[{"data":1,"prerenderedAt":4},["ShallowReactive",2],{"readme:ontobricks":3},"\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Fdatabrickslabs\u002Fontobricks\u002FHEAD\u002Fsrc\u002Ffront\u002Fstatic\u002Fglobal\u002Fimg\u002Fontobricks-icon.svg\" alt=\"OntoBricks Logo\" width=\"120\" height=\"120\" \u002F>\n\u003C\u002Fp>\u003Ch1>OntoBricks 0.6.2\u003C\u002Fh1>\u003Cp align=\"center\">\n  \u003Cstrong>Knowledge Graph Builder for Databricks\u003C\u002Fstrong>\n\u003C\u002Fp>\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fpython-3.10+-blue.svg\" alt=\"Python\" \u002F>\n  \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Ffastapi-0.109+-green.svg\" alt=\"FastAPI\" \u002F>\n\u003C\u002Fp>\u003Ch2>Project Description\u003C\u002Fh2>\n\u003Cp>OntoBricks is a web application that transforms Databricks tables into a materialized graph viewer. It lets you design ontologies (OWL), map them to Unity Catalog tables via R2RML, materialize triples into a Delta-backed triple store and a Lakebase Postgres graph engine, reason over the graph (OWL 2 RL, SWRL, SHACL), and query it through an auto-generated GraphQL API. The entire pipeline — from metadata import to a queryable graph viewer — can run in four clicks using LLM-powered automation.\u003C\u002Fp>\n\u003Ch2>Project Support\u003C\u002Fh2>\n\u003Cp>Please note that all projects in the \u002Fdatabrickslabs github account are provided for your exploration only, and are not formally supported by Databricks with Service Level Agreements (SLAs). They are provided AS-IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects.\u003C\u002Fp>\n\u003Cp>Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.\u003C\u002Fp>\n\u003Ch2>Building the Project\u003C\u002Fh2>\n\u003Cp>OntoBricks uses \u003Ca href=\"https:\u002F\u002Fdocs.astral.sh\u002Fuv\u002F\" rel=\"nofollow ugc noopener\">uv\u003C\u002Fa> for dependency management. All dependencies are declared in \u003Ccode>pyproject.toml\u003C\u002Fcode>.\u003C\u002Fp>\n\u003Cpre>\u003Ccode class=\"language-bash\"># Clone the repository\ngit clone <repository-url>\ncd OntoBricks\n\n# Install dependencies (uv resolves them from pyproject.toml)\nuv sync\n\n# Or use the setup script\nscripts\u002Fsetup.sh\n\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Ch3>Prerequisites\u003C\u002Fh3>\n\u003Cul>\n\u003Cli>Python 3.10 or higher\u003C\u002Fli>\n\u003Cli>Databricks workspace access (Databricks Apps must be enabled). Local\ndevelopment uses a Personal Access Token; production uses the App's\nservice principal.\u003C\u002Fli>\n\u003Cli>A SQL Warehouse (you'll need its ID for local dev).\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Databricks Lakebase Autoscaling\u003C\u002Fstrong> project + branch + Postgres\ndatabase — \u003Cstrong>required since v0.4.0\u003C\u002Fstrong> for the domain registry\n(domains, versions, permissions, schedules, global config) and the\nGraph DB triple store. Provisioned Lakebase instances are \u003Cstrong>not\u003C\u002Fstrong>\nsupported. The Postgres driver (\u003Ccode>psycopg[binary]\u003C\u002Fcode> + \u003Ccode>psycopg-pool\u003C\u002Fcode>)\nis declared as an optional dependency so volume-only forks can opt\nout — install with \u003Ccode>uv sync --extra lakebase\u003C\u002Fcode> for any normal\ndeployment.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Unity Catalog Volume\u003C\u002Fstrong> in the catalog\u002Fschema that hosts the\ntriplestore VIEWs (\u003Ccode>triplestore_<domain>_v<n>\u003C\u002Fcode>). The volume is\nreserved for binary artefacts (\u003Ccode>documents\u002F\u003C\u002Fcode> uploads — domain-scoped\nattachments imported by the ontology designer).\u003C\u002Fli>\n\u003Cli>\u003Ccode>psql\u003C\u002Fcode> (libpq client) on \u003Ccode>PATH\u003C\u002Fcode> for the Lakebase permission\nbootstrap scripts (\u003Ccode>brew install libpq && brew link --force libpq\u003C\u002Fcode>\non macOS).\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2>Deploying \u002F Installing the Project\u003C\u002Fh2>\n\u003Ch3>Local Development\u003C\u002Fh3>\n\u003Cpre>\u003Ccode class=\"language-bash\"># Configure credentials\ncp .env.example .env\n# Edit .env with your Databricks host, token, and warehouse ID\n\n# Start the application\nscripts\u002Fstart.sh\n# Open http:\u002F\u002Flocalhost:8000\n\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Ch3>Deploy to Databricks Apps\u003C\u002Fh3>\n\u003Cpre>\u003Ccode class=\"language-bash\"># Install and authenticate the Databricks CLI (>= 0.250.0)\nbrew install databricks            # or curl -fsSL https:\u002F\u002Fdatabricks.com\u002Finstall.sh | sh\ndatabricks auth login --host https:\u002F\u002F<workspace>\n\n# Edit scripts\u002Fdeploy.config.sh (CLI profile, warehouse, registry catalog\u002Fschema,\n# Lakebase project\u002Fbranch\u002Fdatabase — see the file header) and then:\nmake deploy\n# Or directly: scripts\u002Fdeploy.sh\n\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Ccode>scripts\u002Fdeploy.sh\u003C\u002Fcode> generates \u003Ccode>app.yaml\u003C\u002Fcode> from \u003Ccode>app.yaml.template\u003C\u002Fcode> +\n\u003Ccode>scripts\u002Fdeploy.config.sh\u003C\u002Fcode>, validates and deploys the DAB bundle on\ntarget \u003Ccode>dev-lakebase\u003C\u002Fcode>, runs \u003Ccode>scripts\u002Fbootstrap-app-permissions.sh\u003C\u002Fcode>\n(app SP \u003Ccode>CAN_MANAGE\u003C\u002Fcode> on itself), then runs\n\u003Ccode>scripts\u002Fbootstrap-lakebase-perms.sh\u003C\u002Fcode> on the regis\u003C\u002Fp>\n",1785888996374]