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lakebase-setup

Configure Databricks Lakebase resources and grant Postgres permissions for agent memory.

2|Updated Apr 6, 2026
Search Tags:#memory#deploy#databricks#lakebase#agent persistence#postgres permissions#embedding configuration
One-click install
npx skills add https://github.com/bcheng004/agent-langgraph-advanced-workshop --skill lakebase-setup-bcheng004
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lakebase-setup
Source: https://github.com/bcheng004/agent-langgraph-advanced-workshop/tree/main/.claude/skills/lakebase-setup
Command: npx skills add https://github.com/bcheng004/agent-langgraph-advanced-workshop --skill lakebase-setup-bcheng004

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires databricks-langchain[memory], jq, python, and includes scripts (resource) components.

What problem does it solve?

This Skill resolves failures setting up or using Lakebase for agent memory by guiding you through the required dependencies, Databricks resource configuration, environment variables, and critical Postgres permission grants.

Core Features & Use Cases

  • End-to-end Lakebase configuration: Covers both provisioned and autoscaling Lakebase instance models, including the correct databricks.yml resource stanza and required env wiring.
  • Memory-ready setup for agent templates: Targets agent short-term and long-term memory use cases (LangGraph templates) and the common operational errors users hit when memory is enabled.
  • Permission-error troubleshooting: Provides a concrete fix for migration/CREATE TABLE and “permission denied” scenarios by granting the app’s service principal the needed Postgres access.
  • Operational runbook: Includes troubleshooting guidance for embedding dimension mismatches, missing store tables, unresolved instance names, and failed connections.

Quick Start

Ask your AI assistant to run through the Lakebase setup for your agent memory by telling it whether you use provisioned or autoscaling Lakebase and what values you have for instance name or project/branch/database id.

Frequently Asked Questions about lakebase-setup

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fix permission denied errors when setting up Databricks Lakebase for agent memory?▼

To fix Databricks Lakebase permission denied errors for agent memory, you must run a Postgres permission grant for the app's service principal. This grants the service principal required database access to resolve migration and CREATE TABLE failures.

How do I configure Databricks Lakebase for LangGraph agent memory persistence?▼

Configuring Databricks Lakebase for agent memory persistence requires setting the correct databricks.yml resources stanza, aligning .env embedding parameters, deploying the bundle, and running Postgres permission grants for the service principal.

Why does my Lakebase agent memory setup fail with embedding dimension mismatches?▼

Lakebase agent memory setups fail with embedding dimension mismatches when the .env embedding parameters are not correctly aligned with the configured Databricks bundle resources, requiring parameter correction and redeployment to resolve.

Does Databricks Lakebase memory configuration work for both provisioned and autoscaling deployments?▼

Databricks Lakebase memory configuration works for both provisioned and autoscaling deployments by applying the correct databricks.yml resource stanzas and Postgres service principal grants to enable short-term checkpoints and long-term user memory.

What dependencies do I need to configure Lakebase memory for agent templates?▼

Configuring Lakebase memory for agent templates requires the databricks-langchain[memory] dependency, jq, and python installed to execute the bundle deployment scripts and Postgres permission grants successfully.

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