230 lines
7.0 KiB
YAML
230 lines
7.0 KiB
YAML
---
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# ------------------------------------------------------------------------------
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# FILE: roles/ollama/tasks/main.yml
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# DESCRIPTION: Deploys Ollama with AMD ROCm GPU acceleration on Ubuntu 24.04.
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# Handles:
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# - ROCm repository and driver stack installation
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# - Data disk preparation (LVM, ext4, persistent mount)
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# - Ollama installation and systemd service configuration
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# - HSA override for RX 5000-series (gfx1010) compatibility
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# - Initial model pull
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# ------------------------------------------------------------------------------
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# ------------------------------------------------------------------------------
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# ROCm prerequisites
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# ------------------------------------------------------------------------------
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- name: Install ROCm prerequisite packages
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apt:
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name:
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- wget
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- gnupg
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- ca-certificates
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- lvm2
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state: present
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update_cache: yes
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- name: Add ROCm apt repository signing key
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apt_key:
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url: https://repo.radeon.com/rocm/rocm.gpg.key
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state: present
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- name: Add ROCm apt repository
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apt_repository:
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repo: "deb [arch=amd64] https://repo.radeon.com/rocm/apt/{{ ollama_rocm_version }} {{ ansible_distribution_release }} main"
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state: present
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filename: rocm
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notify: update apt cache
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- name: Flush handlers to update apt cache before ROCm install
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meta: flush_handlers
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# ------------------------------------------------------------------------------
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# ROCm driver stack
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# hip-runtime-amd pulls in the full ROCm stack as a dependency.
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# rocminfo is used to verify GPU visibility after install.
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# ------------------------------------------------------------------------------
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- name: Install ROCm packages
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apt:
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name: "{{ ollama_rocm_packages }}"
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state: present
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notify: update initramfs
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- name: Create /opt/rocm symlink to versioned directory
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file:
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src: "/opt/rocm-{{ ollama_rocm_version }}.0"
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dest: /opt/rocm
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state: link
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force: false
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- name: Add ROCm binaries to system PATH
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copy:
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dest: /etc/profile.d/rocm.sh
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content: |
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export PATH=$PATH:/opt/rocm/bin
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/rocm/lib
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mode: '0644'
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- name: Add wed user to render and video groups for GPU access
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user:
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name: "{{ ansible_user }}"
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groups:
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- render
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- video
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append: yes
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- name: Add ollama user to render and video groups (created by Ollama installer)
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user:
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name: ollama
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groups:
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- render
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- video
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append: yes
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ignore_errors: yes
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# ollama user does not exist yet at this point — Ollama installer creates it.
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# This task re-runs after install via the post-install handler.
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# ------------------------------------------------------------------------------
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# Data disk — LVM setup on /dev/sdb
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# Follows the same pattern as the monitoring role (cinderella-castle).
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# Wipes any stale GPT/partition signatures before creating the PV to avoid
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# the "GPT protective partition" error encountered during monitoring deploy.
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# ------------------------------------------------------------------------------
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- name: Wipe any existing partition signatures from data disk
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command: wipefs -a {{ ollama_data_disk }}
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args:
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creates: /dev/{{ ollama_data_vg }}
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when: ollama_setup_data_disk | bool
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- name: Create LVM physical volume on data disk
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command: pvcreate {{ ollama_data_disk }}
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args:
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creates: /dev/{{ ollama_data_vg }}
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when: ollama_setup_data_disk | bool
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- name: Create LVM volume group
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lvg:
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vg: "{{ ollama_data_vg }}"
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pvs: "{{ ollama_data_disk }}"
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when: ollama_setup_data_disk | bool
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- name: Create LVM logical volume using 100% of VG
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lvol:
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vg: "{{ ollama_data_vg }}"
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lv: "{{ ollama_data_lv }}"
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size: 100%FREE
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shrink: false
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when: ollama_setup_data_disk | bool
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- name: Format logical volume as ext4
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filesystem:
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fstype: ext4
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dev: "/dev/{{ ollama_data_vg }}/{{ ollama_data_lv }}"
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opts: "-L ollama-data"
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when: ollama_setup_data_disk | bool
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- name: Create Ollama model directory mount point
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file:
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path: "{{ ollama_data_dir }}"
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state: directory
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mode: '0755'
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- name: Mount Ollama data volume and add fstab entry
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mount:
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path: "{{ ollama_data_dir }}"
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src: "/dev/{{ ollama_data_vg }}/{{ ollama_data_lv }}"
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fstype: ext4
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opts: defaults,noatime
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state: mounted
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when: ollama_setup_data_disk | bool
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# noatime: eliminates inode access time writes on every model file read.
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# Meaningful win for large sequential reads like model loading.
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# ------------------------------------------------------------------------------
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# Ollama installation
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# Uses the official install script which creates the ollama user and
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# systemd service unit. We override the service with our own config.
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# ------------------------------------------------------------------------------
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- name: Download Ollama install script
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get_url:
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url: https://ollama.ai/install.sh
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dest: /tmp/ollama_install.sh
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mode: '0755'
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- name: Run Ollama install script
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command: /tmp/ollama_install.sh
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environment: "{{ {} if ollama_version == 'latest' else {'OLLAMA_VERSION': ollama_version} }}"
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args:
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creates: /usr/local/bin/ollama
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- name: Add ollama user to render and video groups (post-install)
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user:
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name: ollama
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groups:
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- render
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- video
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append: yes
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- name: Set ownership of Ollama data directory to ollama user
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file:
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path: "{{ ollama_data_dir }}"
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owner: ollama
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group: ollama
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recurse: yes
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# ------------------------------------------------------------------------------
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# Systemd service override
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# Injects HSA_OVERRIDE_GFX_VERSION for RX 5000-series compatibility and
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# sets OLLAMA_MODELS to the data disk mount point.
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# ------------------------------------------------------------------------------
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- name: Create systemd override directory for ollama service
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file:
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path: /etc/systemd/system/ollama.service.d
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state: directory
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mode: '0755'
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- name: Deploy ollama systemd service override
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template:
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src: ollama-override.conf.j2
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dest: /etc/systemd/system/ollama.service.d/override.conf
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mode: '0644'
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notify:
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- reload systemd
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- restart ollama
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- name: Flush handlers to apply service config before model pull
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meta: flush_handlers
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- name: Enable and start Ollama service
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systemd:
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name: ollama
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state: started
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enabled: yes
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daemon_reload: yes
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- name: Wait for Ollama API to become available
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uri:
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url: "http://localhost:{{ ollama_port }}/api/tags"
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status_code: 200
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register: ollama_health
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retries: 12
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delay: 5
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until: ollama_health.status == 200
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# ------------------------------------------------------------------------------
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# Initial model pull
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# ------------------------------------------------------------------------------
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- name: Pull initial model
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command: ollama pull {{ ollama_default_model }}
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environment:
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OLLAMA_HOST: "http://localhost:{{ ollama_port }}"
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register: model_pull
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changed_when: "'pulled' in model_pull.stdout or model_pull.rc == 0"
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timeout: 600
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# Qwen3 8B Q4_K_M is ~5GB — allow 10 minutes on first pull.
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