SuperAPI AI Directory

databricks-agent-bricks

Agents & models

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Updated 10-16 05:05

About this skill

Agent Bricks

Agent Bricks are pre-built AI tiles in Databricks that provide conversational interfaces. This skill covers Knowledge Assistants and Supervisor Agents.

Brick Purpose This Skill
Knowledge Assistant (KA) Document Q&A using RAG on PDFs/text in Volumes ✓
Supervisor Agent Orchestrates multiple agents (KA, endpoints, UC functions, MCP) ✓

Knowledge Assistant

# Find volumes
databricks volumes list CATALOG SCHEMA
databricks experimental aitools tools query --warehouse WH "LIST '/Volumes/catalog/schema/volume/'"
Create KA

databricks knowledge-assistants create-knowledge-assistant "Name" "Description"

Add knowledge source. With --json, pass ONLY the PARENT as a positional arg and put display_name / description / source_type / the source body (files|index|file_table) inside the JSON. Mixing positional DISPLAY_NAME/DESCRIPTION/SOURCE_TYPE with --json errors.

databricks knowledge-assistants create-knowledge-source
"knowledge-assistants/{ka_id}"
--json '{ "display_name": "Docs", "description": "Documentation files", "source_type": "files", "files": {"path": "/Volumes/catalog/schema/volume/"} }'

Sync and check status

databricks knowledge-assistants sync-knowledge-sources "knowledge-assistants/{ka_id}" databricks knowledge-assistants get-knowledge-assistant "knowledge-assistants/{ka_id}"

List/manage

databricks knowledge-assistants list-knowledge-assistants databricks knowledge-assistants delete-knowledge-assistant "knowledge-assistants/{ka_id}" # destructive & irreversible — confirm the id first


**Source types:** `files` (Volume path) or `index` (Vector Search: `index.index_name`, `index.text_col`, `index.doc_uri_col`)

**Status:** `CREATING` (2-5 min) → `ONLINE` → `OFFLINE`

---

## Supervisor Agent

Native CLI: `databricks supervisor-agents` (Beta, requires CLI ≥ v1.0.0). Resource paths look like `supervisor-agents/{id}` — every command takes either that full path or a `PARENT` of that shape. `list-supervisor-agents` and `list-examples`/`list-tools` return bare JSON arrays.

```bash
# Create the supervisor agent (display name positional, description/instructions as flags)
databricks supervisor-agents create-supervisor-agent "My Supervisor" \
    --description "Routes queries to specialized agents" \
    --instructions "Route data questions to analyst, document questions to docs_agent."
# → returns {name: "supervisor-agents/<uuid>", endpoint_name: "mas-<short>-endpoint", ...}

# List / get / find by name
databricks supervisor-agents list-supervisor-agents
databricks supervisor-agents get-supervisor-agent supervisor-agents/<id>
databricks supervisor-agents list-supervisor-agents | jq '.[] | select(.display_name == "My Supervisor")'

# Update — UPDATE_MASK + new DISPLAY_NAME are positional; description/instructions optional flags
databricks supervisor-agents update-supervisor-agent supervisor-agents/<id> \
    "display_name,description,instructions" "My Supervisor (v2)" \
    --description "..." --instructions "..."

# Delete (destructive & irreversible — confirm the id first)
databricks supervisor-agents delete-supervisor-agent supervisor-agents/<id>

Tools (the agents the supervisor routes to)

Each tool wires the supervisor to a downstream resource. tool_type lives in --json (the CLI rejects it as a positional when --json is used). Each type has a type-specific block (genie_space, knowledge_assistant, etc.) whose identifier field differs by type — see the table below.

# Attach a Genie space — find its space_id with `databricks genie list-spaces`
databricks supervisor-agents create-tool supervisor-agents/<id> analyst --json '{
    "tool_type": "genie_space",
    "description": "SQL analytics on the analytics warehouse",
    "genie_space": {"id": "<genie_space_id>"}
}'

# Attach a Knowledge Assistant — find ka_id with `databricks knowledge-assistants list-knowledge-assistants`
databricks supervisor-agents create-tool supervisor-agents/<id> docs_agent --json '{
    "tool_type": "knowledge_assistant",
    "description": "Answers from product documentation",
    "knowledge_assistant": {"knowledge_assistant_id": "<ka_id>"}
}'

# List / get / delete tools
databricks supervisor-agents list-tools supervisor-agents/<id>
databricks supervisor-agents get-tool supervisor-agents/<id>/tools/<tool_id>
databricks supervisor-agents delete-tool supervisor-agents/<id>/tools/<tool_id>

Tool types (tool_type value → type-specific block):

tool_type Block Use for
genie_space {"id": "<space_id>"} Natural language → SQL via Genie
knowledge_assistant {"knowledge_assistant_id": "<ka_id>"} Document Q&A via a KA
uc_function {"name": "catalog.schema.func"} UC SQL/Python function
uc_connection {"name": "<connection_name>"} External MCP server via UC HTTP Connection
volume {"name": "<full_volume_name>"} UC Volume browsing
app {"name": "<app_name>"} Databricks App
Other types (serving_endpoint, lakeview_dashboard, supervisor_agent, uc_table, vector_search_index, catalog, schema, web_search) Block name and field shape vary Run databricks supervisor-agents create-tool --help and probe — these were not verified end-to-end here.

Examples (training the supervisor)

Examples must use --json — the positional GUIDELINES arg doesn't accept any encoding because guidelines is a repeated string.

databricks supervisor-agents create-example supervisor-agents/<id> --json '{
    "question": "What were Q4 revenue numbers?",
    "guidelines": ["Route to analyst Genie space", "Always group by region"]
}'

databricks supervisor-agents list-examples supervisor-agents/<id>
databricks supervisor-agents get-example supervisor-agents/<id>/examples/<ex_id>
databricks supervisor-agents delete-example supervisor-agents/<id>/examples/<ex_id>

Endpoint readiness: after create-supervisor-agent, the serving endpoint takes up to ~10 minutes to come online before it can answer queries. get-supervisor-agent returns the endpoint name immediately, but querying it is gated on the endpoint's own readiness — check via databricks serving-endpoints get <endpoint_name>.


Reference

Topic File
KA source types, index, troubleshooting references/1-knowledge-assistants.md
UC functions, MCP servers, examples references/2-supervisor-agents.md