力标记                                                                                                                                                                      |
+| `src/llm-providers.test.ts`                                    | 31                            | provider 解析、默认值、覆盖优先级、错误提示、能力标记                                                                                                                                                                      |
 | `src/config.test.ts`                                           | 5                             | loadConfig 解析 provider 字段、compression/logLevel 默认值、错误信息不泄漏 key                                                                                                                                             |
 | `src/llm.test.ts`                                              | 10                            | non-streaming 路径、streaming content/tool_calls 聚合、llmLogger 调用                                                                                                                                                      |
-| `src/foundation-models.test.ts`                                | 14                            | Profile 注册表、exact/prefix/fallback 匹配、provider 兼容校验、显式 profile、stale warning                                                                                                                                 |
-| `src/runtime-policy.test.ts`                                   | 19                            | Policy 默认值、env 覆盖、非法覆盖报错、协议 fallback、compression 派生                                                                                                                                                     |
+| `src/foundation-models.test.ts`                                | 17                            | Profile 注册表、exact/prefix/fallback 匹配、provider 兼容校验、显式 profile、stale warning                                                                                                                                 |
+| `src/runtime-policy.test.ts`                                   | 20                            | Policy 默认值、env 覆盖、非法覆盖报错、协议 fallback、compression 派生                                                                                                                                                     |
 | `src/context-budget.test.ts`                                   | 9                             | 三种模式预算分配、总和约束、override 处理、裁剪优先级、极小预算边界                                                                                                                                                        |
 | `src/runtime-policy-store.test.ts`                             | 15                            | Override 合并、reset、snapshot、非法更新报错                                                                                                                                                                               |
 | `src/llm-adapter.test.ts`                                      | 15                            | 请求构建、reasoning 占位、streaming 聚合、max token 字段、usage 解析                                                                                                                                                       |

diff --git a/src/foundation-models.test.ts b/src/foundation-models.test.ts
@@ -74,6 +74,34 @@ describe("resolveFoundationModelProfile", () => {
     expect(result.id).toBe("deepseek-v4");
   });
 
+  it("matches exact model id for glm-5.2", () => {
+    const result = resolveFoundationModelProfile({
+      provider: "zhipuai_cn",
+      model: "glm-5.2",
+    });
+    expect(result.id).toBe("glm-5.2");
+    expect(result.provider).toBe("zhipuai_cn");
+    expect(result.limits.contextWindowTokens).toBe(1000000);
+    expect(result.limits.effectiveContextBudgetTokens).toBe(750000);
+    expect(result.thinking.defaultMode).toBe("adaptive");
+    expect(result.reasoning.responseFields).toEqual(["reasoning_content"]);
+    expect(result.cache.supported).toBe(false);
+  });
+
+  it("matches GLM-5.2 aliases and prefixes conservatively", () => {
+    const exactAlias = resolveFoundationModelProfile({
+      provider: "zhipuai_cn",
+      model: "GLM5.2",
+    });
+    const prefixAlias = resolveFoundationModelProfile({
+      provider: "zhipuai_cn",
+      model: "glm-5.2-long-context",
+    });
+
+    expect(exactAlias.id).toBe("glm-5.2");
+    expect(prefixAlias.id).toBe("glm-5.2");
+  });
+
   it("uses explicit profile id when provided", () => {
     const result = resolveFoundationModelProfile({
       provider: "kimi_platform_cn",
@@ -83,6 +111,15 @@ describe("resolveFoundationModelProfile", () => {
     expect(result.id).toBe("kimi-k2.6");
   });
 
+  it("returns zhipuai default profile before generic for unknown zhipu model", () => {
+    const result = resolveFoundationModelProfile({
+      provider: "zhipuai_cn",
+      model: "glm-custom-alias",
+    });
+    expect(result.id).toBe("glm-5.2");
+    expect(result.provider).toBe("zhipuai_cn");
+  });
+
   it("throws for unknown explicit profile id", () => {
     expect(() =>
       resolveFoundationModelProfile({
@@ -147,6 +184,7 @@ describe("getRegisteredModelProfileIds", () => {
     expect(ids).toContain("minimax-m3");
     expect(ids).toContain("mimo-v2.5-pro");
     expect(ids).toContain("qwen3.7-max");
+    expect(ids).toContain("glm-5.2");
     expect(ids).toContain("glm-5.1");
   });
 });
diff --git a/src/foundation-models.ts b/src/foundation-models.ts
@@ -781,6 +781,85 @@ const modelProfiles: FoundationModelProfile[] = [
     },
   },
 
