haive.core.models.llm.providers.xai¶

xAI Provider Module.

This module implements the xAI language model provider for the Haive framework, supporting Grok models developed by Elon Musk’s xAI company.

The provider handles API key management, model configuration, and safe imports of the langchain-xai package dependencies.

Examples

Basic usage:

from haive.core.models.llm.providers.xai import XAIProvider

provider = XAIProvider(
    model="grok-beta",
    temperature=0.7,
    max_tokens=1000
)
llm = provider.instantiate()

With custom parameters:

provider = XAIProvider(
    model="grok-1",
    temperature=0.1,
    top_p=0.9,
    stream=True
)

XAIProvider(*[, requests_per_second, ...])

xAI language model provider configuration.

Classes¶

XAIProvider

xAI language model provider configuration.

Module Contents¶

class haive.core.models.llm.providers.xai.XAIProvider(/, **data)[source]¶

Bases: haive.core.models.llm.providers.base.BaseLLMProvider

xAI language model provider configuration.

This provider supports xAI’s Grok family of models known for their real-time information access and conversational capabilities.

Parameters:

data (Any)
requests_per_second (float | None)
tokens_per_second (int | None)
tokens_per_minute (int | None)
max_retries (int)
retry_delay (float)
check_every_n_seconds (float | None)
burst_size (int | None)
provider (LLMProvider)
model (str | None)
name (str | None)
api_key (SecretStr)
cache_enabled (bool)
cache_ttl (int | None)
extra_params (dict[str, Any] | None)
debug (bool)
temperature (float | None)
max_tokens (int | None)
top_p (float | None)
stream (bool)
stop (list[str] | None)

provider¶

Always LLMProvider.XAI

Type:: LLMProvider

model¶

The xAI model to use

Type:: str

temperature¶

Sampling temperature (0.0-2.0)

Type:: float

max_tokens¶

Maximum tokens in response

Type:: int

top_p¶

Nucleus sampling parameter

Type:: float

stream¶

Enable streaming responses

Type:: bool

stop¶

Stop sequences for generation

Type:: list

Examples

Grok Beta for general conversation:

provider = XAIProvider(
    model="grok-beta",
    temperature=0.7,
    max_tokens=2000
)

Grok with streaming:

provider = XAIProvider(
    model="grok-1",
    temperature=0.1,
    stream=True,
    top_p=0.9
)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

classmethod get_models()[source]¶

Get available xAI models.

Return type:: list[str]

max_tokens: int | None = None¶: Get maximum total tokens for this model.