Alibaba Cloud Model Studio:Overview

import os
from openai import OpenAI

try:
    client = OpenAI(
        # API keys differ by region. Get your API key: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
        # If you have not set an environment variable, replace the next line with your Model Studio API key: api_key="sk-xxx",
        api_key=os.getenv("DASHSCOPE_API_KEY"),
        # Configuration varies by region. Update the URL for your region.
        base_url="https://dashscope-intl.aliyuncs.com/api/v2/apps/protocols/compatible-mode/v1",
    )

    response = client.responses.create(
        model="qwen3.5-plus", 
        input="Briefly introduce what you can do?"
    )

    print(response)
except Exception as e:
    print(f"Error message: {e}")
    print("See documentation: https://www.alibabacloud.com/help/zh/model-studio/error-code")

Response

The response includes these main fields:

• id: The response ID.

• output: The output list. Includes reasoning and message.

  reasoning field appears only when deep thinking is enabled (for example, it is enabled by default in the Qwen3.5 series).

• usage: Token usage statistics.

The following is an example response. For the full response, see curl.

Hello! I'm an AI assistant with knowledge current up to 2026. Here's a brief overview of what I can do:

*   **Content Creation:** Write emails, articles, stories, scripts, and more.
*   **Coding & Tech:** Generate, debug, and explain code across various programming languages.
*   **Analysis & Summarization:** Process documents, interpret data, and extract key insights.
*   **Problem Solving:** Assist with math, logic, reasoning, and strategic planning.
*   **Learning & Translation:** Explain complex topics simply or translate between multiple languages.

Feel free to ask me anything or give me a task to get started!

// Requires Node.js v18+. Run in an ES Module environment.
import OpenAI from "openai";

const openai = new OpenAI({
    // API keys differ by region. Get your API key: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
    // If you have not set an environment variable, replace the next line with your Model Studio API key: apiKey: "sk-xxx",
    apiKey: process.env.DASHSCOPE_API_KEY,
    // Configuration varies by region. Update the URL for your region.
    baseURL: "https://dashscope-intl.aliyuncs.com/api/v2/apps/protocols/compatible-mode/v1"
});

async function main() {
    try {
        const response = await openai.responses.create({
            model: "qwen3.5-plus",
            input: "Briefly introduce what you can do?"
        });

        // Get model response
        console.log(response);
    } catch (error) {
        console.error("Error:", error);
    }
}

main();

Response

The response includes these main fields:

• id: The response ID.

• output: The output list. Includes reasoning and message.

  reasoning field appears only when deep thinking is enabled (for example, it is enabled by default in the Qwen3.5 series).

• usage: Token usage statistics.

The following is an example response. For the full response, see curl.

Hello! I'm an AI assistant with knowledge current up to 2026. Here's a brief overview of what I can do:

*   **Content Creation:** Write emails, articles, stories, scripts, and more.
*   **Coding & Tech:** Generate, debug, and explain code across various programming languages.
*   **Analysis & Summarization:** Process documents, interpret data, and extract key insights.
*   **Problem Solving:** Assist with math, logic, reasoning, and strategic planning.
*   **Learning & Translation:** Explain complex topics simply or translate between multiple languages.

Feel free to ask me anything or give me a task to get started!

# Configuration varies by region. Update the URL for your region.
curl -X POST https://dashscope-intl.aliyuncs.com/api/v2/apps/protocols/compatible-mode/v1/responses \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
    "model": "qwen3.5-plus",
    "input": "Briefly introduce what you can do?",
    "enable_thinking": true
}'

