Alibaba Cloud Model Studio:Streaming output

from openai import OpenAI
import os

client = OpenAI(
    # Kunci API berbeda tiap wilayah. Dapatkan Kunci API Anda: https://www.alibabacloud.com/help/zh/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"),
    # URL wilayah Singapura. Ganti {WorkspaceId} dengan ID ruang kerja aktual Anda. URL berbeda tiap wilayah.
    base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen3-vl-plus",  # Ganti dengan model multimodal lain sesuai kebutuhan dan sesuaikan messages-nya
    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": "Adegan apa yang digambarkan dalam gambar ini?"}]}],
    stream=True,
  # stream_options={"include_usage": True}
)
full_content = ""
print("Konten keluaran streaming:")
for chunk in completion:
    # Jika stream_options.include_usage bernilai True, field choices pada chunk terakhir adalah daftar kosong dan harus dilewati (token usage dapat diperoleh melalui 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"Konten lengkap: {full_content}")

# ======= Catatan penting =======
# URL wilayah Singapura. Ganti {WorkspaceId} dengan ID ruang kerja aktual Anda. URL berbeda tiap wilayah.
# Kunci API berbeda tiap wilayah. Dapatkan Kunci API Anda: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Hapus komentar ini sebelum menjalankan ===

curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.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": "Adegan apa yang digambarkan dalam gambar ini?"
        }
      ]
    }
  ],
    "stream":true,
    "stream_options":{"include_usage":true}
}'

import os
from dashscope import MultiModalConversation
import dashscope
# URL wilayah Singapura. Ganti {WorkspaceId} dengan ID ruang kerja aktual Anda. URL berbeda tiap wilayah.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'

messages = [
    {
        "role": "user",
        "content": [
            {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
            {"text": "Adegan apa yang digambarkan dalam gambar ini?"}
        ]
    }
]

responses = MultiModalConversation.call(
    # Kunci API berbeda tiap wilayah. Dapatkan Kunci API Anda: https://www.alibabacloud.com/help/zh/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',  #  Ganti dengan model multimodal lain sesuai kebutuhan dan sesuaikan messages-nya
    messages=messages,
    stream=True,
    incremental_output=True)
    
full_content = ""
print("Konten keluaran streaming:")
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"Konten lengkap: {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 {
        // URL wilayah Singapura. Ganti {WorkspaceId} dengan ID ruang kerja aktual Anda. URL berbeda tiap wilayah.
        Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
    }
    public static void streamCall()
            throws ApiException, NoApiKeyException, UploadFileException {
        MultiModalConversation conv = new MultiModalConversation();
        // harus membuat map yang mutable.
        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", "Adegan apa yang digambarkan dalam gambar ini?"))).build();
        MultiModalConversationParam param = MultiModalConversationParam.builder()
                // Kunci API berbeda tiap wilayah. Dapatkan Kunci API Anda: https://www.alibabacloud.com/help/zh/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")  //  Ganti dengan model multimodal lain sesuai kebutuhan dan sesuaikan messages-nya
                .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);
    }
}

# ======= Catatan penting =======
# Kunci API berbeda tiap wilayah. Dapatkan Kunci API Anda: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# URL wilayah Singapura. Ganti {WorkspaceId} dengan ID ruang kerja aktual Anda. URL berbeda tiap wilayah.
# === Hapus komentar ini sebelum menjalankan ===

curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.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": "Adegan apa yang digambarkan dalam gambar ini?"}
                ]
            }
        ]
    },
    "parameters": {
        "incremental_output": true
    }
}'

Kode contoh

from openai import OpenAI
import os

# Inisialisasi klien OpenAI
client = OpenAI(
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti dengan Kunci API Alibaba Cloud Model Studio Anda: api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)

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

completion = client.chat.completions.create(
    model="qwen-plus",  # Ganti dengan model berpikir mendalam lainnya sesuai kebutuhan
    messages=messages,
    # Parameter enable_thinking mengaktifkan proses berpikir. Parameter ini tidak berpengaruh pada 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 = ""  # Proses berpikir lengkap
answer_content = ""  # Tanggapan lengkap
is_answering = False  # Apakah sedang dalam tahap memberikan tanggapan
print("\n" + "=" * 20 + "Thought 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 memberikan tanggapan
    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

Tanggapan

====================Thought process====================

Okay, the user asked "Who are you," so I need to give an accurate and friendly answer. First, I should confirm my identity as Qwen, developed by Tongyi Lab under Alibaba Group. Next, explain my main functions, like answering questions, creating text, logical reasoning, etc. Keep the tone approachable and avoid overly technical terms so the user feels comfortable. Also, avoid complex jargon and ensure the answer is concise. Additionally, include some interactive elements to encourage further questions. Finally, check for any missing key information, such as my Chinese name "Tongyi Qianwen" and English name "Qwen," along with my company and lab. Make sure the response is comprehensive and meets user expectations.
====================Full response====================

Hello! I am Qwen, a large-scale language model independently developed by Tongyi Lab under Alibaba Group. I can answer questions, create text, perform logical reasoning, programming, and more, aiming to provide high-quality information and services. You can call me Qwen or simply Tongyi Qianwen. How can I help you?

