add function call and reasoning docs

docs/CN/source/index.rst

@@ -53,6 +53,8 @@ Lightllm 整合了众多的开源方案的优点，包括但不限于 FasterTran
    多模态部署 <tutorial/multimodal>
    奖励模型部署 <tutorial/reward_model>
    OpenAI 接口使用 <tutorial/openai>
+   工具调用（Function Calling） <tutorial/function_calling>
+   思考解析（Reasoning Parser） <tutorial/reasoning_parser>
    APIServer 参数详解 <tutorial/api_server_args_zh>
    lightllm api介绍 <tutorial/api_param>
 

docs/CN/source/tutorial/function_calling.rst

@@ -0,0 +1,287 @@
+.. _function_calling:
+
+工具调用（Function Calling）
+============================
+
+LightLLM 支持多种主流模型的工具调用功能，提供 OpenAI 兼容的 API。
+
+支持的模型
+----------
+
+Qwen2.5/Qwen3
+~~~~~~~~~~~~~
+
+**解析器**: ``qwen25``
+
+**格式**:
+
+.. code-block:: xml
+
+    <tool_call>
+    {"name": "function_name", "arguments": {"param": "value"}}
+    </tool_call>
+
+**启动**:
+
+.. code-block:: bash
+
+    python -m lightllm.server.api_server \
+        --model_dir /path/to/qwen2.5 \
+        --tool_call_parser qwen25 \
+        --tp 1
+
+Llama 3.2
+~~~~~~~~~
+
+**解析器**: ``llama3``
+
+**格式**: ``<|python_tag|>{"name": "func", "arguments": {...}}``
+
+**启动**:
+
+.. code-block:: bash
+
+    python -m lightllm.server.api_server \
+        --model_dir /path/to/llama-3.2 \
+        --tool_call_parser llama3 \
+        --tp 1
+
+Mistral
+~~~~~~~
+
+**解析器**: ``mistral``
+
+**格式**: ``[TOOL_CALLS] [{"name": "func", "arguments": {...}}, ...]``
+
+DeepSeek-V3
+~~~~~~~~~~~
+
+**解析器**: ``deepseekv3``
+
+**格式**:
+
+.. code-block:: xml
+
+    <｜tool▁calls▁begin｜>
+    <｜tool▁call▁begin｜>function<｜tool▁sep｜>func_name
+    ```json
+    {"param": "value"}
+    ```
+    <｜tool▁call▁end｜>
+    <｜tool▁calls▁end｜>
+
+DeepSeek-V3.1
+~~~~~~~~~~~~~
+
+**解析器**: ``deepseekv31``
+
+**格式**: 简化的 V3 格式，参数直接内联，无代码块包围
+
+Kimi K2
+~~~~~~~
+
+**解析器**: ``kimi_k2``
+
+**格式**:
+
+.. code-block:: xml
+
+    <|tool_calls_section_begin|>
+    <|tool_call_begin|>functions.func_name:0
+    <|tool_call_argument_begin|>{"param": "value"}
+    <|tool_call_end|>
+    <|tool_calls_section_end|>
+
+基本使用
+--------
+
+定义工具
+~~~~~~~~
+
+.. code-block:: python
+
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "get_weather",
+                "description": "获取指定城市的天气信息",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "city": {
+                            "type": "string",
+                            "description": "城市名称"
+                        }
+                    },
+                    "required": ["city"]
+                }
+            }
+        }
+    ]
+
+非流式调用
+~~~~~~~~~~
+
+.. code-block:: python
+
+    import requests
+    import json
+
+    url = "http://localhost:8088/v1/chat/completions"
+    data = {
+        "model": "model_name",
+        "messages": [
+            {"role": "user", "content": "北京今天天气怎么样？"}
+        ],
+        "tools": tools,
+        "tool_choice": "auto"  # "auto" | "none" | "required"
+    }
+
+    response = requests.post(url, json=data).json()
+    message = response["choices"][0]["message"]
+
+    if message.get("tool_calls"):
+        for tc in message["tool_calls"]:
+            print(f"工具: {tc['function']['name']}")
+            print(f"参数: {tc['function']['arguments']}")
+
+流式调用
+~~~~~~~~
+
+.. code-block:: python
+
+    data = {
+        "model": "model_name",
+        "messages": [{"role": "user", "content": "查询北京和上海的天气"}],
