Databricks recipes (`fh add`)

Scaffold Lakebase, SQL, Vector Search, Lakeflow, Jobs, cost controls, and Apps wiring with managed Fabric Harness recipes.

Use managed Databricks recipes to wire @fabric-harness/databricks into an existing project without copying examples by hand. Recipes write versioned files under .fabricharness/databricks/ (or a job for the analyst composite), update dependencies, and leave secrets in environment variables.

Greenfield projects can still start with:

fh init --template databricks

Recipes are for adding one product surface (or a small workload composite) afterward.

Generated Databricks recipes default to DATABRICKS_MODEL=system.ai.gpt-oss-20b and DATABRICKS_INFERENCE_MODE=auto. Set DATABRICKS_HOST to the workspace origin, for example https://<workspace-host>; do not include /ai-gateway/mlflow/v1 in the host value.

List and install

fh add
fh add --json

fh add databricks core
fh add databricks sql
fh add lakebase          # alias
fh add vector-search
fh add lakeflow
fh add jobs
fh add system-tables-cost
fh add apps
fh add lakehouse         # analyst composite (sql + tables)

fh add databricks lakebase --dry-run
fh update databricks sql

Catalog

Recipe	Alias examples	Managed files	Dependencies	Maps to
`core`	`databricks-core`	`databricks/identity.ts`, `policies/databricks.ts`	`@fabric-harness/databricks`	Workspace identity + UC egress policy
`sql`	`databricks-sql`	`databricks/sql.ts`	`@fabric-harness/databricks`	SQL Warehouse + table discovery
`lakebase`	`databricks-lakebase`	`databricks/lakebase.ts`	`@fabric-harness/databricks`, `pg`	Lakebase persistence
`vector-search`	`databricks-rag`	`databricks/vector-search.ts`	`@fabric-harness/databricks`	Agentic `search` tool bundle
`rag-chain`	`databricks-rag-chain`	`databricks/rag-chain.ts`, `jobs/rag-answer.ts`	`@fabric-harness/databricks`	Cookbook online chain + MLflow 3 eval export (RAG docs)
`lakeflow`	`databricks-dataeng`	`databricks/lakeflow.ts`	`@fabric-harness/databricks`	with-databricks-dataeng
`jobs`	`databricks-compute`	`databricks/jobs.ts`	`@fabric-harness/databricks`	with-databricks-compute
`system-tables-cost`	`databricks-cost`	`databricks/cost.ts`	`@fabric-harness/databricks`	with-databricks-cost-attribution
`apps`	`databricks-app`	`databricks/apps.ts`	`@fabric-harness/databricks`, `@fabric-harness/node`	Apps runtime preset + deploy targets
`analyst`	`lakehouse`	`jobs/databricks-analyst.ts`	`@fabric-harness/databricks`	init template / simple analyst job

“Lakehouse” is an alias for the analyst composite (governed SQL + UC tools), not a separate Databricks SDK product.

Typical flows

SQL analyst on Apps

fh init --template minimal
fh add databricks core
fh add databricks sql
fh add databricks analyst
# set DATABRICKS_* in .env
fh run databricks-analyst --question "What tables are in main?" --mock
fh build --target databricks-app

RAG support agent

# Deterministic cookbook chain (retrieve → augment → generate):
fh add databricks rag-chain
fh run rag-answer --question "How do I reset my password?"

# Or agentic multi-tool search (SQL + search + …):
fh add vector-search
# Import createVectorSearchBundle() and pass modelProvider + tools into init()

See RAG on Databricks for citation validation, MLflow 3 export, and the quality workflow.

Lakebase durable state

fh add lakebase
# In .fabricharness/config.ts:
#   import { createLakebasePersistence } from './databricks/lakebase.js';
#   persistence: createLakebasePersistence(),

Data engineering

fh add lakeflow
fh add jobs
# Use createLakeflowBundle() / createDatabricksJobsTools() in agent init

Conventions

Package owns behavior — recipes only wire @fabric-harness/databricks into your workspace.
Managed markers — files start with // fabric-harness-recipe: databricks/<name>@1 for safe fh update.
No secrets in source — only env names are written to .env.example.
Runnable verification — generated tests import from ../../.fabricharness/ and are compiled by the recipe contract suite.
Merge config yourself — recipes do not silently rewrite config.ts; they print paths and env requirements.
Deploy — Apps/Serving artifacts still come from fh build --target databricks-app|databricks-serving.