fix(issue-1223): [bug]-llm-渠道测试将-your-request-was-blocked

Author: ZhuLinsen

apps/dsa-web/src/components/settings/LLMChannelEditor.tsx

@@ -711,6 +711,7 @@ const LLM_ERROR_LABELS: Record<string, string> = {
   model_not_found: '模型不可用',
   empty_response: '空响应',
   format_error: '格式异常',
+  request_blocked: '请求被拦截',
   network_error: '网络异常',
   invalid_config: '配置无效',
   unsupported_protocol: '协议暂不支持',
@@ -724,6 +725,7 @@ const LLM_TROUBLESHOOTING_HINTS: Record<string, string> = {
   quota: '请检查余额、套餐额度、RPM/TPM 限流或并发设置，必要时稍后重试。',
   model_not_found: '请确认模型名与渠道协议匹配，并先用“获取模型”核对该渠道实际可用模型列表。',
   empty_response: '渠道已连通但未返回正文；可尝试切换兼容模型、关闭额外响应模式后再测试。',
+  request_blocked: '服务商或中转网关拒绝了本次请求；请检查账号风控、地域限制、模型权限、网关策略、内容安全策略或请求来源限制。',
   network_error: '请检查 Base URL、代理、TLS/证书、中转网关或本地网络策略，并可稍后重试。',
   invalid_config: '先补齐协议、Base URL、API Key 和模型配置，再执行一键测试。',
   unsupported_protocol: '当前仅对 OpenAI Compatible / DeepSeek 渠道提供自动模型发现，请改为手动维护模型列表。',
@@ -739,6 +741,7 @@ const LLM_REASON_HINTS: Record<string, string> = {
   tls_error: 'TLS/证书握手失败；请检查 HTTPS 证书、中转网关或公司代理策略。',
   connection_refused: '目标服务拒绝连接；请确认 Base URL 端口、服务进程和防火墙配置。',
   model_access_denied: '当前账号无法使用该模型；请确认模型是否已开通、账号是否可见，或模型是否已被禁用。',
+  provider_blocked: '服务商或中转网关拦截了请求；请检查账号风控、地域限制、模型权限、网关策略、内容安全策略或请求来源限制。',
   provider_prefix_mismatch: '模型 provider 前缀与当前渠道不匹配；请确认模型名是否应使用该渠道的 OpenAI-compatible 路由。',
   capability_unsupported: '当前模型或兼容层不支持该能力；这不影响基础文本连接，可换模型或关闭该能力依赖。',
 };

apps/dsa-web/src/components/settings/__tests__/LLMChannelEditor.test.tsx

@@ -988,6 +988,47 @@ describe('LLMChannelEditor', () => {
     }));
   });
 
+  it('shows provider blocked troubleshooting hints without network wording', async () => {
+    testLLMChannel.mockResolvedValue({
+      success: false,
+      message: 'LLM request was blocked by provider or gateway policy',
+      error: 'litellm.APIError: APIError: OpenAIException - Your request was blocked.',
+      errorCode: 'request_blocked',
+      stage: 'chat_completion',
+      retryable: false,
+      details: { reason: 'provider_blocked', model: 'openai/gpt-5.5' },
+      resolvedProtocol: 'openai',
+      resolvedModel: 'openai/gpt-5.5',
+      latencyMs: null,
+    });
+
+    render(
+      <LLMChannelEditor
+        items={[
+          { key: 'LLM_CHANNELS', value: 'openai' },
+          { key: 'LLM_OPENAI_PROTOCOL', value: 'openai' },
+          { key: 'LLM_OPENAI_BASE_URL', value: 'https://proxy.example.com/v1' },
+          { key: 'LLM_OPENAI_ENABLED', value: 'true' },
+          { key: 'LLM_OPENAI_API_KEY', value: 'secret-key' },
+          { key: 'LLM_OPENAI_MODELS', value: 'gpt-5.5,gpt-4o-mini' },
+        ]}
+        configVersion="v1"
+        maskToken="******"
+        onSaved={() => {}}
+      />
+    );
+
+    fireEvent.click(screen.getByRole('button', { name: /OpenAI 官方/i }));
+    fireEvent.click(screen.getByRole('button', { name: '测试连接' }));
+
+    expect(await screen.findByText(/聊天调用 · 请求被拦截：LLM request was blocked/i)).toBeInTheDocument();
+    expect(screen.getByText(/本次测试模型：openai\/gpt-5\.5/i)).toBeInTheDocument();
+    expect(screen.getByText(/基础连接测试默认使用模型列表首项：gpt-5\.5/i)).toBeInTheDocument();
+    expect(screen.getByText(/账号风控、地域限制、模型权限、网关策略、内容安全策略/i)).toBeInTheDocument();
+    expect(screen.queryByText(/Base URL、代理、TLS/i)).not.toBeInTheDocument();
+    expect(screen.queryByText(/调整模型顺序或移除不可用模型/i)).not.toBeInTheDocument();
+  });
+
   it('shows focused quota exceeded troubleshooting hints', async () => {
     testLLMChannel.mockResolvedValue({
       success: false,

