dockerfile

.dockerignore

@@ -1,20 +1,48 @@
-*.egg-info
-__pycache__
-.pytest_cache
-.ruff_cache
-.env
-.env.*
-.DS_Store
-.idea
-.venv
-.vscode
-*.pyc
+# Python bytecode and artifacts
+__pycache__/
+*.py[cod]
 *.pyo
 *.pyd
+*.egg-info/
+dist/
+build/
+
+# Virtual environments
+.venv/
+venv/
+
+# Caches and test output
+.cache/
+.pytest_cache/
+.ruff_cache/
+coverage/
+
+# Logs and temp files
+*.log
+*.gz
+*.tgz
+.tmp
+.cache
+
+# Environment variables
+.env
+.env.*
+
+# VCS, editor, OS
 .git
 .gitignore
+.gitattributes
+.github/
+.idea/
+.vscode/
+.DS_Store
+
+# Project docs and misc
 README.md
 LICENSE
-.github 
-tests/
 
+# Project tests
+test/
+tests/
+eval/
+evals/

Dockerfile

@@ -1,77 +1,43 @@
-# This sample Dockerfile creates a production-ready container for a LiveKit voice AI agent
 # syntax=docker/dockerfile:1
 
-# Use the official UV Python base image with Python 3.11 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
-FROM ghcr.io/astral-sh/uv:python3.11-bookworm-slim
+ARG PYTHON_VERSION=3.11
+# Fast Python builds using uv on Debian bookworm-slim
+FROM 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.
+ARG UID=10001
+
+# Ensures that logs are captured in realtime
 ENV PYTHONUNBUFFERED=1
 
-# Define the program entrypoint file where your agent is started
-ARG PROGRAM_MAIN="src/agent.py"
-ENV PROGRAM_MAIN=${PROGRAM_MAIN}
-
-# Create a non-privileged user that the app will run under.
-# See https://docs.docker.com/develop/develop-images/dockerfile_best-practices/#user
-ARG UID=10001
+# Create unprivileged user
 RUN adduser \
     --disabled-password \
     --gecos "" \
-    --home "/home/appuser" \
+    --home "/app" \
     --shell "/sbin/nologin" \
     --uid "${UID}" \
     appuser
 
-# Install build dependencies required for Python packages with native extensions
-# gcc: C compiler needed for building Python packages with C extensions
-# 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 \
+# System build deps for common Python wheels
+RUN apt-get update && apt-get install -y \
     gcc \
     python3-dev \
-    && rm -rf /var/lib/apt/lists/*
+  && rm -rf /var/lib/apt/lists/*
 
-# Set the working directory to the user's home directory
-# This is where our application code will live
-WORKDIR /home/appuser
+WORKDIR /app
 
-# Copy all application 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 /home/appuser
-
-# Switch to the non-privileged user for all subsequent operations
-# This improves security by not running as root
-USER appuser
-
-# Create a cache directory for the user
-# This is used by UV and Python for caching packages and bytecode
-RUN mkdir -p /home/appuser/.cache
-
-# 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
+# Dependency install first for better caching
+COPY pyproject.toml uv.lock ./
+RUN mkdir -p src
 RUN uv sync --locked
 
-# 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 "$PROGRAM_MAIN" download-files
+# Copy application code
+COPY . .
+RUN chown -R appuser:appuser /app
+USER appuser
 
-# Expose the healthcheck port
-# This allows Docker and orchestration systems to check if the container is healthy
-EXPOSE 8081
+# Pre-download models/assets at build time
+RUN uv run src/agent.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", "$PROGRAM_MAIN", "start"]
+# Start the agent
+CMD ["uv", "run", "src/agent.py", "start"]