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+# MiniMax-M2.1 工具调用指南
+
+[英文版](./tool_calling_guide.md) | [中文版](./tool_calling_guide_cn.md)
+
+MiniMax-M2.1 支持与 MiniMax-M2 相同的工具调用语法。
+
+## 简介
+
+MiniMax-M2.1 模型支持工具调用功能，使模型能够识别何时需要调用外部工具，并以结构化格式输出工具调用参数。本文档提供了有关如何使用 MiniMax-M2.1 工具调用功能的详细说明。
+
+## 基础示例
+
+以下 Python 脚本基于 OpenAI SDK 实现了一个天气查询工具调用示例：
+
+```python
+from openai import OpenAI
+import json
+
+client = OpenAI(base_url="http://localhost:8000/v1", api_key="dummy")
+
+def get_weather(location: str, unit: str):
+    return f"Getting the weather for {location} in {unit}..."
+
+tool_functions = {"get_weather": get_weather}
+
+tools = [{
+    "type": "function",
+    "function": {
+        "name": "get_weather",
+        "description": "Get the current weather in a given location",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "location": {"type": "string", "description": "City and state, e.g., 'San Francisco, CA'"},
+                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
+            },
+            "required": ["location", "unit"]
+        }
+    }
+}]
+
+response = client.chat.completions.create(
+    model=client.models.list().data[0].id,
+    messages=[{"role": "user", "content": "What's the weather like in San Francisco? use celsius."}],
+    tools=tools,
+    tool_choice="auto"
+)
+
+print(response)
+
+tool_call = response.choices[0].message.tool_calls[0].function
+print(f"Function called: {tool_call.name}")
+print(f"Arguments: {tool_call.arguments}")
+print(f"Result: {get_weather(**json.loads(tool_call.arguments))}")
+```
+
+**输出示例：**
+```
+Function called: get_weather
+Arguments: {"location": "San Francisco, CA", "unit": "celsius"}
+Result: Getting the weather for San Francisco, CA in celsius...
+```
+
+## 手动解析模型输出
+
+**我们强烈建议使用 vLLM 或 SGLnag 来解析工具调用。** 如果您无法使用支持 MiniMax-M2.1 的推理引擎（如 vLLM 和 SGLang）的内置解析器，或需要使用其他推理框架（如 transformers、TGI 等），您可以使用以下方法手动解析模型的原始输出。这种方法需要您自己解析模型输出的 XML 标签格式。
+
+### 使用 Transformers 的示例
+
+这是一个使用 transformers 库的完整示例：
+
+```python
+from transformers import AutoTokenizer
+
+def get_default_tools():
+    return [
+        {
+          "name": "get_current_weather",
+          "description": "Get the latest weather for a location",
+          "parameters": {
+              "type": "object", 
+              "properties": {
+                  "location": {
+                      "type": "string", 
+                      "description": "A certain city, such as Beijing, Shanghai"
+                  }
+              }, 
+          }
+          "required": ["location"],
+          "type": "object"
+        }
+    ]
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+prompt = "What's the weather like in Shanghai today?"
