nevamind-ai--memu/docs/providers/grok.md

Grok (xAI) Provider

memU includes first-class support for Grok, allowing you to leverage xAI's powerful language models directly within your application.

Prerequisites

To use this provider, you must have an active xAI account.

1. Navigate to the xAI Console.
2. Sign up or log in.
3. Create a new API Key in the API Keys section.

Configuration

The integration is designed to work out-of-the-box with minimal configuration.

Environment Variables

Set the following environment variable in your .env file or system environment:

GROK_API_KEY=xai-YOUR_API_KEY_HERE

Defaults

When you select the grok provider, memU automatically configures the following defaults:

• Base URL: https://api.x.ai/v1
• Model: grok-2-latest

Usage Example

You can enable the Grok provider by setting the provider field to "grok" in your application configuration.

Using Python Configuration

import os
from memu.app.settings import LLMConfig
from memu.app.service import MemoryService

# Configure the LLM provider to use Grok
llm_config = LLMConfig(
    provider="grok",
    api_key=os.environ.get("GROK_API_KEY", ""),
)

# Initialize the service — pass config via llm_profiles, not llm_config
service = MemoryService(llm_profiles={"default": llm_config})
print(f"Service initialized with model: {llm_config.chat_model}")
# Output: Service initialized with model: grok-2-latest

Troubleshooting

Connection Issues

If you are unable to connect to the xAI API:

1. Verify that your GROK_API_KEY is set correctly and has not expired.
2. Ensure that the base_url is resolving to https://api.x.ai/v1. If you have manual overrides in your settings, they might be conflicting with the default.

Model Availability

If you receive a 404 or "Model not found" error, xAI may have updated their model names. You can override the model manually in the config if needed:

config = LLMConfig(
    provider="grok",
    chat_model="grok-beta" # Example override
)