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xAI (Grok)

xAI (Grok)

Configure xAI (X.AI) language models for Letta agents.

Enabling xAI (Grok) models

Section titled “Enabling xAI (Grok) models”

To enable the xAI provider, set your key as an environment variable:

Terminal window
export XAI_API_KEY="..."

Enabling xAI with Docker

Section titled “Enabling xAI with Docker”

To enable xAI models when running the Letta server with Docker, set your XAI_API_KEY as an environment variable:

Terminal window
# replace `~/.letta/.persist/pgdata` with wherever you want to store your agent data
docker run \
  -v ~/.letta/.persist/pgdata:/var/lib/postgresql/data \
  -p 8283:8283 \
  -e XAI_API_KEY="your_xai_api_key" \
  letta/letta:latest

See the self-hosting guide for more information on running Letta with Docker.

Specifying agent models

Section titled “Specifying agent models”

When creating agents on your self-hosted server, you must specify both the LLM and embedding models to use. You can additionally specify a context window limit (which must be less than or equal to the maximum size).

from letta_client import Letta
import os


# Connect to your self-hosted server
client = Letta(base_url="http://localhost:8283")


agent = client.agents.create(
    model="xai/grok-2-1212",
    embedding="openai/text-embedding-3-small",  # An embedding model is required for self-hosted
    # optional configuration
    context_window_limit=30000
)

xAI (Grok) models have very large context windows, which will be very expensive and high latency. We recommend setting a lower context_window_limit when using xAI (Grok) models.