Docs for LiteLLM integration (#532)

docs/ja/quickstart.md

@@ -186,4 +186,4 @@ if __name__ == "__main__":
 
 -   [エージェント](agents.md) の設定方法について学ぶ
 -   [エージェントの実行](running_agents.md) について学ぶ
--   [tools](tools.md)、[guardrails](guardrails.md)、[models](models.md) について学ぶ
+-   [tools](tools.md)、[guardrails](guardrails.md)、[models](models/index.md) について学ぶ

docs/models/index.md

@@ -70,9 +70,9 @@ You can use other LLM providers in 3 ways (examples [here](https://github.com/op
 
 1. [`set_default_openai_client`][agents.set_default_openai_client] is useful in cases where you want to globally use an instance of `AsyncOpenAI` as the LLM client. This is for cases where the LLM provider has an OpenAI compatible API endpoint, and you can set the `base_url` and `api_key`. See a configurable example in [examples/model_providers/custom_example_global.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_global.py).
 2. [`ModelProvider`][agents.models.interface.ModelProvider] is at the `Runner.run` level. This lets you say "use a custom model provider for all agents in this run". See a configurable example in [examples/model_providers/custom_example_provider.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_provider.py).
-3. [`Agent.model`][agents.agent.Agent.model] lets you specify the model on a specific Agent instance. This enables you to mix and match different providers for different agents. See a configurable example in [examples/model_providers/custom_example_agent.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_agent.py).
+3. [`Agent.model`][agents.agent.Agent.model] lets you specify the model on a specific Agent instance. This enables you to mix and match different providers for different agents. See a configurable example in [examples/model_providers/custom_example_agent.py](https://github.com/openai/openai-agents-python/tree/main/examples/model_providers/custom_example_agent.py). An easy way to use most available models is via the [LiteLLM integration](./litellm.md).
 
-In cases where you do not have an API key from `platform.openai.com`, we recommend disabling tracing via `set_tracing_disabled()`, or setting up a [different tracing processor](tracing.md).
+In cases where you do not have an API key from `platform.openai.com`, we recommend disabling tracing via `set_tracing_disabled()`, or setting up a [different tracing processor](../tracing.md).
 
 !!! note
 
@@ -86,7 +86,7 @@ If you get errors related to tracing, this is because traces are uploaded to Ope
 
 1. Disable tracing entirely: [`set_tracing_disabled(True)`][agents.set_tracing_disabled].
 2. Set an OpenAI key for tracing: [`set_tracing_export_api_key(...)`][agents.set_tracing_export_api_key]. This API key will only be used for uploading traces, and must be from [platform.openai.com](https://platform.openai.com/).
-3. Use a non-OpenAI trace processor. See the [tracing docs](tracing.md#custom-tracing-processors).
+3. Use a non-OpenAI trace processor. See the [tracing docs](../tracing.md#custom-tracing-processors).
 
 ### Responses API support
 

docs/models/litellm.md

@@ -0,0 +1,73 @@
+# Using any model via LiteLLM
+
+!!! note
+
+    The LiteLLM integration is in beta. You may run into issues with some model providers, especially smaller ones. Please report any issues via [Github issues](https://github.com/openai/openai-agents-python/issues) and we'll fix quickly.
+
+[LiteLLM](https://docs.litellm.ai/docs/) is a library that allows you to use 100+ models via a single interface. We've added a LiteLLM integration to allow you to use any AI model in the Agents SDK.
+
+## Setup
+
+You'll need to ensure `litellm` is available. You can do this by installing the optional `litellm` dependency group:
+
+```bash
+pip install "openai-agents[litellm]"
+```
+
+Once done, you can use [`LitellmModel`][agents.extensions.models.litellm_model.LitellmModel] in any agent.
+
+## Example
+
+This is a fully working example. When you run it, you'll be prompted for a model name and API key. For example, you could enter:
+
+-   `openai/gpt-4.1` for the model, and your OpenAI API key
+-   `anthropic/claude-3-5-sonnet-20240620` for the model, and your Anthropic API key
+-   etc
+
+For a full list of models supported in LiteLLM, see the [litellm providers docs](https://docs.litellm.ai/docs/providers).
+
+```python
+from __future__ import annotations
+
+import asyncio
+
+from agents import Agent, Runner, function_tool, set_tracing_disabled
+from agents.extensions.models.litellm_model import LitellmModel
+
+@function_tool
+def get_weather(city: str):
+    print(f"[debug] getting weather for {city}")
+    return f"The weather in {city} is sunny."
+
+
+async def main(model: str, api_key: str):
+    agent = Agent(
+        name="Assistant",
+        instructions="You only respond in haikus.",
+        model=LitellmModel(model=model, api_key=api_key),
+        tools=[get_weather],
+    )
+
+    result = await Runner.run(agent, "What's the weather in Tokyo?")
+    print(result.final_output)
+
+
+if __name__ == "__main__":
+    # First try to get model/api key from args
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model", type=str, required=False)
+    parser.add_argument("--api-key", type=str, required=False)
+    args = parser.parse_args()
+
+    model = args.model
+    if not model:
+        model = input("Enter a model name for Litellm: ")
+
+    api_key = args.api_key
+    if not api_key:
+        api_key = input("Enter an API key for Litellm: ")
+
+    asyncio.run(main(model, api_key))
+```

docs/quickstart.md

@@ -186,4 +186,4 @@ Learn how to build more complex agentic flows:
 
 -   Learn about how to configure [Agents](agents.md).
 -   Learn about [running agents](running_agents.md).
--   Learn about [tools](tools.md), [guardrails](guardrails.md) and [models](models.md).
+-   Learn about [tools](tools.md), [guardrails](guardrails.md) and [models](models/index.md).

docs/ref/extensions/litellm.md

@@ -0,0 +1,3 @@
+# `LiteLLM Models`
+
+::: agents.extensions.models.litellm_model

mkdocs.yml

@@ -66,7 +66,9 @@ plugins:
                 - context.md
                 - guardrails.md
                 - multi_agent.md
-                - models.md
+                - Models:
+                    - models/index.md
+                    - models/litellm.md
                 - config.md
                 - visualization.md
                 - Voice agents:
@@ -123,6 +125,7 @@ plugins:
                 - Extensions:
                     - ref/extensions/handoff_filters.md
                     - ref/extensions/handoff_prompt.md
+                    - ref/extensions/litellm.md
 
         - locale: ja
           name: 日本語

src/agents/extensions/models/litellm_model.py

@@ -47,6 +47,11 @@ from ...usage import Usage
 
 
 class LitellmModel(Model):
+    """This class enables using any model via LiteLLM. LiteLLM allows you to acess OpenAPI,
+    Anthropic, Gemini, Mistral, and many other models.
+    See supported models here: [litellm models](https://docs.litellm.ai/docs/providers).
+    """
+
     def __init__(
         self,
         model: str,
@@ -140,9 +145,6 @@ class LitellmModel(Model):
         *,
         previous_response_id: str | None,
     ) -> AsyncIterator[TResponseStreamEvent]:
-        """
-        Yields a partial message as it is generated, as well as the usage information.
-        """
         with generation_span(
             model=str(self.model),
             model_config=dataclasses.asdict(model_settings)