---
title: Anthropic
slug: guides/server/providers/anthropic
---
<Tip>To enable Anthropic models with Letta, set `ANTHROPIC_API_KEY` in your environment variables. </Tip>

You can use Letta with Anthropic if you have an Anthropic account and API key.
Currently, only there are no supported **embedding** models for Anthropic (only LLM models).
You will need to use a seperate provider (e.g. OpenAI) or the Letta embeddings endpoint (`letta-free`) for embeddings.

## Enabling Anthropic models
To enable the Anthropic provider, set your key as an environment variable:
```bash
export ANTHROPIC_API_KEY="sk-ant-..."
```
Now, Anthropic models will be enabled with you run `letta run` or start the Letta server.

### Using the `docker run` server with Anthropic
To enable Anthropic models, simply set your `ANTHROPIC_API_KEY` as an environment variable:
```bash
# 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 ANTHROPIC_API_KEY="your_anthropic_api_key" \
  letta/letta:latest
```

<Accordion icon="square-terminal" title="CLI (pypi only)">
### Using `letta run` and `letta server` with Anthropic
To chat with an agent, run:
```bash
export ANTHROPIC_API_KEY="sk-ant-..."
letta run
```
This will prompt you to select an Anthropic model.
```
? Select LLM model: (Use arrow keys)
 » letta-free [type=openai] [ip=https://inference.letta.com]
   claude-3-opus-20240229 [type=anthropic] [ip=https://api.anthropic.com/v1]
   claude-3-sonnet-20240229 [type=anthropic] [ip=https://api.anthropic.com/v1]
   claude-3-haiku-20240307 [type=anthropic] [ip=https://api.anthropic.com/v1]
```
To run the Letta server, run:
```bash
export ANTHROPIC_API_KEY="sk-ant-..."
letta server
```
To select the model used by the server, use the dropdown in the ADE or specify a `LLMConfig` object in the Python SDK.
</Accordion>

## Configuring Anthropic models

When creating agents, you must specify 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). Note that Anthropic does not have embedding models, so you will need to use another provider.

```python
from letta_client import Letta

client = Letta(base_url="http://localhost:8283")

agent = client.agents.create(
    model="anthropic/claude-3-5-sonnet-20241022",
    embedding="openai/text-embedding-3-small",
    # optional configuration
    context_window_limit=30000
)
```
Anthropic models have very large context windows, which will be very expensive and high latency. We recommend setting a lower `context_window_limit` when using Anthropic models.