[CI/Build] Replace vllm.entrypoints.openai.api_server entrypoint with vllm serve command (#25967)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2025-10-03 01:04:57 +08:00
committed by GitHub
parent 3b279a84be
commit d00d652998
22 changed files with 101 additions and 66 deletions

View File

@@ -32,6 +32,7 @@ See the vLLM SkyPilot YAML for serving, [serving.yaml](https://github.com/skypil
ports: 8081 # Expose to internet traffic.
envs:
PYTHONUNBUFFERED: 1
MODEL_NAME: meta-llama/Meta-Llama-3-8B-Instruct
HF_TOKEN: <your-huggingface-token> # Change to your own huggingface token, or use --env to pass.
@@ -47,9 +48,8 @@ See the vLLM SkyPilot YAML for serving, [serving.yaml](https://github.com/skypil
run: |
conda activate vllm
echo 'Starting vllm api server...'
python -u -m vllm.entrypoints.openai.api_server \
vllm serve $MODEL_NAME \
--port 8081 \
--model $MODEL_NAME \
--trust-remote-code \
--tensor-parallel-size $SKYPILOT_NUM_GPUS_PER_NODE \
2>&1 | tee api_server.log &
@@ -131,6 +131,7 @@ SkyPilot can scale up the service to multiple service replicas with built-in aut
ports: 8081 # Expose to internet traffic.
envs:
PYTHONUNBUFFERED: 1
MODEL_NAME: meta-llama/Meta-Llama-3-8B-Instruct
HF_TOKEN: <your-huggingface-token> # Change to your own huggingface token, or use --env to pass.
@@ -146,9 +147,8 @@ SkyPilot can scale up the service to multiple service replicas with built-in aut
run: |
conda activate vllm
echo 'Starting vllm api server...'
python -u -m vllm.entrypoints.openai.api_server \
vllm serve $MODEL_NAME \
--port 8081 \
--model $MODEL_NAME \
--trust-remote-code \
--tensor-parallel-size $SKYPILOT_NUM_GPUS_PER_NODE \
2>&1 | tee api_server.log
@@ -243,6 +243,7 @@ This will scale the service up to when the QPS exceeds 2 for each replica.
ports: 8081 # Expose to internet traffic.
envs:
PYTHONUNBUFFERED: 1
MODEL_NAME: meta-llama/Meta-Llama-3-8B-Instruct
HF_TOKEN: <your-huggingface-token> # Change to your own huggingface token, or use --env to pass.
@@ -258,9 +259,8 @@ This will scale the service up to when the QPS exceeds 2 for each replica.
run: |
conda activate vllm
echo 'Starting vllm api server...'
python -u -m vllm.entrypoints.openai.api_server \
vllm serve $MODEL_NAME \
--port 8081 \
--model $MODEL_NAME \
--trust-remote-code \
--tensor-parallel-size $SKYPILOT_NUM_GPUS_PER_NODE \
2>&1 | tee api_server.log