lakebase-setup
Installation
SKILL.md
Lakebase Setup for Agent Persistence
Profile reminder: All
databricksCLI commands must include the profile from.env:databricks <command> --profile <profile>orDATABRICKS_CONFIG_PROFILE=<profile> databricks <command>
Lakebase (autoscaling): This skill uses autoscaling Lakebase — the project/branch/endpoint model. Make sure you have the autoscaling endpoint (a short endpoint name or the full resource path
projects/<p>/branches/<b>/endpoints/<e>), or the project + branch.
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.