feat: add LLM proxy toggle

app/agent/__init__.py

@@ -470,6 +470,7 @@ class MoviePilotAgent:
             base_url=settings.LLM_BASE_URL,
             base_url_preset=settings.LLM_BASE_URL_PRESET,
             user_agent=settings.LLM_USER_AGENT,
+            use_proxy=settings.LLM_USE_PROXY,
             thinking_level=None,
         )
         selected_event = await eventmanager.async_send_event(
@@ -502,6 +503,9 @@ class MoviePilotAgent:
                 self._clean_optional_text(self._get_event_value(resolved_data, "user_agent"))
                 or settings.LLM_USER_AGENT
         )
+        use_proxy = self._get_event_value(resolved_data, "use_proxy")
+        if use_proxy is None:
+            use_proxy = settings.LLM_USE_PROXY
         thinking_level = self._clean_optional_text(
             self._get_event_value(resolved_data, "thinking_level")
         )
@@ -528,6 +532,7 @@ class MoviePilotAgent:
             "base_url": base_url,
             "base_url_preset": base_url_preset,
             "user_agent": user_agent,
+            "use_proxy": bool(use_proxy),
             "thinking_level": thinking_level,
         }
         return self._llm_runtime_config

app/agent/llm/helper.py

@@ -137,6 +137,57 @@ def _get_httpx_proxy_key() -> str:
         return "proxies"
 
 
+def _resolve_llm_proxy(use_proxy: bool | None = None) -> str | None:
+    """
+    解析本次 LLM 调用应使用的系统代理地址。
+    """
+    should_use_proxy = settings.LLM_USE_PROXY if use_proxy is None else use_proxy
+    return settings.PROXY_HOST if should_use_proxy and settings.PROXY_HOST else None
+
+
+def _build_httpx_proxy_kwargs(proxy_url: str | None) -> dict[str, str]:
+    """
+    构造兼容当前 httpx 版本的代理参数。
+    """
+    if not proxy_url:
+        return {}
+    return {_get_httpx_proxy_key(): proxy_url}
+
+
+def _build_google_client_args(proxy_url: str | None) -> dict[str, Any]:
+    """
+    构造 Google SDK 透传给 httpx 的客户端参数。
+    """
+    return {
+        "trust_env": False,
+        **_build_httpx_proxy_kwargs(proxy_url),
+    }
+
+
+def _build_httpx_client(
+        proxy_url: str | None,
+        *,
+        async_client: bool = False,
+        timeout: float | None = None,
+):
+    """
+    构造显式代理策略的 httpx 客户端。
+
+    当关闭 LLM 代理时也返回 trust_env=False 的客户端，避免 httpx 自动读取
+    进程环境变量中的代理配置。
+    """
+    import httpx
+
+    client_cls = httpx.AsyncClient if async_client else httpx.Client
+    kwargs: dict[str, Any] = {
+        "trust_env": False,
+        **_build_httpx_proxy_kwargs(proxy_url),
+    }
+    if timeout is not None:
+        kwargs["timeout"] = timeout
+    return client_cls(**kwargs)
+
+
 def _deepseek_thinking_toggle(extra_body: Any) -> bool | None:
     """
     解析 DeepSeek extra_body 中显式传入的 thinking 开关。
@@ -733,6 +784,7 @@ class LLMHelper:
             base_url: str | None = None,
             base_url_preset: str | None = None,
             user_agent: str | None = None,
+            use_proxy: bool | None = None,
     ):
         """
         获取LLM实例
@@ -747,6 +799,7 @@ class LLMHelper:
         :param base_url: API Base URL。未显式传入时使用当前配置项 LLM_BASE_URL。
         :param base_url_preset: Base URL 预设。未显式传入时使用当前配置项 LLM_BASE_URL_PRESET。
         :param user_agent: OpenAI兼容接口请求 User-Agent。未显式传入时使用配置项 LLM_USER_AGENT。
+        :param use_proxy: 是否为本次 LLM 调用使用系统代理。未显式传入时使用配置项 LLM_USE_PROXY。
         :return: LLM实例
         """
         provider_name = str(provider if provider is not None else settings.LLM_PROVIDER).lower()
@@ -772,6 +825,7 @@ class LLMHelper:
                 base_url=base_url_value,
                 base_url_preset_id=base_url_preset_value,
                 user_agent=user_agent_value,
+                use_proxy=use_proxy,
             )
         except Exception as err:
             logger.debug(f"LLM provider 目录不可用，回退到旧运行时逻辑: {err}")
@@ -797,6 +851,7 @@ class LLMHelper:
             model=model_name,
             runtime=runtime,
         )
+        llm_proxy = _resolve_llm_proxy(use_proxy)
 
         if runtime["runtime"] == "google":
             # 修补 Gemini 2.5 思考模型的 thought_signature 兼容性
@@ -807,18 +862,13 @@ class LLMHelper:
             # 会导致工具调用时报错 400
             from langchain_google_genai import ChatGoogleGenerativeAI
 
