MLC Bakery

A Python-based service for managing ML model provenance and lineage, built with FastAPI and SQLAlchemy. Support for Croissant metadata validation.

Features

• Dataset management with collection support
• Entity tracking
• Activity logging
• Provenance relationships tracking
• RESTful API endpoints

Running with Docker

1. Set up Environment Variables: Create a .env file in the project root by copying the example:

   cp env.example .env

2. Start docker containers: The bakery relies on a postgres database and Typesense for search. The MCP server makes REST calls to the API server, which then calls the persistence layer.

   docker compose up -d
   

3. Run Database Migrations: Apply the latest database schema using Alembic. uv run executes commands within the project's managed environment.

   docker compose exec db psql -U postgres -c "create DATABASE mlcbakery;"
   docker compose exec api alembic upgrade head

Access the bakery

By default, the API will be available on localhost.

• Swagger UI: http://bakery.localhost/docs
• ReDoc: http://bakery.localhost/redoc
• Streamable MCP HTTP: http://mcp.localhost/mcp (you may need to add this to your /etc/hosts for local development)

Running the Server (Locally)

Prerequisites

• Python 3.12+
• uv (Python package manager)

Development steps

1. Clone the repository:

   git clone [email protected]:jettyio/mlcbakery.git
   cd mlcbakery

2. Install Dependencies: uv uses pyproject.toml to manage dependencies. It will automatically create a virtual environment if one doesn't exist.

   curl -LsSf https://astral.sh/uv/install.sh | sh

   pip install poetry uvicorn
   uv run poetry install --no-interaction --no-ansi --no-root --with mcp
   

Start the FastAPI application using uvicorn:

# Make sure your .env file is present for the DATABASE_URL
uv run uvicorn mlcbakery.main:app --reload --host 0.0.0.0 --port 8000

Running Tests

The tests are configured to run against a PostgreSQL database defined by the DATABASE_URL environment variable. You can use the same database as your development environment or configure a separate test database in your .env file if preferred (adjust connection string as needed).

# Ensure DATABASE_URL is set in your environment or .env file
uv run pytest