64 lines
1.9 KiB
YAML
64 lines
1.9 KiB
YAML
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services:
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ollama:
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image: ollama/ollama:latest
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ports:
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- "11434:11434"
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volumes:
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- ollama_models:/root/.ollama
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healthcheck:
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test: ["CMD", "ollama", "list"]
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interval: 5s
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timeout: 5s
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retries: 60
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# Uncomment the block below if you have an NVIDIA GPU and the
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# NVIDIA container toolkit installed. Vision models are dramatically
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# faster with a GPU, but everything in this example also runs on CPU.
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# deploy:
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# resources:
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# reservations:
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# devices:
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# - driver: nvidia
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# count: all
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# capabilities: [gpu]
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model-puller:
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image: ollama/ollama:latest
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depends_on:
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ollama:
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condition: service_healthy
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environment:
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- OLLAMA_HOST=http://ollama:11434
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entrypoint: ["/bin/bash", "-c"]
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# `ollama pull` shows a redrawing progress bar with carriage returns and
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# ANSI cursor-hide codes. Without a TTY (which is the case here) that
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# comes out of `docker logs` as invisible output plus a hijacked cursor.
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# The pipeline below converts \r into \n so each progress update becomes
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# its own log line, and strips ANSI escape sequences so the cursor is
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# left alone.
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command:
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- |
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set -eo pipefail
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echo "Pulling ${OLLAMA_MODEL:-qwen3.5:9b} (this may take a while on first run)..."
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ollama pull "${OLLAMA_MODEL:-qwen3.5:9b}" 2>&1 \
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| stdbuf -oL tr '\r' '\n' \
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| stdbuf -oL sed -E 's/\x1b\[[?0-9;]*[a-zA-Z]//g'
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echo "Model ${OLLAMA_MODEL:-qwen3.5:9b} is ready. You can now run the demo scripts on the host."
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restart: "no"
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web:
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build: ./web
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ports:
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- "8082:8080"
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environment:
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- OLLAMA_URL=http://ollama:11434
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- OLLAMA_MODEL=${OLLAMA_MODEL:-qwen3.5:9b}
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volumes:
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- ./scripts:/app/scripts:ro
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- ./sample_images:/app/sample_images:ro
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depends_on:
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ollama:
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condition: service_healthy
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volumes:
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ollama_models:
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