创建聊天对话

POST

chat

completions

创建聊天对话

curl --request POST \
  --url https://api.lmm.best/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "gpt-4",
  "messages": [
    {
      "content": "<string>",
      "name": "<string>",
      "tool_calls": [
        {
          "id": "<string>",
          "type": "function",
          "function": {
            "name": "<string>",
            "arguments": "<string>"
          }
        }
      ],
      "tool_call_id": "<string>",
      "reasoning_content": "<string>"
    }
  ]
}
'

import requests

url = "https://api.lmm.best/v1/chat/completions"

payload = {
    "model": "gpt-4",
    "messages": [
        {
            "content": "<string>",
            "name": "<string>",
            "tool_calls": [
                {
                    "id": "<string>",
                    "type": "function",
                    "function": {
                        "name": "<string>",
                        "arguments": "<string>"
                    }
                }
            ],
            "tool_call_id": "<string>",
            "reasoning_content": "<string>"
        }
    ]
}
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: 'gpt-4',
    messages: [
      {
        content: '<string>',
        name: '<string>',
        tool_calls: [
          {
            id: '<string>',
            type: 'function',
            function: {name: '<string>', arguments: '<string>'}
          }
        ],
        tool_call_id: '<string>',
        reasoning_content: '<string>'
      }
    ]
  })
};

fetch('https://api.lmm.best/v1/chat/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

package main

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

func main() {

	url := "https://api.lmm.best/v1/chat/completions"

	payload := strings.NewReader("{\n  \"model\": \"gpt-4\",\n  \"messages\": [\n    {\n      \"content\": \"<string>\",\n      \"name\": \"<string>\",\n      \"tool_calls\": [\n        {\n          \"id\": \"<string>\",\n          \"type\": \"function\",\n          \"function\": {\n            \"name\": \"<string>\",\n            \"arguments\": \"<string>\"\n          }\n        }\n      ],\n      \"tool_call_id\": \"<string>\",\n      \"reasoning_content\": \"<string>\"\n    }\n  ]\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))

}

{
  "id": "<string>",
  "object": "chat.completion",
  "created": 123,
  "model": "<string>",
  "choices": [
    {
      "index": 123,
      "message": {
        "role": "system",
        "content": "<string>",
        "name": "<string>",
        "tool_calls": [
          {
            "id": "<string>",
            "type": "function",
            "function": {
              "name": "<string>",
              "arguments": "<string>"
            }
          }
        ],
        "tool_call_id": "<string>",
        "reasoning_content": "<string>"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123,
    "prompt_tokens_details": {
      "cached_tokens": 123,
      "text_tokens": 123,
      "audio_tokens": 123,
      "image_tokens": 123
    },
    "completion_tokens_details": {
      "text_tokens": 123,
      "audio_tokens": 123,
      "reasoning_tokens": 123
    }
  },
  "system_fingerprint": "<string>"
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

授权

Authorization

string

header

必填

使用 Bearer Token 认证。格式: Authorization: Bearer sk-xxxxxx

请求体

application/json

model

string

必填

模型 ID

示例:

"gpt-4"

messages

object[]

必填

对话消息列表

Show child attributes

temperature

number

默认值:1

采样温度

必填范围: 0 <= x <= 2

top_p

number

默认值:1

核采样参数

必填范围: 0 <= x <= 1

integer

默认值:1

生成数量

必填范围: x >= 1

stream

boolean

默认值:false

是否流式响应

stream_options

object

Show child attributes

stop

停止序列

max_tokens

integer

最大生成 Token 数

max_completion_tokens

integer

最大补全 Token 数

presence_penalty

number

默认值:0

必填范围: -2 <= x <= 2

frequency_penalty

number

默认值:0

必填范围: -2 <= x <= 2

logit_bias

object

Show child attributes

user

string

tools

object[]

Show child attributes

tool_choice

可用选项:

none,

auto,

required

response_format

object

Show child attributes

seed

integer

reasoning_effort

enum<string>

推理强度 (用于支持推理的模型)

可用选项:

low,

medium,

high

modalities

enum<string>[]

可用选项:

text,

audio

audio

object

Show child attributes

响应

成功创建响应

string

object

string

示例:

"chat.completion"

created

integer

model

string

choices

object[]

Show child attributes

usage

object

Show child attributes

system_fingerprint

string

最后修改于 2026年9月23日

创建聊天对话

curl --request POST \
  --url https://api.lmm.best/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "gpt-4",
  "messages": [
    {
      "content": "<string>",
      "name": "<string>",
      "tool_calls": [
        {
          "id": "<string>",
          "type": "function",
          "function": {
            "name": "<string>",
            "arguments": "<string>"
          }
        }
      ],
      "tool_call_id": "<string>",
      "reasoning_content": "<string>"
    }
  ]
}
'

import requests

url = "https://api.lmm.best/v1/chat/completions"

payload = {
    "model": "gpt-4",
    "messages": [
        {
            "content": "<string>",
            "name": "<string>",
            "tool_calls": [
                {
                    "id": "<string>",
                    "type": "function",
                    "function": {
                        "name": "<string>",
                        "arguments": "<string>"
                    }
                }
            ],
            "tool_call_id": "<string>",
            "reasoning_content": "<string>"
        }
    ]
}
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: 'gpt-4',
    messages: [
      {
        content: '<string>',
        name: '<string>',
        tool_calls: [
          {
            id: '<string>',
            type: 'function',
            function: {name: '<string>', arguments: '<string>'}
          }
        ],
        tool_call_id: '<string>',
        reasoning_content: '<string>'
      }
    ]
  })
};

fetch('https://api.lmm.best/v1/chat/completions', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

package main

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

func main() {

	url := "https://api.lmm.best/v1/chat/completions"

	payload := strings.NewReader("{\n  \"model\": \"gpt-4\",\n  \"messages\": [\n    {\n      \"content\": \"<string>\",\n      \"name\": \"<string>\",\n      \"tool_calls\": [\n        {\n          \"id\": \"<string>\",\n          \"type\": \"function\",\n          \"function\": {\n            \"name\": \"<string>\",\n            \"arguments\": \"<string>\"\n          }\n        }\n      ],\n      \"tool_call_id\": \"<string>\",\n      \"reasoning_content\": \"<string>\"\n    }\n  ]\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))

}

{
  "id": "<string>",
  "object": "chat.completion",
  "created": 123,
  "model": "<string>",
  "choices": [
    {
      "index": 123,
      "message": {
        "role": "system",
        "content": "<string>",
        "name": "<string>",
        "tool_calls": [
          {
            "id": "<string>",
            "type": "function",
            "function": {
              "name": "<string>",
              "arguments": "<string>"
            }
          }
        ],
        "tool_call_id": "<string>",
        "reasoning_content": "<string>"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123,
    "prompt_tokens_details": {
      "cached_tokens": 123,
      "text_tokens": 123,
      "audio_tokens": 123,
      "image_tokens": 123
    },
    "completion_tokens_details": {
      "text_tokens": 123,
      "audio_tokens": 123,
      "reasoning_tokens": 123
    }
  },
  "system_fingerprint": "<string>"
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": "<string>",
    "code": "<string>"
  }
}

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