hyperrouter-ai 0.2.0

The official Python SDK for HyperRouter — a unified API gateway for all major AI models.

HyperRouter

The official Python SDK for HyperRouter — a unified API gateway for all major AI models. One API key, one SDK, any model.

To learn more about how to use the HyperRouter SDK, check out our API Reference and Documentation.

SDK Installation

Note: The SDK requires a valid API key.

The SDK can be installed with pip, uv, or other package managers.

pip

pip install hyperrouter-ai

uv

uv is a fast Python package installer and resolver, designed as a drop-in replacement for pip and pip-tools.

uv add hyperrouter-ai

Poetry

poetry add hyperrouter-ai

Shell and script usage

You can use this SDK in a Python shell with uv and the --with command-line option:

# Launch a Python shell
uv run --with hyperrouter-ai python

# Run a script directly
uv run --with hyperrouter-ai python my_script.py

Requirements

This SDK requires Python 3.8 or higher.

IDE Support

PyCharm

Generally, the SDK will work well with most IDEs out of the box. However, when using PyCharm, you can enjoy much better integration by installing an additional plugin.

• PyCharm Pydantic Plugin

SDK Usage

Synchronous

from hyperrouter import HyperRouter

client = HyperRouter(api_key="hr-your-key-here")
# Or set HYPERROUTER_API_KEY env var and call HyperRouter()

response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4.6",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is HyperRouter?"},
    ],
)

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

Async

The SDK client can also be used to make asynchronous requests with asyncio:

from hyperrouter import AsyncHyperRouter
import asyncio

client = AsyncHyperRouter()  # Uses HYPERROUTER_API_KEY env var

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

asyncio.run(main())

Streaming

Stream responses token-by-token for real-time output:

from hyperrouter import HyperRouter

client = HyperRouter()

stream = client.chat.completions.create(
    model="deepseek/deepseek-v4-pro",
    messages=[{"role": "user", "content": "Write a haiku about AI."}],
    stream=True,
)

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

Async Streaming

from hyperrouter import AsyncHyperRouter
import asyncio

client = AsyncHyperRouter()

async def main():
    stream = await client.chat.completions.create(
        model="anthropic/claude-sonnet-4.6",
        messages=[{"role": "user", "content": "Explain quantum computing."}],
        stream=True,
    )

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

asyncio.run(main())

Using Different Models

HyperRouter gives you access to 300+ models from 50+ providers through a single API. Just change the model parameter:

from hyperrouter import HyperRouter

client = HyperRouter()

# Anthropic
response = client.chat.completions.create(
    model="anthropic/claude-opus-4.6",
    messages=[{"role": "user", "content": "Hello from Claude!"}],
)

# OpenAI
response = client.chat.completions.create(
    model="openai/gpt-4.1",
    messages=[{"role": "user", "content": "Hello from GPT!"}],
)

# DeepSeek
response = client.chat.completions.create(
    model="deepseek/deepseek-v4-pro",
    messages=[{"role": "user", "content": "Hello from DeepSeek!"}],
)

# Google
response = client.chat.completions.create(
    model="google/gemma-4-31b-it",
    messages=[{"role": "user", "content": "Hello from Gemma!"}],
)

# Meta
response = client.chat.completions.create(
    model="meta-llama/llama-4-scout",
    messages=[{"role": "user", "content": "Hello from Llama!"}],
)

# Auto Router — let HyperRouter pick the best model
response = client.chat.completions.create(
    model="hyperrouter/auto",
    messages=[{"role": "user", "content": "Pick the best model for me!"}],
)

Browse all available models at hyperrouter.ai/models.

OpenAI Compatibility

HyperRouter is fully compatible with the OpenAI SDK. If you already use openai, you can switch by changing the base URL:

from openai import OpenAI

client = OpenAI(
    api_key="hr-your-key-here",
    base_url="https://api.hyperrouter.ai/v1",
)

response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4.6",
    messages=[{"role": "user", "content": "Hello!"}],
)

Resource Management

The SDK implements the standard context manager protocol, so you can use it with with statements to ensure connections are properly closed:

from hyperrouter import HyperRouter

with HyperRouter() as client:
    response = client.chat.completions.create(
        model="anthropic/claude-sonnet-4.6",
        messages=[{"role": "user", "content": "Hello!"}],
    )
    print(response.choices[0].message.content)
# Connection is automatically closed

For async:

from hyperrouter import AsyncHyperRouter
import asyncio

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

asyncio.run(main())

Environment Variables

Variable	Description
HYPERROUTER_API_KEY	Your HyperRouter API key (hr-...). Used when no api_key is passed to the client.

Debugging

You can turn on debug logging to see raw HTTP requests and responses:

from hyperrouter import HyperRouter
import logging

logging.basicConfig(level=logging.DEBUG)

client = HyperRouter()

Links

• Documentation
• API Reference
• Models Explorer
• Dashboard
• GitHub