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Use Auriko as your LLM provider in the OpenAI Agents SDK.

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Prerequisites

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Installation

pip install "auriko[agents]"

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Use SDK adapter

Use the AurikoModel adapter: 
from auriko.frameworks.agents import AurikoModel

model = AurikoModel(model="gpt-5.4")
AurikoModel replaces 4 lines of global client configuration with a single model parameter. It extends OpenAIChatCompletionsModel with routing injection, error mapping, and per-task metadata isolation via ContextVar. 
import asyncio
from auriko.frameworks.agents import AurikoModel
from agents import Agent, Runner

model = AurikoModel(model="gpt-5.4")

agent = Agent(
    name="assistant",
    instructions="You are a helpful assistant.",
    model=model,
)

async def main():
    result = await Runner.run(agent, input="What is the capital of France?")
    print(result.final_output)

asyncio.run(main())

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Configure options

ParameterTypeDefaultDescription
modelstr(required)Model ID
api_keystr | NoneAURIKO_API_KEY envAPI key
routingRoutingOptions | NoneNoneRouting configuration
base_urlstr"https://api.auriko.ai/v1"API base URL

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Configure routing

Configure routing options: 
import asyncio
from auriko.frameworks.agents import AurikoModel
from auriko.route_types import RoutingOptions
from agents import Agent, Runner

model = AurikoModel(
    model="gpt-5.4",
    routing=RoutingOptions(optimize="cost"),
)

agent = Agent(name="assistant", instructions="You are helpful.", model=model)

async def main():
    result = await Runner.run(agent, input="Hello!")
    print(result.final_output)

asyncio.run(main())
Routing metadata is isolated per async task using ContextVar, so concurrent Runner.run() calls sharing the same AurikoModel instance don’t interfere with each other.

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Configure manually

If you prefer to configure the SDK’s client directly:
import asyncio
import os
from openai import AsyncOpenAI
from agents import Agent, Runner, set_default_openai_client, set_default_openai_api, set_tracing_disabled

set_default_openai_api("chat_completions")
set_tracing_disabled(True)

client = AsyncOpenAI(
    base_url="https://api.auriko.ai/v1",
    api_key=os.environ["AURIKO_API_KEY"],
)
set_default_openai_client(client, use_for_tracing=False)

agent = Agent(name="assistant", instructions="You are helpful.", model="gpt-5.4")

async def main():
    result = await Runner.run(agent, input="Hello!")
    print(result.final_output)

asyncio.run(main())
Note: set_default_openai_api("chat_completions") is required because Auriko implements the Chat Completions API, not the Responses API. Routing options, error mapping, and per-task metadata isolation aren’t available with manual configuration.

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Notes

  • AurikoModel extends OpenAIChatCompletionsModel — it works with all Agents SDK features: tools, handoffs, streaming, guardrails.
  • OpenAI API errors are automatically mapped to typed Auriko error classes (RateLimitError, BudgetExceededError, etc.).
  • Concurrent agent runs using the same AurikoModel instance have isolated routing metadata via ContextVar.