-            client_args = None
-            if settings.PROXY_HOST:
-                proxy_key = _get_httpx_proxy_key()
-                client_args = {proxy_key: settings.PROXY_HOST}
-
             model = ChatGoogleGenerativeAI(
                 model=model_name,
                 api_key=runtime["api_key"],
                 retries=3,
                 temperature=settings.LLM_TEMPERATURE,
                 streaming=streaming,
-                client_args=client_args,
+                client_args=_build_google_client_args(llm_proxy),
                 **thinking_kwargs,
             )
         elif runtime["runtime"] == "deepseek":
@@ -833,6 +883,8 @@ class LLMHelper:
                 temperature=settings.LLM_TEMPERATURE,
                 streaming=streaming,
                 stream_usage=True,
+                http_client=_build_httpx_client(llm_proxy),
+                http_async_client=_build_httpx_client(llm_proxy, async_client=True),
                 **thinking_kwargs,
             )
         elif runtime["runtime"] in {"anthropic_compatible", "copilot_anthropic"}:
@@ -846,7 +898,7 @@ class LLMHelper:
                 temperature=settings.LLM_TEMPERATURE,
                 streaming=streaming,
                 stream_usage=True,
-                anthropic_proxy=settings.PROXY_HOST,
+                anthropic_proxy=llm_proxy,
                 default_headers=default_headers,
                 **thinking_kwargs,
             )
@@ -867,7 +919,15 @@ class LLMHelper:
                 temperature=settings.LLM_TEMPERATURE,
                 streaming=streaming,
                 stream_usage=True,
-                openai_proxy=settings.PROXY_HOST,
+                openai_proxy=llm_proxy,
+                **(
+                    {}
+                    if llm_proxy
+                    else {
+                        "http_client": _build_httpx_client(llm_proxy),
+                        "http_async_client": _build_httpx_client(llm_proxy, async_client=True),
+                    }
+                ),
                 default_headers=default_headers,
                 use_responses_api=use_responses_api,
                 **thinking_kwargs,
@@ -945,6 +1005,7 @@ class LLMHelper:
             base_url: str | None = None,
             base_url_preset: str | None = None,
             user_agent: str | None = None,
+            use_proxy: bool | None = None,
     ) -> dict:
         """
         使用当前已保存配置执行一次最小 LLM 调用。
@@ -961,6 +1022,7 @@ class LLMHelper:
             base_url=base_url,
             base_url_preset=base_url_preset,
             user_agent=user_agent,
+            use_proxy=use_proxy,
         )
         try:
             response = await asyncio.wait_for(llm.ainvoke(prompt), timeout=timeout)
@@ -992,6 +1054,7 @@ class LLMHelper:
             base_url: str | None = None,
             base_url_preset: str | None = None,
             user_agent: str | None = None,
+            use_proxy: bool | None = None,
             force_refresh: bool = False,
     ) -> List[dict[str, Any]]:
         """
@@ -1010,6 +1073,7 @@ class LLMHelper:
                 base_url=base_url,
                 base_url_preset_id=base_url_preset,
                 user_agent=user_agent,
+                use_proxy=use_proxy,
                 force_refresh=force_refresh,
             )
         except Exception as err:
@@ -1017,7 +1081,10 @@ class LLMHelper:
             if provider == "google":
                 return [
                     {"id": model_id, "name": model_id}
-                    for model_id in await self._get_google_models(api_key or "")
+                    for model_id in await self._get_google_models(
+                        api_key or "",
+                        use_proxy=use_proxy,
+                    )
                 ]
             try:
                 from app.agent.llm.provider import LLMProviderManager
@@ -1039,24 +1106,23 @@ class LLMHelper:
                     api_key or "",
                     model_list_base_url,
                     user_agent=user_agent,
+                    use_proxy=use_proxy,
                 )
             ]
 
     @staticmethod
-    async def _get_google_models(api_key: str) -> List[str]:
+    async def _get_google_models(api_key: str, use_proxy: bool | None = None) -> List[str]:
         """获取Google模型列表（使用 google-genai SDK v1）"""
         try:
             from google import genai
             from google.genai.types import HttpOptions
 