+  // -------------------------------------------------------------------------
+  // GLM-5.2
+  // -------------------------------------------------------------------------
+  {
+    id: "glm-5.2",
+    displayName: "GLM-5.2",
+    provider: "zhipuai_cn",
+    match: {
+      exactModelIds: ["glm-5.2", "GLM-5.2", "glm5.2", "GLM5.2"],
+      modelIdPrefixes: ["glm-5.2", "GLM-5.2"],
+    },
+    protocol: {
+      preferred: "openai-chat-completions",
+      fallbacks: [],
+      implemented: ["openai-chat-completions"],
+    },
+    limits: {
+      contextWindowTokens: 1000000,
+      effectiveContextBudgetTokens: 750000,
+      longContextThresholdTokens: 512000,
+      maxOutputTokens: 65536,
+      maxTokensField: "max_tokens",
+    },
+    thinking: {
+      supported: true,
+      defaultMode: "adaptive",
+      efforts: ["default"],
+      enableForAgenticTasks: true,
+      disableForSimpleChat: true,
+      requestShape: "extra_body_thinking",
+    },
+    reasoning: {
+      returned: true,
+      mustReplayWithToolCalls: false,
+      preserveRawAssistantMessage: true,
+      responseFields: ["reasoning_content"],
+      streamingDeltaFields: ["reasoning_content"],
+    },
+    tools: {
+      supported: true,
+      supportsToolChoiceRequired: false,
+      allowedToolChoiceModes: ["auto", "none"],
+      streamingArguments: true,
+      multimodalToolResults: false,
+    },
+    cache: {
+      supported: false,
+      automatic: false,
+      exposesUsage: false,
+      usageFields: {},
+    },
+    modalities: {
+      text: true,
+      image: false,
+      video: false,
+      audio: false,
+    },
+    optimizationHints: {
+      bestFor: ["coding", "long_horizon_agent", "large_context"],
+      defaultCompressionMode: "long_context",
+      prefersStreaming: true,
+      goodForSubagents: false,
+    },
+    knownQuirks: [
+      "官方资料确认 1M context 与 reasoning_content，但本仓尚未做 live smoke test",
+      "max output 和 cache usage 字段未在当前资料中核实，先使用保守上限并关闭 cache telemetry",
+      "thinking effort 的具体枚举未核实，暂不暴露 low/medium/high 等非 default 覆盖",
+    ],
+    documentation: {
+      sourceUrls: [
+        "https://github.com/zai-org/glm-5/blob/main/README.md",
+        "https://github.com/metaglm/zhipuai-sdk-python-v4",
+      ],
+      verifiedAt: "2026-06-26",
+      updateRisk: "high",
+      status: "experimental",
+    },
+  },
+
   // -------------------------------------------------------------------------
   // GLM-5.1
   // -------------------------------------------------------------------------

diff --git a/src/llm-providers.test.ts b/src/llm-providers.test.ts
@@ -180,6 +180,49 @@ describe("minimax_cn provider", () => {
   });
 });
 
+// ============================================================
+// zhipuai_cn 解析
+// ============================================================
+
+describe("zhipuai_cn provider", () => {
+  it("只设置 ZHIPUAI_API_KEY 时可解析成功", () => {
+    const config = resolveLLMProviderConfig({
+      LLM_PROVIDER: "zhipuai_cn",
+      ZHIPUAI_API_KEY: "sk-zhipu-test",
+    });
+    expect(config.provider).toBe("zhipuai_cn");
+    expect(config.apiKey).toBe("sk-zhipu-test");
+    expect(config.baseURL).toBe("https://open.bigmodel.cn/api/paas/v4/");
+    expect(config.model).toBe("glm-5.2");
+  });
+
+  it("BIGMODEL_API_KEY 也可作为 fallback", () => {
+    const config = resolveLLMProviderConfig({
+      LLM_PROVIDER: "zhipuai_cn",
+      BIGMODEL_API_KEY: "sk-bigmodel-fallback",
+    });
+    expect(config.apiKey).toBe("sk-bigmodel-fallback");
+  });
+
+  it("LLM_MODEL 优先于 GLM-5.2 默认模型", () => {
+    const config = resolveLLMProviderConfig({
+      LLM_PROVIDER: "zhipuai_cn",
+      ZHIPUAI_API_KEY: "sk-zhipu-test",
+      LLM_MODEL: "glm-5.2-proxy",
+    });
+    expect(config.model).toBe("glm-5.2-proxy");
+  });
+
+  it("声明 supportsThinking 和 prefersStreaming 能力", () => {
+    const config = resolveLLMProviderConfig({
+      LLM_PROVIDER: "zhipuai_cn",
+      ZHIPUAI_API_KEY: "sk-zhipu-test",
+    });
+    expect(config.capabilities.supportsThinking).toBe(true);
+    expect(config.capabilities.prefersStreaming).toBe(true);
+  });
+});
+
 // ============================================================
 // 启发式推断
 // ============================================================
@@ -213,6 +256,16 @@ describe("baseURL 启发式推断", () => {
     expect(config.provider).toBe("kimi_platform_cn");
   });
 
