Alibaba Cloud Model Studio：Streaming

from openai import OpenAI
import os

client = OpenAI(
    # Kunci API untuk wilayah Singapura dan China (Beijing) berbeda. Untuk mendapatkan kunci API, kunjungi: https://www.alibabacloud.com/help/en/model-studio/get-api-key
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan kunci API Model Studio Anda: api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Berikut adalah URL dasar untuk wilayah Singapura. Jika Anda menggunakan model di wilayah China (Beijing), ganti base_url dengan: https://dashscope.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen3-vl-plus",  # Anda dapat mengganti ini dengan model multimodal lain dan menyesuaikan pesan sesuai kebutuhan.
    messages=[
        {"role": "user",
        "content": [{"type": "image_url",
                    "image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},},
                    {"type": "text", "text": "What scene is depicted in the image?"}]}],
    stream=True,
  # stream_options={"include_usage": True}
)
full_content = ""
print("Streaming output content:")
for chunk in completion:
    # Jika stream_options.include_usage bernilai True, bidang choices pada chunk terakhir adalah daftar kosong dan harus dilewati. Anda bisa mendapatkan penggunaan token dari chunk.usage.
    if chunk.choices and chunk.choices[0].delta.content != "":
        full_content += chunk.choices[0].delta.content
        print(chunk.choices[0].delta.content)
print(f"Full content: {full_content}")

# ======= Penting =======
# Berikut adalah URL dasar untuk wilayah Singapura. Jika Anda menggunakan model di wilayah China (Beijing), ganti URL dasar dengan: https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
# Kunci API untuk wilayah Singapura dan China (Beijing) berbeda. Untuk mendapatkan kunci API, kunjungi: https://www.alibabacloud.com/help/en/model-studio/get-api-key
# === Hapus komentar ini sebelum eksekusi ===

curl --location 'https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model": "qwen3-vl-plus",
    "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": {
            "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
          }
        },
        {
          "type": "text",
          "text": "What scene is depicted in the image?"
        }
      ]
    }
  ],
    "stream":true,
    "stream_options":{"include_usage":true}
}'

import os
from dashscope import MultiModalConversation
import dashscope
# Berikut adalah URL dasar untuk wilayah Singapura. Jika Anda menggunakan model di wilayah China (Beijing), ganti base_url dengan: https://dashscope.aliyuncs.com/compatible-mode/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {
        "role": "user",
        "content": [
            {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
            {"text": "What scene is depicted in the image?"}
        ]
    }
]

responses = MultiModalConversation.call(
    # Kunci API untuk wilayah Singapura dan China (Beijing) berbeda. Untuk mendapatkan kunci API, kunjungi: https://www.alibabacloud.com/help/en/model-studio/get-api-key
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan kunci API Model Studio Anda: api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    model='qwen3-vl-plus',  #  Anda dapat mengganti ini dengan model multimodal lain dan menyesuaikan pesan sesuai kebutuhan.
    messages=messages,
    stream=True,
    incremental_output=True)
    
full_content = ""
print("Streaming output content:")
for response in responses:
    if response["output"]["choices"][0]["message"].content:
        print(response.output.choices[0].message.content[0]['text'])
        full_content += response.output.choices[0].message.content[0]['text']
print(f"Full content: {full_content}")

import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.Map;

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.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import io.reactivex.Flowable;
import com.alibaba.dashscope.utils.Constants;

public class Main {
    static {
        // Berikut adalah URL dasar untuk wilayah Singapura. Jika Anda menggunakan model di wilayah China (Beijing), ganti base_url dengan: https://dashscope.aliyuncs.com/api/v1
        Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";
    }
    public static void streamCall()
            throws ApiException, NoApiKeyException, UploadFileException {
        MultiModalConversation conv = new MultiModalConversation();
        // must create mutable map.
        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"),
                        Collections.singletonMap("text", "What scene is depicted in the image?"))).build();
        MultiModalConversationParam param = MultiModalConversationParam.builder()
                // Kunci API untuk wilayah Singapura dan China (Beijing) berbeda. Untuk mendapatkan kunci API, kunjungi: https://www.alibabacloud.com/help/en/model-studio/get-api-key
                // Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan kunci API Model Studio Anda: .apiKey("sk-xxx")
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .model("qwen3-vl-plus")  //  Anda dapat mengganti ini dengan model multimodal lain dan menyesuaikan pesan sesuai kebutuhan.
                .messages(Arrays.asList(userMessage))
                .incrementalOutput(true)
                .build();
        Flowable<MultiModalConversationResult> result = conv.streamCall(param);
        result.blockingForEach(item -> {
            try {
                List<Map<String, Object>> content = item.getOutput().getChoices().get(0).getMessage().getContent();
                    // Periksa apakah konten ada dan tidak kosong.
                if (content != null &&  !content.isEmpty()) {
                    System.out.println(content.get(0).get("text"));
                    }
            } catch (Exception e){
                System.exit(0);
            }
        });
    }