-            http_options = None
+            llm_proxy = _resolve_llm_proxy(use_proxy)
-            if settings.PROXY_HOST:
+            google_client_args = _build_google_client_args(llm_proxy)
-                proxy_key = _get_httpx_proxy_key()
+            http_options = HttpOptions(
-                proxy_args = {proxy_key: settings.PROXY_HOST}
+                client_args=google_client_args,
-                http_options = HttpOptions(
+                async_client_args=google_client_args,
-                    client_args=proxy_args,
+            )
-                    async_client_args=proxy_args,
-                )
 
             client = genai.Client(api_key=api_key, http_options=http_options)
             models = await client.aio.models.list()
@@ -1077,6 +1143,7 @@ class LLMHelper:
             api_key: str,
             base_url: str = None,
             user_agent: str | None = None,
+            use_proxy: bool | None = None,
     ) -> List[str]:
         """获取OpenAI兼容模型列表"""
         try:
@@ -1092,6 +1159,11 @@ class LLMHelper:
                     None,
                     user_agent=user_agent,
                 ),
+                http_client=_build_httpx_client(
+                    _resolve_llm_proxy(use_proxy),
+                    async_client=True,
+                    timeout=15.0,
+                ),
             )
             models = await client.models.list()
             await client.close()

app/agent/llm/provider.py

@@ -1085,14 +1085,20 @@ class LLMProviderManager(metaclass=Singleton):
         return builtin_specs + self._dynamic_provider_specs(builtin_specs)
 
     async def _get_provider_async(
-            self, provider_id: str, force_refresh: bool = False
+            self,
+            provider_id: str,
+            force_refresh: bool = False,
+            use_proxy: Optional[bool] = None,
     ) -> ProviderSpec:
         """异步获取指定 provider 的 ProviderSpec 实例。"""
         normalized_provider_id = self._normalize_provider_id(provider_id)
         try:
             return self.get_provider(normalized_provider_id)
         except LLMProviderError:
-            await self.get_models_dev_data(force_refresh=force_refresh)
+            await self.get_models_dev_data(
+                force_refresh=force_refresh,
+                use_proxy=use_proxy,
+            )
             return self.get_provider(normalized_provider_id)
 
     def _serialize_provider(self, spec: ProviderSpec) -> dict[str, Any]:
@@ -1132,11 +1138,16 @@ class LLMProviderManager(metaclass=Singleton):
         }
 
     async def list_providers_async(
-            self, force_refresh: bool = False
+            self,
+            force_refresh: bool = False,
+            use_proxy: Optional[bool] = None,
     ) -> list[dict[str, Any]]:
         """返回前端可渲染的 provider 目录，并优先补齐 models.dev 动态平台。"""
         try:
-            await self.get_models_dev_data(force_refresh=force_refresh)
+            await self.get_models_dev_data(
+                force_refresh=force_refresh,
+                use_proxy=use_proxy,
+            )
         except Exception as err:
             logger.debug(f"加载 models.dev provider 目录失败，回退内置列表: {err}")
         return self.list_providers()
@@ -1327,10 +1338,14 @@ class LLMProviderManager(metaclass=Singleton):
         params = httpx.Client.__init__.__code__.co_varnames
         return "proxy" if "proxy" in params else "proxies"
 
-    def _build_httpx_kwargs(self) -> dict[str, Any]:
+    def _build_httpx_kwargs(self, use_proxy: Optional[bool] = None) -> dict[str, Any]:
         """构造用于 httpx 客户端的参数，如代理等。"""
-        kwargs: dict[str, Any] = {"timeout": self._DEFAULT_TIMEOUT}
+        should_use_proxy = settings.LLM_USE_PROXY if use_proxy is None else use_proxy
-        if settings.PROXY_HOST:
+        kwargs: dict[str, Any] = {
+            "timeout": self._DEFAULT_TIMEOUT,
+            "trust_env": False,
+        }
+        if should_use_proxy and settings.PROXY_HOST:
             kwargs[self._httpx_proxy_key()] = settings.PROXY_HOST
         return kwargs
 
@@ -1441,15 +1456,19 @@ class LLMProviderManager(metaclass=Singleton):
         except Exception as err:
             logger.warning(f"写入 models.dev 缓存失败: {err}")
 
-    async def _fetch_models_dev(self) -> dict[str, Any]:
+    async def _fetch_models_dev(self, use_proxy: Optional[bool] = None) -> dict[str, Any]:
         """通过网络请求获取最新 models.dev 数据。"""
         headers = {"User-Agent": "MoviePilot/1.0"}
-        async with httpx.AsyncClient(**self._build_httpx_kwargs()) as client:
+        async with httpx.AsyncClient(**self._build_httpx_kwargs(use_proxy)) as client:
             response = await client.get(self._MODELS_DEV_URL, headers=headers)
             response.raise_for_status()
             return response.json()
 
-    async def get_models_dev_data(self, force_refresh: bool = False) -> dict[str, Any]:
+    async def get_models_dev_data(
+            self,
+            force_refresh: bool = False,
+            use_proxy: Optional[bool] = None,
+    ) -> dict[str, Any]:
         """
         返回 models.dev 原始数据。
 
