agent-bricks
Agent Bricks
Create and manage Databricks Agent Bricks - pre-built AI components for building conversational applications.
Overview
Agent Bricks are three types of pre-built AI tiles in Databricks:
| Brick | Purpose | Data Source |
|---|---|---|
| Knowledge Assistant (KA) | Document-based Q&A using RAG | PDF/text files in Volumes |
| Genie Space | Natural language to SQL | Unity Catalog tables |
| Multi-Agent Supervisor (MAS) | Multi-agent orchestration | Model serving endpoints |
Prerequisites
Before creating Agent Bricks, ensure you have the required data:
For Knowledge Assistants
More from databricks-solutions/ai-dev-kit
databricks-python-sdk
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
132python-dev
Python development guidance with code quality standards, error handling, testing practices, and environment management. Use when writing, reviewing, or modifying Python code (.py files) or Jupyter notebooks (.ipynb files).
68skill-test
Testing framework for evaluating Databricks skills. Use when building test cases for skills, running skill evaluations, comparing skill versions, or creating ground truth datasets with the Generate-Review-Promote (GRP) pipeline. Triggers include "test skill", "evaluate skill", "skill regression", "ground truth", "GRP pipeline", "skill quality", and "skill metrics".
53databricks-docs
Databricks documentation reference via llms.txt index. Use when other skills do not cover a topic, looking up unfamiliar Databricks features, or needing authoritative docs on APIs, configurations, or platform capabilities.
29databricks-config
Manage Databricks workspace connections: check current workspace, switch profiles, list available workspaces, or authenticate to a new workspace. Use when the user mentions \"switch workspace\", \"which workspace\", \"current profile\", \"databrickscfg\", \"connect to workspace\", or \"databricks auth\".
26databricks-app-python
Builds Python-based Databricks applications using Dash, Streamlit, Gradio, Flask, FastAPI, or Reflex. Handles OAuth authorization (app and user auth), app resources, SQL warehouse and Lakebase connectivity, model serving integration, foundation model APIs, LLM integration, and deployment. Use when building Python web apps, dashboards, ML demos, or REST APIs for Databricks, or when the user mentions Streamlit, Dash, Gradio, Flask, FastAPI, Reflex, or Databricks app.
22