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": prompt},
+]
+
+# Enable function calling tools
+tools = get_default_tools()
+
+# Apply chat template and include tool definitions
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+    tools=tools
+)
+
+# Send request (using any inference service)
+import requests
+payload = {
+    "model": "MiniMaxAI/MiniMax-M2.1",
+    "prompt": text,
+    "max_tokens": 4096
+}
+response = requests.post(
+    "http://localhost:8000/v1/completions",
+    headers={"Content-Type": "application/json"},
+    json=payload,
+    stream=False,
+)
+
+# Model output needs manual parsing
+raw_output = response.json()["choices"][0]["text"]
+print("Raw output:", raw_output)
+
+# Use the parsing function below to process the output
+tool_calls = parse_tool_calls(raw_output, tools)
+```
+
+## 🛠️ 工具调用定义
+
+### 工具结构
+
+工具调用需要在请求体中定义 `tools` 字段。每个工具由以下部分组成：
+
+```json
+{
+  "tools": [
+    {
+      "name": "search_web",
+      "description": "Search function.",
+      "parameters": {
+        "properties": {
+          "query_list": {
+            "description": "Keywords for search, list should contain 1 element.",
+            "items": { "type": "string" },
+            "type": "array"
+          },
+          "query_tag": {
+            "description": "Category of query",
+            "items": { "type": "string" },
+            "type": "array"
+          }
+        },
+        "required": [ "query_list", "query_tag" ],
+        "type": "object"
+      }
+    }
+  ]
+}
+```
+
+**字段说明：**
+- `name`：函数名称
+- `description`：函数描述
+- `parameters`：函数参数定义
+  - `properties`：参数属性定义，其中键是参数名称，值包含详细的参数描述
+  - `required`：必需参数列表
+  - `type`：参数类型（通常为 "object"）
+
+### 内部处理格式
+
+在 MiniMax-M2.1 模型内部处理时，工具定义会被转换为特殊格式并连接到输入文本中。以下是一个完整示例：
+
+```
+]~!b[]~b]system
+You are a helpful assistant.
+
+# Tools
+You may call one or more tools to assist with the user query.
+Here are the tools available in JSONSchema format:
+
+<tools>
+<tool>{"name": "search_web", "description": "Search function.", "parameters": {"type": "object", "properties": {"query_list": {"type": "array", "items": {"type": "string"}, "description": "Keywords for search, list should contain 1 element."}, "query_tag": {"type": "array", "items": {"type": "string"}, "description": "Category of query"}}, "required": ["query_list", "query_tag"]}}</tool>
+</tools>
+
+When making tool calls, use XML format to invoke tools and pass parameters:
+
+<minimax:tool_call>
+<invoke name="tool-name-1">
+<parameter name="param-key-1">param-value-1</parameter>
+<parameter name="param-key-2">param-value-2</parameter>
+...
+</invoke>
+[e~[
+]~b]user
+When were the latest announcements from OpenAI and Gemini?[e~[
+]~b]ai
+<think>
+```
+
+**格式说明：**
+
+- `]~!b[]~b]system`：系统消息开始标记
+- `[e~[`：消息结束标记
+- `]~b]user`：用户消息开始标记
+- `]~b]ai`：助手消息开始标记
+- `]~b]tool`：工具结果消息开始标记
+- `<tools>...</tools>`：工具定义区域，每个工具都用 `<tool>` 标签包装，内容为 JSON Schema
+- `<minimax:tool_call>...</minimax:tool_call>`：工具调用区域
+- `<think>...</think>`：生成过程中的思考过程标记
+
+### 模型输出格式
+
+MiniMax-M2.1 使用结构化的 XML 标签格式：
+
+```xml
+<minimax:tool_call>
+<invoke name="search_web">
+<parameter name="query_tag">["technology", "events"]</parameter>
+<parameter name="query_list">["\"OpenAI\" \"latest\" \"release\""]</parameter>
+</invoke>
+<invoke name="search_web">
+<parameter name="query_tag">["technology", "events"]</parameter>
+<parameter name="query_list">["\"Gemini\" \"latest\" \"release\""]</parameter>
+</invoke>
+</minimax:tool_call>
+```
+
+每个工具调用使用 `<invoke name="function_name">` 标签，参数使用 `<parameter name="parameter_name">` 标签包装。
+
+## 手动解析工具调用结果
+
+### 解析工具调用
+
+MiniMax-M2.1 使用结构化的 XML 标签，这需要一种不同的解析方法。核心函数如下：
+
+```python
+import re
+import json
+from typing import Any, Optional, List, Dict
+
+
+def extract_name(name_str: str) -> str:
+    """Extract name from quoted string"""
+    name_str = name_str.strip()
+    if name_str.startswith('"') and name_str.endswith('"'):
+        return name_str[1:-1]
+    elif name_str.startswith("'") and name_str.endswith("'"):
+        return name_str[1:-1]
+    return name_str
+
+
+def convert_param_value(value: str, param_type: str) -> Any:
+    """Convert parameter value based on parameter type"""
+    if value.lower() == "null":
+        return None
+        
+    param_type = param_type.lower()
+    
+    if param_type in ["string", "str", "text"]:
+        return value
+    elif param_type in ["integer", "int"]:
+        try:
+            return int(value)
+        except (ValueError, TypeError):
+            return value
+    elif param_type in ["number", "float"]:
+        try:
+            val = float(value)
+            return val if val != int(val) else int(val)
+        except (ValueError, TypeError):
+            return value
+    elif param_type in ["boolean", "bool"]:
+        return value.lower() in ["true", "1"]
+    elif param_type in ["object", "array"]:
+        try:
+            return json.loads(value)
+        except json.JSONDecodeError:
+            return value
+    else:
+        # Try JSON parsing, return string if failed