    public static void main(String[] args) {
        try {
            streamCall();
        } catch (ApiException | NoApiKeyException | UploadFileException e) {
            System.out.println(e.getMessage());
        }
        System.exit(0);
    }
}

# ======= Penting =======
# Kunci API untuk wilayah Singapura dan China (Beijing) berbeda. Untuk mendapatkan kunci API, kunjungi: https://www.alibabacloud.com/help/en/model-studio/get-api-key
# Berikut adalah URL dasar untuk wilayah Singapura. Jika Anda menggunakan model di wilayah China (Beijing), ganti URL dasar dengan: https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation
# === Hapus komentar ini sebelum eksekusi ===

curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-H 'X-DashScope-SSE: enable' \
-d '{
    "model": "qwen3-vl-plus",
    "input":{
        "messages":[
            {
                "role": "user",
                "content": [
                    {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
                    {"text": "What scene is depicted in the image?"}
                ]
            }
        ]
    },
    "parameters": {
        "incremental_output": true
    }
}'

Kode contoh

from openai import OpenAI
import os

# Inisialisasi client OpenAI.
client = OpenAI(
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan kunci API Model Studio Anda: api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

messages = [{"role": "user", "content": "Who are you?"}]

completion = client.chat.completions.create(
    model="qwen-plus",  # Anda dapat mengganti ini dengan model pemikiran mendalam lain sesuai kebutuhan.
    messages=messages,
    # Parameter enable_thinking mengaktifkan proses berpikir. Parameter ini tidak didukung untuk model qwen3-30b-a3b-thinking-2507, qwen3-235b-a22b-thinking-2507, dan QwQ.
    extra_body={"enable_thinking": True},
    stream=True,
    # stream_options={
    #     "include_usage": True
    # },
)

reasoning_content = ""  # Seluruh proses berpikir
answer_content = ""  # Seluruh respons
is_answering = False  # Apakah tahap menjawab telah dimulai
print("\n" + "=" * 20 + "Thinking process" + "=" * 20 + "\n")

for chunk in completion:
    if not chunk.choices:
        print("\nUsage:")
        print(chunk.usage)
        continue

    delta = chunk.choices[0].delta

    # Kumpulkan hanya konten berpikir.
    if hasattr(delta, "reasoning_content") and delta.reasoning_content is not None:
        if not is_answering:
            print(delta.reasoning_content, end="", flush=True)
        reasoning_content += delta.reasoning_content

    # Menerima konten, mulai menjawab.
    if hasattr(delta, "content") and delta.content:
        if not is_answering:
            print("\n" + "=" * 20 + "Full response" + "=" * 20 + "\n")
            is_answering = True
        print(delta.content, end="", flush=True)
        answer_content += delta.content

Contoh respons

====================Thinking process====================

Okay, the user is asking "Who are you?". I need to provide an accurate and friendly answer. First, I must confirm my identity: Qwen, developed by the Tongyi Lab at Alibaba Group. Next, I should explain my main functions, such as answering questions, creating text, and logical reasoning. I need to maintain a friendly tone and avoid being too technical to make the user feel at ease. I should also avoid complex jargon to keep the answer simple and clear. Additionally, I might add some interactive elements, inviting the user to ask more questions to encourage further conversation. Finally, I'll check if I've missed any important information, such as my Chinese name "Tongyi Qianwen" and English name "Qwen", and my parent company and lab. I need to ensure the answer is comprehensive and meets the user's expectations.
====================Full response====================

Hello! I am Qwen, a large-scale language model developed by the Tongyi Lab at Alibaba Group. I can answer questions, create text, perform logical reasoning, write code, and more, all to provide users with high-quality information and services. You can call me Qwen, or just Tongyi Qianwen. How can I help you?

