Alibaba Cloud Model Studio:Coding capabilities (Qwen-Coder)

Request example

import os
from openai import OpenAI

client = OpenAI(
    # API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
    # If you have not configured an environment variable, replace the next line with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
    # This example uses qwen3-coder-plus. You can replace it with another model name as needed.
    model="qwen3-coder-plus", 
    messages=[
        {'role': 'system', 'content': 'You are a helpful assistant.'},
        {'role': 'user', 'content': 'Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks.'}],
)
print(completion.choices[0].message.content)

Response

def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes

Request example

import OpenAI from "openai";

const client = new OpenAI(
    {
        // API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
        // If you have not configured an environment variable, replace the next line with your Model Studio API key: apiKey: "sk-xxx",
        apiKey: process.env.DASHSCOPE_API_KEY,
        // The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/compatible-mode/v1
        baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
    }
);

async function main() {
    const completion = await client.chat.completions.create({
        model: "qwen3-coder-plus",  //This example uses qwen3-coder-plus. You can replace it with another model name as needed.
        messages: [
            { role: "system", content: "You are a helpful assistant." },
            { role: "user", content: "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks." }
        ],
    });
    console.log(completion.choices[0].message.content);
}

main();

Response

def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes

Request example

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": "qwen3-coder-plus",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user", 
            "content": "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks."
        }
    ]
}'

Response

{
    "choices": [
        {
            "message": {
                "content": "def find_prime_numbers(n):\n    if n <= 2:\n        return []\n    \n    primes = []\n    \n    for num in range(2, n):\n        is_prime = True\n        for i in range(2, int(num ** 0.5) + 1):\n            if num % i == 0:\n                is_prime = False\n                break\n        if is_prime:\n            primes.append(num)\n    \n    return primes",
                "role": "assistant"
            },
            "finish_reason": "stop",
            "index": 0,
            "logprobs": null
        }
    ],
    "object": "chat.completion",
    "usage": {
        "prompt_tokens": 96,
        "completion_tokens": 90,
        "total_tokens": 186,
        "prompt_tokens_details": {
            "cached_tokens": 0
        }
    },
    "created": 1761615592,
    "system_fingerprint": null,
    "model": "qwen3-coder-plus",
    "id": "chatcmpl-3de690bd-ae7f-461d-8eb6-d65b0577e803"
}

Request example

import dashscope
import os

# The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {
        "role": "system",
        "content": "You are a helpful assistant."
    },
    {
        "role": "user",
        "content": "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks."
    }
]

response = dashscope.Generation.call(
    # API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
    # If you have not configured an environment variable, replace the next line with your Model Studio API key: api_key = "sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # This example uses qwen3-coder-plus. You can replace it with another model name as needed.
    model="qwen3-coder-plus",
    messages=messages,
    result_format="message"
)

if response.status_code == 200:
    print(response.output.choices[0].message.content)
else:
    print(f"HTTP status code: {response.status_code}")
    print(f"Error code: {response.code}")
    print(f"Error message: {response.message}")

Result

def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes

Request example

import java.util.Arrays;
import com.alibaba.dashscope.aigc.generation.Generation;
import com.alibaba.dashscope.aigc.generation.GenerationResult;
import com.alibaba.dashscope.aigc.generation.GenerationParam;
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.protocol.Protocol;


public class Main {
    public static GenerationResult callWithMessage()
            throws NoApiKeyException, ApiException, InputRequiredException {
        String apiKey = System.getenv("DASHSCOPE_API_KEY");
        // The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/api/v1
        Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-intl.aliyuncs.com/api/v1");
        Message sysMsg = Message.builder()
                .role(Role.SYSTEM.getValue())
                .content("You are a helpful assistant.").build();
        Message userMsg = Message.builder()
                .role(Role.USER.getValue())
                .content("Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks.").build();
        // This example uses qwen3-coder-plus. You can replace it with another model name as needed.
        GenerationParam param = GenerationParam.builder()
                .apiKey(apiKey)
                .model("qwen3-coder-plus")
                .messages(Arrays.asList(sysMsg, userMsg))
                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                .build();
        return gen.call(param);
    }
    public static void main(String[] args){
        try {
            GenerationResult result = callWithMessage();
            System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent());
        } catch (ApiException | NoApiKeyException | InputRequiredException e) {
            System.err.println("Request exception: " + e.getMessage());
            e.printStackTrace();
        }
    }
}

Result

def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes

Request example

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" \
-d '{
    "model": "qwen3-coder-plus",
    "input":{
        "messages":[      
            {
                "role": "system",
                "content": "You are a helpful assistant."
            },
            {
                "role": "user",
                "content": "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks."
            }
        ]
    },
    "parameters": {
        "result_format": "message"
    }
}'