docs/CHANGELOG.md

@@ -15,6 +15,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/).
 - [改进] 放宽 LiteLLM 依赖约束，保留 `>=1.80.10` 最低版本并显式排除 PyPI 事故版本 `1.82.7` / `1.82.8`，允许安装后续 1.x 修复版本。
 - [改进] 补齐通知渠道 P0 基线、Actions 映射与 `--check-notify` 只读诊断，完善 AstrBot 配置入口和通知回归快照。
 - [修复] 修正 LLM 渠道测试中 `Model disabled` 被误报为网络异常的问题，并在失败提示中展示本次实际测试模型。
+- [修复] 修正 LLM 渠道测试中 `Your request was blocked` 等上游拦截错误被误报为网络异常的问题。
 - [chore] 清理仓库根目录：移除误入库的 `.codex`、`review.md` 跟踪记录，将 smoke 测试入口迁移到 `scripts/`、环境检查脚本迁移为 `scripts/check_env.py`，并将 LiteLLM YAML 示例迁移到 `docs/examples/`。
 - [新功能] Web 设置页新增通知渠道一键测试，支持临时配置、耗时与脱敏 attempts 展示。
 

src/services/system_config_service.py

@@ -2572,6 +2572,13 @@ def _classify_llm_http_error(status_code: int, error_text: str) -> _LLMDiagnosti
                 "Configured model could not be found on this channel",
                 "model_not_found",
             )
+        if SystemConfigService._has_provider_blocked_signal(error_text or ""):
+            return _LLMDiagnostic(
+                "request_blocked",
+                False,
+                "LLM request was blocked by provider or gateway policy",
+                "provider_blocked",
+            )
         if status_code in {401, 403} or any(token in lowered for token in ("unauthorized", "forbidden", "invalid api key", "authentication")):
             return _LLMDiagnostic("auth", False, "LLM authentication failed", "api_key_rejected")
         if status_code == 402 or any(token in lowered for token in ("billing", "balance", "insufficient balance")):
@@ -2656,6 +2663,18 @@ def _has_model_access_denied_signal(text: str) -> bool:
         )
         return any(token in lowered for token in access_denied_tokens)
 
+    @staticmethod
+    def _has_provider_blocked_signal(text: str) -> bool:
+        lowered = text.lower()
+        blocked_tokens = (
+            "your request was blocked",
+            "request was blocked",
+            "request blocked",
+            "blocked by policy",
+            "moderation_blocked",
+        )
+        return any(token in lowered for token in blocked_tokens)
+
     @staticmethod
     def _has_provider_prefix_mismatch_signal(text: str) -> bool:
         lowered = text.lower()
@@ -2696,6 +2715,13 @@ def _classify_llm_exception(exc: Exception) -> _LLMDiagnostic:
                 "LLM request was rejected by quota or rate limiting",
                 "rate_limit",
             )
+        if SystemConfigService._has_provider_blocked_signal(str(exc)):
+            return _LLMDiagnostic(
+                "request_blocked",
+                False,
+                "LLM request was blocked by provider or gateway policy",
+                "provider_blocked",
+            )
         if SystemConfigService._has_provider_prefix_mismatch_signal(text):
             return _LLMDiagnostic(
                 "model_not_found",

tests/test_system_config_service.py

@@ -1411,6 +1411,9 @@ class RateLimitError(Exception):
             (Exception("model gpt-4o is not authorized for this account"), "model_not_found", "model_access_denied"),
             (Exception("litellm.APIError: APIError: OpenAIException - Model disabled."), "model_not_found", "model_access_denied"),
             (Exception("Model is disabled for this account"), "model_not_found", "model_access_denied"),
+            (Exception("litellm.APIError: APIError: OpenAIException - Your request was blocked."), "request_blocked", "provider_blocked"),
+            (Exception("request was blocked by policy"), "request_blocked", "provider_blocked"),
+            (Exception("moderation_blocked"), "request_blocked", "provider_blocked"),
             (Exception("LLM Provider NOT provided for model foo"), "model_not_found", "provider_prefix_mismatch"),
         ]
 
@@ -1496,6 +1499,8 @@ def test_discover_llm_channel_models_classifies_error_scenarios(self, mock_get)
         quota_exceeded_response.json.return_value = {"error": {"message": "insufficient_quota"}}
         rate_limit_response = Mock(ok=False, status_code=429, text="too many requests")
         rate_limit_response.json.return_value = {"error": {"message": "too many requests"}}
+        blocked_response = Mock(ok=False, status_code=403, text="Your request was blocked.")
+        blocked_response.json.return_value = {"error": {"message": "Your request was blocked."}}
         invalid_json_response = Mock(ok=True, status_code=200, text="<html>bad gateway</html>")
         invalid_json_response.json.side_effect = ValueError("invalid json")
 
@@ -1506,6 +1511,7 @@ def test_discover_llm_channel_models_classifies_error_scenarios(self, mock_get)
             (billing_rate_limit_response, "quota", "model_discovery", True, "insufficient_balance"),
             (quota_exceeded_response, "quota", "model_discovery", True, "quota_exceeded"),
             (rate_limit_response, "quota", "model_discovery", True, "rate_limit"),
+            (blocked_response, "request_blocked", "model_discovery", False, "provider_blocked"),
             (invalid_json_response, "format_error", "response_parse", False, "non_json"),
         ]:
             with self.subTest(error_code=error_code):