@@ -1475,7 +1494,7 @@ class LLMProviderManager(metaclass=Singleton):
                         return cached
 
             try:
-                payload = await self._fetch_models_dev()
+                payload = await self._fetch_models_dev(use_proxy=use_proxy)
                 self._models_dev_data = payload
                 self._models_dev_loaded_at = now
                 await self._write_models_dev_to_disk(payload)
@@ -1499,9 +1518,13 @@ class LLMProviderManager(metaclass=Singleton):
             provider_id: str,
             base_url: Optional[str] = None,
             base_url_preset_id: Optional[str] = None,
+            use_proxy: Optional[bool] = None,
     ) -> dict[str, Any]:
         """获取指定 provider 在 models.dev 中的完整负载。"""
-        spec = await self._get_provider_async(provider_id)
+        spec = await self._get_provider_async(
+            provider_id,
+            use_proxy=use_proxy,
+        )
         models_dev_provider_id = self._resolve_provider_models_dev_provider_id(
             spec,
             base_url,
@@ -1509,7 +1532,9 @@ class LLMProviderManager(metaclass=Singleton):
         )
         if not models_dev_provider_id:
             return {}
-        return (await self.get_models_dev_data()).get(models_dev_provider_id, {}) or {}
+        return (
+            await self.get_models_dev_data(use_proxy=use_proxy)
+        ).get(models_dev_provider_id, {}) or {}
 
     async def _models_dev_model(
             self,
@@ -1517,12 +1542,14 @@ class LLMProviderManager(metaclass=Singleton):
             model_id: str,
             base_url: Optional[str] = None,
             base_url_preset_id: Optional[str] = None,
+            use_proxy: Optional[bool] = None,
     ) -> dict[str, Any] | None:
         """获取指定模型的 models.dev 元数据。"""
         payload = await self._models_dev_provider_payload(
             provider_id,
             base_url=base_url,
             base_url_preset_id=base_url_preset_id,
+            use_proxy=use_proxy,
         )
         models = payload.get("models") if isinstance(payload, dict) else None
         if not isinstance(models, dict):
@@ -1621,19 +1648,23 @@ class LLMProviderManager(metaclass=Singleton):
             return normalized[:-3]
         return normalized
 
-    async def _list_models_from_google(self, api_key: str) -> list[dict[str, Any]]:
+    async def _list_models_from_google(
+            self,
+            api_key: str,
+            use_proxy: Optional[bool] = None,
+    ) -> list[dict[str, Any]]:
         """从 Google AI Studio 获取模型列表。"""
         from google import genai
         from google.genai.types import HttpOptions
 
-        http_options = None
+        should_use_proxy = settings.LLM_USE_PROXY if use_proxy is None else use_proxy
-        if settings.PROXY_HOST:
+        client_args: dict[str, Any] = {"trust_env": False}
-            proxy_key = self._httpx_proxy_key()
+        if should_use_proxy and settings.PROXY_HOST:
-            proxy_args = {proxy_key: settings.PROXY_HOST}
+            client_args[self._httpx_proxy_key()] = settings.PROXY_HOST
-            http_options = HttpOptions(
+        http_options = HttpOptions(
-                client_args=proxy_args,
+            client_args=client_args,
-                async_client_args=proxy_args,
+            async_client_args=client_args,
-            )
+        )
 
         client = genai.Client(api_key=api_key, http_options=http_options)
         response = await client.aio.models.list()
@@ -1643,7 +1674,11 @@ class LLMProviderManager(metaclass=Singleton):
             if "generateContent" not in supported:
                 continue
             model_id = model.name
-            metadata = await self._models_dev_model("google", model_id) or {}
+            metadata = await self._models_dev_model(
+                "google",
+                model_id,
+                use_proxy=use_proxy,
+            ) or {}
             results.append(
                 self._normalize_model_record(
                     model_id=model_id,
@@ -1660,6 +1695,7 @@ class LLMProviderManager(metaclass=Singleton):
             api_key: str,
             base_url: str,
             default_headers: Optional[dict[str, str]] = None,
+            use_proxy: Optional[bool] = None,
     ) -> list[dict[str, Any]]:
         """通过 OpenAI 兼容接口获取模型列表。"""
         from openai import AsyncOpenAI
@@ -1670,6 +1706,7 @@ class LLMProviderManager(metaclass=Singleton):
             default_headers=default_headers,
             timeout=15.0,
             max_retries=2,
+            http_client=httpx.AsyncClient(**self._build_httpx_kwargs(use_proxy)),
         )
         results = []
         response = await client.models.list()
@@ -1678,6 +1715,7 @@ class LLMProviderManager(metaclass=Singleton):
                 provider_id,
                 model.id,
                 base_url=base_url,
+                use_proxy=use_proxy,
             ) or {}
             results.append(
                 self._normalize_model_record(
@@ -1695,6 +1733,7 @@ class LLMProviderManager(metaclass=Singleton):
             transport: str = "openai",
             base_url: Optional[str] = None,
             base_url_preset_id: Optional[str] = None,
+            use_proxy: Optional[bool] = None,
     ) -> list[dict[str, Any]]:
         """
         某些 provider 没有统一稳定的 models.list 行为，
@@ -1705,6 +1744,7 @@ class LLMProviderManager(metaclass=Singleton):
             provider_id,
             base_url=base_url,
             base_url_preset_id=base_url_preset_id,
+            use_proxy=use_proxy,
         )
         models = payload.get("models") if isinstance(payload, dict) else None
         if not isinstance(models, dict):
@@ -1741,9 +1781,13 @@ class LLMProviderManager(metaclass=Singleton):
             headers["Authorization"] = f"Bearer {token}"
         return headers
 