Response

{
    "output": {
        "choices": [
            {
                "message": {
                    "content": "def find_prime_numbers(n):\n    if n <= 2:\n        return []\n    \n    primes = []\n    \n    for num in range(2, n):\n        is_prime = True\n        for i in range(2, int(num ** 0.5) + 1):\n            if num % i == 0:\n                is_prime = False\n                break\n        if is_prime:\n            primes.append(num)\n    \n    return primes",
                    "role": "assistant"
                },
                "finish_reason": "stop"
            }
        ]
    },
    "usage": {
        "total_tokens": 186,
        "output_tokens": 90,
        "input_tokens": 96,
        "prompt_tokens_details": {
            "cached_tokens": 0
        }
    },
    "request_id": "b1b8d1f8-0d26-4651-a466-66eefa0e7c51"
}

Request example

import os
from openai import OpenAI

client = OpenAI(
    # API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
    # If you have not configured an environment variable, replace the next line with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen3-coder-plus",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks."}
    ],
    stream=True,
    # Get the token usage for this request from the last chunk
    stream_options={"include_usage": True}
)

content_parts = []
print("="*20+"Response"+"="*20)

for chunk in completion:
    # The last chunk does not contain choices, but it contains usage information.
    if chunk.choices:
        # delta.content might be None. Use 'or ""' to avoid errors during concatenation.
        content = chunk.choices[0].delta.content or ""
        print(content, end="", flush=True)
        content_parts.append(content)
    elif chunk.usage:
        print("\n"+"="*20+"Token Usage"+"="*20)
        print(f"Input Tokens: {chunk.usage.prompt_tokens}")
        print(f"Output Tokens: {chunk.usage.completion_tokens}")
        print(f"Total Tokens: {chunk.usage.total_tokens}")

full_response = "".join(content_parts)
# To get the full response string, uncomment the next line.
# print(f"\n--- Full Response ---\n{full_response}")

Response

====================Response====================
def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes
====================Token Usage====================
Input Tokens: 66
Output Tokens: 89
Total Tokens: 155

Request example

import OpenAI from "openai";

const client = new OpenAI(
    {
        // API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
        // If you have not configured an environment variable, replace the next line with your Model Studio API key: apiKey: "sk-xxx",
        apiKey: process.env.DASHSCOPE_API_KEY,
        // The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/compatible-mode/v1
        baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
    }
);

async function main() {
    const stream = await client.chat.completions.create({
        model: "qwen3-coder-plus",
        messages: [
            { role: "system", content: "You are a helpful assistant." },
            { role: "user", content: "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks." },
        ],
        stream: true,
        // Get the token usage for this request from the last chunk
        stream_options: { include_usage: true },
    });

    const contentParts = [];
    console.log("=".repeat(20) + "Response" + "=".repeat(20));
    
    for await (const chunk of stream) {
        // The last chunk does not contain choices, but it contains usage information.
        if (chunk.choices && chunk.choices.length > 0) {
            const content = chunk.choices[0]?.delta?.content || "";
            process.stdout.write(content);
            contentParts.push(content);
        } else if (chunk.usage) {
            // The request is complete. Print the token usage.
            console.log("\n"+"=".repeat(20) + "Token Usage" + "=".repeat(20));
            console.log(`Input Tokens: ${chunk.usage.prompt_tokens}`);
            console.log(`Output Tokens: ${chunk.usage.completion_tokens}`);
            console.log(`Total Tokens: ${chunk.usage.total_tokens}`);
        }
    }
    
    const fullResponse = contentParts.join("");
    // To get the full response string, uncomment the next line.
    // console.log(`\n--- Full Response ---\n${fullResponse}`);
}

main();

Response

====================Response====================
def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes
====================Token Usage====================
Input Tokens: 66
Output Tokens: 89
Total Tokens: 155

Request example

Response

data: {"choices":[{"delta":{"content":"","role":"assistant"},"index":0,"logprobs":null,"finish_reason":null}],"object":"chat.completion.chunk","usage":null,"created":1763085409,"system_fingerprint":null,"model":"qwen3-coder-plus","id":"chatcmpl-61f94113-f29b-4f7d-9730-551749d40ef4"}

data: {"choices":[{"finish_reason":null,"logprobs":null,"delta":{"content":"def"},"index":0}],"object":"chat.completion.chunk","usage":null,"created":1763085409,"system_fingerprint":null,"model":"qwen3-coder-plus","id":"chatcmpl-61f94113-f29b-4f7d-9730-551749d40ef4"}

data: {"choices":[{"delta":{"content":" find_prime_numbers(n"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1763085409,"system_fingerprint":null,"model":"qwen3-coder-plus","id":"chatcmpl-61f94113-f29b-4f7d-9730-551749d40ef4"}

