Skip vLLM image pull when no GPU present
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---
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# vLLM — high-performance LLM inference with OpenAI-compatible API
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# vLLM — high-performance LLM inference with OpenAI-compatible API
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# Entry tier: runs as a Docker container (easier to manage than pip install)
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# Skipped automatically if no GPU is present.
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- name: Check for NVIDIA GPU
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shell: nvidia-smi --query-gpu=name --format=csv,noheader 2>/dev/null | head -1
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register: gpu_check
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ignore_errors: true
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changed_when: false
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- name: Skip vLLM if no GPU detected
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debug:
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msg: "No GPU detected — skipping vLLM image pull. Run manually when GPU is available: docker pull vllm/vllm-openai:latest"
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when: gpu_check.stdout == "" or gpu_check.rc != 0
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- name: Pull vLLM Docker image
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- name: Pull vLLM Docker image
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shell: docker pull vllm/vllm-openai:latest
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shell: docker pull vllm/vllm-openai:latest
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retries: 3
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retries: 3
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delay: 15
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delay: 15
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when: gpu_check.stdout != "" and gpu_check.rc == 0
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- name: Create vLLM systemd service
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- name: Create vLLM systemd service
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copy:
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copy:
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@ -38,16 +51,6 @@
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WantedBy=multi-user.target
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WantedBy=multi-user.target
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mode: "0644"
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mode: "0644"
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- name: Enable vLLM (but don't start yet — model selection needed first)
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systemd:
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name: vllm
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enabled: yes
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daemon_reload: yes
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# Note: vLLM service is enabled but not started by default.
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# Start manually after choosing a model:
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# sudo systemctl start vllm
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# Or change the --model flag in /etc/systemd/system/vllm.service first.
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- name: Create vLLM model directory
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- name: Create vLLM model directory
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file:
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file:
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path: /opt/cezen/models/hf_cache
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path: /opt/cezen/models/hf_cache
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