-    async def _list_models_from_copilot(self, token: str) -> list[dict[str, Any]]:
+    async def _list_models_from_copilot(
+            self,
+            token: str,
+            use_proxy: Optional[bool] = None,
+    ) -> list[dict[str, Any]]:
         """从 GitHub Copilot 端点获取模型列表。"""
-        async with httpx.AsyncClient(**self._build_httpx_kwargs()) as client:
+        async with httpx.AsyncClient(**self._build_httpx_kwargs(use_proxy)) as client:
             response = await client.get(
                 "https://api.githubcopilot.com/models",
                 headers=self._copilot_headers(token),
@@ -1780,7 +1824,11 @@ class LLMProviderManager(metaclass=Singleton):
 
             limits = ((item.get("capabilities") or {}).get("limits") or {})
             supports = ((item.get("capabilities") or {}).get("supports") or {})
-            metadata = await self._models_dev_model("github-copilot", model_id) or {}
+            metadata = await self._models_dev_model(
+                "github-copilot",
+                model_id,
+                use_proxy=use_proxy,
+            ) or {}
             results.append(
                 self._normalize_model_record(
                     model_id=model_id,
@@ -1811,6 +1859,7 @@ class LLMProviderManager(metaclass=Singleton):
             provider_id: str,
             base_url: Optional[str] = None,
             base_url_preset_id: Optional[str] = None,
+            use_proxy: Optional[bool] = None,
     ) -> list[dict[str, Any]]:
         """获取开启 OAuth 的 ChatGPT 模型列表。"""
         # ChatGPT OAuth 仍然是 chatgpt provider 专属能力，但模型目录不再维护
@@ -1819,6 +1868,7 @@ class LLMProviderManager(metaclass=Singleton):
             provider_id,
             base_url=base_url,
             base_url_preset_id=base_url_preset_id,
+            use_proxy=use_proxy,
         )
         models = payload.get("models") if isinstance(payload, dict) else None
         if not isinstance(models, dict):
@@ -1843,10 +1893,15 @@ class LLMProviderManager(metaclass=Singleton):
             base_url: Optional[str] = None,
             base_url_preset_id: Optional[str] = None,
             user_agent: Optional[str] = None,
+            use_proxy: Optional[bool] = None,
             force_refresh: bool = False,
     ) -> list[dict[str, Any]]:
         """返回标准化后的模型目录。"""
-        spec = await self._get_provider_async(provider_id, force_refresh=force_refresh)
+        spec = await self._get_provider_async(
+            provider_id,
+            force_refresh=force_refresh,
+            use_proxy=use_proxy,
+        )
         resolved_model_list_strategy = self._resolve_provider_model_list_strategy(
             spec,
             base_url,
@@ -1860,7 +1915,10 @@ class LLMProviderManager(metaclass=Singleton):
             # 对依赖 models.dev 的 provider 主动刷新一次缓存，保证“刷新模型列表”
             # 在使用目录型 provider 时也能拿到最新参数。
             if force_refresh:
-                await self.get_models_dev_data(force_refresh=True)
+                await self.get_models_dev_data(
+                    force_refresh=True,
+                    use_proxy=use_proxy,
+                )
 
         if resolved_model_list_strategy == "manual":
             # 万擎等推理点型平台没有稳定的全局模型目录，模型 ID 需要用户从控制台复制。
@@ -1873,13 +1931,20 @@ class LLMProviderManager(metaclass=Singleton):
             base_url=base_url,
             base_url_preset_id=base_url_preset_id,
             user_agent=user_agent,
+            use_proxy=use_proxy,
         )
 
         if resolved_model_list_strategy == "google":
-            return await self._list_models_from_google(runtime["api_key"])
+            return await self._list_models_from_google(
+                runtime["api_key"],
+                use_proxy=use_proxy,
+            )
 
         if resolved_model_list_strategy == "github_copilot":
-            return await self._list_models_from_copilot(runtime["api_key"])
+            return await self._list_models_from_copilot(
+                runtime["api_key"],
+                use_proxy=use_proxy,
+            )
 