+        try:
+            return json.loads(value)
+        except json.JSONDecodeError:
+            return value
+
+
+def parse_tool_calls(model_output: str, tools: Optional[List[Dict]] = None) -> List[Dict]:
+    """
+    Extract all tool calls from model output
+    
+    Args:
+        model_output: Complete output text from the model
+        tools: Tool definition list for getting parameter type information, format can be:
+               - [{"name": "...", "parameters": {...}}]
+               - [{"type": "function", "function": {"name": "...", "parameters": {...}}}]
+    
+    Returns:
+        Parsed tool call list, each element contains name and arguments fields
+    
+    Example:
+        >>> tools = [{
+        ...     "name": "get_weather",
+        ...     "parameters": {
+        ...         "type": "object",
+        ...         "properties": {
+        ...             "location": {"type": "string"},
+        ...             "unit": {"type": "string"}
+        ...         }
+        ...     }
+        ... }]
+        >>> output = '''<minimax:tool_call>
+        ... <invoke name="get_weather">
+        ... <parameter name="location">San Francisco</parameter>
+        ... <parameter name="unit">celsius</parameter>
+        ... </invoke>
+        ... </minimax:tool_call>'''
+        >>> result = parse_tool_calls(output, tools)
+        >>> print(result)
+        [{'name': 'get_weather', 'arguments': {'location': 'San Francisco', 'unit': 'celsius'}}]
+    """
+    # Quick check if tool call marker is present
+    if "<minimax:tool_call>" not in model_output:
+        return []
+    
+    tool_calls = []
+    
+    try:
+        # Match all <minimax:tool_call> blocks
+        tool_call_regex = re.compile(r"<minimax:tool_call>(.*?)</minimax:tool_call>", re.DOTALL)
+        invoke_regex = re.compile(r"<invoke name=(.*?)</invoke>", re.DOTALL)
+        parameter_regex = re.compile(r"<parameter name=(.*?)</parameter>", re.DOTALL)
+        
+        # Iterate through all tool_call blocks
+        for tool_call_match in tool_call_regex.findall(model_output):
+            # Iterate through all invokes in this block
+            for invoke_match in invoke_regex.findall(tool_call_match):
+                # Extract function name
+                name_match = re.search(r'^([^>]+)', invoke_match)
+                if not name_match:
+                    continue
+                
+                function_name = extract_name(name_match.group(1))
+                
+                # Get parameter configuration
+                param_config = {}
+                if tools:
+                    for tool in tools:
+                        tool_name = tool.get("name") or tool.get("function", {}).get("name")
+                        if tool_name == function_name:
+                            params = tool.get("parameters") or tool.get("function", {}).get("parameters")
+                            if isinstance(params, dict) and "properties" in params:
+                                param_config = params["properties"]
+                            break
+                
+                # Extract parameters
+                param_dict = {}
+                for match in parameter_regex.findall(invoke_match):
+                    param_match = re.search(r'^([^>]+)>(.*)', match, re.DOTALL)
+                    if param_match:
+                        param_name = extract_name(param_match.group(1))
+                        param_value = param_match.group(2).strip()
+                        
+                        # Remove leading and trailing newlines
+                        if param_value.startswith('\n'):
+                            param_value = param_value[1:]
+                        if param_value.endswith('\n'):
+                            param_value = param_value[:-1]
+                        
+                        # Get parameter type and convert
+                        param_type = "string"
+                        if param_name in param_config:
+                            if isinstance(param_config[param_name], dict) and "type" in param_config[param_name]:
+                                param_type = param_config[param_name]["type"]
+                        
+                        param_dict[param_name] = convert_param_value(param_value, param_type)
+                
+                tool_calls.append({
+                    "name": function_name,
+                    "arguments": param_dict
+                })
+    
+    except Exception as e:
+        print(f"Failed to parse tool calls: {e}")
+        return []
+    
+    return tool_calls
+```
+
+**使用示例：**
+
+```python
+# Define tools
+tools = [
+    {
+        "name": "get_weather",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "location": {"type": "string"},
+                "unit": {"type": "string"}
+            },
+            "required": ["location", "unit"]
+        }
+    }
+]
+
+# Model output
+model_output = """Let me help you query the weather.