Kode contoh

import OpenAI from "openai";
import process from 'process';

// Inisialisasi client OpenAI.
const openai = new OpenAI({
    apiKey: process.env.DASHSCOPE_API_KEY, // Baca dari variabel lingkungan
    baseURL: 'https://dashscope-intl.aliyuncs.com/compatible-mode/v1'
});

let reasoningContent = '';
let answerContent = '';
let isAnswering = false;

async function main() {
    try {
        const messages = [{ role: 'user', content: 'Who are you?' }];
        const stream = await openai.chat.completions.create({
            // Anda dapat mengganti ini dengan model Qwen3 atau QwQ lain sesuai kebutuhan.
            model: 'qwen-plus',
            messages,
            stream: true,
            // Parameter enable_thinking mengaktifkan proses berpikir. Parameter ini tidak didukung untuk model qwen3-30b-a3b-thinking-2507, qwen3-235b-a22b-thinking-2507, dan QwQ.
            enable_thinking: true
        });
        console.log('\n' + '='.repeat(20) + 'Thinking process' + '='.repeat(20) + '\n');

        for await (const chunk of stream) {
            if (!chunk.choices?.length) {
                console.log('\nUsage:');
                console.log(chunk.usage);
                continue;
            }

            const delta = chunk.choices[0].delta;
            
            // Kumpulkan hanya konten berpikir.
            if (delta.reasoning_content !== undefined && delta.reasoning_content !== null) {
                if (!isAnswering) {
                    process.stdout.write(delta.reasoning_content);
                }
                reasoningContent += delta.reasoning_content;
            }

            // Mulai menjawab setelah menerima konten.
            if (delta.content !== undefined && delta.content) {
                if (!isAnswering) {
                    console.log('\n' + '='.repeat(20) + 'Full response' + '='.repeat(20) + '\n');
                    isAnswering = True;
                }
                process.stdout.write(delta.content);
                answerContent += delta.content;
            }
        }
    } catch (error) {
        console.error('Error:', error);
    }
}

main();

Contoh respons

====================Thinking process====================

Okay, the user is asking "Who are you?". I need to answer with my identity. First, I should clearly state that I am Qwen, a large-scale language model developed by Alibaba Cloud. Next, I can mention my main functions, such as answering questions, creating text, and logical reasoning. I should also emphasize my multilingual support, including Chinese and English, so the user knows I can handle requests in different languages. Additionally, I might need to explain my application scenarios, such as helping with study, work, and daily life. However, the user's question is quite direct, so I should keep it concise. I also need to ensure a friendly tone and invite the user to ask further questions. I will check for any missing important information, such as my version or latest updates, but the user probably doesn't need that level of detail. Finally, I will confirm the answer is accurate and free of errors.
====================Full response====================

I am Qwen, a large-scale language model developed by the Tongyi Lab at Alibaba Group. I can perform various tasks such as answering questions, creating text, logical reasoning, and coding. I support multiple languages, including Chinese and English. If you have any questions or need help, feel free to let me know!

Kode contoh

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": "Who are you?"
        }
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    },
    "enable_thinking": true
}'

Contoh respons

data: {"choices":[{"delta":{"content":null,"role":"assistant","reasoning_content":""},"index":0,"logprobs":null,"finish_reason":null}],"object":"chat.completion.chunk","usage":null,"created":1745485391,"system_fingerprint":null,"model":"qwen-plus","id":"chatcmpl-e2edaf2c-8aaf-9e54-90e2-b21dd5045503"}

.....

data: {"choices":[{"finish_reason":"stop","delta":{"content":"","reasoning_content":null},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1745485391,"system_fingerprint":null,"model":"qwen-plus","id":"chatcmpl-e2edaf2c-8aaf-9e54-90e2-b21dd5045503"}

data: {"choices":[],"object":"chat.completion.chunk","usage":{"prompt_tokens":10,"completion_tokens":360,"total_tokens":370},"created":1745485391,"system_fingerprint":null,"model":"qwen-plus","id":"chatcmpl-e2edaf2c-8aaf-9e54-90e2-b21dd5045503"}

data: [DONE]

