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README.md

@@ -30,7 +30,7 @@
 
 - `services.openai.host` / `services.openai.port`：OpenAI 协议服务监听地址与端口（默认 `0.0.0.0:8001`）
 - `public_model_name`：对外固定模型名，切换底层模型时可保持调用方参数不变
-- `reasoning_enabled`：思考推理开关，默认 `false`（关闭）
+- `reasoning_enabled`：是否启用推理解析器参数注入，默认 `false`
 - `api_key`：OpenAI 接口访问密钥
 - `tensor_parallel_size`：张量并行数，双卡建议 `2`
 - `dtype`：推理精度，默认 `bfloat16`
@@ -84,7 +84,7 @@ curl http://localhost:<services.openai.port>/v1/models
 curl -X POST "http://localhost:8001/v1/chat/completions" \
   -H "Content-Type: application/json" \
   -H "Authorization: Bearer <config.json中的api_key>" \
-  -d "{\"model\":\"Qwen_local_model\",\"messages\":[{\"role\":\"user\",\"content\":\"你好，介绍一下你自己\"}],\"temperature\":0.7}"
+  -d "{\"model\":\"Qwen_local_model\",\"messages\":[{\"role\":\"user\",\"content\":\"你好，介绍一下你自己\"}],\"temperature\":0.7,\"chat_template_kwargs\":{\"enable_thinking\":false}}"
 ```
 
 ## OpenClaw 调用说明
@@ -92,7 +92,8 @@ curl -X POST "http://localhost:8001/v1/chat/completions" \
 - Base URL 使用 `http://<服务器IP>:8001/v1`
 - API Key 使用 `config.json` 中 `api_key`
 - 模型名固定使用 `config.json` 中 `public_model_name`（默认 `Qwen_local_model`）
-- 若要启用思考推理，将 `config.json` 中 `reasoning_enabled` 设为 `true`
+- 思考模式按请求控制：`chat_template_kwargs.enable_thinking=false/true`
+- 仅当模型需要推理解析器时，再将 `config.json` 中 `reasoning_enabled` 设为 `true`
 - 若使用工具调用，`config.json` 中应配置 `tool_call_parser` 与 `enable_auto_tool_choice`
 - 服务强制离线模式，不会回退到 Hugging Face 远程下载
 - 所有路径按 Ubuntu 规范填写，本地模型建议使用 `/opt/model/<模型目录>`

app/config.py

@@ -17,6 +17,7 @@ class Settings(BaseModel):
     port: int = 8000
     openai_host: str = "0.0.0.0"
     openai_port: int = 8001
+    vllm_openai_internal_url: str = "http://127.0.0.1:8001/v1"
     public_model_name: str = "Qwen_local_model"
     reasoning_enabled: bool = False
     model_root: str = "/opt/model"
@@ -46,6 +47,7 @@ def get_settings() -> Settings:
         port=runtime["port"],
         openai_host=runtime["openai_host"],
         openai_port=runtime["openai_port"],
+        vllm_openai_internal_url=runtime["vllm_openai_internal_url"],
         public_model_name=runtime["public_model_name"],
         reasoning_enabled=runtime["reasoning_enabled"],
         model_root=runtime["model_root"],

app/engine.py

@@ -25,6 +25,8 @@ class InferenceEngine:
         }
         if req.stop:
             payload["stop"] = req.stop
+        if req.enable_thinking is not None:
+            payload["chat_template_kwargs"] = {"enable_thinking": req.enable_thinking}
         response = self.client.post(
             f"{self.settings.vllm_openai_internal_url}/chat/completions",
             headers=headers,

app/model_catalog.py

@@ -63,11 +63,16 @@ def resolve_runtime_settings(content: dict[str, Any]) -> dict[str, Any]:
     api_service = dict(services.get("api", {}))
     openai_service = dict(services.get("openai", {}))
     models = dict(content.get("models", {}))
+    openai_port = _to_int(openai_service.get("port"), 8001)
+    internal_url = _to_str(content.get("vllm_openai_internal_url"))
+    if not internal_url:
+        internal_url = f"http://127.0.0.1:{openai_port}/v1"
     return {
         "host": str(api_service.get("host", "0.0.0.0")),
         "port": _to_int(api_service.get("port"), 8000),
         "openai_host": str(openai_service.get("host", "0.0.0.0")),
-        "openai_port": _to_int(openai_service.get("port"), 8001),
+        "openai_port": openai_port,
+        "vllm_openai_internal_url": internal_url.rstrip("/"),
         "public_model_name": _to_str(content.get("public_model_name"), "Qwen_local_model"),
         "api_key": str(content.get("api_key", "")).strip() or None,
         "reasoning_enabled": _to_bool(content.get("reasoning_enabled"), False),

app/schemas.py

@@ -10,6 +10,7 @@ class GenerateRequest(BaseModel):
     top_p: float = Field(default=0.95, gt=0.0, le=1.0)
     repetition_penalty: float = Field(default=1.0, ge=0.5, le=2.0)
     stop: Optional[List[str]] = None
+    enable_thinking: Optional[bool] = None
 
 
 class GenerateResponse(BaseModel):