         if resolved_model_list_strategy == "chatgpt":
             if runtime.get("auth_mode") == "oauth":
@@ -1887,6 +1952,7 @@ class LLMProviderManager(metaclass=Singleton):
                     provider_id=provider_id,
                     base_url=base_url,
                     base_url_preset_id=base_url_preset_id,
+                    use_proxy=use_proxy,
                 )
             return await self._list_models_from_openai_compatible(
                 provider_id="chatgpt",
@@ -1900,6 +1966,7 @@ class LLMProviderManager(metaclass=Singleton):
                     runtime.get("default_headers"),
                     user_agent,
                 ),
+                use_proxy=use_proxy,
             )
 
         if resolved_model_list_strategy == "anthropic_compatible":
@@ -1908,6 +1975,7 @@ class LLMProviderManager(metaclass=Singleton):
                 transport="anthropic",
                 base_url=base_url,
                 base_url_preset_id=base_url_preset_id,
+                use_proxy=use_proxy,
             )
             
         if resolved_model_list_strategy == "models_dev_only":
@@ -1916,6 +1984,7 @@ class LLMProviderManager(metaclass=Singleton):
                 transport="openai",
                 base_url=base_url,
                 base_url_preset_id=base_url_preset_id,
+                use_proxy=use_proxy,
             )
 
         # openai-compatible / deepseek 默认走官方 models 端点。
@@ -1931,6 +2000,7 @@ class LLMProviderManager(metaclass=Singleton):
                 runtime.get("default_headers"),
                 user_agent,
             ),
+            use_proxy=use_proxy,
         )
 
     async def resolve_model_metadata(
@@ -1939,6 +2009,7 @@ class LLMProviderManager(metaclass=Singleton):
             model_id: Optional[str],
             base_url: Optional[str] = None,
             base_url_preset_id: Optional[str] = None,
+            use_proxy: Optional[bool] = None,
     ) -> dict[str, Any] | None:
         """解析并返回指定模型在 models.dev 中的元数据。"""
         if not model_id:
@@ -1948,13 +2019,18 @@ class LLMProviderManager(metaclass=Singleton):
             model_id,
             base_url=base_url,
             base_url_preset_id=base_url_preset_id,
+            use_proxy=use_proxy,
         )
         if metadata:
             return metadata
         if provider_id == "chatgpt":
-            return await self._models_dev_model("openai", model_id)
+            return await self._models_dev_model(
+                "openai",
+                model_id,
+                use_proxy=use_proxy,
+            )
         if provider_id == "openai":
-            models_dev = await self.get_models_dev_data()
+            models_dev = await self.get_models_dev_data(use_proxy=use_proxy)
             return models_dev.get("openai", {}).get("models", {}).get(model_id)
         return None
 
@@ -2424,6 +2500,7 @@ class LLMProviderManager(metaclass=Singleton):
             base_url: Optional[str] = None,
             base_url_preset_id: Optional[str] = None,
             user_agent: Optional[str] = None,
+            use_proxy: Optional[bool] = None,
     ) -> dict[str, Any]:
         """
         解析 provider 运行时参数。
@@ -2435,7 +2512,10 @@ class LLMProviderManager(metaclass=Singleton):
             normalized_provider_id,
             base_url_preset_id,
         )
-        spec = await self._get_provider_async(normalized_provider_id)
+        spec = await self._get_provider_async(
+            normalized_provider_id,
+            use_proxy=use_proxy,
+        )
         resolved_runtime = self._resolve_provider_runtime(
             spec,
             base_url,
@@ -2455,6 +2535,7 @@ class LLMProviderManager(metaclass=Singleton):
                         base_url=base_url,
                         base_url_preset_id=normalized_base_url_preset_id,
                         user_agent=user_agent,
+                        use_proxy=use_proxy,
                     )
                         if item["id"] == model
                     ),
@@ -2474,6 +2555,7 @@ class LLMProviderManager(metaclass=Singleton):
                 model,
                 base_url=base_url,
                 base_url_preset_id=normalized_base_url_preset_id,
+                use_proxy=use_proxy,
             ),
             "default_headers": None,
             "use_responses_api": None,

app/api/endpoints/llm.py

@@ -36,6 +36,7 @@ class LlmTestRequest(BaseModel):
     base_url: Optional[str] = None
     base_url_preset: Optional[str] = None
     user_agent: Optional[str] = None
+    use_proxy: Optional[bool] = None
 
