Python / Node / curl / Java / Go

Python

安装

bash
pip install openai

使用

python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AICODEDOG_KEY"],
    base_url="https://api.aicodedog.com/v1",
)

# Chat
resp = client.chat.completions.create(
    model="gpt-5.4",
    messages=[{"role": "user", "content": "你好"}],
)
print(resp.choices[0].message.content)

# Streaming
stream = client.chat.completions.create(
    model="gpt-5.4",
    messages=[{"role": "user", "content": "讲个故事"}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="", flush=True)

# Image
img = client.images.generate(
    model="nano-banana-pro",
    prompt="a sunset over Mt Fuji, ghibli style",
    size="1024x1024",
)
print(img.data[0].url)

Node.js / TypeScript

安装

bash
npm install openai
# 或
pnpm add openai

使用

ts
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.AICODEDOG_KEY,
  baseURL: 'https://api.aicodedog.com/v1',
});

// Chat
const resp = await client.chat.completions.create({
  model: 'gpt-5.4',
  messages: [{ role: 'user', content: '你好' }],
});
console.log(resp.choices[0].message.content);

// Streaming
const stream = await client.chat.completions.create({
  model: 'gpt-5.4',
  messages: [{ role: 'user', content: '讲个故事' }],
  stream: true,
});
for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? '');
}

// Image
const img = await client.images.generate({
  model: 'nano-banana-pro',
  prompt: 'a sunset over Mt Fuji, ghibli style',
  size: '1024x1024',
});
console.log(img.data[0].url);

curl（任何语言都能复用）

bash
# Chat
curl https://api.aicodedog.com/v1/chat/completions \
  -H "Authorization: Bearer $AICODEDOG_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.4",
    "messages": [{"role": "user", "content": "你好"}]
  }'

# Image
curl https://api.aicodedog.com/v1/images/generations \
  -H "Authorization: Bearer $AICODEDOG_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nano-banana-pro",
    "prompt": "a sunset over Mt Fuji, ghibli style",
    "size": "1024x1024"
  }'

# Embeddings
curl https://api.aicodedog.com/v1/embeddings \
  -H "Authorization: Bearer $AICODEDOG_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-small",
    "input": "把这段文字转成向量"
  }'

Java

推荐用 openai-java 官方 SDK：

java
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.ChatCompletion;
import com.openai.models.ChatCompletionCreateParams;

OpenAIClient client = OpenAIOkHttpClient.builder()
    .apiKey(System.getenv("AICODEDOG_KEY"))
    .baseUrl("https://api.aicodedog.com/v1")
    .build();

ChatCompletion resp = client.chat().completions().create(
    ChatCompletionCreateParams.builder()
        .model("gpt-5.4")
        .addUserMessage("你好")
        .build()
);
System.out.println(resp.choices().get(0).message().content());

Go

推荐用 go-openai：

go
package main

import (
    "context"
    "fmt"
    "os"

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

func main() {
    config := openai.DefaultConfig(os.Getenv("AICODEDOG_KEY"))
    config.BaseURL = "https://api.aicodedog.com/v1"
    client := openai.NewClientWithConfig(config)

    resp, err := client.CreateChatCompletion(context.Background(),
        openai.ChatCompletionRequest{
            Model: "gpt-5.4",
            Messages: []openai.ChatCompletionMessage{
                {Role: openai.ChatMessageRoleUser, Content: "你好"},
            },
        })
    if err != nil { panic(err) }
    fmt.Println(resp.Choices[0].Message.Content)
}

框架适配

LangChain (Python)

python
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="gpt-5.4",
    api_key="<KEY>",
    base_url="https://api.aicodedog.com/v1",
)

LlamaIndex

python
from llama_index.llms.openai import OpenAI

llm = OpenAI(
    model="gpt-5.4",
    api_key="<KEY>",
    api_base="https://api.aicodedog.com/v1",
)

Vercel AI SDK

ts
import { createOpenAI } from '@ai-sdk/openai';

const aicodedog = createOpenAI({
  apiKey: process.env.AICODEDOG_KEY,
  baseURL: 'https://api.aicodedog.com/v1',
});

const result = await streamText({
  model: aicodedog('gpt-5.4'),
  prompt: '你好',
});