alpe/inference-manager

Inference Manager

inference-manager

The inference-manager manages inference runtimes (e.g., vLLM and Ollama) in containers, load models, and process requests.

Inferece Request flow.

Please see inference_request_flow.md.

Set up Inference Server/Engine for development

Requirements:

• Docker
• Kind
• Helmfile

Run the following command:

make setup-all

Tip

• Run just only make helm-reapply-inference-server or make helm-reapply-inference-engine, it will rebuild inference-manager container images, deploy them using the local helm chart, and restart containers.
• You can configure parameters in .values.yaml.

Run vLLM on ARM macOS

To run vLLM on ARM CPU (macOS), you'll need to build an image.

git clone https://github.com/vllm-project/vllm.git
cd vllm
docker build -f Dockerfile.arm -t vllm-cpu-env --shm-size=4g .
kind load docker-image vllm-cpu-env:latest

Then, run make with the RUNTIME option.

make setup-all RUNTIME=vllm

Note

See vLLM - ARM installation for details.

Try out inference APIs

with curl:

curl --request POST http://localhost:8080/v1/chat/completions -d '{
  "model": "google-gemma-2b-it-q4_0",
  "messages": [{"role": "user", "content": "hello"}]
}'

with llma:

export LLMARINER_API_KEY=dummy
llma chat completions create \
    --model google-gemma-2b-it-q4_0 \
    --role system \
    --completion 'hi'