Alibaba Cloud Model Studio:Function calling

サンプルコード

import os
from openai import OpenAI

# Initialize the OpenAI client and configure the Alibaba Cloud DashScope service
client = OpenAI(
    # If you have not configured the environment variable, replace the following line with: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),  # Read API key from environment variable
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

# Define the list of available tools
tools = [
    # Tool 1: Get the current time
    {
        "type": "function",
        "function": {
            "name": "get_current_time",
            "description": "This is useful when you want to know the current time.",
            "parameters": {}  # No parameters needed
        }
    },  
    # Tool 2: Get the weather for a specified city
    {
        "type": "function",
        "function": {
            "name": "get_current_weather",
            "description": "This is useful when you want to query the weather in a specific city.",
            "parameters": {  
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "A city or district, such as Beijing, Hangzhou, or Yuhang District."
                    }
                },
                "required": ["location"]  # Required parameter
            }
        }
    }
]

messages = [{"role": "user", "content": input("Please enter your question: ")}]

# Example message for multimodal model
# messages = [{
#     "role": "user",
#     "content": [
#              {"type": "image_url","image_url": {"url": "https://img.alicdn.com/imgextra/i4/O1CN014CJhzi20NOzo7atOC_!!6000000006837-2-tps-2048-1365.png"}},
#              {"type": "text", "text": "What is the current weather at the location in the image?"}]
#     }]

completion = client.chat.completions.create(
    # This example uses qwen-plus. It can be replaced with other deep thinking models.
    model="qwen-plus",
    messages=messages,
    extra_body={
        # Enable deep thinking. This parameter is invalid for qwen3-30b-a3b-thinking-2507, qwen3-235b-a22b-thinking-2507, and QwQ models.
        "enable_thinking": True
    },
    tools=tools,
    parallel_tool_calls=True,
    stream=True,
    # Uncomment to get token consumption information
    # stream_options={
    #     "include_usage": True
    # }
)

reasoning_content = ""  # Defines the complete thinking process
answer_content = ""     # Defines the complete reply
tool_info = []          # Stores tool call information
is_answering = False   # Determines if the thinking process has ended and the reply has begun
print("="*20+"Thinking Process"+"="*20)
for chunk in completion:
    if not chunk.choices:
        # Process usage statistics
        print("\n"+"="*20+"Usage"+"="*20)
        print(chunk.usage)
    else:
        delta = chunk.choices[0].delta
        # Process the AI's thinking process (chain of thought)
        if hasattr(delta, 'reasoning_content') and delta.reasoning_content is not None:
            reasoning_content += delta.reasoning_content
            print(delta.reasoning_content,end="",flush=True)  # Output the thinking process in real time
            
        # Process the final reply content
        else:
            if not is_answering:  # Print the title when entering the reply phase for the first time
                is_answering = True
                print("\n"+"="*20+"Reply Content"+"="*20)
            if delta.content is not None:
                answer_content += delta.content
                print(delta.content,end="",flush=True)  # Stream the reply content
            
            # Process tool call information (supports parallel tool calls)
            if delta.tool_calls is not None:
                for tool_call in delta.tool_calls:
                    index = tool_call.index  # Tool call index, for parallel calls
                    
                    # Dynamically expand the tool information storage list
                    while len(tool_info) <= index:
                        tool_info.append({})
                    
                    # Collect the tool call ID (for subsequent function calls)
                    if tool_call.id:
                        tool_info[index]['id'] = tool_info[index].get('id', '') + tool_call.id
                    
                    # Collect the function name (for subsequent routing to a specific function)
                    if tool_call.function and tool_call.function.name:
                        tool_info[index]['name'] = tool_info[index].get('name', '') + tool_call.function.name
                    
                    # Collect function arguments (in JSON string format, requires subsequent parsing)
                    if tool_call.function and tool_call.function.arguments:
                        tool_info[index]['arguments'] = tool_info[index].get('arguments', '') + tool_call.function.arguments
            
print(f"\n"+"="*19+"Tool Call Information"+"="*19)
if not tool_info:
    print("No tool calls")
else:
    print(tool_info)

返された結果

「4つの市区町村の天気」と入力すると、以下の結果が返されます：

====================Thinking Process====================
Okay, the user is asking for the "weather in the four municipalities". First, I need to identify which four municipalities are being referred to. According to China's administrative divisions, the municipalities include Beijing, Shanghai, Tianjin, and Chongqing. So the user wants to know the weather conditions in these four cities.