......

data: {"choices":[{"delta":{"content":" primes"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1763085409,"system_fingerprint":null,"model":"qwen3-coder-plus","id":"chatcmpl-61f94113-f29b-4f7d-9730-551749d40ef4"}

data: {"choices":[{"finish_reason":"stop","delta":{"content":""},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1763085409,"system_fingerprint":null,"model":"qwen3-coder-plus","id":"chatcmpl-61f94113-f29b-4f7d-9730-551749d40ef4"}

data: {"choices":[],"object":"chat.completion.chunk","usage":{"prompt_tokens":66,"completion_tokens":89,"total_tokens":155,"prompt_tokens_details":{"cached_tokens":0}},"created":1763085409,"system_fingerprint":null,"model":"qwen3-coder-plus","id":"chatcmpl-61f94113-f29b-4f7d-9730-551749d40ef4"}

data: [DONE]

Request example

import os
from http import HTTPStatus
import dashscope
from dashscope import Generation

# The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks."},
]

responses = Generation.call(
    # API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
    # If you have not configured an environment variable, replace the next line with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model="qwen3-coder-plus",
    messages=messages,
    result_format="message",
    stream=True,
    # Incremental output. Each data block contains only the newly generated content.
    incremental_output=True,
)

content_parts = []
print("="*20+"Response"+"="*20+"\n", end="", flush=True)

for resp in responses:
    if resp.status_code == HTTPStatus.OK:
        content = resp.output.choices[0].message.content
        print(content, end="", flush=True)
        content_parts.append(content)

        if resp.output.choices[0].finish_reason == "stop":
            print("\n"+"=" * 20 + "Token Usage" + "=" * 20)
            print(f"Input Tokens: {resp.usage.input_tokens}")
            print(f"Output Tokens: {resp.usage.output_tokens}")
            print(f"Total Tokens: {resp.usage.total_tokens}")
    else:
        print(f"HTTP status code: {resp.status_code}")
        print(f"Error code: {resp.code}")
        print(f"Error message: {resp.message}")
full_response = "".join(content_parts)
# To get the full response string, uncomment the next line.
# print(f"\n--- Full Response ---\n{full_response}")

Response

====================Response====================
def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes
====================Token Usage====================
Input Tokens: 66
Output Tokens: 89
Total Tokens: 155

Request example

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 io.reactivex.Flowable;
import io.reactivex.schedulers.Schedulers;
import java.util.Arrays;
import java.util.concurrent.CountDownLatch;
import com.alibaba.dashscope.protocol.Protocol;

public class Main {
    public static void main(String[] args) {
        String apiKey = System.getenv("DASHSCOPE_API_KEY");

        // The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/api/v1
        Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-intl.aliyuncs.com/api/v1");
        CountDownLatch latch = new CountDownLatch(1);

        GenerationParam param = GenerationParam.builder()
                .apiKey(apiKey)
                .model("qwen3-coder-plus")
                .messages(Arrays.asList(
                        Message.builder()
                                .role(Role.USER.getValue())
                                .content("Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks.")
                                .build()
                ))
                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                .incrementalOutput(true) // Enable incremental output for streaming, where each data block contains only the newly generated content.
                .build();
        try {
            Flowable<GenerationResult> result = gen.streamCall(param);
            StringBuilder fullContent = new StringBuilder();
            System.out.println("====================Response====================");
            result
                    .subscribeOn(Schedulers.io()) // Execute the request on an I/O thread.
                    .observeOn(Schedulers.computation()) // Process the response on a computation thread.
                    .subscribe(
                            // onNext: Process each response chunk.
                            message -> {
                                String content = message.getOutput().getChoices().get(0).getMessage().getContent();
                                String finishReason = message.getOutput().getChoices().get(0).getFinishReason();
                                // Output the content.
                                System.out.print(content);
                                fullContent.append(content);
                                // When finishReason is not null, it indicates the last chunk. Output the usage information.
                                if (finishReason != null && !"null".equals(finishReason)) {
                                    System.out.println("\n====================Token Usage====================");
                                    System.out.println("Input Tokens: " + message.getUsage().getInputTokens());
                                    System.out.println("Output Tokens: " + message.getUsage().getOutputTokens());
                                    System.out.println("Total Tokens: " + message.getUsage().getTotalTokens());
                                }
                                System.out.flush(); // Flush the output immediately.
                            },
                            // onError: Handle errors.
                            error -> {
                                System.err.println("\nRequest failed: " + error.getMessage());
                                latch.countDown();
                            },
                            // onComplete: Completion callback.
                            () -> {
                                System.out.println(); // Add a new line.
                                // To get the full response string, uncomment the next line.
                                // System.out.println("Full response: " + fullContent.toString());
                                latch.countDown();
                            }
                    );
            // Wait for the asynchronous task to complete in the main thread.
            latch.await();
        } catch (Exception e) {
            System.err.println("Request exception: " + e.getMessage());
            e.printStackTrace();
        }
    }
}

