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Merge branch 'dev' into makefile-fix
Signed-off-by: Shmuel Kallner <kallner@il.ibm.com>
2 parents ba911e0 + c23cdb3 commit c3419f3

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.tekton/README.md

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<!-- NOTE TO CONTRIBUTORS: every repo in the hc4ai organization is intended to have the same contents in this file. The origin is the copy in https://github.ibm.com/mspreitz/hc4ai-hello-neural/blob/dev/.tekton/README.md; submit PRs against that one -->
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This pipeline is designed to support safe, efficient, and traceable development and deployment workflows using [OpenShift Pipelines-as-Code](https://pipelinesascode.com/), [Tekton](https://tekton.dev/), [buildah](https://buildah.io/), GitHub, and Quay.io.
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This pipeline is designed to support safe, efficient, and traceable development and deployment workflows using [OpenShift Pipelines-as-Code](https://pipelinesascode.com/), [Tekton](https://tekton.dev/), [buildah](https://buildah.io/), GitHub, and ghcr.io.
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This pipeline is used for CI/CD of the `dev` and `main` branches. This pipeline runs from source through container image build to deployment and testing in the hc4ai cluster.
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```json
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{
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"dev-version": "0.0.5",
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"dev-registry": "quay.io/llm-d/<your project name>-dev",
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"dev-registry": "ghcr.io/llm-d/<your project name>-dev",
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"prod-version": "0.0.4",
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"prod-registry": "quay.io/llm-d/<your project name>"
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"prod-registry": "ghcr.io/llm-d/<your project name>"
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}
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```
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This pipeline maintains two container repositories for this GitHub repository, as follows.
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- `quay.io/llm-d/<repoName>-dev`. Hold builds from the `dev` branch as described below.
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- `quay.io/llm-d/<repoName>`. Holds promotions to prod, as described below.
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- `ghcr.io/llm-d/<repoName>-dev`. Hold builds from the `dev` branch as described below.
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- `ghcr.io/llm-d/<repoName>`. Holds promotions to prod, as described below.
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---
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.tekton/buildah-build.yaml

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cp /workspace/registry/.dockerconfigjson /root/.docker/config.json
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echo "🔐 Extracting credentials..."
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USERNAME=$(jq -r '.auths["quay.io"].username' /root/.docker/config.json)
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PASSWORD=$(jq -r '.auths["quay.io"].password' /root/.docker/config.json)
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USERNAME=$(jq -r '.auths["ghcr.io"].username' /root/.docker/config.json)
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PASSWORD=$(jq -r '.auths["ghcr.io"].password' /root/.docker/config.json)
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if [ "$USERNAME" = "null" ] || [ "$PASSWORD" = "null" ]; then
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echo "❌ Error: Missing registry credentials"
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exit 1
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fi
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echo "🔓 Logging in to registry with Buildah..."
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buildah logout quay.io || true
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buildah login --username "$USERNAME" --password "$PASSWORD" quay.io
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buildah logout ghcr.io || true
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buildah login --username "$USERNAME" --password "$PASSWORD" ghcr.io
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export DOCKER_CONFIG=/root/.docker
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export BUILDER=buildah

.tekton/pipelinerun.yaml

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apiVersion: tekton.dev/v1
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kind: PipelineRun
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metadata:
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name: vllm-sim
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name: llm-d-inference-sim
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annotations:
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pipelinesascode.tekton.dev/on-event: "[pull_request, push]"
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pipelinesascode.tekton.dev/on-target-branch: "[main, dev]"
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secretName: "{{ git_auth_secret }}"
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- name: git-auth
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secret:
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secretName: "git-auth-secret-neuralmagic"
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secretName: "git-auth-secret-llm-d"
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# - name: registry-secret
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# secret:
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# secretName: quay-secret-llm-d
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- name: registry-secret
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secret:
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secretName: quay-secret-llm-d
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secretName: ghcr-secret-llm-d