Response

{
    "created_at": 1772249518,
    "id": "7ad48c6b-3cc4-904f-9284-5f419c6c5xxx",
    "model": "qwen3.5-plus",
    "object": "response",
    "output": [
        {
            "id": "msg_94805179-2801-45da-ac1c-a87e8ea20xxx",
            "summary": [
                {
                    "text": "Okay, the user is asking me to briefly introduce what I can do. Let me start by recalling the capabilities listed in the system message. I need to make sure I cover the main points without getting too detailed.\n\nFirst, I should mention my enhanced language foundation and architecture efficiency. Then, the upgraded logical reasoning and mathematical capabilities. Visual analysis is another key point, including charts and formulas. Autonomous agent planning and code generation are important too. Human alignment optimization for better interaction, long-context handling up to 256K, and multilingual support with OCR.\n\nWait, the user said \"briefly,\" so I need to keep it concise. Maybe group some points together. Let me check the examples given in the system message. They have sections like Enhanced Language Foundation, Advanced Logical Reasoning, etc. But since it's a brief intro, I should summarize each capability in a sentence or two.\n\nAlso, the user might be looking for practical applications. Maybe highlight how these features help in real tasks. For example, handling long documents, solving math problems, analyzing images, writing code, etc.\n\nI should avoid technical jargon where possible. Make it clear and straightforward. Let me structure it as a list of key capabilities with short explanations. Start with a greeting, then list the main points, and end with an offer to help with specific tasks.\n\nWait, the system message says \"You are Qwen3.5,\" so I need to introduce myself as such. But the user just asked what I can do, so maybe start with \"I'm Qwen3.5...\" and then list the capabilities.\n\nCheck if all the upgraded features from Qwen3 to Qwen3.5 are covered. The main upgrades are in language foundation, reasoning, visual analysis, agent planning, code, alignment, context length, and multilingual OCR.\n\nMake sure not to mention the knowledge cutoff unless relevant. The user's current time is 2026, but since my knowledge is up to 2026, that's covered.\n\nOkay, let me draft a concise response highlighting each capability briefly. Keep it friendly and inviting for the user to ask for specific help.\n",
                    "type": "summary_text"
                }
            ],
            "type": "reasoning"
        },
        {
            "content": [
                {
                    "annotations": [],
                    "text": "I'm **Qwen3.5**, a large language model designed to assist with a wide range of tasks. Here's what I can do:  \n\n- **Understand & Generate Text**: Handle complex instructions, creative writing, and multi-step tasks with improved accuracy.  \n- **Solve Problems**: Tackle advanced math, logic puzzles, and scientific reasoning with step-by-step clarity.  \n- **Analyze Visuals**: Interpret charts, diagrams, formulas, and even extract text from images (OCR).  \n- **Plan & Execute**: Break down goals into actionable steps, run code, or interact with tools autonomously.  \n- **Code & Debug**: Write, explain, or fix code in multiple programming languages.  \n- **Long-Context Mastery**: Process documents, books, or videos up to **256K tokens** without losing key details.  \n- **Multilingual Support**: Communicate fluently in **100+ languages**, including low-resource ones.  \n\nNeed help with something specific? Just ask!",
                    "type": "output_text"
                }
            ],
            "id": "msg_35be06c6-ca4d-4f2b-9677-7897e488dxxx",
            "role": "assistant",
            "status": "completed",
            "type": "message"
        }
    ],
    "parallel_tool_calls": false,
    "status": "completed",
    "tool_choice": "auto",
    "tools": [],
    "usage": {
        "input_tokens": 54,
        "input_tokens_details": {
            "cached_tokens": 0
        },
        "output_tokens": 662,
        "output_tokens_details": {
            "reasoning_tokens": 447
        },
        "total_tokens": 716,
        "x_details": [
            {
                "input_tokens": 54,
                "output_tokens": 662,
                "output_tokens_details": {
                    "reasoning_tokens": 447
                },
                "total_tokens": 716,
                "x_billing_type": "response_api"
            }
        ]
    }
}

import os
from openai import OpenAI

try:
    client = OpenAI(
        # API keys differ by region. Get your API key: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
        # If you have not set an environment variable, replace the next line with your Model Studio API key: api_key="sk-xxx",
        api_key=os.getenv("DASHSCOPE_API_KEY"),
        # Configuration varies by region. Update the URL for your region.
        base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
    )

    completion = client.chat.completions.create(
        model="qwen3.5-plus",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "Who are you?"},
        ],
    )
    print(completion.choices[0].message.content)
except Exception as e:
    print(f"Error message: {e}")
    print("See documentation: https://www.alibabacloud.com/help/zh/model-studio/error-code")

Response

I'm Qwen, a large language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions, create text, write stories, official documents, emails, scripts, do logical reasoning, code, express opinions, play games, and more. If you have any questions or need help, feel free to ask!

// Requires Node.js v18+. Run in an ES Module environment.
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // API keys differ by region. Get your API key: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
        // If you have not set an environment variable, replace the next line with: apiKey: "sk-xxx",
        apiKey: process.env.DASHSCOPE_API_KEY,
        // Configuration varies by region. Update the URL for your region.
        baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"

    }
);
const completion = await openai.chat.completions.create({
    model: "qwen3.5-plus",
    messages: [
        { role: "system", content: "You are a helpful assistant." },
        { role: "user", content: "Who are you?" }
    ],
});
console.log(completion.choices[0].message.content);

Response

I'm Qwen, a large language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions, create text, write stories, official documents, emails, scripts, do logical reasoning, code, express opinions, play games, and more. If you have any questions or need help, feel free to ask!

