routra 0.1.1

Routra Python SDK - OpenAI-compatible client with intelligent multi-provider routing

Routra Python SDK

Thin wrapper over the OpenAI Python SDK. Adds typed routing metadata, policy helpers, and async support.

Installation

pip install routra
# or
uv add routra

Quick Start

from routra import Routra

client = Routra(api_key="rtr-...")
response = client.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "Hello"}],
)

# Typed routing metadata on every non-streaming response
if response.routra:
    print(response.routra.provider)    # "groq"
    print(response.routra.latency_ms)  # 245
    print(response.routra.score)       # 0.8642
    print(response.routra.cost_usd)    # 0.000089

Routing Policies

# Set a default policy for all requests
client = Routra(api_key="rtr-...", policy="cheapest")

# Per-request policy override
fast_client = client.with_policy("fastest")
response = fast_client.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "Urgent request"}],
)

Async Support

from routra import AsyncRoutra

client = AsyncRoutra(api_key="rtr-...")
response = await client.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.routra.provider)

Environment Variables

Variable	Description
ROUTRA_API_KEY	Default API key (used when api_key parameter is not provided)
ROUTRA_BASE_URL	Override API base URL (default: https://api.routra.dev/v1)

import os
os.environ["ROUTRA_API_KEY"] = "rtr-..."

# No need to pass api_key
client = Routra()

Routing Metadata

The response.routra field is a RoutingMetadata object with these fields:

Field	Type	Description
provider	str	Provider slug that served the request (e.g. "groq")
latency_ms	int	Total provider response time in milliseconds
score	float	Normalized routing score (0–1)
cost_usd	float | None	Estimated cost in USD
input_tokens	int | None	Input token count
output_tokens	int | None	Output token count
failover	bool | None	Whether the request was rerouted due to a provider failure
ttfb_ms	int | None	Time to first byte (streaming only)

Note: routra metadata is only available on non-streaming responses. For streaming, use the x-routra-provider response header.

Multimodal Routing

All OpenAI-compatible endpoints are proxied through Routra — use the same client for chat, embeddings, images, TTS, and STT with automatic cost routing:

# Image — routes to cheapest: FLUX Schnell ($0.001) vs GPT Image 1.5 ($0.13)
image = client.images.generate(
    model="auto:image",
    prompt="a sunset over mountains",
    size="1024x1024",
)

# TTS — voice passthrough, streaming supported
audio = client.audio.speech.create(
    model="auto:tts",
    input="Hello, welcome to our service.",
    voice="alloy",
)

# STT — multipart form-data forwarded transparently
transcript = client.audio.transcriptions.create(
    model="auto:stt",
    file=open("audio.mp3", "rb"),
)

Use auto:image, auto:tts, auto:stt for cheapest routing, or pin a provider with model="openai/gpt-image-1.5" or model="fireworks/flux-1-schnell".

OpenAI Compatibility

Since Routra extends openai.OpenAI, all OpenAI SDK features work transparently:

# Streaming (metadata via headers, not response object)
stream = client.chat.completions.create(
    model="auto",
    messages=[{"role": "user", "content": "Count to 10"}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content, end="")

# Embeddings
embedding = client.embeddings.create(
    model="text-embedding-3-small",
    input="Hello world",
)

# Image Generation — auto-routes to cheapest provider
image = client.images.generate(
    model="auto:image",  # FLUX Schnell ($0.001) vs GPT Image 1.5 ($0.13)
    prompt="a sunset over mountains",
    size="1024x1024",
)

# Text-to-Speech
audio = client.audio.speech.create(
    model="auto:tts",
    input="Hello, welcome to our service.",
    voice="alloy",
)

# Speech-to-Text
transcript = client.audio.transcriptions.create(
    model="auto:stt",
    file=open("audio.mp3", "rb"),
)

License

MIT