Community Edition — Prerequisites

Choose the path that best fits your needs:

Databricks App — Recommended for teams and organizations that already have an established Databricks workspace and wish to leverage existing Unity Catalog governance and compute resources.
Local Run — Recommended for individual researchers, data scientists, and curious minds seeking a lightweight, zero-cloud setup directly on their local machine.

Prerequisites Checklist

Databricks App Local Run

Deploy and run Bianor natively inside your Databricks workspace.

Component		Description
Databricks Workspace	Free account is sufficient	Access to a workspace with Unity Catalog, SQL Warehouses, and Databricks Apps enabled. Start at databricks.com.
SQL Warehouse	An active SQL Warehouse	Needed to serve analytical queries. Will be attached as an App Resource during deployment.
Target Catalog & Schema	Designated Unity Catalog schema	Catalog and schema (e.g. `workspace.bianor`) where metadata tables and models will reside.
App Permissions	Schema & Warehouse access	The app's Service Principal will require schema read (`SELECT`), model `EXECUTE`, and warehouse `CAN USE` permissions once created.
Application Repository	`ophelia-rnd/bianor`	Source repository to clone into your Databricks workspace Git folder.
Toolkit	`pypi/bianor-databricks-kit`	Python library to initialize metadata tables and link models.
Modeling Library	`ophelia-rnd/minisom-representation`	Python library to train `SomRepresentation` models on your data.

Run Bianor completely standalone on your local workstation without requiring a Databricks account or connection.

Component		Description
Environment	Python 3.10+	Python environment (Jupyter optional for exploratory workflows).
Application Repository	`ophelia-rnd/bianor`	Source repository to clone onto your local machine.
Modeling Library	`ophelia-rnd/minisom-representation`	Python library to train `SomRepresentation` models on your data.

Once you are ready, proceed to Launch Bianor to configure and launch your app.