Example
from phi.agent import Agent
from phi.model.cohere import CohereChat
agent = Agent(
model=CohereChat(id="command-r-08-2024"),
show_tool_calls=True,
markdown=True,
)
agent.print_response("Give me in-depth analysis of NVDA and TSLA")
Cohere Params
| Parameter | Type | Default | Description |
|---|---|---|---|
id | str | "command-r-08-2024" | The specific model ID used for generating responses. |
name | str | "CohereChat" | The name identifier for the agent. |
provider | str | "Cohere" | The provider of the model. |
temperature | Optional[float] | - | 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] | - | The maximum number of tokens to generate in the response. |
top_k | Optional[int] | - | The number of highest probability vocabulary tokens to keep for top-k-filtering. |
top_p | Optional[float] | - | Nucleus sampling parameter. The model considers the results of the tokens with top_p probability mass. |
frequency_penalty | Optional[float] | - | 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] | - | 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. |
request_params | Optional[Dict[str, Any]] | - | Additional parameters to include in the request. |
add_chat_history | bool | False | Whether to add chat history to the Cohere messages instead of using the conversation_id. |
api_key | Optional[str] | - | The API key for authenticating requests to the Cohere service. |
client_params | Optional[Dict[str, Any]] | - | Additional parameters for client configuration. |
cohere_client | Optional[CohereClient] | - | A pre-configured instance of the Cohere client. |
Cohere is a subclass of the Model class and has access to the same params.