Next, I need to check the available tools. The provided tools include the get_current_weather function, which takes a location of type string as a parameter. Each city needs to be queried separately because the function can only check one location at a time. Therefore, I need to call this function once for each municipality.

Then, I need to consider how to generate the correct tool calls. Each call should include the city name as a parameter. For example, the first call is for Beijing, the second for Shanghai, and so on. I need to make sure the parameter name is `location` and the value is the correct city name.

Also, the user probably wants the weather information for each city, so I need to ensure each function call is correct. It might require four consecutive calls, one for each city. However, based on the tool usage rules, it might need to be handled in multiple steps, or multiple calls might be generated at once. But based on the example, it seems only one function is called at a time, so it might need to be done step by step.

Finally, I need to confirm if there are any other factors to consider, such as whether the parameters are correct, the city names are accurate, and whether to handle possible error situations, like the city not existing or the API being unavailable. But for now, the four municipalities are clear, so it should be fine.
====================Reply Content====================

===================Tool Call Information===================
[{'id': 'call_767af2834c12488a8fe6e3', 'name': 'get_current_weather', 'arguments': '{"location": "Beijing"}'}, {'id': 'call_2cb05a349c89437a947ada', 'name': 'get_current_weather', 'arguments': '{"location": "Shanghai"}'}, {'id': 'call_988dd180b2ca4b0a864ea7', 'name': 'get_current_weather', 'arguments': '{"location": "Tianjin"}'}, {'id': 'call_4e98c57ea96a40dba26d12', 'name': 'get_current_weather', 'arguments': '{"location": "Chongqing"}'}]

サンプルコード

import OpenAI from "openai";
import readline from 'node:readline/promises';
import { stdin as input, stdout as output } from 'node:process';

const openai = new OpenAI({
    apiKey: process.env.DASHSCOPE_API_KEY,
    baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
});

const tools = [
    {
        type: "function",
        function: {
            name: "get_current_time",
            description: "This is useful when you want to know the current time.",
            parameters: {}
        }
    },
    {
        type: "function",
        function: {
            name: "get_current_weather",
            description: "This is useful when you want to query the weather in a specific city.",
            parameters: {
                type: "object",
                properties: {
                    location: {
                        type: "string",
                        description: "A city or district, such as Beijing, Hangzhou, or Yuhang District."
                    }
                },
                required: ["location"]
            }
        }
    }
];

async function main() {
    const rl = readline.createInterface({ input, output });
    const question = await rl.question("Please enter your question: "); 
    rl.close();
    
    const messages = [{ role: "user", content: question }];
    // マルチモーダルモデルのメッセージ例
    // const messages= [{
    //     role: "user",
    //     content: [{type: "image_url", image_url: {url: "https://img.alicdn.com/imgextra/i2/O1CN01FbTJon1ErXVGMRdsN_!!6000000000405-0-tps-1024-683.jpg"}},
    //               {type: "text", text: "What's the weather at the location in the image?"}]
    //   }];
    let reasoningContent = "";
    let answerContent = "";
    const toolInfo = [];
    let isAnswering = false;

    console.log("=".repeat(20) + "Thinking Process" + "=".repeat(20));
    
    try {
        const stream = await openai.chat.completions.create({
            // この例では qwen-plus を使用しています。他のディープシンキングモデルに置き換えることができます。
            model: "qwen-plus",
            messages,
            // ディープシンキングを有効にします。このパラメーターは qwen3-30b-a3b-thinking-2507、qwen3-235b-a22b-thinking-2507、および QwQ モデルでは無効です。
            enable_thinking: true,
            tools,
            stream: true,
            parallel_tool_calls: true
        });

        for await (const chunk of stream) {
            if (!chunk.choices?.length) {
                console.log("\n" + "=".repeat(20) + "Usage" + "=".repeat(20));
                console.log(chunk.usage);
                continue;
            }

            const delta = chunk.choices[0]?.delta;
            if (!delta) continue;