Response

====================Response====================
def find_prime_numbers(n):
    if n <= 2:
        return []
    
    primes = []
    for num in range(2, n):
        is_prime = True
        for i in range(2, int(num ** 0.5) + 1):
            if num % i == 0:
                is_prime = False
                break
        if is_prime:
            primes.append(num)
    
    return primes
====================Token Usage====================
Input Tokens: 66
Output Tokens: 89
Total Tokens: 155

Request example

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": "qwen3-coder-plus",
    "input":{
        "messages":[      
            {
                "role": "system",
                "content": "You are a helpful assistant."
            },
            {
                "role": "user",
                "content": "Write a Python function named find_prime_numbers that accepts an integer n as a parameter and returns a list of all prime numbers less than n. Do not output any content other than the code and do not use Markdown code blocks."
            }
        ]
    },
    "parameters": {
        "result_format": "message",
        "incremental_output":true
    }
}'

Return value

id:1
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"def","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":67,"output_tokens":1,"input_tokens":66,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fadfc21b-4411-40d5-b143-8c3573284c42"}

id:2
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":" find_prime_numbers(n","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":71,"output_tokens":5,"input_tokens":66,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fadfc21b-4411-40d5-b143-8c3573284c42"}

id:3
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"):\n    if n","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":75,"output_tokens":9,"input_tokens":66,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fadfc21b-4411-40d5-b143-8c3573284c42"}

...

id:26
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":" primes","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":155,"output_tokens":89,"input_tokens":66,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fadfc21b-4411-40d5-b143-8c3573284c42"}

id:27
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"","role":"assistant"},"finish_reason":"stop"}]},"usage":{"total_tokens":155,"output_tokens":89,"input_tokens":66,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fadfc21b-4411-40d5-b143-8c3573284c42"}

Request example

import os
import json
from openai import OpenAI

client = OpenAI(
    # API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
    # If you have not configured an environment variable, replace the next line with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

tools = [
    {
        "type": "function",
        "function": {
            "name": "write_file",
            "description": "Writes content to the specified file. If the file does not exist, it is created.",
            "parameters": {
                "type": "object",
                "properties": {
                    "path": {
                        "type": "string",
                        "description": "The relative or absolute path of the target file."
                    },
                    "content": {
                        "type": "string",
                        "description": "The string content to write to the file."
                    }
                },
                "required": ["path", "content"]
            }
        }
    }
]

# Tool function implementation
def write_file(path: str, content: str) -> str:
    """Write file content"""
    try:
        # Ensure the directory exists
        os.makedirs(os.path.dirname(path),
                    exist_ok=True) if os.path.dirname(path) else None
        with open(path, 'w', encoding='utf-8') as f:
            f.write(content)
        return f"Success: The file '{path}' has been written."
    except Exception as e:
        return f"Error: An exception occurred while writing the file - {str(e)}"


messages = [{"role": "user", "content": "Write a Python script for quick sort and name it quick_sort.py."}]

completion = client.chat.completions.create(
    model="qwen3-coder-plus",
    messages=messages,
    tools=tools
)

assistant_output = completion.choices[0].message
if assistant_output.content is None:
    assistant_output.content = ""
messages.append(assistant_output)

# If no tool call is needed, print the content directly.
if assistant_output.tool_calls is None:
    print(f"No tool call needed, responding directly: {assistant_output.content}")
else:
    # Enter the tool calling loop
    while assistant_output.tool_calls is not None:
        for tool_call in assistant_output.tool_calls:
            tool_call_id = tool_call.id
            func_name = tool_call.function.name
            arguments = json.loads(tool_call.function.arguments)
            print(f"Calling tool [{func_name}] with arguments: {arguments}")
            # Execute the tool
            tool_result = write_file(**arguments)
            # Construct the tool return message
            tool_message = {
                "role": "tool",
                "tool_call_id": tool_call_id,
                "content": tool_result,
            }
            print(f"Tool returned: {tool_message['content']}")
            messages.append(tool_message)
        # Call the model again to get a summarized natural language response
        response = client.chat.completions.create(
            model="qwen3-coder-plus",
            messages=messages,
            tools=tools
        )
        assistant_output = response.choices[0].message
        if assistant_output.content is None:
            assistant_output.content = ""
        messages.append(assistant_output)
    print(f"Model's final response: {assistant_output.content}")

