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Work on dataset metadata with MLCommons Croissant validation and creation.

🔥🔥FreeQuick setup

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

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 with Docker

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

Running the Server (Locally)

Prerequisites

Python 3.12+
uv (Python package manager)

Development steps

Clone the repository:

git clone git@github.com:jettyio/mlcbakery.git
cd mlcbakery

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

Authentication

The Bakery is setup to authenticate requests with two methods: JWT Tokens and a "Master Admin Token". Both are configured in the ENV variables (.env file). Both JWT tokens and the Master Admin Token should be provided as "Bearer" Authorization header values.

ADMIN_AUTH_TOKEN: A fixed value that is the token a user would need to provide to have admin permissions (unrestricted access to all resources).
JWT_VERIFICATION_STRATEGY: The URL of a trusted JWT token issuer, such as Clerk. We have a development instance of Clerk running that you can use. You can sign up for an account via flows.jetty.io (alpha), or contact dev@jetty.io for access to Jetty's Cloud.

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