Kode contoh

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

// Inisialisasi klien openai
const openai = new OpenAI({
    apiKey: process.env.DASHSCOPE_API_KEY, // Baca dari variabel lingkungan
    baseURL: 'https://{WorkspaceId}.ap-southeast-1.maas.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({
            // Ganti dengan model Qwen3 lainnya atau model QwQ sesuai kebutuhan
            model: 'qwen-plus',
            messages,
            stream: true,
            // Parameter enable_thinking mengaktifkan proses berpikir. Parameter ini tidak berpengaruh pada model qwen3-30b-a3b-thinking-2507, qwen3-235b-a22b-thinking-2507, dan QwQ.
            enable_thinking: true
        });
        console.log('\n' + '='.repeat(20) + 'Thought 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;
            }

            // Menerima konten, mulai memberikan tanggapan
            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();

Tanggapan

====================Thought process====================

Okay, the user asked "Who are you," so I need to state my identity. First, I should clearly say I am Qwen, a large-scale language model developed by Alibaba Cloud. Next, mention my main functions, like answering questions, creating text, logical reasoning, etc. Also emphasize my multilingual support, including Chinese and English, so users know I can handle requests in different languages. Additionally, explain my application scenarios, such as helping with learning, work, and daily life. However, since the user's question is direct, detailed information might not be necessary—keep it concise. Also, ensure a friendly tone and invite further questions. Check for any missing key information, like my version or latest updates, but the user probably doesn't need that much detail. Finally, confirm the response is accurate and error-free.
====================Full response====================

I am Qwen, a large-scale language model independently developed by Tongyi Lab under Alibaba Group. I can handle various tasks like answering questions, creating text, logical reasoning, and programming, supporting multiple languages including Chinese and English. If you have any questions or need help, feel free to tell me anytime!

Kode contoh

curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.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
}'

Tanggapan

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://{WorkspaceId}.ap-southeast-1.maas.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 Alibaba Cloud Model Studio Anda: api_key = "sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Ganti dengan model berpikir mendalam lainnya sesuai kebutuhan
    model="qwen-plus",
    messages=messages,
    result_format="message", # Model open-source Qwen3 hanya mendukung "message"; untuk pengalaman lebih baik, kami sarankan mengatur ini ke "message" juga untuk model lainnya.
    # 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 mengatur ini ke true juga untuk model lainnya.
)

# Definisikan proses berpikir lengkap
reasoning_content = ""
# Definisikan tanggapan lengkap
answer_content = ""
# Tentukan apakah sudah selesai berpikir dan mulai memberikan tanggapan
is_answering = False

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

for chunk in completion:
    # Jika proses berpikir dan tanggapan keduanya kosong, lewati
    if (
        chunk.output.choices[0].message.content == ""
        and chunk.output.choices[0].message.reasoning_content == ""
    ):
        pass
    else:
        # Jika saat ini dalam tahap 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 saat ini dalam tahap tanggapan
        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 proses berpikir lengkap dan tanggapan lengkap, hapus komentar baris berikut dan jalankan
# print("=" * 20 + "Full thought process" + "=" * 20 + "\n")
# print(f"{reasoning_content}")
# print("=" * 20 + "Full response" + "=" * 20 + "\n")
# print(f"{answer_content}")

Tanggapan

====================Thought process====================
Okay, the user asked: "Who are you?" I need to answer this question. First, clarify my identity as Qwen, a large-scale language model developed by Alibaba Cloud. Next, explain my functions and purposes, like answering questions, creating text, logical reasoning, etc. Also, emphasize my goal of being a helpful assistant.

Keep the expression conversational, avoiding professional jargon or complex sentence structures. Add friendly phrases like "Hello there～" to make the conversation natural. Also, ensure accuracy and don't omit key points like my developer, main functions, and usage scenarios.

Consider possible follow-up questions from the user, such as specific application examples or technical details, so subtly hint at further inquiries in the response. For example, mention "Whether it's everyday questions or professional issues, I'll do my best to help," which is both comprehensive and open-ended.

Finally, check for fluency, repetition, or redundant information to keep the response concise. Maintain a balance between friendliness and professionalism so users feel both approachable and reliable.
====================Full response====================
Hello there～ I'm Qwen, a large-scale language model developed by Alibaba Cloud. I can answer questions, create text, perform logical reasoning, programming, and more, aiming to provide help and support. Whether it's everyday questions or professional issues, I'll do my best to help. How can I assist you?

Kode contoh

// dashscope SDK versi >= 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://{WorkspaceId}.ap-southeast-1.maas.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("====================Thought 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 Alibaba Cloud 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);
    }
}

Tanggapan

====================Thought process====================
Okay, the user asked "Who are you?", so I need to answer based on previous settings. First, my role is Qwen, a large-scale language model under Alibaba Group. Keep it conversational and simple.

The user might be new to me or confirming my identity. Start by directly stating who I am, then briefly explain my functions and purposes, like answering questions, creating text, programming, etc. Also mention multilingual support so users know I handle different languages.

Also, per guidelines, maintain human-like qualities, so use a friendly tone, maybe add emojis for warmth. Guide users to ask further questions or use my features, like asking what they need help with.

Avoid complex terms and keep it concise. Check for missing key points like multilingual support and specific capabilities. Ensure the response meets all requirements, including conversational style and simplicity.
====================Full response====================
Hello! I'm Qwen, a large-scale language model under Alibaba Group. I can answer questions, create text like stories, official documents, emails, scripts, perform logical reasoning, programming, express opinions, play games, and more. I'm proficient in multiple languages, including but not limited to Chinese, English, German, French, and Spanish. How can I help you?

Kode contoh

# ======= Catatan penting =======
# Kunci API berbeda-beda per wilayah. Dapatkan Kunci API Anda: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# URL wilayah Singapura. Ganti {WorkspaceId} dengan ID ruang kerja aktual Anda. URL berbeda-beda per wilayah.
# === Hapus komentar ini sebelum menjalankan ===
curl -X POST "https://{WorkspaceId}.ap-southeast-1.maas.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"
    }
}'

Tanggapan

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
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id:3
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id:4
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id:5
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......

id:358
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id:359
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id:360
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id:361
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id:362
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id:363
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id:364
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id:365
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