            // 思考プロセスを処理
            if (delta.reasoning_content) {
                reasoningContent += delta.reasoning_content;
                process.stdout.write(delta.reasoning_content);
            }
            // 応答内容を処理
            else {
                if (!isAnswering) {
                    isAnswering = true;
                    console.log("\n" + "=".repeat(20) + "Reply Content" + "=".repeat(20));
                }
                if (delta.content) {
                    answerContent += delta.content;
                    process.stdout.write(delta.content);
                }
                // ツール呼び出しを処理
                if (delta.tool_calls) {
                    for (const toolCall of delta.tool_calls) {
                        const index = toolCall.index;
                        
                        // 配列の長さが十分であることを確認
                        while (toolInfo.length <= index) {
                            toolInfo.push({});
                        }
                        
                        // ツール ID を更新
                        if (toolCall.id) {
                            toolInfo[index].id = (toolInfo[index].id || "") + toolCall.id;
                        }
                        
                        // 関数名を更新
                        if (toolCall.function?.name) {
                            toolInfo[index].name = (toolInfo[index].name || "") + toolCall.function.name;
                        }
                        
                        // パラメーターを更新
                        if (toolCall.function?.arguments) {
                            toolInfo[index].arguments = (toolInfo[index].arguments || "") + toolCall.function.arguments;
                        }
                    }
                }
            }
        }

        console.log("\n" + "=".repeat(19) + "Tool Call Information" + "=".repeat(19));
        console.log(toolInfo.length ? toolInfo : "No tool calls");

    } catch (error) {
        console.error("An error occurred:", error);
    }
}

main(); 

返された結果

「四大直轄市の天気」と入力すると、次の結果が返されます。

Please enter your question: Weather in the four municipalities
====================Thinking Process====================
Okay, the user is asking about the weather in the four municipalities. First, I need to clarify which four municipalities in China are being referred to. Beijing, Shanghai, Tianjin, and Chongqing, right? Next, I need to call the weather query function for each city.

However, the user's question may require me to get the weather conditions for these four cities separately. Each city requires a call to the get_current_weather function, with its respective city name as the parameter. I need to make sure the parameters are correct, such as the full names of the municipalities, for example, "Beijing Municipality", "Shanghai Municipality", "Tianjin Municipality", and "Chongqing Municipality".

Then, I need to call the weather API for these four cities in sequence. Each call requires a separate tool_call. The user probably wants the current weather information for each city, so I need to ensure each call is correct. I might need to pay attention to the correct spelling and name of each city to avoid errors. For example, Chongqing is sometimes abbreviated, so the full name should be used in the parameter.

Now, I need to generate four tool_calls, one for each municipality. I will check if each parameter is correct and then arrange them in order. This way, the user will get the weather data for all four municipalities.
====================Reply Content====================

===================Tool Call Information===================
[
  {
    id: 'call_21dc802e717f491298d1b2',
    name: 'get_current_weather',
    arguments: '{"location": "Beijing"}'
  },
  {
    id: 'call_2cd3be1d2f694c4eafd4e5',
    name: 'get_current_weather',
    arguments: '{"location": "Shanghai"}'
  },
  {
    id: 'call_48cf3f78e02940bd9085e4',
    name: 'get_current_weather',
    arguments: '{"location": "Tianjin"}'
  },
  {
    id: 'call_e230a2b4c64f4e658d223e',
    name: 'get_current_weather',
    arguments: '{"location": "Chongqing"}'
  }
]