Response

Calling tool [write_file] with arguments: {'content': 'def quick_sort(arr):\\n    if len(arr) <= 1:\\n        return arr\\n    pivot = arr[len(arr) // 2]\\n    left = [x for x in arr if x < pivot]\\n    middle = [x for x in arr if x == pivot]\\n    right = [x for x in arr if x > pivot]\\n    return quick_sort(left) + middle + quick_sort(right)\\n\\nif __name__ == \\"__main__\\":\\n    example_list = [3, 6, 8, 10, 1, 2, 1]\\n    print(\\"Original list:\\", example_list)\\n    sorted_list = quick_sort(example_list)\\n    print(\\"Sorted list:\\", sorted_list)', 'path': 'quick_sort.py'}
Tool returned: Success: The file 'quick_sort.py' has been written.
Model's final response: Okay, I have created the file named `quick_sort.py` for you, which contains the Python implementation of quick sort. You can run this file to see the example output. Let me know if you need any further modifications or explanations!

Request example

import OpenAI from "openai";
import fs from "fs/promises";
import path from "path";

const client = new OpenAI({
    // API keys for the Singapore and Beijing regions are different. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
    // If you have not configured an environment variable, replace the next line with your Model Studio API key: apiKey: "sk-xxx",
    apiKey: process.env.DASHSCOPE_API_KEY,
    // The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/compatible-mode/v1
    baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
});

const tools = [
    {
        "type": "function",
        "function": {
            "name": "write_file",
            "description": "Writes content to the specified file. If the file does not exist, it is created.",
            "parameters": {
                "type": "object",
                "properties": {
                    "path": {
                        "type": "string",
                        "description": "The relative or absolute path of the target file."
                    },
                    "content": {
                        "type": "string",
                        "description": "The string content to write to the file."
                    }
                },
                "required": ["path", "content"]
            }
        }
    }
];

// Tool function implementation
async function write_file(filePath, content) {
    try {
        // For security reasons, the file writing feature is disabled by default. To use it, uncomment the code and ensure the path is secure.
        // const dir = path.dirname(filePath);
        // if (dir) {
        //     await fs.mkdir(dir, { recursive: true });
        // }
        // await fs.writeFile(filePath, content, "utf-8");
        return `Success: The file '${filePath}' has been written.`;
    } catch (error) {
        return `Error: An exception occurred while writing the file - ${error.message}`;
    }
}

const messages = [{"role": "user", "content": "Write a Python script for quick sort and name it quick_sort.py."}];

async function main() {
    const completion = await client.chat.completions.create({
        model: "qwen3-coder-plus",
        messages: messages,
        tools: tools
    });

    let assistant_output = completion.choices[0].message;
    // Ensure content is not null
    if (!assistant_output.content) assistant_output.content = "";
    messages.push(assistant_output);

    // If no tool call is needed, print the content directly.
    if (!assistant_output.tool_calls) {
        console.log(`No tool call needed, responding directly: ${assistant_output.content}`);
    } else {
        // Enter the tool calling loop
        while (assistant_output.tool_calls) {
            for (const tool_call of assistant_output.tool_calls) {
                const tool_call_id = tool_call.id;
                const func_name = tool_call.function.name;
                const args = JSON.parse(tool_call.function.arguments);
                console.log(`Calling tool [${func_name}] with arguments:`, args);
                // Execute the tool
                const tool_result = await write_file(args.path, args.content);
                // Construct the tool return message
                const tool_message = {
                    "role": "tool",
                    "tool_call_id": tool_call_id,
                    "content": tool_result
                };
                console.log(`Tool returned: ${tool_message.content}`);
                messages.push(tool_message);
            }
            // Call the model again to get a summarized natural language response
            const response = await client.chat.completions.create({
                model: "qwen3-coder-plus",
                messages: messages,
                tools: tools
            });
            assistant_output = response.choices[0].message;
            if (!assistant_output.content) assistant_output.content = "";
            messages.push(assistant_output);
        }
        console.log(`Model's final response: ${assistant_output.content}`);
    }
}

main();

Response

Calling tool [write_file] with arguments: {
  content: 'def quick_sort(arr):\\n    if len(arr) <= 1:\\n        return arr\\n    pivot = arr[len(arr) // 2]\\n    left = [x for x in arr if x < pivot]\\n    middle = [x for x in arr if x == pivot]\\n    right = [x for x in arr if x > pivot]\\n    return quick_sort(left) + middle + quick_sort(right)\\n\\nif __name__ == \\"__main__\\":\\n    example_list = [3, 6, 8, 10, 1, 2, 1]\\n    print(\\"Original list:\\", example_list)\\n    sorted_list = quick_sort(example_list)\\n    print(\\"Sorted list:\\", sorted_list)',
  path: 'quick_sort.py'
}
Tool returned: Success: The file 'quick_sort.py' has been written.
Model's final response: The `quick_sort.py` file has been successfully created with the Python implementation of quick sort. You can run the file to see the sorting result for the example list. Let me know if you need any further modifications or explanations!

