migrate to uv + pyproject.toml

- 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

core/gpu/run.sh

@@ -2,7 +2,7 @@
 # Run the inference server
 #
 # Usage:
-#   ./run.sh                  # Local (pip install -r requirements.txt first)
+#   ./run.sh                  # Local: uv sync + run server.py (auto-installs/activates .venv)
 #   ./run.sh docker           # Docker (CPU)
 #   ./run.sh docker-gpu       # Docker with GPU
 #   ./run.sh stop             # Stop Docker container
@@ -26,7 +26,12 @@ fi
 
 case "${1:-local}" in
     local)
-        python server.py
+        if ! command -v uv >/dev/null 2>&1; then
+            echo "uv not found. Install: curl -LsSf https://astral.sh/uv/install.sh | sh"
+            exit 1
+        fi
+        uv sync
+        uv run python server.py
         ;;
     docker)
         docker build -t mpr-inference .