Генерация текста Qwen3.8-Max

response = client.chat.completions.create(
    model="qwen3.8-max",
    messages=[{"role": "user", "content": "Hello"}],
    reasoning_effort="none",
    max_tokens=500,
)

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-apiyi-key",
    base_url="https://api.apiyi.com/v1"
)

# Everyday chat: thinking off, fast and cheap
resp = client.chat.completions.create(
    model="qwen3.8-max",
    messages=[{"role": "user", "content": "Explain load balancing in one sentence."}],
    reasoning_effort="none",
    max_tokens=500,
)
print(resp.choices[0].message.content)

# Hard reasoning: keep the default thinking tier
resp = client.chat.completions.create(
    model="qwen3.8-max",
    messages=[{"role": "user", "content": "Prove that among any 5 integers, some 3 sum to a multiple of 3."}],
    max_tokens=4000,
)
print(resp.choices[0].message.reasoning_content)  # thinking trace
print(resp.choices[0].message.content)            # final answer

import base64

with open("chart.png", "rb") as f:
    b64 = base64.b64encode(f.read()).decode()

resp = client.chat.completions.create(
    model="qwen3.8-max",
    messages=[{"role": "user", "content": [
        {"type": "text", "text": "What number is written in this image?"},
        {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64}"}},
    ]}],
    max_tokens=500,
)

resp = client.chat.completions.create(
    model="qwen3.8-max",
    messages=[{"role": "user", "content": [
        {"type": "text", "text": "What happens in this video?"},
        {"type": "video_url", "video_url": {"url": f"data:video/mp4;base64,{b64_video}"}},
    ]}],
    max_tokens=1000,
)

curl https://api.apiyi.com/v1/chat/completions \
  -H "Authorization: Bearer sk-your-apiyi-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.8-max",
    "messages": [{"role": "user", "content": "Hello"}],
    "reasoning_effort": "none"
  }'

resp = client.chat.completions.create(
    model="qwen3.8-max",
    messages=[{"role": "user", "content": "What's the weather in Beijing?"}],
    tools=tools,
    tool_choice={"type": "function", "function": {"name": "get_weather"}},
    reasoning_effort="none",   # required
)

def strip_thinking(blocks):
    return [b for b in blocks if b.get("type") != "thinking"]

messages.append({"role": "assistant", "content": strip_thinking(resp["content"])})