tokenrouter 1.0.13

Python SDK for TokenRouter - Intelligent LLM Routing API

TokenRouter Python SDK

OpenAI Responses API compatible client for TokenRouter - intelligent LLM routing service.

Installation

pip install tokenrouter

Quick Start

import os
from tokenrouter import TokenRouter

client = TokenRouter(
    api_key=os.environ.get('TOKENROUTER_API_KEY'),  # This is the default and can be omitted
    base_url=os.environ.get('TOKENROUTER_BASE_URL'),  # Default: https://api.tokenrouter.io/api
)

response = client.responses.create(
    model="gpt-4.1",
    input="Tell me a three sentence bedtime story about a unicorn."
)

print(response.output_text)

OpenAI Compatibility

This SDK is designed to be a drop-in replacement for OpenAI's SDK when using the Responses API. Simply change your import and API key:

# Before (OpenAI)
from openai import OpenAI
client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))

# After (TokenRouter)
from tokenrouter import TokenRouter
client = TokenRouter(api_key=os.environ.get("TOKENROUTER_API_KEY"))

Configuration

Environment Variables

• TOKENROUTER_API_KEY - Your TokenRouter API key
• TOKENROUTER_BASE_URL - API base URL (default: https://api.tokenrouter.io/api)

Client Options

from tokenrouter import TokenRouter

client = TokenRouter(
    api_key='tr_...',  # Your API key
    base_url='https://api.tokenrouter.io/api',  # API base URL
    timeout=60.0,  # Request timeout in seconds (default: 60)
    max_retries=3,  # Max retry attempts (default: 3)
    headers={  # Additional headers
        'X-Custom-Header': 'value'
    }
)

API Reference

Create Response

response = client.responses.create(
    # Required
    input="Your prompt here",  # or list of input items

    # Optional
    model="gpt-4.1",  # Model to use
    instructions="System instructions",
    max_output_tokens=1000,
    temperature=0.7,
    top_p=0.9,
    stream=False,  # Set to True for streaming
    tools=[],  # Function calling tools
    tool_choice="auto",
    text={"format": {"type": "text"}},  # Response format
    # ... other OpenAI-compatible parameters
)

# Access the response text directly
print(response.output_text)

Streaming Responses

stream = client.responses.create(
    input="Write a poem",
    stream=True
)

for event in stream:
    if event.type == "response.delta" and event.delta and event.delta.output:
        for item in event.delta.output:
            if item.get("content"):
                for content in item["content"]:
                    if content.get("text"):
                        print(content["text"], end="", flush=True)

Function Calling

response = client.responses.create(
    input="What's the weather in San Francisco?",
    tools=[
        {
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get the current weather",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {"type": "string"}
                    },
                    "required": ["location"]
                }
            }
        }
    ]
)

# Check for function calls in the response
for item in response.output:
    if item.type == "tool_call" and item.tool_calls:
        for tool_call in item.tool_calls:
            if tool_call.function:
                print(f"Function: {tool_call.function.get('name')}")
                print(f"Arguments: {tool_call.function.get('arguments')}")

Multi-turn Conversations

# First message
response1 = client.responses.create(
    input="My name is Alice",
    store=True  # Store for later retrieval
)

# Continue conversation
response2 = client.responses.create(
    input="What's my name?",
    previous_response_id=response1.id
)

Other Methods

# Get response by ID
response = client.responses.get("resp_123")

# Delete response
result = client.responses.delete("resp_123")

# Cancel background response
response = client.responses.cancel("resp_123")

# List input items
items = client.responses.list_input_items("resp_123")

Async Support

The SDK provides a fully async client for asynchronous applications:

import asyncio
from tokenrouter import AsyncTokenRouter

async def main():
    async with AsyncTokenRouter(api_key="tr_...") as client:
        response = await client.responses.create(
            input="Hello, world!"
        )
        print(response.output_text)

asyncio.run(main())

Async Streaming

async with AsyncTokenRouter(api_key="tr_...") as client:
    stream = await client.responses.create(
        input="Count to 5",
        stream=True
    )

    async for event in stream:
        if event.type == "response.delta" and event.delta:
            # Process streaming chunks
            pass

Response Format

The SDK adds a convenience property output_text to responses that aggregates all text output:

response = client.responses.create(input="Hello")

# Access aggregated text directly
print(response.output_text)

# Or access the full response structure
print(response.output)  # List of output items
print(response.usage)  # Token usage
print(response.model)  # Model used

Error Handling

from tokenrouter import (
    TokenRouterError,
    AuthenticationError,
    RateLimitError,
    InvalidRequestError
)

try:
    response = client.responses.create(input="Hello")
except AuthenticationError:
    print("Invalid API key")
except RateLimitError as e:
    print(f"Rate limit exceeded, retry after: {e.retry_after}")
except InvalidRequestError as e:
    print(f"Invalid request: {e.message}")
except TokenRouterError as e:
    print(f"Unexpected error: {e}")

Type Hints

The SDK provides comprehensive type hints for all models:

from tokenrouter import TokenRouter, Response, ResponseStreamEvent
from typing import Iterator

def process_response(response: Response) -> str:
    return response.output_text or ""

def handle_stream(stream: Iterator[ResponseStreamEvent]) -> None:
    for event in stream:
        # Process events with full type support
        pass

Examples

See the examples directory for more detailed usage:

• simple.py - Basic usage matching the OpenAI pattern
• responses_example.py - Comprehensive examples of all features

Requirements

• Python 3.7+
• httpx>=0.24.0
• typing-extensions>=4.0.0

License

MIT