vision-agents-plugins-xai 0.4.7

XAI for stream agents

XAI Plugin for Stream Agents

This package provides xAI (Grok) integration for the Stream Agents ecosystem, enabling you to use xAI's powerful language models in your conversational AI applications.

Features

• Native xAI SDK Integration: Full access to xAI's chat completion and streaming APIs
• Conversation Memory: Automatic conversation history management
• Streaming Support: Real-time response streaming with standardized events
• Multimodal Support: Handle text and image inputs
• Event System: Subscribe to response events for custom handling
• Easy Integration: Drop-in replacement for other LLM providers

Installation

uv add "vision-agents[xai]"
# or directly
uv add vision-agents-plugins-xai

Quick Start

import asyncio
from vision_agents.plugins import xai

async def main():
    # Initialize with your xAI API key
    llm = xai.LLM(
        model="grok-4",
        api_key="your_xai_api_key"  # or set XAI_API_KEY environment variable
    )

    # Simple response
    response = await llm.simple_response("Explain quantum computing in simple terms")

    print(f"\n\nComplete response: {response.text}")

if __name__ == "__main__":
    asyncio.run(main())

Advanced Usage

Conversation with Memory

from vision_agents.plugins import xai

llm = xai.LLM(model="grok-4", api_key="your_api_key")

# First message
await llm.simple_response("My name is Alice and I have 2 cats")

# Second message - the LLM remembers the context
response = await llm.simple_response("How many pets do I have?")
print(response.text)  # Will mention the 2 cats

Using Instructions

llm = LLM(
    model="grok-4",
    api_key="your_api_key"
)

# Create a response with system instructions
response = await llm.create_response(
    input="Tell me about the weather",
    instructions="You are a helpful weather assistant. Always be cheerful and optimistic.",
    stream=True
)

Multimodal Input

# Handle complex multimodal messages
advanced_message = [
    {
        "role": "user",
        "content": [
            {"type": "input_text", "text": "What do you see in this image?"},
            {"type": "input_image", "image_url": "https://example.com/image.jpg"},
        ],
    }
]

messages = LLM._normalize_message(advanced_message)
# Use with your conversation system

API Reference

XAILLM Class

Constructor

LLM(
    model: str = "grok-4",
    api_key: Optional[str] = None,
    client: Optional[AsyncClient] = None
)

Parameters:

• model: xAI model to use (default: "grok-4")
• api_key: Your xAI API key (default: reads from XAI_API_KEY environment variable)
• client: Optional pre-configured xAI AsyncClient

Methods

async simple_response(text: str, processors=None, participant=None)

Generate a simple response to text input.

Parameters:

• text: Input text to respond to
• processors: Optional list of processors for video/voice AI context
• participant: Optional participant object

Returns: LLMResponseEvent[Response] with the generated text

async create_response(input: str, instructions: str = "", model: str = None, stream: bool = True)

Create a response with full control over parameters.

Parameters:

• input: Input text
• instructions: System instructions for the model
• model: Override the default model
• stream: Whether to stream the response (default: True)

Returns: LLMResponseEvent[Response] with the generated text

Configuration

Environment Variables

• XAI_API_KEY: Your xAI API key (required if not provided in constructor)

Requirements

• Python 3.10+
• xai-sdk
• vision-agents-core

License

Apache-2.0