サンプルコード

curl -X POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
    "model": "qwen-plus",
    "messages": [
        {
            "role": "user", 
            "content": "What is the weather like in Hangzhou?"
        }
    ],
    "tools": [
    {
        "type": "function",
        "function": {
            "name": "get_current_time",
            "description": "This is useful when you want to know the current time.",
            "parameters": {}
        }
    },
    {
        "type": "function",
        "function": {
            "name": "get_current_weather",
            "description": "This is useful when you want to query the weather in a specific city.",
            "parameters": {
                "type": "object",
                "properties": {
                    "location":{
                        "type": "string",
                        "description": "A city or district, such as Beijing, Hangzhou, or Yuhang District."
                    }
                },
                "required": ["location"]
            }
        }
    }
  ],
  "enable_thinking": true,
  "stream": true
}'

サンプルコード

import dashscope
dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1/"
tools = [
    # ツール 1：現在時刻の取得
    {
        "type": "function",
        "function": {
            "name": "get_current_time",
            "description": "This is useful when you want to know the current time.",
            "parameters": {}  # 現在時刻の取得には入力パラメーターが不要なため、parameters は空の辞書です。
        }
    },  
    # ツール 2：指定された都市の天気の取得
    {
        "type": "function",
        "function": {
            "name": "get_current_weather",
            "description": "This is useful when you want to query the weather in a specific city.",
            "parameters": {  
                "type": "object",
                "properties": {
                    # 天気照会には location が必要なため、パラメーターは location に設定されます。
                    "location": {
                        "type": "string",
                        "description": "A city or district, such as Beijing, Hangzhou, or Yuhang District."
                    }
                },
                "required": ["location"]
            }
        }
    }
]

# 質問を定義
messages = [{"role": "user", "content": input("Please enter your question: ")}]

# Qwen3-VL のメッセージ例
# messages = [
# {
#     "role": "user",
#     "content": [
#     {"image": "https://img.alicdn.com/imgextra/i2/O1CN01FbTJon1ErXVGMRdsN_!!6000000000405-0-tps-1024-683.jpg"},
#     {"text": "Weather at the image location?"}]
# }]

# マルチモーダルモデルを使用する場合は、Generation を MultiModalConversation インターフェイスに置き換えてください。
completion = dashscope.Generation.call(
    # この例では qwen-plus を使用しています。他のディープシンキングモデルに置き換えることができます。
    model="qwen-plus", 
    messages=messages,
    enable_thinking=True,
    tools=tools,
    parallel_tool_calls=True,
    stream=True,
    incremental_output=True,
    result_format="message"
)

reasoning_content = ""
answer_content = ""
tool_info = []
is_answering = False
print("="*20+"Thinking Process"+"="*20)

for chunk in completion:
    if chunk.status_code == 200:
        msg = chunk.output.choices[0].message
        
        # 思考プロセスを処理
        if 'reasoning_content' in msg and msg.reasoning_content:
            reasoning_content += msg.reasoning_content
            print(msg.reasoning_content, end="", flush=True)
        
        # 応答内容を処理
        if 'content' in msg and msg.content:
            if not is_answering:
                is_answering = True
                print("\n"+"="*20+"Reply Content"+"="*20)
            answer_content += msg.content
            print(msg.content, end="", flush=True)
        
        # ツール呼び出しを処理
        if 'tool_calls' in msg and msg.tool_calls:
            for tool_call in msg.tool_calls:
                index = tool_call['index']
                
                while len(tool_info) <= index:
                    tool_info.append({'id': '', 'name': '', 'arguments': ''})  # すべてのフィールドを初期化
                
                # ツール ID を増分更新
                if 'id' in tool_call:
                    tool_info[index]['id'] += tool_call.get('id', '')
                
                # 関数情報を増分更新
                if 'function' in tool_call:
                    func = tool_call['function']
                    # 関数名を増分更新
                    if 'name' in func:
                        tool_info[index]['name'] += func.get('name', '')
                    # パラメーターを増分更新
                    if 'arguments' in func:
                        tool_info[index]['arguments'] += func.get('arguments', '')

print(f"\n"+"="*19+"Tool Call Information"+"="*19)
if not tool_info:
    print("No tool calls")
else:
    print(tool_info)

