Pre-release
This release is a pre-release and may not be stable for production use.
Union vLLM Plugin
Serve large language models using vLLM with Flyte Apps.
This plugin provides the VLLMAppEnvironment class for deploying and serving LLMs using vLLM.
Installation
pip install --pre flyteplugins-vllm
Usage
import flyte
import flyte.app
from flyteplugins.vllm import VLLMAppEnvironment
# Define the vLLM app environment
vllm_app = VLLMAppEnvironment(
name="my-llm-app",
model="s3://your-bucket/models/your-model",
model_id="your-model-id",
resources=flyte.Resources(cpu="4", memory="16Gi", gpu="L40s:1"),
stream_model=True, # Stream model directly from blob store to GPU
scaling=flyte.app.Scaling(
replicas=(0, 1),
scaledown_after=300,
),
)
if __name__ == "__main__":
flyte.init_from_config()
app = flyte.serve(vllm_app)
print(f"Deployed vLLM app: {app.url}")
Features
- Streaming Model Loading: Stream model weights directly from object storage to GPU memory, reducing startup time and disk requirements.
- OpenAI-Compatible API: The deployed app exposes an OpenAI-compatible API for chat completions.
- Auto-scaling: Configure scaling policies to scale up/down based on traffic.
- Tensor Parallelism: Support for distributed inference across multiple GPUs.
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