openrouter-oai-agentsdk 0.1.2

Plug OpenRouter into the OpenAI Agents SDK with a drop-in model provider and RunConfig.

openrouter-oai-agentsdk

Use OpenRouter models inside the OpenAI Agents SDK without changing your agent architecture.

This package provides:

• an OpenRouter-backed ModelProvider
• a ready-to-use RunConfig for Runner.run(...) and Runner.run_streamed(...)
• environment-based configuration with optional OpenRouter attribution headers

Install

uv add openrouter-oai-agentsdk

Or:

pip install openrouter-oai-agentsdk

What problem this solves

The OpenAI Agents SDK expects a model provider. This library plugs OpenRouter in as that provider, so you can keep using:

• Agent(...)
• Runner.run(...) / Runner.run_streamed(...)
• ModelSettings(...)

Instead of wiring your own client/provider every time, you create one run config from this package and pass it to Runner.

Quick start (step by step)

1. Create or open your project and install dependencies:

uv add openai-agents openrouter-oai-agentsdk

2. Set your OpenRouter API key:

export OPENROUTER_API_KEY="sk-or-v1-..."

3. Create main.py:

from agents import Agent, Runner
from openrouter_oai_agentsdk import create_openrouter_run_config

agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant.",
    model="openai/gpt-4o-mini",
)

result = Runner.run_sync(
    agent,
    "In one sentence, what is gravity?",
    run_config=create_openrouter_run_config(),
)
print(result.final_output)

4. Run it:

uv run python main.py

What each line does:

1. Agent(...) defines behavior and the model you want.
2. create_openrouter_run_config() wires OpenRouter as the provider.
3. Runner.run_sync(...) executes one request using that provider.
4. result.final_output prints the agent's final text response.

If you already set OPENROUTER_MODEL, you can omit model=... on Agent(...).

Next step: streaming (optional)

Use Runner.run_streamed(...) only when you want token-by-token output in real time. Start with run_sync first.

Usage patterns

Pattern A: zero-config run config from env

from openrouter_oai_agentsdk import OPENROUTER_RUN_CONFIG
from agents import Runner

# Pass OPENROUTER_RUN_CONFIG directly to Runner calls.

Pattern B: explicit settings in code

from openrouter_oai_agentsdk import OpenRouterSettings, create_openrouter_run_config

settings = OpenRouterSettings(
    api_key="sk-or-v1-...",
    fallback_model="openai/gpt-5-mini",
    http_referer="https://your-app.example",
    x_title="Your App Name",
)
run_config = create_openrouter_run_config(settings=settings)

Use this pattern when you want fully explicit config (service containers, tests, multi-tenant apps).

Environment variables

Required:

• OPENROUTER_API_KEY: your OpenRouter key (sk-or-v1-...)

Optional:

• OPENROUTER_MODEL: fallback model if an agent does not define one
• OPENROUTER_BASE_URL: defaults to https://openrouter.ai/api/v1
• OPENROUTER_HTTP_REFERER: app/site URL for OpenRouter attribution
• OPENROUTER_X_TITLE: app title for OpenRouter attribution
• OPENROUTER_DISABLE_TRACING: true by default

Common errors

• OPENROUTER_API_KEY is not set: export OPENROUTER_API_KEY before running.
• No model provided: set Agent(model=...) or set OPENROUTER_MODEL.

Import compatibility

The preferred import is:

from openrouter_oai_agentsdk import OPENROUTER_RUN_CONFIG

Legacy import path is still supported:

from openrouter_provider import OPENROUTER_RUN_CONFIG

Build and publish (maintainers)

Build distributions:

uv build --no-sources

Bump version:

uv version --bump patch

Publish to PyPI:

uv publish --token "$UV_PUBLISH_TOKEN"

Publish to a configured custom index:

uv publish --index testpypi --token "$UV_PUBLISH_TOKEN"

Trusted publishing from GitHub Actions is also supported via .github/workflows/publish.yml.

Verify install/import (without local project shadowing):

uv run --with openrouter-oai-agentsdk --no-project -- \
  python -c "import openrouter_oai_agentsdk; print(openrouter_oai_agentsdk.__version__)"