 
 class LlmProviderAuthStartRequest(BaseModel):
@@ -77,6 +78,7 @@ async def get_llm_models(
     base_url: Optional[str] = None,
     base_url_preset: Optional[str] = None,
     user_agent: Optional[str] = None,
+    use_proxy: Optional[bool] = None,
     force_refresh: Optional[bool] = False,
     _: User = Depends(get_current_active_user_async),
 ):
@@ -91,6 +93,7 @@ async def get_llm_models(
             base_url=base_url,
             base_url_preset=base_url_preset,
             user_agent=user_agent,
+            use_proxy=use_proxy,
             force_refresh=bool(force_refresh),
         )
         return schemas.Response(
@@ -250,6 +253,7 @@ async def llm_test(
         base_url=settings.LLM_BASE_URL,
         base_url_preset=settings.LLM_BASE_URL_PRESET,
         user_agent=settings.LLM_USER_AGENT,
+        use_proxy=settings.LLM_USE_PROXY,
     )
 
     if not payload.provider:
@@ -282,6 +286,7 @@ async def llm_test(
             base_url=payload.base_url,
             base_url_preset=payload.base_url_preset,
             user_agent=payload.user_agent,
+            use_proxy=payload.use_proxy,
         )
         if not result.get("reply_preview"):
             return schemas.Response(

app/core/config.py

@@ -562,6 +562,8 @@ class ConfigModel(BaseModel):
     LLM_API_KEY: Optional[str] = None
     # LLM基础URL（用于自定义API端点）
     LLM_BASE_URL: Optional[str] = "https://api.deepseek.com"
+    # LLM调用是否使用系统代理
+    LLM_USE_PROXY: bool = True
     # LLM Base URL 预设标识，用于区分同一 Base URL 下的不同模型目录
     LLM_BASE_URL_PRESET: Optional[str] = None
     # LLM最大上下文Token数量（K）

app/schemas/event.py

@@ -69,7 +69,7 @@ class AgentLLMProviderEventData(ChainEventData):
     Agent LLM 供应商选择事件数据。
 
     事件发出方会带入当前系统配置作为默认值；插件可覆盖 provider、base_url、
-    api_key、model、user_agent 等字段，并通过 selected_provider_id 标记本次选择，方便
+    api_key、model、user_agent、use_proxy 等字段，并通过 selected_provider_id 标记本次选择，方便
     后续用量事件精确回写到同一个配额条目。
     """
 
@@ -79,6 +79,7 @@ class AgentLLMProviderEventData(ChainEventData):
     model: Optional[str] = Field(default=None, description="模型名称")
     base_url_preset: Optional[str] = Field(default=None, description="Base URL 预设ID")
     user_agent: Optional[str] = Field(default=None, description="OpenAI兼容接口User-Agent")
+    use_proxy: Optional[bool] = Field(default=None, description="是否使用系统代理")
     thinking_level: Optional[str] = Field(default=None, description="思考模式级别")
     selected_provider_id: Optional[str] = Field(default=None, description="插件侧供应商ID")
     selected_provider_name: Optional[str] = Field(default=None, description="插件侧供应商名称")

tests/test_agent_tokens_events.py

@@ -107,6 +107,7 @@ class AgentTokensEventsTest(unittest.IsolatedAsyncioTestCase):
             base_url="https://tokens.example.com/v1",
             base_url_preset=None,
             user_agent="AgentTokens-UA/1.0",
+            use_proxy=True,
             thinking_level=None,
         )
         self.assertEqual("provider-1", agent._llm_provider_selection["selected_provider_id"])

tests/test_llm_helper_testcall.py

@@ -135,6 +135,7 @@ _stub_module(
         LLM_THINKING_LEVEL=None,
         LLM_TEMPERATURE=0.1,
         LLM_MAX_CONTEXT_TOKENS=64,
+        LLM_USE_PROXY=True,
         PROXY_HOST=None,
     ),
 )
@@ -188,6 +189,7 @@ class LlmHelperTestCallTest(unittest.TestCase):
             base_url="https://api.deepseek.com",
             base_url_preset="deepseek-default",
             user_agent=None,
+            use_proxy=None,
         )
         self.assertEqual(result["provider"], "deepseek")
         self.assertEqual(result["model"], "deepseek-chat")
@@ -489,6 +491,7 @@ class LlmHelperTestCallTest(unittest.TestCase):
                 "base_url": "https://updated.example.com/v1",
                 "base_url_preset_id": "updated-preset",
                 "user_agent": None,
+                "use_proxy": None,
             },
         )
         self.assertEqual(len(llm_calls), 1)
@@ -500,6 +503,46 @@ class LlmHelperTestCallTest(unittest.TestCase):
         )
         self.assertEqual(llm_calls[0].get("default_headers"), {"X-Test": "1"})
 