Kode contoh

import os
from dashscope import Generation
import dashscope
dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1/"

messages = [{"role": "user", "content": "Who are you?"}]

completion = Generation.call(
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan kunci API Model Studio Anda: api_key = "sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Anda dapat mengganti ini dengan model pemikiran mendalam lain sesuai kebutuhan.
    model="qwen-plus",
    messages=messages,
    result_format="message", # Model open-source Qwen3 hanya mendukung "message". Untuk pengalaman lebih baik, kami sarankan Anda mengatur parameter ini ke "message" untuk model lain juga.
    # Aktifkan pemikiran mendalam. Parameter ini tidak berpengaruh pada model qwen3-30b-a3b-thinking-2507, qwen3-235b-a22b-thinking-2507, dan QwQ.
    enable_thinking=True,
    stream=True,
    incremental_output=True, # Model open-source Qwen3 hanya mendukung true. Untuk pengalaman lebih baik, kami sarankan Anda mengatur parameter ini ke true untuk model lain juga.
)

# Definisikan seluruh proses berpikir.
reasoning_content = ""
# Definisikan seluruh respons.
answer_content = ""
# Tentukan apakah proses berpikir telah selesai dan respons sedang dihasilkan.
is_answering = False

print("=" * 20 + "Thinking process" + "=" * 20)

for chunk in completion:
    # Jika proses berpikir dan respons keduanya kosong, jangan lakukan apa-apa.
    if (
        chunk.output.choices[0].message.content == ""
        and chunk.output.choices[0].message.reasoning_content == ""
    ):
        pass
    else:
        # Jika bagian saat ini adalah proses berpikir.
        if (
            chunk.output.choices[0].message.reasoning_content != ""
            and chunk.output.choices[0].message.content == ""
        ):
            print(chunk.output.choices[0].message.reasoning_content, end="", flush=True)
            reasoning_content += chunk.output.choices[0].message.reasoning_content
        # Jika bagian saat ini adalah respons.
        elif chunk.output.choices[0].message.content != "":
            if not is_answering:
                print("\n" + "=" * 20 + "Full response" + "=" * 20)
                is_answering = True
            print(chunk.output.choices[0].message.content, end="", flush=True)
            answer_content += chunk.output.choices[0].message.content

# Untuk mencetak seluruh proses berpikir dan respons, hapus komentar dan jalankan kode berikut.
# print("=" * 20 + "Full thinking process" + "=" * 20 + "\n")
# print(f"{reasoning_content}")
# print("=" * 20 + "Full response" + "=" * 20 + "\n")
# print(f"{answer_content}")

Contoh respons

====================Thinking process====================
Okay, the user is asking, "Who are you?" I need to answer this question. First, I must clarify my identity: Qwen, a large-scale language model developed by Alibaba Cloud. Next, I should explain my functions and purposes, such as answering questions, creating text, and logical reasoning. I should also emphasize my goal of being a helpful assistant to users, providing help and support.

When responding, I should maintain a conversational tone and avoid using technical jargon or complex sentence structures. I can use friendly expressions, like "Hello there! ~", to make the conversation more natural. I also need to ensure the information is accurate and does not omit key points, such as my developer, main functions, and application scenarios.

I should also consider potential follow-up questions from the user, such as specific application examples or technical details. So, I can subtly set up opportunities in my answer to guide the user to ask more questions. For example, by mentioning, "Whether it's a question about daily life or a professional field, I can do my best to help," which is both comprehensive and open-ended.

Finally, I will check if the response is fluent, without repetition or redundancy, ensuring it is concise and clear. I will also maintain a balance between being friendly and professional, so the user feels that I am both approachable and reliable.
====================Full response====================
Hello there! ~ I am Qwen, a large-scale language model developed by Alibaba Cloud. I can answer questions, create text, perform logical reasoning, write code, and more, all to provide help and support to users. Whether it's a question about daily life or a professional field, I can do my best to help. How can I assist you?

Kode contoh

// dashscope SDK version >= 2.19.4
import java.util.Arrays;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
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 io.reactivex.Flowable;
import java.lang.System;
import com.alibaba.dashscope.utils.Constants;

public class Main {
    static {
        Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";
    }
    private static final Logger logger = LoggerFactory.getLogger(Main.class);
    private static StringBuilder reasoningContent = new StringBuilder();
    private static StringBuilder finalContent = new StringBuilder();
    private static boolean isFirstPrint = true;

    private static void handleGenerationResult(GenerationResult message) {
        String reasoning = message.getOutput().getChoices().get(0).getMessage().getReasoningContent();
        String content = message.getOutput().getChoices().get(0).getMessage().getContent();

        if (!reasoning.isEmpty()) {
            reasoningContent.append(reasoning);
            if (isFirstPrint) {
                System.out.println("====================Thinking process====================");
                isFirstPrint = false;
            }
            System.out.print(reasoning);
        }