返された結果

「四大直轄市の天気」と入力すると、次の結果が返されます。

Please enter your question: Weather in the four municipalities
====================Thinking Process====================
Okay, the user is asking about the weather in the four municipalities. First, I need to confirm which four municipalities in China are being referred to. Beijing, Shanghai, Tianjin, and Chongqing, right? Next, the user needs the weather conditions for each city, so I need to call the weather query function.

However, a problem arises: the user did not specify the city names, only "the four municipalities". I might need to clarify the name of each municipality and then query them separately. For example, Beijing, Shanghai, Tianjin, and Chongqing. I need to make sure each city is correct.

Then, I need to check the available tools. The user has provided the `get_current_weather` function with a `location` parameter. Therefore, I need to call this function for each municipality, passing the corresponding city name as the parameter. For example, the first call's location is Beijing, the second is Shanghai, the third is Tianjin, and the fourth is Chongqing.

However, I might need to be careful. For a municipality like Chongqing, a more specific district might sometimes be needed, but the user probably only needs the city-level weather. So, using the municipality name directly should be fine. Next, I need to generate four separate function calls, one for each municipality. This way, the user will get the weather conditions for all four cities.

Finally, I will ensure that the parameters for each call are correct and that none are missed. This will provide a complete answer to the user's question.
===================Tool Call Information===================
[{'id': 'call_2f774ed97b0e4b24ab10ec', 'name': 'get_current_weather', 'arguments': '{"location": "Beijing"}'}, {'id': 'call_dc3b05b88baa48c58bc33a', 'name': 'get_current_weather', 'arguments': '{"location": "Shanghai"}}'}, {'id': 'call_249b2de2f73340cdb46cbc', 'name': 'get_current_weather', 'arguments': '{"location": "Tianjin"}'}, {'id': 'call_833333634fda49d1b39e87', 'name': 'get_current_weather', 'arguments': '{"location": "Chongqing"}}'}]

サンプルコード

// dashscope SDK バージョン >= 2.19.4
import java.util.Arrays;

import com.alibaba.dashscope.exception.UploadFileException;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.aigc.generation.Generation;
import com.alibaba.dashscope.aigc.generation.GenerationParam;
import com.alibaba.dashscope.aigc.generation.GenerationResult;
import com.alibaba.dashscope.common.Message;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.InputRequiredException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.utils.Constants;
import com.alibaba.dashscope.utils.JsonUtils;
import com.alibaba.dashscope.tools.ToolFunction;
import com.alibaba.dashscope.tools.FunctionDefinition;
import io.reactivex.Flowable;
import com.fasterxml.jackson.databind.node.ObjectNode;
import java.lang.System;
import com.github.victools.jsonschema.generator.Option;
import com.github.victools.jsonschema.generator.OptionPreset;
import com.github.victools.jsonschema.generator.SchemaGenerator;
import com.github.victools.jsonschema.generator.SchemaGeneratorConfig;
import com.github.victools.jsonschema.generator.SchemaGeneratorConfigBuilder;
import com.github.victools.jsonschema.generator.SchemaVersion;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
import java.util.Collections;

public class Main {
    private static final Logger logger = LoggerFactory.getLogger(Main.class);
    private static ObjectNode jsonSchemaWeather;
    private static ObjectNode jsonSchemaTime;
    
    static {Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";}

    static class TimeTool {
        public String call() {
            LocalDateTime now = LocalDateTime.now();
            DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");
            return "Current time: " + now.format(formatter) + ".";
        }
    }

    static class WeatherTool {
        private String location;

        public WeatherTool(String location) {
            this.location = location;
        }

        public String call() {
            return this.location + " is sunny today";
        }
    }