Request example

This example shows the first step of the tool calling process: making a request and obtaining the model's intent to call a tool.

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": "qwen3-coder-plus",
    "messages": [
        {
            "role": "user", 
            "content": "Write a Python script for quick sort and name it quick_sort.py."
        }
    ],
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "write_file",
                "description": "Writes content to the specified file. If the file does not exist, it is created.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "path": {
                            "type": "string",
                            "description": "The relative or absolute path of the target file."
                        },
                        "content": {
                            "type": "string",
                            "description": "The string content to write to the file."
                        }
                    },
                    "required": ["path", "content"]
                }
            }
        }
    ]
}'

Response

{
    "choices": [
        {
            "message": {
                "content": "",
                "role": "assistant",
                "tool_calls": [
                    {
                        "index": 0,
                        "id": "call_0ca7505bb6e44471a40511e5",
                        "type": "function",
                        "function": {
                            "name": "write_file",
                            "arguments": "{\"content\": \"def quick_sort(arr):\\\\n    if len(arr) <= 1:\\\\n        return arr\\\\n    pivot = arr[len(arr) // 2]\\\\n    left = [x for x in arr if x < pivot]\\\\n    middle = [x for x in arr if x == pivot]\\\\n    right = [x for x in arr if x > pivot]\\\\n    return quick_sort(left) + middle + quick_sort(right)\\\\n\\\\nif __name__ == \\\\\\\"__main__\\\\\\\":\\\\n    example_list = [3, 6, 8, 10, 1, 2, 1]\\\\n    print(\\\\\\\"Original list:\\\\\\\", example_list)\\\\n    sorted_list = quick_sort(example_list)\\\\n    print(\\\\\\\"Sorted list:\\\\\\\", sorted_list)\", \"path\": \"quick_sort.py\"}"
                        }
                    }
                ]
            },
            "finish_reason": "tool_calls",
            "index": 0,
            "logprobs": null
        }
    ],
    "object": "chat.completion",
    "usage": {
        "prompt_tokens": 494,
        "completion_tokens": 193,
        "total_tokens": 687,
        "prompt_tokens_details": {
            "cached_tokens": 0
        }
    },
    "created": 1761620025,
    "system_fingerprint": null,
    "model": "qwen3-coder-plus",
    "id": "chatcmpl-20e96159-beea-451f-b3a4-d13b218112b5"
}

Request example

import os
import json
import dashscope

# The following base_url is for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

tools = [
    {
        "type": "function",
        "function": {
            "name": "write_file",
            "description": "Writes content to the specified file. If the file does not exist, it is created.",
            "parameters": {
                "type": "object",
                "properties": {
                    "path": {
                        "type": "string",
                        "description": "The relative or absolute path of the target file."
                    },
                    "content": {
                        "type": "string",
                        "description": "The string content to write to the file."
                    }
                },
                "required": ["path", "content"]
            }
        }
    }
]

# Tool function implementation
def write_file(path: str, content: str) -> str:
    """Write file content"""
    try:
        # For security reasons, the file writing feature is disabled by default. To use it, uncomment the code and ensure the path is secure.
        # os.makedirs(os.path.dirname(path),exist_ok=True) if os.path.dirname(path) else None
        # with open(path, 'w', encoding='utf-8') as f:
        #     f.write(content)
        return f"Success: The file '{path}' has been written."
    except Exception as e:
        return f"Error: An exception occurred while writing the file - {str(e)}"


messages = [{"role": "user", "content": "Write a Python script for quick sort and name it quick_sort.py."}]

response = dashscope.Generation.call(
    # If you have not configured an environment variable, replace the next line with your Model Studio API key: api_key="sk-xxx",
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model='qwen3-coder-plus',
    messages=messages,
    tools=tools,
    result_format='message'
)

if response.status_code == 200:
    assistant_output = response.output.choices[0].message
    messages.append(assistant_output)