        if (!content.isEmpty()) {
            finalContent.append(content);
            if (!isFirstPrint) {
                System.out.println("\n====================Full response====================");
                isFirstPrint = true;
            }
            System.out.print(content);
        }
    }
    private static GenerationParam buildGenerationParam(Message userMsg) {
        return GenerationParam.builder()
                // Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan kunci API Model Studio Anda: .apiKey("sk-xxx")
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .model("qwen-plus")
                .enableThinking(true)
                .incrementalOutput(true)
                .resultFormat("message")
                .messages(Arrays.asList(userMsg))
                .build();
    }
    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));
    }

    public static void main(String[] args) {
        try {
            Generation gen = new Generation();
            Message userMsg = Message.builder().role(Role.USER.getValue()).content("Who are you?").build();
            streamCallWithMessage(gen, userMsg);
//             Cetak hasil akhir.
//            if (reasoningContent.length() > 0) {
//                System.out.println("\n====================Full response====================");
//                System.out.println(finalContent.toString());
//            }
        } catch (ApiException | NoApiKeyException | InputRequiredException e) {
            logger.error("An exception occurred: {}", e.getMessage());
        }
        System.exit(0);
    }
}

Hasil

====================Thinking process====================
Okay, the user is asking "Who are you?". I need to answer based on my previous settings. First, my role is Qwen, a large-scale language model from Alibaba Group. I need to keep my language conversational, simple, and easy to understand.

The user might be new to me or wants to confirm my identity. I should first directly answer who I am, then briefly explain my functions and uses, such as answering questions, creating text, and coding. I also need to mention my multilingual support so the user knows I can handle requests in different languages.

Also, according to the guidelines, I need to maintain a human-like personality, so my tone should be friendly, and I might use emojis to add a touch of warmth. I might also need to guide the user to ask further questions or use my functions, for example, by asking them what they need help with.

I need to be careful not to use complex jargon and avoid being long-winded. I will check for any missed key points, such as multilingual support and specific capabilities. I will ensure the answer meets all requirements, including being conversational and concise.
====================Full response====================
Hello! I am Qwen, a large-scale language model from Alibaba Group. I can answer questions, create text such as stories, official documents, emails, and scripts, perform logical reasoning, write code, express opinions, and play games. I am proficient in multiple languages, including but not limited to Chinese, English, German, French, and Spanish. Is there anything I can help you with?

Kode contoh

# ======= Penting =======
# Kunci API untuk wilayah Singapura dan China (Beijing) berbeda. Untuk mendapatkan kunci API, kunjungi: https://www.alibabacloud.com/help/en/model-studio/get-api-key
# Berikut adalah URL untuk wilayah Singapura. Jika Anda menggunakan model di wilayah China (Beijing), ganti URL dengan: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation
# === Hapus komentar ini sebelum eksekusi ===

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": "Who are you?"
            }
        ]
    },
    "parameters":{
        "enable_thinking": true,
        "incremental_output": true,
        "result_format": "message"
    }
}'

Contoh respons

id:1
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"","reasoning_content":"Hmm","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":14,"input_tokens":11,"output_tokens":3},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:2
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"","reasoning_content":",","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":15,"input_tokens":11,"output_tokens":4},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:3
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"","reasoning_content":" the user","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":16,"input_tokens":11,"output_tokens":5},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:4
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"","reasoning_content":" is asking","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":17,"input_tokens":11,"output_tokens":6},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:5
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"","reasoning_content":" '","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":18,"input_tokens":11,"output_tokens":7},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}
......

id:358
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":" help","reasoning_content":"","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":373,"input_tokens":11,"output_tokens":362},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:359
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":",","reasoning_content":"","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":374,"input_tokens":11,"output_tokens":363},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:360
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":" feel free to","reasoning_content":"","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":375,"input_tokens":11,"output_tokens":364},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:361
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":" let me","reasoning_content":"","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":376,"input_tokens":11,"output_tokens":365},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:362
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":" know","reasoning_content":"","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":377,"input_tokens":11,"output_tokens":366},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:363
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"!","reasoning_content":"","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":378,"input_tokens":11,"output_tokens":367},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}

id:364
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"","reasoning_content":"","role":"assistant"},"finish_reason":"stop"}]},"usage":{"total_tokens":378,"input_tokens":11,"output_tokens":367},"request_id":"25d58c29-c47b-9e8d-a0f1-d6c309ec58b1"}