    static {
        SchemaGeneratorConfigBuilder configBuilder = new SchemaGeneratorConfigBuilder(
                SchemaVersion.DRAFT_2020_12, OptionPreset.PLAIN_JSON);
        SchemaGeneratorConfig config = configBuilder
                .with(Option.EXTRA_OPEN_API_FORMAT_VALUES)
                .without(Option.FLATTENED_ENUMS_FROM_TOSTRING)
                .build();
        SchemaGenerator generator = new SchemaGenerator(config);
        jsonSchemaWeather = generator.generateSchema(WeatherTool.class);
        jsonSchemaTime = generator.generateSchema(TimeTool.class);
    }
    private static void handleGenerationResult(GenerationResult message) {
        System.out.println(JsonUtils.toJson(message));
    }
    
    // テキスト生成モデル用のツール呼び出しメソッドを作成
    public static void streamCallWithMessage(Generation gen, Message userMsg)
            throws NoApiKeyException, ApiException, InputRequiredException {
        GenerationParam param = buildGenerationParam(userMsg);
        Flowable<GenerationResult> result = gen.streamCall(param);
        result.blockingForEach(message -> handleGenerationResult(message));
    }
    // ツール呼び出しをサポートするテキスト生成モデルのパラメーターを構築
    private static GenerationParam buildGenerationParam(Message userMsg) {
        FunctionDefinition fdWeather = buildFunctionDefinition(
                "get_current_weather", "Get the weather for a specified region", jsonSchemaWeather);
        FunctionDefinition fdTime = buildFunctionDefinition(
                "get_current_time", "Get the current time", jsonSchemaTime);

        return GenerationParam.builder()
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .model("qwen-plus")
                .enableThinking(true)
                .messages(Arrays.asList(userMsg))
                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                .incrementalOutput(true)
                .tools(Arrays.asList(
                        ToolFunction.builder().function(fdWeather).build(),
                        ToolFunction.builder().function(fdTime).build()))
                .build();
    }

    // マルチモーダルモデル用のツール呼び出しメソッドを作成
    public static void streamCallWithMultiModalMessage(MultiModalConversation conv, MultiModalMessage userMsg)
            throws NoApiKeyException, ApiException, UploadFileException {
        MultiModalConversationParam param = buildMultiModalConversationParam(userMsg);
        Flowable<MultiModalConversationResult> result = conv.streamCall(param);
        result.blockingForEach(message -> System.out.println(JsonUtils.toJson(message)));
    }

    // ツール呼び出しをサポートするマルチモーダルモデルのパラメーターを構築
    private static MultiModalConversationParam buildMultiModalConversationParam(MultiModalMessage userMsg) {
        FunctionDefinition fdWeather = buildFunctionDefinition(
                "get_current_weather", "Get the weather for a specified region", jsonSchemaWeather);
        FunctionDefinition fdTime = buildFunctionDefinition(
                "get_current_time", "Get the current time", jsonSchemaTime);

        return MultiModalConversationParam.builder()
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .model("qwen3-vl-plus")  // マルチモーダルモデル Qwen3-vl を使用
                .enableThinking(true)
                .messages(Arrays.asList(userMsg))
                .tools(Arrays.asList(  // ツールリストを設定
                        ToolFunction.builder().function(fdWeather).build(),
                        ToolFunction.builder().function(fdTime).build()))
                .build();
    }

    private static FunctionDefinition buildFunctionDefinition(
            String name, String description, ObjectNode schema) {
        return FunctionDefinition.builder()
                .name(name)
                .description(description)
                .parameters(JsonUtils.parseString(schema.toString()).getAsJsonObject())
                .build();
    }

