> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-studio-tools-doc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Cohere

> Use Cohere command models with Agno agents.

Leverage Cohere's powerful command models and more.

[Cohere](https://cohere.com) has a wide range of models and is really good for fine-tuning. See their library of models [here](https://docs.cohere.com/v2/docs/models).

We recommend experimenting to find the best-suited model for your use-case. Here are some general recommendations:

* `command` model is good for most basic use-cases.
* `command-light` model is good for smaller tasks and faster inference.
* `command-r7b-12-2024` model is good with RAG tasks, complex reasoning and multi-step tasks.

Cohere also supports fine-tuning models. Here is a [guide](https://docs.cohere.com/v2/docs/fine-tuning) on how to do it.

Cohere has tier-based rate limits. See the [docs](https://docs.cohere.com/v2/docs/rate-limits) for more information.

## Authentication

Set your `CO_API_KEY` environment variable. Get your key from [here](https://dashboard.cohere.com/api-keys).

<CodeGroup>
  ```bash Mac theme={null}
  export CO_API_KEY=***
  ```

  ```bash Windows theme={null}
  setx CO_API_KEY ***
  ```
</CodeGroup>

## Example

Use `Cohere` with your `Agent`:

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

  agent = Agent(
      model=Cohere(id="command-r-08-2024"),
      markdown=True
  )

  # Print the response in the terminal
  agent.print_response("Share a 2 sentence horror story.")

  ```
</CodeGroup>

<Note> View more examples [here](/models/providers/native/cohere/usage/basic). </Note>

## Params

| Parameter           | Type                          | Default            | Description                                                                                                                                                                                |
| ------------------- | ----------------------------- | ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `id`                | `str`                         | `"command-r-plus"` | The specific model ID used for generating responses.                                                                                                                                       |
| `name`              | `str`                         | `"cohere"`         | The name identifier for the agent.                                                                                                                                                         |
| `provider`          | `str`                         | `"Cohere"`         | The provider of the model.                                                                                                                                                                 |
| `temperature`       | `Optional[float]`             | `None`             | The sampling temperature to use, between 0 and 2. Higher values like 0.8 make the output more random, while lower values like 0.2 make it more focused and deterministic.                  |
| `max_tokens`        | `Optional[int]`               | `None`             | The maximum number of tokens to generate in the response.                                                                                                                                  |
| `top_k`             | `Optional[int]`               | `None`             | The number of highest probability vocabulary tokens to keep for top-k-filtering.                                                                                                           |
| `top_p`             | `Optional[float]`             | `None`             | Nucleus sampling parameter. The model considers the results of the tokens with top\_p probability mass.                                                                                    |
| `frequency_penalty` | `Optional[float]`             | `None`             | Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. |
| `presence_penalty`  | `Optional[float]`             | `None`             | Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.              |
| `seed`              | `Optional[int]`               | `None`             | Random seed for deterministic text generation.                                                                                                                                             |
| `logprobs`          | `Optional[bool]`              | `None`             | Whether to return log probabilities of the output tokens.                                                                                                                                  |
| `request_params`    | `Optional[Dict[str, Any]]`    | `None`             | Additional parameters to include in the request.                                                                                                                                           |
| `strict_tools`      | `bool`                        | `False`            | Whether to use strict mode for tools (enforce strict parameter requirements).                                                                                                              |
| `add_chat_history`  | `bool`                        | `False`            | Whether to add chat history to the Cohere messages instead of using the conversation\_id.                                                                                                  |
| `api_key`           | `Optional[str]`               | `None`             | The API key for authenticating requests to the Cohere service.                                                                                                                             |
| `client_params`     | `Optional[Dict[str, Any]]`    | `None`             | Additional parameters for client configuration.                                                                                                                                            |
| `client`            | `Optional[CohereClient]`      | `None`             | A pre-configured instance of the Cohere client.                                                                                                                                            |
| `async_client`      | `Optional[CohereAsyncClient]` | `None`             | A pre-configured instance of the async Cohere client.                                                                                                                                      |

`Cohere` is a subclass of the [Model](/reference/models/model) class and has access to the same params.