Web extractor

import os
from openai import OpenAI

client = OpenAI(
    # Jika variabel lingkungan belum dikonfigurasi, ganti baris berikut dengan api_key="sk-xxx" (tidak disarankan), menggunakan Kunci API Model Studio Anda.
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Wilayah Singapura. Ganti {WorkspaceId} dengan ID Workspace aktual Anda. URL berbeda tergantung wilayah.
    base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
)

stream = client.chat.completions.create(
    model="qwen3-max",
    messages=[
        {"role": "user", "content": "Please visit the official Alibaba Cloud Model Studio documentation for the code interpreter and summarize its main content"}
    ],
    extra_body={
        "enable_thinking": True,
        "enable_search": True,
        "search_options": {"search_strategy": "agent_max"}
    },
    stream=True
)

reasoning_started = False
output_started = False

for chunk in stream:
    if chunk.choices:
        delta = chunk.choices[0].delta
        # Cetak proses berpikir
        if hasattr(delta, 'reasoning_content') and delta.reasoning_content:
            if not reasoning_started:
                print("="*20 + "Thinking Process" + "="*20)
                reasoning_started = True
            print(delta.reasoning_content, end='', flush=True)
        # Cetak konten respons
        if delta.content:
            if not output_started:
                print("\n" + "="*20 + "Response Content" + "="*20)
                output_started = True
            print(delta.content, end='', flush=True)

import os
import dashscope
from dashscope import Generation

# Jika variabel lingkungan belum dikonfigurasi, ganti baris berikut dengan dashscope.api_key = "sk-xxx", menggunakan Kunci API Model Studio Anda.
dashscope.api_key = os.getenv("DASHSCOPE_API_KEY")
# Wilayah Singapura. Ganti {WorkspaceId} dengan ID Workspace aktual Anda. URL berbeda tergantung wilayah.
dashscope.base_http_api_url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1"

response = Generation.call(
    model="qwen3-max",
    messages=[
        {"role": "user", "content": "Please visit the official Alibaba Cloud Model Studio documentation for the code interpreter and summarize its main content"}
    ],
    enable_search=True,
    search_options={"search_strategy": "agent_max"},
    enable_thinking=True,
    result_format="message",
    stream=True,
    incremental_output=True
)

reasoning_started = False
output_started = False

for chunk in response:
    if chunk.status_code == 200:
        message = chunk.output.choices[0].message

        # Cetak proses berpikir
        if hasattr(message, 'reasoning_content') and message.reasoning_content:
            if not reasoning_started:
                print("="*20 + "Thinking Process" + "="*20)
                reasoning_started = True
            print(message.reasoning_content, end='', flush=True)

        # Cetak konten respons
        if hasattr(message, 'content') and message.content:
            if not output_started:
                print("\n" + "="*20 + "Response Content" + "="*20)
                output_started = True
            print(message.content, end='', flush=True)
    else:
        print(f"\nRequest failed: code={chunk.code}, message={chunk.message}")
        break