Groq

Example

from phi.agent import Agent
from phi.model.groq import Groq

agent = Agent(
    model=Groq(id="llama3-groq-70b-8192-tool-use-preview"),
    show_tool_calls=True,
    markdown=True,
)

agent.print_response("What is the stock price of NVDA and TSLA")

Groq Params

Parameter	Type	Default	Description
`id`	`str`	`"llama3-groq-70b-8192-tool-use-preview"`	The specific model ID used for generating responses.
`name`	`str`	`"Groq"`	The name identifier for the agent.
`provider`	`str`	`"Groq"`	The provider of the model.
`frequency_penalty`	`Optional[float]`	-	A 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.
`logit_bias`	`Optional[Any]`	-	A JSON object that modifies the likelihood of specified tokens appearing in the completion by mapping token IDs to bias values between -100 and 100.
`logprobs`	`Optional[bool]`	-	Whether to return log probabilities of the output tokens.
`max_tokens`	`Optional[int]`	-	The maximum number of tokens to generate in the chat completion.
`presence_penalty`	`Optional[float]`	-	A 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.
`response_format`	`Optional[Dict[str, Any]]`	-	Specifies the format that the model must output. Setting to `{ "type": "json_object" }` enables JSON mode, ensuring the message generated is valid JSON.
`seed`	`Optional[int]`	-	A seed value for deterministic sampling, ensuring repeated requests with the same seed and parameters return the same result.
`stop`	`Optional[Union[str, List[str]]]`	-	Up to 4 sequences where the API will stop generating further tokens.
`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.
`top_logprobs`	`Optional[int]`	-	The number of top log probabilities to return for each generated token.
`top_p`	`Optional[float]`	-	Nucleus sampling parameter. The model considers the results of the tokens with top_p probability mass.
`user`	`Optional[str]`	-	A unique identifier representing your end-user, helping to monitor and detect abuse.
`request_params`	`Optional[Dict[str, Any]]`	-	Additional parameters to include in the request.
`api_key`	`Optional[str]`	-	The API key for authenticating requests to the service.
`base_url`	`Optional[Union[str, httpx.URL]]`	-	The base URL for making API requests to the service.
`timeout`	`Optional[int]`	-	The timeout duration for requests, specified in seconds.
`max_retries`	`Optional[int]`	-	The maximum number of retry attempts for failed requests.
`client_params`	`Optional[Dict[str, Any]]`	-	Additional parameters for client configuration.
`groq_client`	`Optional[GroqClient]`	-	An instance of GroqClient provided for making API requests.

Groq is a subclass of the Model class and has access to the same params.

Building Blocks

Command Line

Example

Groq Params

​Example

​Groq Params

Example

Groq Params