Responses API

使用 OpenAI Responses 格式调用文本模型

POST /v1/responses

Responses API

cURL

curl --request POST \
  --url https://api.chenyu.cn/v1/responses \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "<string>",
  "input": {},
  "stream": true,
  "temperature": 123,
  "max_output_tokens": 123,
  "reasoning": {}
}
'

import requests

url = "https://api.chenyu.cn/v1/responses"

payload = {
    "model": "<string>",
    "input": {},
    "stream": True,
    "temperature": 123,
    "max_output_tokens": 123,
    "reasoning": {}
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: '<string>',
    input: {},
    stream: true,
    temperature: 123,
    max_output_tokens: 123,
    reasoning: {}
  })
};

fetch('https://api.chenyu.cn/v1/responses', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.chenyu.cn/v1/responses",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'model' => '<string>',
    'input' => [
        
    ],
    'stream' => true,
    'temperature' => 123,
    'max_output_tokens' => 123,
    'reasoning' => [
        
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.chenyu.cn/v1/responses"

	payload := strings.NewReader("{\n  \"model\": \"<string>\",\n  \"input\": {},\n  \"stream\": true,\n  \"temperature\": 123,\n  \"max_output_tokens\": 123,\n  \"reasoning\": {}\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.chenyu.cn/v1/responses")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"<string>\",\n  \"input\": {},\n  \"stream\": true,\n  \"temperature\": 123,\n  \"max_output_tokens\": 123,\n  \"reasoning\": {}\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.chenyu.cn/v1/responses")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"model\": \"<string>\",\n  \"input\": {},\n  \"stream\": true,\n  \"temperature\": 123,\n  \"max_output_tokens\": 123,\n  \"reasoning\": {}\n}"

response = http.request(request)
puts response.read_body

200

{
  "id": "<string>",
  "object": "<string>",
  "status": "<string>",
  "model": "<string>",
  "output": [
    {}
  ],
  "usage": {}
}

Responses API

使用 OpenAI Responses 兼容格式调用文本模型。适合使用 input 组织请求，或需要携带模型专属参数的场景。

请求参数

model · string · required

模型 ID。可通过 模型列表 查询

input · string | array · required

输入内容。可以是字符串，也可以是 Responses 格式的输入数组

stream · boolean

是否使用流式响应

temperature · number

采样温度

max_output_tokens · integer

最大输出 token 数

reasoning · object

推理相关参数，具体支持范围以模型为准

响应参数

id · string

响应 ID

object · string

响应类型，通常为 response

status · string

响应状态，如 completed

model · string

实际调用的模型 ID

output · array

输出内容数组

usage · object

token 用量

代码示例

Python

import requests

url = "https://api.chenyu.cn/v1/responses"
headers = {
    "Authorization": "Bearer your_api_key",
    "Content-Type": "application/json"
}
payload = {
    "model": "doubao-seed-2-0-lite-260428",
    "input": "用三句话说明 GPU 云服务适合哪些场景"
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

const axios = require('axios');

axios.post('https://api.chenyu.cn/v1/responses', {
  model: 'doubao-seed-2-0-lite-260428',
  input: '用三句话说明 GPU 云服务适合哪些场景'
}, {
  headers: {
    Authorization: 'Bearer your_api_key',
    'Content-Type': 'application/json'
  }
}).then((response) => {
  console.log(response.data);
});

curl -X POST "https://api.chenyu.cn/v1/responses" \
  -H "Authorization: Bearer your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seed-2-0-lite-260428",
    "input": "用三句话说明 GPU 云服务适合哪些场景"
  }'

模型专属参数

{
  "model": "doubao-seed-2-0-lite-260428",
  "input": "分析这个问题",
  "thinking": {"type": "enabled"},
  "reasoning": {"effort": "low"}
}

响应示例

{
  "id": "resp_xxx",
  "object": "response",
  "status": "completed",
  "model": "doubao-seed-2-0-lite-260428",
  "output": [
    {
      "type": "message",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "GPU 云服务适合模型训练、推理部署和批量数据处理。"
        }
      ]
    }
  ],
  "usage": {
    "input_tokens": 18,
    "output_tokens": 16,
    "total_tokens": 34
  }
}