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Yelp Fusion AI MCP Server

by Yelp
Apache 2.0
19
Dockerfile1.76 kB
# Dockerfile # Use an official Python runtime as a parent image FROM python:3.12-slim-bookworm # Install uv using the official distroless image. # Pinning to a specific version (e.g., :0.7.20) is recommended for reproducibility. COPY --from=ghcr.io/astral-sh/uv:0.7.20 /uv /uvx /bin/ # Set the working directory in the container WORKDIR /app # Copy project definition (pyproject.toml) and lock file (if available) # Assumes pyproject.toml exists in your project root (shellserver). # If you generate and use a lock file (uv.lock), uncomment the second COPY line for reproducible builds. COPY pyproject.toml ./ COPY uv.lock ./ # Install dependencies using uv sync. # Leverages Docker layer caching via --mount=type=cache. # --frozen ensures installs match the lock file (if provided and copied). Remove if no lock file. # --no-install-project skips installing the local project code in this layer, optimizing caching. # NOTE: This command relies on 'pyproject.toml' correctly listing dependencies, including 'mcp'. # Ensure the 'mcp' package is resolvable based on your project setup (see pyproject.toml notes). RUN --mount=type=cache,target=/root/.cache/uv \ uv sync --frozen --no-install-project # Copy the application code into the container COPY src/yelp_agent ./src/yelp_agent # If you decided to vendor the 'mcp' package (copying it into shellserver), uncomment the next line: # COPY ./mcp ./mcp # Install the project itself using uv sync. # This step makes your 'shellserver' project available in the environment managed by uv. # Use --frozen if you have a lock file copied. RUN --mount=type=cache,target=/root/.cache/uv \ uv sync --frozen # Define the command to run the application using 'uv run' CMD ["uv", "run", "mcp-yelp-agent"]

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