lakebase-setup

Installation
SKILL.md

Lakebase Setup for Agent Persistence

Profile reminder: All databricks CLI commands must include the profile from .env: databricks <command> --profile <profile> or DATABRICKS_CONFIG_PROFILE=<profile> databricks <command>

Two types of Lakebase: Databricks supports provisioned instances (with instance name) and autoscaling instances (project/branch model). This skill covers both. Make sure you know which Lakebase instance the user is using, ask the user which type they are using if unclear.

Use Cases

Lakebase is used for three distinct purposes across the agent templates:

Use case Templates Description
Chat UI conversation history All templates The built-in chat UI (e2e-chatbot-app-next) can persist conversations across page refreshes and browser sessions. This is purely UI-side persistence — the agent itself is stateless.
Agent short-term memory agent-langgraph-advanced, agent-openai-advanced Conversation threads within a session via AsyncCheckpointSaver (LangGraph) or AsyncDatabricksSession (OpenAI SDK). The agent remembers what was said earlier in the same conversation.
Agent long-term memory agent-langgraph-advanced User facts across sessions via AsyncDatabricksStore. The agent remembers things about a user from previous conversations.

Note: When the quickstart prompts for Lakebase on a non-memory template, it's for chat UI history only — not for the agent. Memory templates always require Lakebase.

Overview

Related skills

More from databricks/app-templates

Installs
21
GitHub Stars
133
First Seen
Feb 15, 2026