+    def test_get_llm_applies_proxy_only_when_enabled(self):
+        """LLM 构造时应按独立开关决定是否传入系统代理。"""
+        calls = []
+
+        class _FakeChatOpenAI:
+            def __init__(self, **kwargs):
+                calls.append(kwargs)
+                self.model = kwargs["model"]
+                self.profile = None
+
+        with patch.object(llm_module.settings, "PROXY_HOST", "http://proxy.example.com:7890"), patch.dict(
+            sys.modules,
+            {"langchain_openai": SimpleNamespace(ChatOpenAI=_FakeChatOpenAI)},
+        ):
+            asyncio.run(
+                llm_module.LLMHelper.get_llm(
+                    provider="openai",
+                    model="gpt-5-mini",
+                    api_key="sk-test",
+                    base_url="https://api.example.com/v1",
+                    use_proxy=True,
+                )
+            )
+            asyncio.run(
+                llm_module.LLMHelper.get_llm(
+                    provider="openai",
+                    model="gpt-5-mini",
+                    api_key="sk-test",
+                    base_url="https://api.example.com/v1",
+                    use_proxy=False,
+                )
+            )
+
+        self.assertEqual(calls[0].get("openai_proxy"), "http://proxy.example.com:7890")
+        self.assertNotIn("http_client", calls[0])
+        self.assertNotIn("http_async_client", calls[0])
+        self.assertIsNone(calls[1].get("openai_proxy"))
+        self.assertIn("http_client", calls[1])
+        self.assertIn("http_async_client", calls[1])
+
     def test_get_llm_passes_user_agent_as_openai_default_header(self):
         calls = []
 

tests/test_llm_provider_registry.py

@@ -182,11 +182,15 @@ class LlmProviderRegistryTest(unittest.TestCase):
         with patch.object(
             manager,
             "get_models_dev_data",
-            AsyncMock(side_effect=lambda force_refresh=False: manager.__dict__.update({"_models_dev_data": payload}) or payload),
+            AsyncMock(
+                side_effect=lambda force_refresh=False, use_proxy=None: manager.__dict__.update(
+                    {"_models_dev_data": payload}
+                ) or payload
+            ),
         ) as fetch_mock:
             providers = asyncio.run(manager.list_providers_async())
 
-        fetch_mock.assert_awaited_once_with(force_refresh=False)
+        fetch_mock.assert_awaited_once_with(force_refresh=False, use_proxy=None)
         self.assertIn("frogbot", {item["id"] for item in providers})
 
     def test_list_models_uses_dynamic_provider_after_refresh(self):
@@ -207,7 +211,7 @@ class LlmProviderRegistryTest(unittest.TestCase):
             }
         }
 
-        async def _load_models_dev(force_refresh: bool = False):
+        async def _load_models_dev(force_refresh: bool = False, use_proxy=None):
             manager._models_dev_data = payload
             return payload
 

tests/test_system_llm_test.py

@@ -147,6 +147,8 @@ class LlmTestEndpointTest(unittest.TestCase):
             system_endpoint.settings, "LLM_BASE_URL_PRESET", "deepseek-default"
         ), patch.object(
             system_endpoint.settings, "LLM_USER_AGENT", "MoviePilot-Test/1.0"
+        ), patch.object(
+            system_endpoint.settings, "LLM_USE_PROXY", True
         ), patch.object(
             system_endpoint.LLMHelper,
             "test_current_settings",
@@ -163,6 +165,7 @@ class LlmTestEndpointTest(unittest.TestCase):
             base_url="https://api.deepseek.com",
             base_url_preset="deepseek-default",
             user_agent="MoviePilot-Test/1.0",
+            use_proxy=True,
         )
         self.assertTrue(resp.success)
         self.assertEqual(resp.data["provider"], "deepseek")
@@ -188,6 +191,7 @@ class LlmTestEndpointTest(unittest.TestCase):
             base_url="https://example.com/v1",
             base_url_preset="openai-default",
             user_agent="MoviePilot-Custom/1.0",
+            use_proxy=False,
         )
 
         with patch.object(system_endpoint.settings, "AI_AGENT_ENABLE", False), patch.object(
@@ -212,6 +216,7 @@ class LlmTestEndpointTest(unittest.TestCase):
             base_url="https://example.com/v1",
             base_url_preset="openai-default",
             user_agent="MoviePilot-Custom/1.0",
+            use_proxy=False,
         )
         self.assertTrue(resp.success)
         self.assertEqual(resp.data["provider"], "openai")
@@ -234,6 +239,7 @@ class LlmTestEndpointTest(unittest.TestCase):
             base_url="https://api.deepseek.com",
             base_url_preset="deepseek-default",
             user_agent=None,
+            use_proxy=None,
         )
 
         with patch.object(system_endpoint.settings, "AI_AGENT_ENABLE", False), patch.object(
@@ -252,6 +258,7 @@ class LlmTestEndpointTest(unittest.TestCase):
             base_url="https://api.deepseek.com",
             base_url_preset="deepseek-default",
             user_agent=None,
+            use_proxy=None,
         )
         self.assertTrue(resp.success)