AI API 调用入门

什么是 AI API

AI API 是一个 HTTP 接口，你发送文本（提示词），它返回 AI 生成的文本（回复）。就像发短信一样 — 你发一条消息，AI 回一条消息。

Anthropic Messages API

Anthropic 的 Claude 使用 Messages API。

curl 示例

curl https://api.anthropic.com/v1/messages \
  -H "content-type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello, Claude!"}
    ]
  }'

Python 示例

import anthropic

client = anthropic.Anthropic(api_key="YOUR_API_KEY")

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "用一句话解释什么是 API"}
    ]
)

print(message.content[0].text)

TypeScript 示例

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({ apiKey: "YOUR_API_KEY" });

const message = await client.messages.create({
  model: "claude-sonnet-4-20250514",
  max_tokens: 1024,
  messages: [
    { role: "user", content: "用一句话解释什么是 API" }
  ],
});

console.log(message.content[0].text);

OpenAI Chat Completions API

OpenAI 的 GPT 使用 Chat Completions API。

curl 示例

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

Python 示例

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY")

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "用一句话解释什么是 API"}
    ]
)

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

TypeScript 示例

import OpenAI from "openai";

const client = new OpenAI({ apiKey: "YOUR_API_KEY" });

const response = await client.chat.completions.create({
  model: "gpt-4o",
  messages: [
    { role: "user", content: "用一句话解释什么是 API" }
  ],
});

console.log(response.choices[0].message.content);

流式响应（Streaming）

默认情况下，API 会等 AI 生成完所有内容后一次性返回。流式响应让你可以逐字接收，实现"打字机"效果。

Anthropic 流式（Python）

import anthropic

client = anthropic.Anthropic()

with client.messages.stream(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "写一首关于编程的诗"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

OpenAI 流式（Python）

from openai import OpenAI

client = OpenAI()

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "写一首关于编程的诗"}],
    stream=True,
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

错误处理

常见错误码：

重试策略（Python）

import time
import anthropic

client = anthropic.Anthropic()

def call_with_retry(messages, max_retries=3):
    for attempt in range(max_retries):
        try:
            return client.messages.create(
                model="claude-sonnet-4-20250514",
                max_tokens=1024,
                messages=messages,
            )
        except anthropic.RateLimitError:
            wait = 2 ** attempt  # 1s, 2s, 4s
            print(f"Rate limited, waiting {wait}s...")
            time.sleep(wait)
        except anthropic.APIError as e:
            if e.status_code >= 500:
                time.sleep(2 ** attempt)
            else:
                raise
    raise Exception("Max retries exceeded")

使用 Inkess API 代理

通过 Inkess LLM 代理服务，你可以用更低的价格访问 Claude、GPT 等模型，且 SDK 完全兼容。

只需修改 base URL：

# Anthropic SDK
client = anthropic.Anthropic(
    api_key="YOUR_INKESS_KEY",
    base_url="https://llm.starapp.net/api/llm",
)

# OpenAI SDK
client = OpenAI(
    api_key="YOUR_INKESS_KEY",
    base_url="https://llm.starapp.net/api/llm/v1",
)

其他代码完全不用改。

总结