> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# OpenAI-compatible models

> Use any OpenAI-compatible endpoint with Agno agents.

Many providers support the OpenAI API format. Use the `OpenAILike` model to access them by replacing the `base_url`.

## Example

<CodeGroup>
  ```python agent.py theme={null}
  from os import getenv
  from agno.agent import Agent
  from agno.models.openai.like import OpenAILike

  agent = Agent(
      model=OpenAILike(
          id="mistralai/Mixtral-8x7B-Instruct-v0.1",
          api_key=getenv("TOGETHER_API_KEY"),
          base_url="https://api.together.xyz/v1",
      )
  )

  # Print the response in the terminal
  agent.print_response("Share a 2 sentence horror story.")
  ```
</CodeGroup>

## Parameters

| Parameter                       | Type            | Default          | Description                                                                                            |
| ------------------------------- | --------------- | ---------------- | ------------------------------------------------------------------------------------------------------ |
| `id`                            | `str`           | `"not-provided"` | The id of the model to use                                                                             |
| `name`                          | `str`           | `"OpenAILike"`   | The name of the model                                                                                  |
| `provider`                      | `str`           | `"OpenAILike"`   | The provider of the model                                                                              |
| `api_key`                       | `Optional[str]` | `"not-provided"` | The API key for authentication                                                                         |
| `base_url`                      | `Optional[str]` | `None`           | The base URL for the API service                                                                       |
| `collect_metrics_on_completion` | `bool`          | `False`          | Collect token metrics only from the final streaming chunk (for providers with cumulative token counts) |

`OpenAILike` extends the OpenAI-compatible interface and supports all parameters from [OpenAIChat](/models/providers/native/openai/completion/overview). Simply change the `base_url` and `api_key` to point to your preferred OpenAI-compatible service.

## Responses API

For providers that implement the [Open Responses API specification](https://openresponses.org), use `OpenResponses`:

<CodeGroup>
  ```python agent.py theme={null}
  from agno.agent import Agent
  from agno.models.openai import OpenResponses

  agent = Agent(
      model=OpenResponses(
          id="your-model-id",
          base_url="https://your-provider.com/v1",
          api_key="your-api-key",
      ),
  )

  agent.print_response("Share a 2 sentence horror story.")
  ```
</CodeGroup>

The Responses API is stateless by default. Each request is independent with no `previous_response_id` chaining.

For specific providers, use the dedicated classes:

* [OllamaResponses](/reference/models/ollama-responses) for Ollama (v0.13.3+)
* [OpenRouterResponses](/reference/models/openrouter-responses) for OpenRouter

See [OpenResponses reference](/reference/models/open-responses) for full parameters.