+        "tools": tools,
+        "stream": True
+    }
+
+    response = requests.post(url, json=data, stream=True)
+    tool_calls = {}
+
+    for line in response.iter_lines():
+        if line and line.startswith(b"data: "):
+            chunk = json.loads(line[6:])
+            delta = chunk["choices"][0]["delta"]
+
+            if delta.get("tool_calls"):
+                for tc in delta["tool_calls"]:
+                    idx = tc.get("index", 0)
+                    if idx not in tool_calls:
+                        tool_calls[idx] = {"function": {"name": "", "arguments": ""}}
+
+                    if tc["function"].get("name"):
+                        tool_calls[idx]["function"]["name"] = tc["function"]["name"]
+                    if tc["function"].get("arguments"):
+                        tool_calls[idx]["function"]["arguments"] += tc["function"]["arguments"]
+
+多轮对话
+~~~~~~~~
+
+.. code-block:: python
+
+    # 1. 用户提问
+    messages = [{"role": "user", "content": "北京天气如何？"}]
+
+    # 2. 模型调用工具
+    response1 = requests.post(url, json={
+        "messages": messages,
+        "tools": tools
+    }).json()
+
+    tool_call = response1["choices"][0]["message"]["tool_calls"][0]
+    messages.append(response1["choices"][0]["message"])
+
+    # 3. 返回工具结果
+    weather_result = {"temperature": 15, "condition": "晴朗"}
+    messages.append({
+        "role": "tool",
+        "tool_call_id": tool_call["id"],
+        "name": tool_call["function"]["name"],
+        "content": json.dumps(weather_result, ensure_ascii=False)
+    })
+
+    # 4. 生成最终回答
+    response2 = requests.post(url, json={"messages": messages}).json()
+    print(response2["choices"][0]["message"]["content"])
+
+高级功能
+--------
+
+并行工具调用
+~~~~~~~~~~~~
+
+.. code-block:: python
+
+    data = {
+        "messages": messages,
+        "tools": tools,
+        "parallel_tool_calls": True  # 启用并行调用
+    }
+
+强制调用特定工具
+~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    data = {
+        "tools": tools,
+        "tool_choice": {
+            "type": "function",
+            "function": {"name": "get_weather"}
+        }
+    }
+
+与推理模型集成
+~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    data = {
+        "model": "deepseek-r1",
+        "tools": tools,
+        "chat_template_kwargs": {"enable_thinking": True},
+        "separate_reasoning": True  # 分离推理内容
+    }
+
+    response = requests.post(url, json=data).json()
+    message = response["choices"][0]["message"]
+
+    print("推理:", message.get("reasoning_content"))
+    print("工具调用:", message.get("tool_calls"))
+
+常见问题
+--------
+
+**工具调用未触发**
+  检查 ``--tool_call_parser`` 参数和工具描述是否清晰
+
+**参数解析错误**
+  确认使用了正确的解析器，检查模型输出格式
+
+**流式模式不完整**
+  正确处理所有 chunks，使用 ``index`` 字段组装多个工具调用
+
+**与推理模型集成失败**
+  确保使用最新版本，正确配置 ``separate_reasoning`` 和 ``chat_template_kwargs``
+
+技术细节
+--------
+
+**核心文件**:
+- ``lightllm/server/function_call_parser.py`` - 解析器实现（1267行）
+- ``lightllm/server/api_openai.py`` - API 集成
+- ``lightllm/server/build_prompt.py`` - 工具注入
+- ``test/test_api/test_openai_api.py`` - 测试示例
+
+**相关 PR**:
+- PR #1158: 支持推理内容中的函数调用
+
+参考资料
+--------
+
+- OpenAI Function Calling: https://platform.openai.com/docs/guides/function-calling
+- JSON Schema: https://json-schema.org/
+- LightLLM GitHub: https://github.com/ModelTC/lightllm