multi-LoRA as extra models in OpenAI server (#2775)

how to serve the loras (mimicking the [multilora inference example](https://github.com/vllm-project/vllm/blob/main/examples/multilora_inference.py)):
```terminal
$ export LORA_PATH=~/.cache/huggingface/hub/models--yard1--llama-2-7b-sql-lora-test/
$ python -m vllm.entrypoints.api_server \
 --model meta-llama/Llama-2-7b-hf \
 --enable-lora \
 --lora-modules sql-lora=$LORA_PATH sql-lora2=$LORA_PATH
```
the above server will list 3 separate values if the user queries `/models`: one for the base served model, and one each for the specified lora modules. in this case sql-lora and sql-lora2 point to the same underlying lora, but this need not be the case. lora config values take the same values they do in EngineArgs

no work has been done here to scope client permissions to specific models
This commit is contained in:
jvmncs
2024-02-17 15:00:48 -05:00
committed by GitHub
parent 185b2c29e2
commit 8f36444c4f
7 changed files with 200 additions and 27 deletions

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@ -49,4 +49,43 @@ the third parameter is the path to the LoRA adapter.
Check out `examples/multilora_inference.py <https://github.com/vllm-project/vllm/blob/main/examples/multilora_inference.py>`_
for an example of how to use LoRA adapters with the async engine and how to use more advanced configuration options.
for an example of how to use LoRA adapters with the async engine and how to use more advanced configuration options.
Serving LoRA Adapters
---------------------
LoRA adapted models can also be served with the Open-AI compatible vLLM server. To do so, we use
``--lora-modules {name}={path} {name}={path}`` to specify each LoRA module when we kickoff the server:
.. code-block:: bash
python -m vllm.entrypoints.api_server \
--model meta-llama/Llama-2-7b-hf \
--enable-lora \
--lora-modules sql-lora=~/.cache/huggingface/hub/models--yard1--llama-2-7b-sql-lora-test/
The server entrypoint accepts all other LoRA configuration parameters (``max_loras``, ``max_lora_rank``, ``max_cpu_loras``,
etc.), which will apply to all forthcoming requests. Upon querying the ``/models`` endpoint, we should see our LoRA along
with its base model:
.. code-block:: bash
curl localhost:8000/v1/models | jq .
{
"object": "list",
"data": [
{
"id": "meta-llama/Llama-2-7b-hf",
"object": "model",
...
},
{
"id": "sql-lora",
"object": "model",
...
}
]
}
Requests can specify the LoRA adapter as if it were any other model via the ``model`` request parameter. The requests will be
processed according to the server-wide LoRA configuration (i.e. in parallel with base model requests, and potentially other
LoRA adapter requests if they were provided and ``max_loras`` is set high enough).