.tekton/vuln-scan-trivy.yaml

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params:
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- name: IMAGE_URL
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type: string
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description: Full image URL (e.g., quay.io/org/image:tag)
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description: Full image URL (e.g., ghcr.io/org/image:tag)
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- name: SEVERITY
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type: string
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default: "CRITICAL,HIGH,MEDIUM"

.version.json

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{
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"dev-version": "0.0.5",
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"dev-registry": "quay.io/llm-d/vllm-sim-dev",
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"prod-version": "0.0.4",
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"prod-registry": "quay.io/llm-d/vllm-sim"
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"dev-version": "0.0.6",
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"dev-registry": "ghcr.io/llm-d/llm-d-inference-sim-dev",
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"prod-version": "0.0.5",
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"prod-registry": "ghcr.io/llm-d/llm-d-inference-sim"
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}

Dockerfile

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RUN go mod download
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# Copy the go source
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COPY cmd/vllm-sim/main.go cmd/cmd.go
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COPY cmd/llm-d-inference-sim/main.go cmd/cmd.go
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COPY . .
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# Build
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# the GOARCH has not a default value to allow the binary be built according to the host where the command
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# was called. For example, if we call make image-build in a local env which has the Apple Silicon M1 SO
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# the docker BUILDPLATFORM arg will be linux/arm64 when for Apple x86 it will be linux/amd64. Therefore,
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# by leaving it empty we can ensure that the container and binary shipped on it will have the same platform.
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RUN CGO_ENABLED=0 GOOS=${TARGETOS:-linux} GOARCH=${TARGETARCH} go build -a -o bin/vllm-sim cmd/cmd.go
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RUN CGO_ENABLED=0 GOOS=${TARGETOS:-linux} GOARCH=${TARGETARCH} go build -a -o bin/llm-d-inference-sim cmd/cmd.go
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# Use distroless as minimal base image to package the manager binary
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# Refer to https://github.com/GoogleContainerTools/distroless for more details
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FROM registry.access.redhat.com/ubi9/ubi:latest
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WORKDIR /
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COPY --from=builder /workspace/bin/vllm-sim /app/vllm-sim
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COPY --from=builder /workspace/bin/llm-d-inference-sim /app/llm-d-inference-sim
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USER 65532:65532
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ENTRYPOINT ["/app/vllm-sim"]
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ENTRYPOINT ["/app/llm-d-inference-sim"]
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Makefile

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# Copyright 2025 The vLLM-Sim Authors.
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# Copyright 2025 The llm-d-inference-sim Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Makefile for the vllm-sim project
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# Makefile for the llm-d-inference-sim project
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CONTAINER_RUNTIME ?= docker
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PACKAGE_VLLM_SIM = github.com/neuralmagic/vllm-sim/cmd/vllm-sim
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VLLM_SIM_NAME = vllm-sim/vllm-sim
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PACKAGE_VLLM_SIM = github.com/llm-d/llm-d-inference-sim/cmd/llm-d-inference-sim
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VLLM_SIM_NAME = llm-d-inference-sim/llm-d-inference-sim
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VLLM_SIM_TAG ?= 0.0.2
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.PHONY: build-vllm-sim
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build-vllm-sim:
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.PHONY: build-llm-d-inference-sim
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build-llm-d-inference-sim:
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go build -o bin/ ${PACKAGE_VLLM_SIM}
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.PHONY: build-vllm-sim-linux
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build-vllm-sim-linux:
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.PHONY: build-llm-d-inference-sim-linux
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build-llm-d-inference-sim-linux:
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CGO_ENABLED=0 GOOS=linux GOARCH=amd64 go build -o bin/linux/ ${PACKAGE_VLLM_SIM}
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.PHONY: build-vllm-sim-image
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build-vllm-sim-image: build-vllm-sim-linux
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$(CONTAINER_RUNTIME) build --file build/vllm-sim.Dockerfile --tag ${VLLM_SIM_NAME}:${VLLM_SIM_TAG} ./bin/linux
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.PHONY: build-llm-d-inference-sim-image
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build-llm-d-inference-sim-image: build-llm-d-inference-sim-linux
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$(CONTAINER_RUNTIME) build --file build/llm-d-inference-sim.Dockerfile --tag ${VLLM_SIM_NAME}:${VLLM_SIM_TAG} ./bin/linux
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SHELL := /usr/bin/env bash
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# Defaults
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PROJECT_NAME ?= vllm-sim
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PROJECT_NAME ?= llm-d-inference-sim
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DEV_VERSION ?= 0.0.1
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PROD_VERSION ?= 0.0.0
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IMAGE_TAG_BASE ?= quay.io/llm-d/$(PROJECT_NAME)
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IMAGE_TAG_BASE ?= ghcr.io/llm-d/$(PROJECT_NAME)
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IMG = $(IMAGE_TAG_BASE):$(DEV_VERSION)
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NAMESPACE ?= hc4ai-operator
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export DEV_VERSION; \
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export PROD_VERSION; \
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fi && \
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CURRENT_DEFAULT="quay.io/llm-d/$(PROJECT_NAME)"; \
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CURRENT_DEFAULT="ghcr.io/llm-d/$(PROJECT_NAME)"; \
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if [ "$(IMAGE_TAG_BASE)" = "$$CURRENT_DEFAULT" ]; then \
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IMAGE_TAG_BASE=$$(jq -r '."dev-registry"' .version.json); \
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echo "✔ Loaded IMAGE_TAG_BASE from .version.json: $$IMAGE_TAG_BASE"; \

