Python

pip install openai

from openai import OpenAI

client = OpenAI(
    base_url="https://api.arouter.com/v1",
    api_key="lr_live_xxxx",
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(response.choices[0].message.content)

# Anthropic via OpenAI SDK
response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4-20250514",
    messages=[{"role": "user", "content": "Hello!"}],
)

# DeepSeek via OpenAI SDK
response = client.chat.completions.create(
    model="deepseek/deepseek-chat",
    messages=[{"role": "user", "content": "Hello!"}],
)

# Gemini via OpenAI SDK
response = client.chat.completions.create(
    model="google/gemini-2.0-flash",
    messages=[{"role": "user", "content": "Hello!"}],
)

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Write a haiku about code."}],
    stream=True,
)

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

import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(
    base_url="https://api.arouter.com/v1",
    api_key="lr_live_xxxx",
)

async def main():
    response = await client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Hello!"}],
    )
    print(response.choices[0].message.content)

asyncio.run(main())

response = client.embeddings.create(
    model="openai/text-embedding-3-small",
    input="The quick brown fox jumps over the lazy dog",
)
print(response.data[0].embedding[:5])

pip install anthropic

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.arouter.com",
    api_key="lr_live_xxxx",
)

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}],
)
print(message.content[0].text)

with client.messages.stream(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a story."}],
) as stream:
    for text in stream.text_stream:
        print(text, end="")

pip install google-generativeai

import google.generativeai as genai

genai.configure(
    api_key="lr_live_xxxx",
    transport="rest",
    client_options={"api_endpoint": "https://api.arouter.com"},
)

model = genai.GenerativeModel("gemini-2.0-flash")
response = model.generate_content("Hello!")
print(response.text)