API 文档

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://toapis.com/v1"
)

# 非流式调用
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "你是一个有帮助的AI助手。"},
        {"role": "user", "content": "用Python写一个快速排序算法"}
    ],
    temperature=0.7,
    max_tokens=2000
)
print(response.choices[0].message.content)

# 流式调用
stream = client.chat.completions.create(
    model="gemini-2.0-flash",
    messages=[
        {"role": "user", "content": "介绍一下人工智能的发展历史"}
    ],
    stream=True
)

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

import OpenAI from 'openai';

const client = new OpenAI({
    apiKey: 'sk-your-api-key',
    baseURL: 'https://toapis.com/v1'
});

// 非流式调用
const response = await client.chat.completions.create({
    model: 'claude-3-5-sonnet',
    messages: [
        { role: 'system', content: '你是一个有帮助的AI助手。' },
        { role: 'user', content: '解释一下量子计算的基本原理' }
    ],
    temperature: 0.7
});
console.log(response.choices[0].message.content);

// 流式调用
const stream = await client.chat.completions.create({
    model: 'gpt-4o',
    messages: [
        { role: 'user', content: 'Hello!' }
    ],
    stream: true
});

for await (const chunk of stream) {
    process.stdout.write(chunk.choices[0]?.delta?.content || '');
}

curl https://toapis.com/v1/chat/completions \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "system", "content": "你是一个有帮助的AI助手。"},
      {"role": "user", "content": "Hello!"}
    ],
    "stream": false,
    "temperature": 0.7
  }'

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://toapis.com/v1"
)

response = client.images.generate(
    model="dall-e-3",
    prompt="A serene Japanese garden with cherry blossoms, koi pond, and a traditional wooden bridge, watercolor style",
    size="1024x1024",
    quality="hd",
    style="natural",
    n=1
)

print(response.data[0].url)

import OpenAI from 'openai';

const client = new OpenAI({
    apiKey: 'sk-your-api-key',
    baseURL: 'https://toapis.com/v1'
});

const response = await client.images.generate({
    model: 'dall-e-3',
    prompt: 'A futuristic city at sunset, cyberpunk style, neon lights',
    size: '1792x1024',
    quality: 'hd',
    n: 1
});

console.log(response.data[0].url);

curl https://toapis.com/v1/images/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "dall-e-3",
    "prompt": "A cute robot reading a book in a cozy library",
    "size": "1024x1024",
    "quality": "hd",
    "n": 1
  }'

import requests

response = requests.post(
    "https://toapis.com/v1/videos/generations",
    headers={
        "Authorization": "Bearer sk-your-api-key",
        "Content-Type": "application/json"
    },
    json={
        "model": "veo-3.1-generate-preview",
        "prompt": "A golden retriever running through a field of sunflowers at sunset, cinematic quality, slow motion",
        "aspect_ratio": "16:9",
        "resolution": "1080p",
        "duration": "4"
    },
    timeout=600  # 10 分钟超时
)

result = response.json()
print(result["data"][0]["url"])

curl https://toapis.com/v1/videos/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  --max-time 600 \
  -d '{
    "model": "veo-3.1-generate-preview",
    "prompt": "A timelapse of clouds moving over a mountain landscape",
    "aspect_ratio": "16:9",
    "resolution": "1080p",
    "duration": "8"
  }'

from openai import OpenAI
from pathlib import Path

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://toapis.com/v1"
)

speech_file_path = Path("speech.mp3")
response = client.audio.speech.create(
    model="tts-1-hd",
    voice="nova",
    input="你好，欢迎使用我们的语音合成服务！",
    speed=1.0
)

response.stream_to_file(speech_file_path)
print(f"Audio saved to {speech_file_path}")

curl https://toapis.com/v1/audio/speech \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "Hello, this is a test of the text to speech API.",
    "voice": "alloy"
  }' \
  --output speech.mp3

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://toapis.com/v1"
)

audio_file = open("meeting.mp3", "rb")
transcript = client.audio.transcriptions.create(
    model="whisper-1",
    file=audio_file,
    language="zh",
    response_format="text"
)

print(transcript)

curl https://toapis.com/v1/audio/transcriptions \
  -H "Authorization: Bearer sk-your-api-key" \
  -F file="@meeting.mp3" \
  -F model="whisper-1" \
  -F language="zh" \
  -F response_format="text"

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://toapis.com/v1"
)

response = client.embeddings.create(
    model="text-embedding-3-small",
    input=["人工智能正在改变世界", "机器学习是AI的一个分支"],
    dimensions=512  # 可选，减小向量维度
)

for i, embedding in enumerate(response.data):
    print(f"文本 {i+1} 的嵌入向量维度: {len(embedding.embedding)}")

curl https://toapis.com/v1/embeddings \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-small",
    "input": "人工智能正在改变世界"
  }'

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://toapis.com/v1"
)

models = client.models.list()

for model in models.data:
    print(f"{model.id} - {model.owned_by}")

curl https://toapis.com/v1/models \
  -H "Authorization: Bearer sk-your-api-key"