控制推理模型努力程度

async function main() {
  const headers = {
  "Authorization": "Bearer " + process.env.tokenba_API_KEY,
  "Content-Type": "application/json"
};
  const body = JSON.stringify({
  "model": "gpt-6.1-sol",
  "messages": [
    {
      "role": "user",
      "content": "请解释 1 到 100 的整数之和如何计算。"
    }
  ],
  "reasoning_effort": "medium",
  "max_completion_tokens": 1000,
  "stream": true
});
  const response = await fetch("https://api.apizt.com/v1/chat/completions", { method: "POST", headers, body });
  if (!response.ok) throw new Error("HTTP " + response.status + ": " + await response.text());
  const decoder = new TextDecoder();
  for await (const chunk of response.body) process.stdout.write(decoder.decode(chunk, { stream: true }));
  process.stdout.write(decoder.decode());
}
main().catch(console.error);

import os
import requests

headers = {"Authorization": "Bearer " + os.environ["tokenba_API_KEY"]}
payload = {'model': 'gpt-6.1-sol',
 'messages': [{'role': 'user', 'content': '请解释 1 到 100 的整数之和如何计算。'}],
 'reasoning_effort': 'medium',
 'max_completion_tokens': 1000,
 'stream': True}
response = requests.post('https://api.apizt.com/v1/chat/completions', headers=headers, json=payload, timeout=120, stream=True)
response.raise_for_status()
response.encoding = "utf-8"
for line in response.iter_lines(decode_unicode=True):
    print(line, flush=True)