    # If no tool call is needed, print the content directly.
    if "tool_calls" not in assistant_output or not assistant_output["tool_calls"]:
        print(f"No tool call needed, responding directly: {assistant_output['content']}")
    else:
        # Enter the tool calling loop
        while "tool_calls" in assistant_output and assistant_output["tool_calls"]:
            for tool_call in assistant_output["tool_calls"]:
                func_name = tool_call["function"]["name"]
                arguments = json.loads(tool_call["function"]["arguments"])
                tool_call_id = tool_call.get("id")
                print(f"Calling tool [{func_name}] with arguments: {arguments}")
                # Execute the tool
                tool_result = write_file(**arguments)
                # Construct the tool return message
                tool_message = {
                    "role": "tool",
                    "content": tool_result,
                    "tool_call_id": tool_call_id
                }
                print(f"Tool returned: {tool_message['content']}")
                messages.append(tool_message)
            # Call the model again to get a summarized natural language response
            response = dashscope.Generation.call(
                api_key=os.getenv('DASHSCOPE_API_KEY'),
                model='qwen3-coder-plus',
                messages=messages,
                tools=tools,
                result_format='message'
            )
            if response.status_code == 200:
                print(f"Model's final response: {response.output.choices[0].message.content}")
                assistant_output = response.output.choices[0].message
                messages.append(assistant_output)
            else:
                print(f"Error during summary response: {response}")
                break
else:
    print(f"Execution error: {response}")

Response

Calling tool [write_file] with arguments: {'content': 'def quick_sort(arr):\\n    if len(arr) <= 1:\\n        return arr\\n    pivot = arr[len(arr) // 2]\\n    left = [x for x in arr if x < pivot]\\n    middle = [x for x in arr if x == pivot]\\n    right = [x for x in arr if x > pivot]\\n    return quick_sort(left) + middle + quick_sort(right)\\n\\nif __name__ == \\"__main__\\":\\n    example_list = [3, 6, 8, 10, 1, 2, 1]\\n    print(\\"Original list:\\", example_list)\\n    sorted_list = quick_sort(example_list)\\n    print(\\"Sorted list:\\", sorted_list)', 'path': 'quick_sort.py'}
Tool returned: Success: The file 'quick_sort.py' has been written.
Model's final response: The `quick_sort.py` file has been successfully created with the Python implementation of quick sort. You can run the file to see the sorting result for the example list. Let me know if you need any further modifications or explanations!

Request example

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.protocol.Protocol;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.InputRequiredException;
import com.alibaba.dashscope.tools.FunctionDefinition;
import com.alibaba.dashscope.tools.ToolCallBase;
import com.alibaba.dashscope.tools.ToolCallFunction;
import com.alibaba.dashscope.tools.ToolFunction;
import com.alibaba.dashscope.utils.JsonUtils;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;

import java.io.File;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

public class Main {

    /**
     * Write file content
     * @param arguments A JSON string passed by the model, containing the parameters required by the tool.
     * @return A string with the result of the tool execution.
     */
    public static String writeFile(String arguments) {
        try {
            ObjectMapper objectMapper = new ObjectMapper();
            JsonNode argsNode = objectMapper.readTree(arguments);
            String path = argsNode.get("path").asText();
            String content = argsNode.get("content").asText();

            // For security reasons, the file writing feature is disabled by default. To use it, uncomment the code and ensure the path is secure.
            // File file = new File(path);
            // File parentDir = file.getParentFile();
            // if (parentDir != null && !parentDir.exists()) {
            //     parentDir.mkdirs();
            // }
            // Files.write(Paths.get(path), content.getBytes(StandardCharsets.UTF_8));
            return "Success: The file '" + path + "' has been written.";
        } catch (Exception e) {
            return "Error: An exception occurred while writing the file - " + e.getMessage();
        }
    }

    public static void main(String[] args) {
        try {
            // Define the tool parameter schema
            String writePropertyParams =
                    "{\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\",\"description\":\"The relative or absolute path of the target file.\"},\"content\":{\"type\":\"string\",\"description\":\"The string content to write to the file.\"}},\"required\":[\"path\",\"content\"]}";

            FunctionDefinition writeFileFunction = FunctionDefinition.builder()
                    .name("write_file")
                    .description("Writes content to the specified file. If the file does not exist, it is created.")
                    .parameters(JsonUtils.parseString(writePropertyParams).getAsJsonObject())
                    .build();

            // The following is the base_url for the Singapore region. If you use a model in the Beijing region, replace the base_url with: https://dashscope.aliyuncs.com/api/v1
            Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-intl.aliyuncs.com/api/v1");

            String userInput = "Write a Python script for quick sort and name it quick_sort.py.";
            List<Message> messages = new ArrayList<>();
            messages.add(Message.builder().role(Role.USER.getValue()).content(userInput).build());

            // First call to the model
            GenerationParam param = GenerationParam.builder()
                    .model("qwen3-coder-plus")
                    .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                    .messages(messages)
                    .tools(Arrays.asList(ToolFunction.builder().function(writeFileFunction).build()))
                    .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                    .build();

