OpenAI SDK v2 完全指南：2026年 Python/JavaScript/Go 最新用法

OpenAI 在 2025 年发布了 SDK v2，接口全面升级，支持更多模型、更简洁的 API、更强大的流式输出。2026 年了，你的代码跟上 v2 了吗？本文详解 Python、JavaScript、Go 的最新用法。

Python SDK v2（推荐方式）

# 安装
pip install anthropic

# 基础调用
from anthropic import Anthropic

client = Anthropic(
    api_key="sk-holysheep-xxx",
    base_url="https://api.holysheep.ai/v1"
)

# 对话
message = client.messages.create(
    model="gpt-4o",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "用 Python 写一个快速排序"}
    ]
)
print(message.content)

JavaScript/TypeScript SDK v2

# 安装
npm install @anthropic-ai/sdk

# 基础调用
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
    apiKey: 'sk-holysheep-xxx',
    baseURL: 'https://api.holysheep.ai/v1'
});

async function main() {
    const message = await client.messages.create({
        model: 'gpt-4o',
        max_tokens: 1024,
        messages: [
            {"role": "user", "content": "用 JavaScript 写一个快速排序"}
        ]
    });
    console.log(message.content);
}
main();

Go SDK

// 安装
// go get github.com/sashabaranov/go-openai

package main

import (
    "context"
    "fmt"
    openai "github.com/sashabaranov/go-openai"
)

func main() {
    client := openai.NewClient("sk-holysheep-xxx")
    client.BaseURL = "https://api.holysheep.ai/v1"

    resp, err := client.CreateChatCompletion(
        context.Background(),
        openai.ChatCompletionRequest{
            Model: "gpt-4o",
            Messages: []openai.ChatCompletionMessage{
                {Role: "user", Content: "用 Go 写一个快速排序"},
            },
        },
    )
    if err != nil {
        panic(err)
    }
    fmt.Println(resp.Choices[0].Message.Content)
}

流式输出（所有语言）

# Python 流式
with client.messages.stream(
    model="gpt-4o",
    max_tokens=1024,
    messages=[{"role": "user", "content": "写一个 Python 教程"}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Function Calling / Tool Use

# Python Function Calling
tools = [
    {
        "name": "get_weather",
        "description": "获取城市天气",
        "input_schema": {
            "type": "object",
            "properties": {"city": {"type": "string"}},
            "required": ["city"]
        }
    }
]

message = client.messages.create(
    model="gpt-4o",
    max_tokens=1024,
    tools=tools,
    messages=[{"role": "user", "content": "北京天气怎么样？"}]
)

for tool in message.tool_calls:
    print(f"调用工具: {tool.name}")
    print(f"参数: {tool.input}")