OpenAI 基础对话示例

以下示例展示如何使用OpenAI兼容的 /v1/chat/completions 接口进行基础文本对话。

快速开始

只需要替换 <API-KEY> 为你的实际API密钥即可运行。

curl -X POST "https://api.tokenops.ai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <API-KEY>" \
  -d '{
    "model": "gpt-5-2025-08-07",
    "messages": [
      {
        "role": "user",
        "content": "你好，请介绍一下你自己"
      }
    ],
    "max_tokens": 1000,
    "temperature": 1
  }'

import requests
import json

# 配置API密钥和基础URL
API_KEY = "<API-KEY>"
BASE_URL = "https://api.tokenops.ai/v1"

def chat_with_ai(message):
    url = f"{BASE_URL}/chat/completions"
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {API_KEY}"
    }
    
    data = {
        "model": "gpt-5-2025-08-07",
        "messages": [
            {
                "role": "user",
                "content": message
            }
        ],
        "max_tokens": 1000,
        "temperature": 1
    }
    
    response = requests.post(url, headers=headers, json=data)
    
    if response.status_code == 200:
        result = response.json()
        return result['choices'][0]['message']['content']
    else:
        return f"错误: {response.status_code} - {response.text}"

# 使用示例
if __name__ == "__main__":
    message = "你好，请介绍一下你自己"
    reply = chat_with_ai(message)
    print(f"AI回复: {reply}")

const axios = require('axios');

// 配置API密钥和基础URL
const API_KEY = '<API-KEY>';
const BASE_URL = 'https://api.tokenops.ai/v1';

async function chatWithAI(message) {
    const url = `${BASE_URL}/chat/completions`;
    
    const headers = {
        'Content-Type': 'application/json',
        'Authorization': `Bearer ${API_KEY}`
    };
    
    const data = {
        model: 'gpt-5-2025-08-07',
        messages: [
            {
                role: 'user',
                content: message
            }
        ],
        max_tokens: 1000,
        temperature: 1
    };
    
    try {
        const response = await axios.post(url, data, { headers });
        return response.data.choices[0].message.content;
    } catch (error) {
        return `错误: ${error.response?.status} - ${error.response?.data || error.message}`;
    }
}

// 使用示例
(async () => {
    const message = '你好，请介绍一下你自己';
    const reply = await chatWithAI(message);
    console.log(`AI回复: ${reply}`);
})();

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io"
    "net/http"
)

const (
    APIKey  = "<API-KEY>"
    BaseURL = "https://api.tokenops.ai/v1"
)

type Message struct {
    Role    string `json:"role"`
    Content string `json:"content"`
}

type ChatRequest struct {
    Model       string    `json:"model"`
    Messages    []Message `json:"messages"`
    MaxTokens   int       `json:"max_tokens"`
    Temperature float64   `json:"temperature"`
}

type Choice struct {
    Message Message `json:"message"`
}

type ChatResponse struct {
    Choices []Choice `json:"choices"`
}

func chatWithAI(message string) (string, error) {
    url := fmt.Sprintf("%s/chat/completions", BaseURL)
    
    reqData := ChatRequest{
        Model: "gpt-5-2025-08-07",
        Messages: []Message{
            {
                Role:    "user",
                Content: message,
            },
        },
        MaxTokens:   1000,
        Temperature: 1,
    }
    
    jsonData, err := json.Marshal(reqData)
    if err != nil {
        return "", err
    }
    
    req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    if err != nil {
        return "", err
    }
    
    req.Header.Set("Content-Type", "application/json")
    req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", APIKey))
    
    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        return "", err
    }
    defer resp.Body.Close()
    
    body, err := io.ReadAll(resp.Body)
    if err != nil {
        return "", err
    }
    
    if resp.StatusCode != 200 {
        return "", fmt.Errorf("API错误: %d - %s", resp.StatusCode, string(body))
    }
    
    var chatResp ChatResponse
    err = json.Unmarshal(body, &chatResp)
    if err != nil {
        return "", err
    }
    
    return chatResp.Choices[0].Message.Content, nil
}

func main() {
    message := "你好，请介绍一下你自己"
    reply, err := chatWithAI(message)
    if err != nil {
        fmt.Printf("错误: %v\n", err)
        return
    }
    
    fmt.Printf("AI回复: %s\n", reply)
}

import java.io.IOException;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.JsonNode;

public class OpenAIBasicChat {
    private static final String API_KEY = "<API-KEY>";
    private static final String BASE_URL = "https://api.tokenops.ai/v1";
    
    public static class Message {
        public String role;
        public String content;
        
        public Message(String role, String content) {
            this.role = role;
            this.content = content;
        }
    }
    
    public static class ChatRequest {
        public String model;
        public Message[] messages;
        public int max_tokens;
        public double temperature;
        
        public ChatRequest(String model, Message[] messages, int maxTokens, double temperature) {
            this.model = model;
            this.messages = messages;
            this.max_tokens = maxTokens;
            this.temperature = temperature;
        }
    }
    
    public static String chatWithAI(String message) throws IOException, InterruptedException {
        HttpClient client = HttpClient.newHttpClient();
        ObjectMapper mapper = new ObjectMapper();
        