README.md

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### Building
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To build a Docker image of the vLLM Simulator, run:
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```bash
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make build-vllm-sim-image
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make build-llm-d-inference-sim-image
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```
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### Running
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To run the vLLM Simulator image under Docker, run:
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```bash
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docker run --rm --publish 8000:8000 ai-aware-router/vllm-sim:0.0.1 /ai-aware-router/vllm-sim --port 8000 --model "Qwen/Qwen2.5-1.5B-Instruct" --lora "tweet-summary-0,tweet-summary-1"
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docker run --rm --publish 8000:8000 ai-aware-router/llm-d-inference-sim:0.0.1 /ai-aware-router/llm-d-inference-sim --port 8000 --model "Qwen/Qwen2.5-1.5B-Instruct" --lora "tweet-summary-0,tweet-summary-1"
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```
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**Note:** The above command exposes the simulator on port 8000, and serves the Qwen/Qwen2.5-1.5B-Instruct model.
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### Building
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To build the vLLM simulator, run:
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```bash
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make build-vllm-sim
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make build-llm-d-inference-sim
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```
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### Running
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To run the router in a standalone test environment, run:
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```bash
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./bin/vllm-sim --model my_model --port 8000
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./bin/llm-d-inference-sim --model my_model --port 8000
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```
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build/vllm-sim.Dockerfile

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# Copyright 2025 The vLLM-Sim Authors.
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# Copyright 2025 The llm-d-inference-sim Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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FROM alpine:3.21
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ADD --chmod=777 ./vllm-sim /vllm-sim/
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ADD --chmod=777 ./llm-d-inference-sim /llm-d-inference-sim/
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WORKDIR /vllm-sim/
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WORKDIR /llm-d-inference-sim/
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ENTRYPOINT ["/vllm-sim/vllm-sim"]
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ENTRYPOINT ["/llm-d-inference-sim/llm-d-inference-sim"]

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/*
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Copyright 2025 The vLLM-Sim Authors.
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Copyright 2025 The llm-d-inference-sim Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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"k8s.io/klog/v2"
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"github.com/neuralmagic/vllm-sim/cmd/signals"
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vllmsim "github.com/neuralmagic/vllm-sim/pkg/vllm-sim"
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"github.com/llm-d/llm-d-inference-sim/cmd/signals"
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vllmsim "github.com/llm-d/llm-d-inference-sim/pkg/llm-d-inference-sim"
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)
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func main() {

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