项目

GPT-5.5

GPT-5.5-Pro

上下文上限

1M tokens

1M tokens

推理精准度

常规水准

幻觉概率极低，行业顶尖，支持多轮校验

响应速度

响应迅速（单轮请求100ms-300ms）

偏慢（单轮请求500ms-1000ms），侧重深度推演

调用成本

相对亲民

偏高

推理架构

轻量化推理引擎，单链路推演

增强型推理引擎，多轮交叉验证

支持功能

基础文本生成、简单工具调用

高精度推理、复杂工具调用、长文本校对

python
import requests
import time

# 基础配置
api_url = "https://startapi.top/v1"
api_key = "填写个人API密钥"
max_retries = 3  # 最大重试次数
retry_interval = 1  # 重试间隔（秒）

def ai_chat(model_name, user_content, temperature=0.2):
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json"
    }
    post_data = {
        "model": model_name,
        "messages": [{"role": "user", "content": user_content}],
        "temperature": temperature,
        "top_p": 0.9  # 补充参数，优化输出多样性（Pro版可精细化调节）
    }
    # 重试机制
    for retry in range(max_retries):
        try:
            result = requests.post(
                f"{api_url}/chat/completions",
                headers=headers,
                json=post_data,
                timeout=10  # 设置超时时间，避免请求阻塞
            )
            # 状态码判断
            if result.status_code == 200:
                return result.json()
            elif result.status_code == 429:
                print(f"请求过于频繁，第{retry+1}次重试...")
                time.sleep(retry_interval)
                continue
            else:
                print(f"接口请求失败，状态码：{result.status_code}，响应内容：{result.text}")
                return None
        except requests.exceptions.Timeout:
            print(f"请求超时，第{retry+1}次重试...")
            time.sleep(retry_interval)
        except requests.exceptions.ConnectionError:
            print(f"网络连接异常，第{retry+1}次重试...")
            time.sleep(retry_interval)
        except Exception as e:
            print(f"请求异常：{str(e)}")
            return None
    print("达到最大重试次数，请求失败")
    return None

# GPT-5.5 调用（通用场景，基础参数）
# print(ai_chat("gpt-5.5", "编写简易接口请求工具类", temperature=0.5))

# GPT-5.5-Pro 调用（高精度场景，精细化参数）
# print(ai_chat("gpt-5.5-pro", "梳理复杂业务逻辑并排查漏洞", temperature=0.1, top_p=0.8))

java
import okhttp3.*;
import org.json.JSONObject;
import java.io.IOException;

public class AiChatDemo {
    private static final String API_URL = "https://startapi.top/v1/chat/completions";
    private static final String API_KEY = "填写个人API密钥";
    private static final OkHttpClient client = new OkHttpClient();

    public static String aiChat(String modelName, String userContent) throws IOException {
        // 请求头配置
        Headers headers = new Headers.Builder()
                .add("Authorization", "Bearer " + API_KEY)
                .add("Content-Type", "application/json")
                .build();

        // 请求体配置
        JSONObject requestBody = new JSONObject();
        requestBody.put("model", modelName);
        requestBody.put("temperature", 0.2);
        // 构建消息体
        JSONObject message = new JSONObject();
        message.put("role", "user");
        message.put("content", userContent);
        requestBody.put("messages", new JSONArray().put(message));

        // 发起POST请求
        Request request = new Request.Builder()
                .url(API_URL)
                .headers(headers)
                .post(RequestBody.create(MediaType.parse("application/json"), requestBody.toString()))
                .build();

        try (Response response = client.newCall(request).execute()) {
            if (!response.isSuccessful()) throw new IOException("请求失败：" + response);
            return response.body().string();
        }
    }

    // 测试调用
    public static void main(String[] args) {
        try {
            // GPT-5.5 调用
            String result1 = aiChat("gpt-5.5", "编写简易Java工具类");
            System.out.println(result1);

            // GPT-5.5-Pro 调用
            String result2 = aiChat("gpt-5.5-pro", "分析Java代码中的内存泄漏风险");
            System.out.println(result2);
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
}