        ChatRequest request = new ChatRequest(
            "gpt-5-2025-08-07",
            new Message[]{new Message("user", message)},
            1000,
            0.7
        );
        
        String jsonBody = mapper.writeValueAsString(request);
        
        HttpRequest httpRequest = HttpRequest.newBuilder()
            .uri(URI.create(BASE_URL + "/chat/completions"))
            .header("Content-Type", "application/json")
            .header("Authorization", "Bearer " + API_KEY)
            .POST(HttpRequest.BodyPublishers.ofString(jsonBody))
            .build();
        
        HttpResponse<String> response = client.send(httpRequest, HttpResponse.BodyHandlers.ofString());
        
        if (response.statusCode() == 200) {
            JsonNode jsonResponse = mapper.readTree(response.body());
            return jsonResponse.get("choices").get(0).get("message").get("content").asText();
        } else {
            throw new RuntimeException("API错误: " + response.statusCode() + " - " + response.body());
        }
    }
    
    public static void main(String[] args) {
        try {
            String message = "你好，请介绍一下你自己";
            String reply = chatWithAI(message);
            System.out.println("AI回复: " + reply);
        } catch (Exception e) {
            System.err.println("错误: " + e.getMessage());
        }
    }
}

<?php

class OpenAIBasicChat {
    private $apiKey;
    private $baseUrl;
    
    public function __construct($apiKey, $baseUrl = 'https://api.tokenops.ai/v1') {
        $this->apiKey = $apiKey;
        $this->baseUrl = $baseUrl;
    }
    
    public function chatWithAI($message) {
        $url = $this->baseUrl . '/chat/completions';
        
        $data = [
            'model' => 'gpt-5-2025-08-07',
            'messages' => [
                [
                    'role' => 'user',
                    'content' => $message
                ]
            ],
            'max_tokens' => 1000,
            'temperature' => 1
        ];
        
        $options = [
            'http' => [
                'header' => [
                    'Content-Type: application/json',
                    'Authorization: Bearer ' . $this->apiKey
                ],
                'method' => 'POST',
                'content' => json_encode($data)
            ]
        ];
        
        $context = stream_context_create($options);
        $response = file_get_contents($url, false, $context);
        
        if ($response === FALSE) {
            return '请求失败';
        }
        
        $responseData = json_decode($response, true);
        
        if (isset($responseData['choices'][0]['message']['content'])) {
            return $responseData['choices'][0]['message']['content'];
        } else {
            return '解析响应失败: ' . $response;
        }
    }
}

// 使用示例
$apiKey = '<API-KEY>';
$chat = new OpenAIBasicChat($apiKey);

$message = '你好，请介绍一下你自己';
$reply = $chat->chatWithAI($message);

echo "AI回复: " . $reply . "\n";

?>

结果示例

200

{
  "id": "165842b19b554b72a471aa73168f8d7c",
  "object": "chat.completion",
  "created": 1759131775,
  "model": "gpt-5-2025-08-07",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "你好！我是你的智能助手，可以用中文或英文和你交流，帮你查找与整理信息、解释概念、写作与改稿、生成和调试代码、做数学与数据分析、制定计划与建议，以及创意发想等。\n\n我的工作方式与特点：\n- 注重清晰与可操作性：会给出分步骤的思路、可执行的方案与示例。\n- 善于追问与澄清：如果问题不够明确，我会先确认需求以避免走偏。\n- 多语言支持：中文、英文为主，也可处理其他常见语言的文本。\n- 知识范围：训练数据覆盖到 2024年10月，之后的最新变化可能不了解；如需最新信息，建议提供来源或具体细节。\n\n使用和安全说明：\n- 隐私：除非你在对话中提供，我无法访问你的个人数据；我也不会在不同对话间记忆你的信息。\n- 局限：可能会出错或过时，涉及重要决策（医疗、法律、金融等）请务必二次核对或咨询专业人士。\n- 外部能力：我不能直接在现实世界执行操作（如下单、打电话），但可以提供步骤指导与模板。\n\n你可以这样和我合作：\n- 给出目标与约束（时间、预算、受众、风格）。\n- 提供已有材料或偏好，我可在此基础上优化。\n- 要代码时说明环境与语言版本；要写作时说明语气与字数。\n\n很高兴认识你！你今天想做什么？我可以先从一个具体问题或任务开始帮你。"
      },
      "finish_reason": "stop",
      "content_filter_results": {
        "hate": {
          "filtered": false
        },
        "self_harm": {
          "filtered": false
        },
        "sexual": {
          "filtered": false
        },
        "violence": {
          "filtered": false
        },
        "jailbreak": {
          "filtered": false,
          "detected": false
        },
        "profanity": {
          "filtered": false,
          "detected": false
        }
      }
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 758,
    "total_tokens": 770,
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    },
    "completion_tokens_details": {
      "audio_tokens": 0,
      "reasoning_tokens": 384,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "system_fingerprint": ""
}

重要参数说明

model: 指定要使用的模型，如 gpt-5-2025-08-07、gpt-5-2025-08-07-mini、gpt-3.5-turbo 等
messages: 对话消息数组，包含角色（role）和内容（content）
max_tokens: 最大生成token数量，控制回复长度
temperature: 控制回复的随机性，注意：gpt-5-2025-08-07 模型仅支持默认值 1