43 lines
1.2 KiB
ReStructuredText
43 lines
1.2 KiB
ReStructuredText
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.. _run_on_llamastack:
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Serving with Llama Stack
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============================
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vLLM is also available via `Llama Stack <https://github.com/meta-llama/llama-stack>`_ .
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To install Llama Stack, run
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.. code-block:: console
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$ pip install llama-stack -q
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Inference using OpenAI Compatible API
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-------------------------------------
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Then start Llama Stack server pointing to your vLLM server with the following configuration:
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.. code-block:: yaml
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inference:
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- provider_id: vllm0
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provider_type: remote::vllm
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config:
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url: http://127.0.0.1:8000
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Please refer to `this guide <https://github.com/meta-llama/llama-stack/blob/main/docs/source/getting_started/distributions/self_hosted_distro/remote_vllm.md>`_ for more details on this remote vLLM provider.
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Inference via Embedded vLLM
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---------------------------
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An `inline vLLM provider
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<https://github.com/meta-llama/llama-stack/tree/main/llama_stack/providers/inline/inference/vllm>`_
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is also available. This is a sample of configuration using that method:
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.. code-block:: yaml
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inference
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- provider_type: vllm
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config:
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model: Llama3.1-8B-Instruct
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tensor_parallel_size: 4
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