文本与多模态对话

使用 OpenAI Chat Completions 格式调用文本和视觉模型

POST /v1/chat/completions

文本与多模态对话

cURL

curl --request POST \
  --url https://api.chenyu.cn/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "<string>",
  "messages": [
    {}
  ],
  "messages[].role": "<string>",
  "messages[].content": {},
  "stream": true,
  "temperature": 123,
  "max_tokens": 123
}
'

import requests

url = "https://api.chenyu.cn/v1/chat/completions"

payload = {
    "model": "<string>",
    "messages": [{}],
    "messages[].role": "<string>",
    "messages[].content": {},
    "stream": True,
    "temperature": 123,
    "max_tokens": 123
}
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>',
    messages: [{}],
    'messages[].role': '<string>',
    'messages[].content': {},
    stream: true,
    temperature: 123,
    max_tokens: 123
  })
};

fetch('https://api.chenyu.cn/v1/chat/completions', 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/chat/completions",
  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>',
    'messages' => [
        [
                
        ]
    ],
    'messages[].role' => '<string>',
    'messages[].content' => [
        
    ],
    'stream' => true,
    'temperature' => 123,
    'max_tokens' => 123
  ]),
  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/chat/completions"

	payload := strings.NewReader("{\n  \"model\": \"<string>\",\n  \"messages\": [\n    {}\n  ],\n  \"messages[].role\": \"<string>\",\n  \"messages[].content\": {},\n  \"stream\": true,\n  \"temperature\": 123,\n  \"max_tokens\": 123\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/chat/completions")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"<string>\",\n  \"messages\": [\n    {}\n  ],\n  \"messages[].role\": \"<string>\",\n  \"messages[].content\": {},\n  \"stream\": true,\n  \"temperature\": 123,\n  \"max_tokens\": 123\n}")
  .asString();

require 'uri'
require 'net/http'

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

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  \"messages\": [\n    {}\n  ],\n  \"messages[].role\": \"<string>\",\n  \"messages[].content\": {},\n  \"stream\": true,\n  \"temperature\": 123,\n  \"max_tokens\": 123\n}"

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

200

{
  "id": "<string>",
  "object": "<string>",
  "model": "<string>",
  "choices": [
    {
      "message.role": "<string>",
      "message.content": "<string>",
      "finish_reason": "<string>"
    }
  ],
  "usage": {}
}

文本与多模态对话

使用 OpenAI Chat Completions 兼容格式调用文本模型或视觉模型。支持普通文本、图片输入、多图输入和流式响应。

请求参数

model · string · required

模型 ID。可通过 模型列表 查询

messages · array · required

对话消息列表

messages[].role · string · required

消息角色，支持 system、user、assistant

messages[].content · string | array · required

消息内容。文本模型可传字符串；视觉模型可传 OpenAI 多模态 content 数组

stream · boolean

是否使用 Server-Sent Events 流式响应

temperature · number

采样温度

max_tokens · integer

最大输出 token 数

响应参数

id · string

响应 ID

object · string

响应类型，通常为 chat.completion

model · string

实际调用的模型 ID

choices · array

输出候选列表

Show choices

message.role · string

输出消息角色

message.content · string

输出文本

finish_reason · string

停止原因

usage · object

token 用量

代码示例

Python

import requests

url = "https://api.chenyu.cn/v1/chat/completions"
headers = {
    "Authorization": "Bearer your_api_key",
    "Content-Type": "application/json"
}
payload = {
    "model": "doubao-seed-2-0-lite-260428",
    "messages": [
        {"role": "user", "content": "你好，简单介绍一下你自己"}
    ]
}

response = requests.post(url, headers=headers, json=payload)
print(response.json()["choices"][0]["message"]["content"])

const axios = require('axios');

axios.post('https://api.chenyu.cn/v1/chat/completions', {
  model: 'doubao-seed-2-0-lite-260428',
  messages: [
    { role: 'user', content: '你好，简单介绍一下你自己' }
  ]
}, {
  headers: {
    Authorization: 'Bearer your_api_key',
    'Content-Type': 'application/json'
  }
}).then((response) => {
  console.log(response.data.choices[0].message.content);
});

curl -X POST "https://api.chenyu.cn/v1/chat/completions" \
  -H "Authorization: Bearer your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seed-2-0-lite-260428",
    "messages": [
      {"role": "user", "content": "你好，简单介绍一下你自己"}
    ]
  }'

多模态示例

{
  "model": "doubao-seed-1-6-vision-250815",
  "messages": [
    {
      "role": "user",
      "content": [
        {"type": "text", "text": "这张图片里有什么？"},
        {
          "type": "image_url",
          "image_url": {
            "url": "https://example.com/image.png"
          }
        }
      ]
    }
  ]
}

响应示例

{
  "id": "chatcmpl_xxx",
  "object": "chat.completion",
  "created": 1780000000,
  "model": "doubao-seed-2-0-lite-260428",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "你好，我是晨羽智云大模型服务。"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 20,
    "completion_tokens": 12,
    "total_tokens": 32
  }
}