buenosairesam
f66d3a273f
- root pyproject.toml replaces requirements.txt and requirements-worker.txt (worker = root + ffmpeg-python which root already had); test deps moved to [dependency-groups] dev - core/gpu/pyproject.toml replaces core/gpu/requirements.txt; uses [tool.uv.sources] to pin torch/torchvision and paddlepaddle-gpu to their CUDA index URLs, replacing the manual reinstall dance from old comments - Dockerfiles use uv sync --frozen against uv.lock for reproducible builds; PATH includes /app/.venv/bin so k8s manifests' bare uvicorn/celery commands resolve without wrapping in uv run - core/gpu/run.sh local mode now does uv sync + uv run python server.py; errors out cleanly if uv is missing
60 lines
1.5 KiB
Bash
Executable File
60 lines
1.5 KiB
Bash
Executable File
#!/bin/bash
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# Run the inference server
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#
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# Usage:
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# ./run.sh # Local: uv sync + run server.py (auto-installs/activates .venv)
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# ./run.sh docker # Docker (CPU)
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# ./run.sh docker-gpu # Docker with GPU
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# ./run.sh stop # Stop Docker container
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set -e
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cd "$(dirname "${BASH_SOURCE[0]}")"
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# Load env (create from template if missing)
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if [ ! -f .env ]; then
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if [ -f .env.template ]; then
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cp .env.template .env
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echo "Created .env from template — edit as needed"
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fi
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fi
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if [ -f .env ]; then
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set -a
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source .env
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set +a
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fi
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case "${1:-local}" in
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local)
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if ! command -v uv >/dev/null 2>&1; then
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echo "uv not found. Install: curl -LsSf https://astral.sh/uv/install.sh | sh"
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exit 1
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fi
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uv sync
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uv run python server.py
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;;
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docker)
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docker build -t mpr-inference .
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ENV_FLAG=""; [ -f .env ] && ENV_FLAG="--env-file .env"
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docker run --rm -p "${PORT:-8000}:8000" \
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$ENV_FLAG \
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--name mpr-inference \
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mpr-inference
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;;
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docker-gpu)
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docker build -t mpr-inference .
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ENV_FLAG=""; [ -f .env ] && ENV_FLAG="--env-file .env"
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docker run --rm --gpus all -p "${PORT:-8000}:8000" \
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$ENV_FLAG \
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--name mpr-inference \
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mpr-inference
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;;
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stop)
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docker stop mpr-inference 2>/dev/null || true
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;;
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*)
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echo "Usage: ./run.sh [local|docker|docker-gpu|stop]"
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exit 1
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;;
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esac
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