Question 1

What is MLC Bakery?

Accepted Answer

MLC Bakery is a Python-based service for managing ML model provenance and lineage, built with FastAPI and SQLAlchemy. It helps track datasets, entities, activities, agents, and relationships in your ML workflows.

Question 2

What are the key features of MLC Bakery?

Accepted Answer

Key features include dataset management with collection support, entity tracking, activity logging, agent management, provenance relationships tracking, and RESTful API endpoints.

Question 3

What are the prerequisites for setting up MLC Bakery?

Accepted Answer

You need Python 3.12+, uv (Python package manager), and PostgreSQL (running locally or via Docker).

Question 4

How do I install the dependencies for MLC Bakery?

Accepted Answer

Use `uv pip install -e .[dev,webclient]` to install main, dev, and webclient dependencies in editable mode.

Question 5

How do I set up the environment variables?

Accepted Answer

Create a `.env` file in the project root by copying the example and edit it with your local PostgreSQL connection details. The key variable is `DATABASE_URL`.

Question 6

How do I run database migrations?

Accepted Answer

Use `uv run alembic upgrade heads` to apply the latest database schema.

Question 7

How do I start the MLC Bakery server locally?

Accepted Answer

Use `uv run uvicorn mlcbakery.main:app --reload --host 0.0.0.0 --port 8000` to start the FastAPI application.

Question 8

Where can I access the API documentation?

Accepted Answer

The Swagger UI is available at `http://localhost:8000/docs`, and the ReDoc documentation is at `http://localhost:8000/redoc`.

Question 9

How do I run tests?

Accepted Answer

Use `uv run pytest` to run all tests, or `uv run pytest tests/test_activities.py -v` to run specific tests.

Question 10

What is the project structure of MLC Bakery?

Accepted Answer

The project structure includes directories for Alembic migrations, GitHub Actions workflows, the main application package (with models, schemas, API routes, and the main entry point), tests, example environment variables, the Alembic configuration file, and the pyproject.toml file.

Question 11

How do I reset the database for local development?

Accepted Answer

Use `dropdb mlcbakery_dev` and `createdb mlcbakery_dev` (using `psql`) to drop and recreate the database, then run `uv run alembic upgrade heads` to re-run migrations. Warning: This deletes all data in the development database.

Question 12

How can I contribute to MLC Bakery?

Accepted Answer

Create a new branch for your feature, make your changes, run tests, commit your changes, push to the branch, and submit a pull request.

Question 13

What license is MLC Bakery released under?

Accepted Answer

MLC Bakery is licensed under the MIT License.

Question 14

How can I deploy MLC Bakery using Docker Compose?

Accepted Answer

Configure the `ADMIN_AUTH_TOKEN` in a `.env` file or directly in the `docker-compose.yml`, then run `docker-compose up --build -d` to build and run the services. Apply database migrations with `docker-compose exec api alembic upgrade head`.

Question 15

What is the `ADMIN_AUTH_TOKEN` and why is it needed?

Accepted Answer

The `ADMIN_AUTH_TOKEN` is required for any mutable API operations (POST, PUT, PATCH, DELETE). Include it in requests as a Bearer token in the Authorization header.

Question 16

What is the relationship between MLC Bakery and the UBOS platform?

Accepted Answer

MLC Bakery integrates with the UBOS platform, a full-stack AI Agent Development Platform, to ensure AI Agents are built on a foundation of trust, transparency, and accountability.

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