lk agent create

failed to Lchown "/Dockerfile" for UID 845483959, GID 1437349805: 
lchown /Dockerfile: invalid argument

[+] Building 0.5s (2/2) FINISHED
 => [internal] load remote build context 0.1s
 => ERROR copy /context / 0.0s
------
 > copy /context /:
------
build failed for <http://iad.ocir.io/axyci3pr8vxm/production-cloud-agents:p-3r36ywewesj-ca-gbxb4sonkna4-v20250918075554|iad.ocir.io/axyci3pr8vxm/production-cloud-agents:p-3r36ywewesj-ca-gbxb4sonkna4-v20250918075554>: failed to solve: failed to read dockerfile: failed to Lchown "/Dockerfile" for UID 845483959, GID 1437349805: lchown /Dockerfile: invalid argument

.
├── Dockerfile
├── README.md
├── livekit
│   └── hold_for_me.py
├── livekit.toml
├── pyproject.toml
├── run_livekit.py
└── uv.lock

# This is an example Dockerfile that builds a minimal container for running LK Agents
# For more information on the build process, see <https://docs.livekit.io/agents/ops/deployment/builds/>
# syntax=docker/dockerfile:1

# Use the official UV Python base image with Python 3.13 on Debian Bookworm
# UV is a fast Python package manager that provides better performance than pip
# We use the slim variant to keep the image size smaller while still having essential tools
ARG PYTHON_VERSION=3.13
FROM <http://ghcr.io/astral-sh/uv:python${PYTHON_VERSION}-bookworm-slim|ghcr.io/astral-sh/uv:python${PYTHON_VERSION}-bookworm-slim> AS base

# Keeps Python from buffering stdout and stderr to avoid situations where
# the application crashes without emitting any logs due to buffering.
ENV PYTHONUNBUFFERED=1

# Create a non-privileged user that the app will run under.
# See <https://docs.docker.com/develop/develop-images/dockerfile_best-practices/#user>
ARG UID=10001
RUN adduser \
    --disabled-password \
    --gecos "" \
    --home "/app" \
    --shell "/sbin/nologin" \
    --uid "${UID}" \
    appuser

# Install build dependencies required for Python packages with native extensions
# gcc: C compiler needed for building Python packages with C extensions
# g++: C++ compiler needed for building Python packages with C++ extensions
# python3-dev: Python development headers needed for compilation
# We clean up the apt cache after installation to keep the image size down
RUN apt-get update && apt-get install -y \
    gcc \
    g++ \
    python3-dev \
  && rm -rf /var/lib/apt/lists/*

# Create a new directory for our application code
# And set it as the working directory
WORKDIR /app

# Copy just the dependency files first, for more efficient layer caching
COPY pyproject.toml uv.lock ./
RUN mkdir -p src

# Install Python dependencies using UV's lock file
# --locked ensures we use exact versions from uv.lock for reproducible builds
# This creates a virtual environment and installs all dependencies
# Ensure your uv.lock file is checked in for consistency across environments
RUN uv sync --locked

# Copy all remaining pplication files into the container
# This includes source code, configuration files, and dependency specifications
# (Excludes files specified in .dockerignore)
COPY . .

# Change ownership of all app files to the non-privileged user
# This ensures the application can read/write files as needed
RUN chown -R appuser:appuser /app

# Switch to the non-privileged user for all subsequent operations
# This improves security by not running as root
USER appuser

# Pre-download any ML models or files the agent needs
# This ensures the container is ready to run immediately without downloading
# dependencies at runtime, which improves startup time and reliability
RUN uv run "run_livekit.py" download-files

# Run the application using UV
# UV will activate the virtual environment and run the agent.
# The "start" command tells the worker to connect to LiveKit and begin waiting for jobs.
CMD ["uv", "run", "run_livekit.py", "start"]