> For the complete documentation index, see [llms.txt](https://infronai.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://infronai.gitbook.io/docs/frameworks-and-integrations/openai-agents-sdk.md).

# OpenAI Agents SDK

Use OpenAI Agents SDK with Infron AI models

Seamlessly integrate Infron AI AI with OpenAI Agents SDK for building multi-agent workflows.

The [OpenAI Agents SDK](https://github.com/openai/openai-agents-python) is a lightweight yet powerful framework for building multi-agent workflows. And the SDK is compatible with any model providers that support the OpenAI Chat Completions API format.

This guide will walk you through how to use Infron AI LLM API with OpenAI Agents SDK.

### Get Started <a href="#get-started" id="get-started"></a>

1. Set up your Python environment and install the Agents SDK.

```sh
python -m venv env
source env/bin/activate
pip install openai-agents==0.0.7
```

2. Set up your Infron AI API key.

Using Infron is to [create an account](https://infron.ai/login) and [get your API key](https://infron.ai/dashboard/apiKeys).

### Hello world example <a href="#hello-world-example" id="hello-world-example"></a>

```python
import os
from openai import AsyncOpenAI
from agents import (
    Agent,
    Runner,
    set_default_openai_api,
    set_default_openai_client,
    set_tracing_disabled,
)

BASE_URL = "https://llm.onerouter.pro/v1"
API_KEY = "Your_API_KEY"
MODEL_NAME = "openai/gpt-5.4"

set_default_openai_api("chat_completions")
set_default_openai_client(AsyncOpenAI(base_url=BASE_URL, api_key=API_KEY))
set_tracing_disabled(disabled=True)

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

result = Runner.run_sync(
    agent, "Write a haiku about recursion in programming. step by step.")
print(result.final_output)

# Code within the code,
# Functions calling themselves,
# Infinite loop's dance.
```

### Handoffs example <a href="#handoffs-example" id="handoffs-example"></a>

```python
import os
import asyncio
from openai import AsyncOpenAI
from agents import (
    Agent,
    Runner,
    set_default_openai_api,
    set_default_openai_client,
    set_tracing_disabled,
)

BASE_URL = "https://llm.onerouter.pro/v1"
API_KEY = "Your_API_KEYS"
MODEL_NAME = "openai/gpt-5.4"

set_default_openai_api("chat_completions")
set_default_openai_client(AsyncOpenAI(base_url=BASE_URL, api_key=API_KEY))
set_tracing_disabled(disabled=True)

spanish_agent = Agent(
    name="Spanish agent",
    instructions="You only speak Spanish.",
    model=MODEL_NAME,
)

english_agent = Agent(
    name="English agent",
    instructions="You only speak English",
    model=MODEL_NAME,
)

triage_agent = Agent(
    name="Triage agent",
    instructions="Handoff to the appropriate agent based on the language of the request.",
    handoffs=[spanish_agent, english_agent],
    model=MODEL_NAME,
)


async def main():
    result = await Runner.run(triage_agent, input="Write a haiku about recursion in programming. step by step.")
    print(result.final_output)


if __name__ == "__main__":
    asyncio.run(main())
```

### Functions example <a href="#functions-example" id="functions-example"></a>

```python
import os
import asyncio
from openai import AsyncOpenAI
from agents import (
    Agent,
    Runner,
    set_default_openai_api,
    set_default_openai_client,
    set_tracing_disabled,
    function_tool,
)

BASE_URL = "https://llm.onerouter.pro/v1"
API_KEY = "Your_API_KEYS"
MODEL_NAME = "openai/gpt-5.4"

set_default_openai_api("chat_completions")
set_default_openai_client(AsyncOpenAI(base_url=BASE_URL, api_key=API_KEY))
set_tracing_disabled(disabled=True)

@function_tool
def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny."

agent = Agent(
    name="Hello world",
    instructions="You are a helpful agent.",
    tools=[get_weather],
    model=MODEL_NAME,
)

async def main():
    result = await Runner.run(agent, input="What's the weather in Tokyo?")
    print(result.final_output)

if __name__ == "__main__":
    asyncio.run(main())
```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://infronai.gitbook.io/docs/frameworks-and-integrations/openai-agents-sdk.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.