# Configuration varies by region. Update the URL for your region.
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": "qwen3.5-plus",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user", 
            "content": "Who are you?"
        }
    ]
}'

Response

{
    "choices": [
        {
            "message": {
                "role": "assistant",
                "content": "I'm Qwen, a large language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions, create text, write stories, official documents, emails, scripts, do logical reasoning, code, express opinions, play games, and more. If you have any questions or need help, feel free to ask!"
            },
            "finish_reason": "stop",
            "index": 0,
            "logprobs": null
        }
    ],
    "object": "chat.completion",
    "usage": {
        "prompt_tokens": 26,
        "completion_tokens": 66,
        "total_tokens": 92
    },
    "created": 1726127645,
    "system_fingerprint": null,
    "model": "qwen3.5-plus",
    "id": "chatcmpl-81951b98-28b8-9659-ab07-xxxxxx"
}

import json
import os
from dashscope import Generation
import dashscope

# Configuration varies by region. Update the URL for your region.
dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1"

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Who are you?"},
]
response = Generation.call(
    # API keys differ by region. Get your API key: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
    # If you have not set an environment variable, replace the next line with: api_key = "sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The Qwen3.5 series uses a multimodal interface. Simply replacing the model will cause an error
    model="qwen-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}")
    print("See documentation: https://www.alibabacloud.com/help/zh/model-studio/error-code")

Response

I'm Qwen, a large language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions, create text, write stories, official documents, emails, scripts, do logical reasoning, code, express opinions, play games, and more. If you have any questions or need help, feel free to ask!

// Requires Node.js v18+
// If you have not set an environment variable, replace the next line with: const apiKey = "sk-xxx";
const apiKey = process.env.DASHSCOPE_API_KEY;

const data = {
    // The Qwen3.5 series uses a multimodal interface. Simply replacing the model will cause an error
    model: "qwen-plus",
    input: {
        messages: [
            {
                role: "system",
                content: "You are a helpful assistant."
            },
            {
                role: "user",
                content: "Who are you?"
            }
        ]
    },
    parameters: {
        result_format: "message"
    }
};

async function callApi() {
    try {
            // Configuration varies by region. Update the URL for your region.
            const response = await fetch('https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation', {
            method: 'POST',
            headers: {
                'Authorization': `Bearer ${apiKey}`,
                'Content-Type': 'application/json'
            },
            body: JSON.stringify(data)
        });

        const result = await response.json();
        console.log(result.output.choices[0].message.content);
    } catch (error) {
        // For more error info, see: https://www.alibabacloud.com/help/zh/model-studio/error-code
        console.error('Call failed:', error.message);
    }
}

callApi();

Response

I'm Qwen, a large language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions, create text, write stories, official documents, emails, scripts, do logical reasoning, code, express opinions, play games, and more. If you have any questions or need help, feel free to ask!

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io"
	"log"
	"net/http"
	"os"
)

func main() {
	requestBody := map[string]interface{}{
		// The Qwen3.5 series uses a multimodal interface. Simply replacing the model will cause an error
		"model": "qwen-plus",
		"input": map[string]interface{}{
			"messages": []map[string]string{
				{
					"role":    "system",
					"content": "You are a helpful assistant.",
				},
				{
					"role":    "user",
					"content": "Who are you?",
				},
			},
		},
		"parameters": map[string]string{
			"result_format": "message",
		},
	}

	// Serialize to JSON
	jsonData, _ := json.Marshal(requestBody)

	// Create HTTP client and request
	client := &http.Client{}
	// Configuration varies by region. Update the URL for your region.
	req, _ := http.NewRequest("POST", "https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation", bytes.NewBuffer(jsonData))

	// Set request headers
	apiKey := os.Getenv("DASHSCOPE_API_KEY")
	req.Header.Set("Authorization", "Bearer "+apiKey)
	req.Header.Set("Content-Type", "application/json")

	// Send request
	resp, err := client.Do(req)
	if err != nil {
		log.Fatal(err)
	}
	defer resp.Body.Close()

	// Read response body
	bodyText, _ := io.ReadAll(resp.Body)

	// Parse JSON and output content
	var result map[string]interface{}
	json.Unmarshal(bodyText, &result)
	content := result["output"].(map[string]interface{})["choices"].([]interface{})[0].(map[string]interface{})["message"].(map[string]interface{})["content"].(string)
	fmt.Println(content)
}

Response

I'm Qwen, a large language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions, create text, write stories, official documents, emails, scripts, do logical reasoning, code, express opinions, play games, and more. If you have any questions or need help, feel free to ask!