API 使用文档

import openai

client = openai.OpenAI(
    base_url="https://api.kanghuiai.com/v1",
    api_key="sk-xxxxx你的API密钥xxxxx"
)

response = client.chat.completions.create(
    model="GLM-5.3-Flash",
    messages=[
        {"role": "system", "content": "你是一个有用的AI助手"},
        {"role": "user", "content": "你好，请介绍一下自己"}
    ],
    temperature=0.7
)

print(response.choices[0].message.content)

const OpenAI = require('openai');

const client = new OpenAI({
    baseURL: 'https://api.kanghuiai.com/v1',
    apiKey: 'sk-xxxxx你的API密钥xxxxx'
});

async function chat() {
    const response = await client.chat.completions.create({
        model: 'GLM-5.3-Flash',
        messages: [
            {role: 'system', content: '你是一个有用的AI助手'},
            {role: 'user', content: '你好，请介绍一下自己'}
        ],
        temperature: 0.7
    });
    
    console.log(response.choices[0].message.content);
}

chat();

import com.theokanning.openai.client.OpenAiApi;
import com.theokanning.openai.completion.chat.ChatCompletionRequest;
import com.theokanning.openai.completion.chat.ChatMessage;
import com.theokanning.openai.service.OpenAiService;
import retrofit2.Retrofit;
import retrofit2.converter.jackson.JacksonConverterFactory;

import java.util.Arrays;

public class Example {
    public static void main(String[] args) {
        String baseUrl = "https://api.kanghuiai.com/v1/";
        String apiKey = "sk-xxxxx你的API密钥xxxxx";
        
        Retrofit retrofit = new Retrofit.Builder()
            .baseUrl(baseUrl)
            .addConverterFactory(JacksonConverterFactory.create())
            .build();
            
        OpenAiApi api = retrofit.create(OpenAiApi.class);
        OpenAiService service = new OpenAiService(api, apiKey);
        
        ChatCompletionRequest request = ChatCompletionRequest.builder()
            .model("GLM-5.3-Flash")
            .messages(Arrays.asList(
                new ChatMessage("system", "你是一个有用的AI助手"),
                new ChatMessage("user", "你好，请介绍一下自己")
            ))
            .temperature(0.7)
            .build();
            
        String response = service.createChatCompletion(request)
            .getChoices()
            .get(0)
            .getMessage()
            .getContent();
            
        System.out.println(response);
    }
}

package main

import (
    "context"
    "fmt"
    "log"

    "github.com/sashabaranov/go-openai"
)

func main() {
    config := openai.DefaultConfig("sk-xxxxx你的API密钥xxxxx")
    config.BaseURL = "https://api.kanghuiai.com/v1"
    client := openai.NewClientWithConfig(config)
    
    resp, err := client.CreateChatCompletion(
        context.Background(),
        openai.ChatCompletionRequest{
            Model: "GLM-5.3-Flash",
            Messages: []openai.ChatCompletionMessage{
                {
                    Role:    openai.ChatMessageRoleSystem,
                    Content: "你是一个有用的AI助手",
                },
                {
                    Role:    openai.ChatMessageRoleUser,
                    Content: "你好，请介绍一下自己",
                },
            },
            Temperature: 0.7,
        },
    )
    
    if err != nil {
        log.Fatal(err)
    }
    
    fmt.Println(resp.Choices[0].Message.Content)
}