Grok

Overview

xAI provides Grok models with real-time information access, strong reasoning capabilities, and multimodal understanding. All Grok models have built-in web search. Model Class: OpenAIChatModel (OpenAI-compatible API)

Authentication

export GROK_API_KEY="xai-..."

Examples

from upsonic import Agent, Task
from upsonic.models.grok import GrokModel

model = GrokModel(model_name="grok-4")

agent = Agent(model=model)

task = Task("Hello, how are you?")
result = agent.do(task)
print(result)

Model Settings

You can set model parameters in two ways: on the model or on the Agent. On the model:

from upsonic import Agent, Task
from upsonic.models.grok import GrokModel, GrokModelSettings

model = GrokModel(
    model_name="grok-4",
    settings=GrokModelSettings(max_tokens=1024, temperature=0.7)
)
agent = Agent(model=model)

On the Agent:

from upsonic import Agent, Task
from upsonic.models.grok import GrokModelSettings

agent = Agent(
    model="grok/grok-4",
    settings=GrokModelSettings(max_tokens=1024)
)

Parameters

Parameter	Type	Description	Default	Source
`max_tokens`	`int`	Maximum tokens to generate	Model default	Base
`temperature`	`float`	Sampling temperature (0.0-2.0)	1.0	Base
`top_p`	`float`	Nucleus sampling	1.0	Base
`seed`	`int`	Random seed	None	Base
`stop_sequences`	`list[str]`	Stop sequences	None	Base
`presence_penalty`	`float`	Token presence penalty	0.0	Base
`frequency_penalty`	`float`	Token frequency penalty	0.0	Base
`parallel_tool_calls`	`bool`	Allow parallel tools	True	Base
`timeout`	`float`	Request timeout (seconds)	600	Base

GET STARTED

CONCEPTS

STARTING AN AGENT PROJECT

READY TO USE SNIPPETS

DEPLOYMENT

FURTHER READINGS

Overview

Authentication

Examples

Model Settings

Parameters

​Overview

​Authentication

​Examples

​Model Settings

​Parameters

Overview

Authentication

Examples

Model Settings

Parameters