            GenerationResult result = gen.call(param);
            Message assistantOutput = result.getOutput().getChoices().get(0).getMessage();
            messages.add(assistantOutput);

            // If no tool call is needed, print the content directly.
            if (assistantOutput.getToolCalls() == null || assistantOutput.getToolCalls().isEmpty()) {
                System.out.println("No tool call needed, responding directly: " + assistantOutput.getContent());
            } else {
                // Enter the tool calling loop
                while (assistantOutput.getToolCalls() != null && !assistantOutput.getToolCalls().isEmpty()) {
                    for (ToolCallBase toolCall : assistantOutput.getToolCalls()) {
                        ToolCallFunction functionCall = (ToolCallFunction) toolCall;
                        String funcName = functionCall.getFunction().getName();
                        String arguments = functionCall.getFunction().getArguments();
                        System.out.println("Calling tool [" + funcName + "] with arguments: " + arguments);

                        // Execute the tool
                        String toolResult = writeFile(arguments);

                        // Construct the tool return message
                        Message toolMessage = Message.builder()
                                .role("tool")
                                .toolCallId(toolCall.getId())
                                .content(toolResult)
                                .build();
                        System.out.println("Tool returned: " + toolMessage.getContent());
                        messages.add(toolMessage);
                    }

                    // Call the model again to get a summarized natural language response
                    param.setMessages(messages);
                    result = gen.call(param);
                    assistantOutput = result.getOutput().getChoices().get(0).getMessage();
                    messages.add(assistantOutput);
                }
                System.out.println("Model's final response: " + assistantOutput.getContent());
            }

        } catch (NoApiKeyException | InputRequiredException e) {
            System.err.println("Error: " + e.getMessage());
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

Response

Calling tool [write_file] with arguments: {"content": "def quick_sort(arr):\\n    if len(arr) <= 1:\\n        return arr\\n    pivot = arr[len(arr) // 2]\\n    left = [x for x in arr if x < pivot]\\n    middle = [x for x in arr if x == pivot]\\n    right = [x for x in arr if x > pivot]\\n    return quick_sort(left) + middle + quick_sort(right)\\n\\nif __name__ == \\\"__main__\\\":\\n    example_array = [3, 6, 8, 10, 1, 2, 1]\\n    print(\\\"Original array:\\\", example_array)\\n    sorted_array = quick_sort(example_array)\\n    print(\\\"Sorted array:\\\", sorted_array)", "path": "quick_sort.py"}
Tool returned: Success: The file 'quick_sort.py' has been written.
Model's final response: I have successfully created the Python code file `quick_sort.py` for you. This file contains a `quick_sort` function and an example of its usage. You can run it in your terminal or editor to test the quick sort functionality.

Request example

This example shows the first step of the tool calling process: making a request and obtaining the model's intent to call a tool.

curl --location "https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
    "model": "qwen3-coder-plus",
    "input": {
        "messages": [{
            "role": "user",
            "content": "Write a Python script for quick sort and name it quick_sort.py."
        }]
    },
    "parameters": {
        "result_format": "message",
        "tools": [
        {
            "type": "function",
            "function": {
                "name": "write_file",
                "description": "Writes content to the specified file. If the file does not exist, it is created.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "path": {
                            "type": "string",
                            "description": "The relative or absolute path of the target file."
                        },
                        "content": {
                            "type": "string",
                            "description": "The string content to write to the file."
                        }
                    },
                    "required": ["path", "content"]
                }
            }
        }
    ]
    }
}'

Response

{
    "output": {
        "choices": [
            {
                "finish_reason": "tool_calls",
                "message": {
                    "role": "assistant",
                    "tool_calls": [
                        {
                            "function": {
                                "name": "write_file",
                                "arguments": "{\"content\": \"def quick_sort(arr):\\\\n    if len(arr) <= 1:\\\\n        return arr\\\\n    pivot = arr[len(arr) // 2]\\\\n    left = [x for x in arr if x < pivot]\\\\n    middle = [x for x in arr if x == pivot]\\\\n    right = [x for x in arr if x > pivot]\\\\n    return quick_sort(left) + middle + quick_sort(right)\\\\n\\\\nif __name__ == \\\\\\\"__main__\\\\\\\":\\\\n    example_list = [3, 6, 8, 10, 1, 2, 1]\\\\n    print(\\\\\\\"Original list:\\\\\\\", example_list)\\\\n    sorted_list = quick_sort(example_list)\\\\n    print(\\\\\\\"Sorted list:\\\\\\\", sorted_list), \"path\": \"quick_sort.py\"}"
                            },
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                        }
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