+<minimax:tool_call>
+<invoke name="get_weather">
+<parameter name="location">San Francisco</parameter>
+<parameter name="unit">celsius</parameter>
+</invoke>
+</minimax:tool_call>"""
+
+# Parse tool calls
+tool_calls = parse_tool_calls(model_output, tools)
+
+# Output results
+for call in tool_calls:
+    print(f"Function called: {call['name']}")
+    print(f"Arguments: {call['arguments']}")
+    # Output: Function called: get_weather
+    #         Arguments: {'location': 'San Francisco', 'unit': 'celsius'}
+```
+
+### 执行工具调用
+
+完成解析后，您可以执行相应的工具并构造返回结果：
+
+```python
+def execute_function_call(function_name: str, arguments: dict):
+    """Execute function call and return result"""
+    if function_name == "get_weather":
+        location = arguments.get("location", "Unknown location")
+        unit = arguments.get("unit", "celsius")
+        # Build function execution result
+        return {
+            "role": "tool", 
+            "content": [
+              {
+                "name": function_name,
+                "type": "text",
+                "text": json.dumps({
+                    "location": location, 
+                    "temperature": "25", 
+                    "unit": unit, 
+                    "weather": "Sunny"
+                }, ensure_ascii=False)
+              }
+            ] 
+          }
+    elif function_name == "search_web":
+        query_list = arguments.get("query_list", [])
+        query_tag = arguments.get("query_tag", [])
+        # Simulate search results
+        return {
+            "role": "tool",
+            "content": [
+              {
+                "name": function_name,
+                "type": "text",
+                "text": f"Search keywords: {query_list}, Category: {query_tag}\nSearch results: Relevant information found"
+              }
+            ]
+          }
+    
+    return None
+```
+
+### 将工具执行结果返回给模型
+
+在成功解析工具调用后，您应该将工具执行结果添加到对话历史中，以便模型在后续交互中可以访问和利用这些信息。请参考 [chat_template.jinja](https://huggingface.co/MiniMaxAI/MiniMax-M2.1/blob/main/chat_template.jinja) 了解连接格式。
+
+## 参考文献
+
+- [MiniMax-M2.1 模型仓库](https://github.com/MiniMax-AI/MiniMax-M2.1)
+- [vLLM 项目主页](https://github.com/vllm-project/vllm)
+- [SGLang 项目主页](https://github.com/sgl-project/sglang)
+- [OpenAI Python SDK](https://github.com/openai/openai-python)
+
+## 获取支持
+
+如果遇到任何问题：
+
+- 通过邮箱 [model@minimax.io](mailto:model@minimax.io) 等官方渠道联系我们的技术支持团队
+
+- 在我们的仓库提交 Issue
+
+- 通过我们的 [官方企业微信交流群](https://github.com/MiniMax-AI/MiniMax-AI.github.io/blob/main/images/wechat-qrcode.jpeg) 反馈
+
+我们会持续优化模型的使用体验，欢迎反馈！