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Xi Yan 2025-03-23 15:48:14 -07:00
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12
docs/source/distributions/self_hosted_distro/remote-vllm.md
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@ -29,7 +29,7 @@ You can use this distribution if you have GPUs and want to run an independent vL
The following environment variables can be configured:
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
- `LLAMA_STACK_PORT`: Port for the Llama Stack distribution server (default: `8321`)
- `INFERENCE_MODEL`: Inference model loaded into the vLLM server (default: `meta-llama/Llama-3.2-3B-Instruct`)
- `VLLM_URL`: URL of the vLLM server with the main inference model (default: `http://host.docker.internal:5100/v1`)
- `MAX_TOKENS`: Maximum number of tokens for generation (default: `4096`)
@ -47,6 +47,7 @@ export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
export CUDA_VISIBLE_DEVICES=0
docker run \
--pull always \
--runtime nvidia \
--gpus $CUDA_VISIBLE_DEVICES \
-v ~/.cache/huggingface:/root/.cache/huggingface \
@ -59,6 +60,8 @@ docker run \
--port $INFERENCE_PORT
```
Note that you'll also need to set `--enable-auto-tool-choice` and `--tool-call-parser` to [enable tool calling in vLLM](https://docs.vllm.ai/en/latest/features/tool_calling.html).
If you are using Llama Stack Safety / Shield APIs, then you will need to also run another instance of a vLLM with a corresponding safety model like `meta-llama/Llama-Guard-3-1B` using a script like:
```bash
@ -67,6 +70,7 @@ export SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
export CUDA_VISIBLE_DEVICES=1
docker run \
--pull always \
--runtime nvidia \
--gpus $CUDA_VISIBLE_DEVICES \
-v ~/.cache/huggingface:/root/.cache/huggingface \
@ -90,10 +94,11 @@ This method allows you to get started quickly without having to build the distri
```bash
export INFERENCE_PORT=8000
export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
export LLAMA_STACK_PORT=5001
export LLAMA_STACK_PORT=8321
docker run \
-it \
--pull always \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ./run.yaml:/root/my-run.yaml \
llamastack/distribution-remote-vllm \
@ -115,6 +120,7 @@ cd /path/to/llama-stack
docker run \
-it \
--pull always \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
-v ./llama_stack/templates/remote-vllm/run-with-safety.yaml:/root/my-run.yaml \
@ -135,7 +141,7 @@ Make sure you have done `uv pip install llama-stack` and have the Llama Stack CL
```bash
export INFERENCE_PORT=8000
export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
export LLAMA_STACK_PORT=5001
export LLAMA_STACK_PORT=8321
cd distributions/remote-vllm
llama stack build --template remote-vllm --image-type conda