58 lines
2.1 KiB
Plaintext
58 lines
2.1 KiB
Plaintext
---
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title: DeepSeek
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slug: guides/server/providers/deepseek
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---
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<Tip>To use Letta with the DeepSeek API, set the environment variable `DEEPSEEK_API_KEY=...`</Tip>
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You can use Letta with [DeepSeek](https://api-docs.deepseek.com/) if you have a DeepSeek account and API key. Once you have set your `DEEPSEEK_API_KEY` in your environment variables, you can select what model and configure the context window size.
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<Warning>
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Please note that R1 doesn't natively support function calling in DeepSeek API and V3 function calling is unstable, which may result in unstable tool calling inside of Letta agents.
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</Warning>
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<Warning>
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The DeepSeek API for R1 is often down. Please make sure you can connect to DeepSeek API directly by running:
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```bash
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curl https://api.deepseek.com/v1/chat/completions \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer $DEEPSEEK_API_KEY" \
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-d '{
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"model": "deepseek-reasoner",
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"messages": [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Hello!"}
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],
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"stream": false
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}'
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```
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</Warning>
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## Enabling DeepSeek as a provider
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To enable the DeepSeek provider, you must set the `DEEPSEEK_API_KEY` environment variable. When this is set, Letta will use available LLM models running on DeepSeek.
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### Using the `docker run` server with DeepSeek
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To enable DeepSeek models, simply set your `DEEPSEEK_API_KEY` as an environment variable:
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```bash
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# replace `~/.letta/.persist/pgdata` with wherever you want to store your agent data
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docker run \
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-v ~/.letta/.persist/pgdata:/var/lib/postgresql/data \
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-p 8283:8283 \
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-e DEEPSEEK_API_KEY="your_deepseek_api_key" \
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letta/letta:latest
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```
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<Accordion icon="square-terminal" title="CLI (pypi only)">
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### Using `letta run` and `letta server` with DeepSeek
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To chat with an agent, run:
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```bash
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export DEEPSEEK_API_KEY="..."
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letta run
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```
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To run the Letta server, run:
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```bash
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export DEEPSEEK_API_KEY="..."
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letta server
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```
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To select the model used by the server, use the dropdown in the ADE or specify a `LLMConfig` object in the Python SDK.
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</Accordion>
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