    public static void main(String[] args) {
        try {
            Generation gen = new Generation();
            Message userMsg = Message.builder()
                    .role(Role.USER.getValue())
                    .content("Please tell me the weather in Hangzhou")
                    .build();
            try {
                streamCallWithMessage(gen, userMsg);
            } catch (InputRequiredException e) {
                throw new RuntimeException(e);
            }
//             マルチモーダルモデルでツール呼び出しを使用する場合は、次の行のコメントを解除してください。
//            MultiModalConversation conv = new MultiModalConversation();
//            MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
//                    .content(Arrays.asList(Collections.singletonMap("image", "https://img.alicdn.com/imgextra/i2/O1CN01FbTJon1ErXVGMRdsN_!!6000000000405-0-tps-1024-683.jpg"),
//                            Collections.singletonMap("text", "Weather at the location in the image"))).build();
//            try {
//                streamCallWithMultiModalMessage(conv,userMessage);
//            } catch (UploadFileException e) {
//                throw new RuntimeException(e);
//            }
        } catch (ApiException | NoApiKeyException e) {
            logger.error("An exception occurred: {}", e.getMessage());
        }
        System.exit(0);
    }
}

返された結果

{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":6,"total_tokens":244},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":"Okay, the user wants me"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":12,"total_tokens":250},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" to tell them the weather in Hangzhou. I"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":16,"total_tokens":254},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" need to first determine if"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":22,"total_tokens":260},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" there are any relevant tools available. Looking at the provided"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":28,"total_tokens":266},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" tools, I see there is a get_current"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":34,"total_tokens":272},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":"_weather function with a location parameter"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":38,"total_tokens":276},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":". So I should call"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":43,"total_tokens":281},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" this function with the parameter"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":48,"total_tokens":286},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" set to Hangzhou. No"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":52,"total_tokens":290},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" other tools are needed because"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":56,"total_tokens":294},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" the user only asked"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":60,"total_tokens":298},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" about the weather. Next, I will construct"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":64,"total_tokens":302},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" the tool_call, filling in"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":68,"total_tokens":306},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" the name and parameters"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":73,"total_tokens":311},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":". I will make sure the parameter is a"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":78,"total_tokens":316},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" JSON object and location is a"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":82,"total_tokens":320},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":" string. After checking for errors"}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":88,"total_tokens":326},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":", I will return."}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":106,"total_tokens":344},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"","reasoning_content":"","tool_calls":[{"type":"function","id":"call_ecc41296dccc47baa01567","function":{"name":"get_current_weather","arguments":"{\"location\": \"Hangzhou"}}]}}]}}
{"requestId":"4edb81cd-4647-9d5d-88f9-a4f30bc6d8dd","usage":{"input_tokens":238,"output_tokens":108,"total_tokens":346},"output":{"choices":[{"finish_reason":"tool_calls","message":{"role":"assistant","content":"","reasoning_content":"","tool_calls":[{"type":"function","id":"","function":{"arguments":"\"}"}}]}}]}}

サンプルコード

# ======= 重要事項 =======
# マルチモーダルモデルを使用する場合は、message パラメーターを変更し、URL を https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation に置き換えてください。
# シンガポールリージョンと中国 (北京) リージョンの API キーは異なります。API キーを取得するには、https://www.alibabacloud.com/help/ja/model-studio/get-api-key をご参照ください。
# 北京リージョンのモデルを使用する場合は、URL を https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation に置き換えてください。
# === 実行前にこのコメントを削除してください ===

curl -X POST "https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation" \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-H "X-DashScope-SSE: enable" \
-d '{
    "model": "qwen-plus",
    "input":{
        "messages":[      
            {
                "role": "user",
                "content": "Hangzhou weather"
            }
        ]
    },
    "parameters": {
        "enable_thinking": true,
        "incremental_output": true,
        "result_format": "message",
        "tools": [{
            "type": "function",
            "function": {
                "name": "get_current_time",
                "description": "This is useful when you want to know the current time.",
                "parameters": {}
            }
        },{
            "type": "function",
            "function": {
                "name": "get_current_weather",
                "description": "This is useful when you want to query the weather in a specific city.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {
                            "type": "string",
                            "description": "A city or district, such as Beijing, Hangzhou, or Yuhang District."
                        }
                    },
                    "required": ["location"]
                }
            }
        }]
    }
}'