tokenrouter 1.0.4

Python SDK for TokenRouter - Intelligent LLM Routing API

TokenRouter Python SDK

Official Python SDK for TokenRouter — an intelligent LLM router that provides OpenAI‑compatible endpoints and a native routing endpoint.

This README focuses on the routing interfaces you’ll use today:

• client.create(...) → Native routing endpoint (/route)
• client.chat.completions.create(...) → OpenAI chat completions (/v1/chat/completions)
• client.completions.create(...) → OpenAI legacy text completions (/v1/completions)

All calls are BYOK. Provide your TokenRouter API key, and configure provider keys in TokenRouter.

Installation

pip install tokenrouter

Quick Start (Native Route)

from tokenrouter import TokenRouter

client = TokenRouter(
    api_key="tr_...",
    base_url="http://localhost:8000"  # or https://api.tokenrouter.io
)

response = client.create(
  model="auto",
  mode="balanced",
  model_preferences=["gpt-4o", "gpt-4o-mini"],
  messages=[
    {"role": "developer", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Hello!"}
  ],
)

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

Endpoints

Native Route (/route)

OpenAI‑like request/response shape plus TokenRouter metadata: cost_usd, latency_ms, routed_model, routed_provider, service_tier, etc.

Non‑streaming

response = client.create(
  model="auto",
  mode="balanced",
  model_preferences=["gpt-4o", "gpt-4o-mini"],
  messages=[
    {"role": "developer", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Hello!"}
  ],
)
print(response.choices[0].message.content)

Streaming

for chunk in client.create(
  model="auto",
  stream=True,
  messages=[
    {"role": "developer", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Stream a short greeting."}
  ],
):
  delta = (chunk.choices[0].get("delta", {}) if chunk.choices else {})
  if delta.get("content"):
    print(delta["content"], end="")

Chat Completions (/v1/chat/completions)

OpenAI‑compatible chat completions.

Non‑streaming

response = client.chat.completions.create(
  model="auto",
  mode="balanced",
  model_preferences=["gpt-4o", "gpt-4o-mini"],
  messages=[
    {"role": "developer", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Hello!"}
  ],
)
print(response.choices[0].message.content)

Streaming

for chunk in client.chat.completions.create(
  model="auto",
  stream=True,
  messages=[
    {"role": "developer", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Hello!"}
  ],
):
  delta = (chunk.choices[0].get("delta", {}) if chunk.choices else {})
  if delta.get("content"):
    print(delta["content"], end="")

Legacy Completions (/v1/completions)

OpenAI legacy text completion format. The SDK returns the raw OpenAI‑style dict.

Non‑streaming

resp = client.completions.create(
  model="auto",
  prompt="Say this is a test",
  mode="balanced",
)
print(resp["choices"][0]["text"])  # text completion shape

Streaming

for chunk in client.completions.create(
  model="auto",
  prompt="Stream this as text",
  stream=True,
):
  if chunk.get("choices"):
    print(chunk["choices"][0].get("text", ""), end="")

Utilities

client.list_models()
client.get_costs()
client.get_analytics()
client.health_check()

Errors

from tokenrouter import AuthenticationError, RateLimitError, InvalidRequestError, APIConnectionError

try:
  response = client.chat.completions.create(
    messages=[{"role": "user", "content": "Hello"}],
    model="auto"
  )
  print(response.choices[0].message.content)
except RateLimitError as e:
  print(f"Rate limited, retry after: {e.retry_after}s")
except AuthenticationError:
  print("Invalid API key")
except InvalidRequestError as e:
  print(f"Invalid request: {e}")
except APIConnectionError as e:
  print(f"Connection error: {e}")

Environment

export TOKENROUTER_API_KEY=tr_your-api-key
# Optional
export TOKENROUTER_BASE_URL=https://api.tokenrouter.io

Using OpenAI SDK against TokenRouter

from openai import OpenAI
client = OpenAI(api_key="sk_...", base_url="https://api.tokenrouter.io/v1")
response = client.chat.completions.create(
  model="auto",
  messages=[{"role": "user", "content": "Hello"}],
)