+  it("未设置 LLM_PROVIDER 时，从 LLM_BASE_URL 推断为 zhipuai_cn", () => {
+    const config = resolveLLMProviderConfig({
+      LLM_API_KEY: "sk-test",
+      LLM_BASE_URL: "https://open.bigmodel.cn/api/paas/v4/",
+      LLM_MODEL: "glm-5.2",
+    });
+    expect(config.provider).toBe("zhipuai_cn");
+    expect(config.capabilities.supportsThinking).toBe(true);
+  });
+
   it("不匹配的 baseURL 回退到 openai_compatible", () => {
     const config = resolveLLMProviderConfig({
       LLM_API_KEY: "sk-test",
@@ -261,15 +314,15 @@ describe("错误提示", () => {
   it("apiKey 缺失错误提示包含 provider id 和候选 key env", () => {
     expect(() =>
       resolveLLMProviderConfig({
-        LLM_PROVIDER: "kimi_code_cn",
+        LLM_PROVIDER: "zhipuai_cn",
       }),
-    ).toThrow('provider "kimi_code_cn"');
+    ).toThrow('provider "zhipuai_cn"');
 
     expect(() =>
       resolveLLMProviderConfig({
-        LLM_PROVIDER: "kimi_code_cn",
+        LLM_PROVIDER: "zhipuai_cn",
       }),
-    ).toThrow("LLM_API_KEY, KIMI_CODE_API_KEY");
+    ).toThrow("LLM_API_KEY, ZHIPUAI_API_KEY, BIGMODEL_API_KEY");
   });
 
   it("错误信息不泄漏已有 key 值", () => {

diff --git a/src/llm-providers.ts b/src/llm-providers.ts
@@ -23,7 +23,8 @@ export type LLMProviderId =
   | "openai_compatible"
   | "minimax_cn"
   | "kimi_platform_cn"
-  | "kimi_code_cn";
+  | "kimi_code_cn"
+  | "zhipuai_cn";
 
 /**
  * Provider 能力标记
@@ -136,6 +137,22 @@ const providerProfiles: Record<LLMProviderId, LLMProviderProfile> = {
       supportsThinking: false,
     },
   },
+  zhipuai_cn: {
+    id: "zhipuai_cn",
+    displayName: "ZhipuAI CN",
+    protocol: "openai-chat-completions",
+    // 智谱官方 SDK 文档使用 open.bigmodel.cn 的 v4 基础路径。
+    // 这里作为可运行默认值；企业代理或自建网关仍通过 LLM_BASE_URL 覆盖。
+    defaultBaseURL: "https://open.bigmodel.cn/api/paas/v4/",
+    defaultModel: "glm-5.2",
+    apiKeyEnvNames: ["ZHIPUAI_API_KEY", "BIGMODEL_API_KEY"],
+    capabilities: {
+      supportsTools: true,
+      supportsToolChoiceRequired: false,
+      prefersStreaming: true,
+      supportsThinking: true,
+    },
+  },
 };
 
 /**

diff --git a/src/runtime-policy.test.ts b/src/runtime-policy.test.ts
@@ -73,6 +73,29 @@ describe("resolveRuntimePolicy defaults", () => {
     expect(policy.context.compressionMode).toBe("balanced");
   });
 
+  it("derives correct defaults for glm-5.2", () => {
+    const profile = resolveFoundationModelProfile({
+      provider: "zhipuai_cn",
+      model: "glm-5.2",
+    });
+    const policy = resolveRuntimePolicy(profile, "glm-5.2");
+
+    expect(policy.modelProfileId).toBe("glm-5.2");
+    expect(policy.context.contextWindowTokens).toBe(1000000);
+    expect(policy.context.effectiveBudgetTokens).toBe(750000);
+    expect(policy.context.longContextThresholdTokens).toBe(512000);
+    expect(policy.context.compressionMode).toBe("long_context");
+    expect(policy.request.prefersStreaming).toBe(true);
+    expect(policy.request.thinkingMode).toBe("adaptive");
+    expect(policy.request.extraBody).toEqual({
+      thinking: { type: "auto" },
+    });
+    expect(policy.reasoning.responseFields).toEqual(["reasoning_content"]);
+    expect(policy.tools.streamingArguments).toBe(true);
+    expect(policy.cache.supported).toBe(false);
+    expect(policy.telemetry.recordCacheTokens).toBe(false);
+  });
+
   it("derives long_context compression with relaxed thresholds", () => {
     const profile = getProfile("deepseek-v4");
     const policy = resolveRuntimePolicy(profile, "deepseek-v4");