Long-Term Memory with Databricks Managed Memory (UC memory-store)

Give your agent durable, cross-session memory about each user, exposed as five tools (save_memory, get_memory, list_memories, update_memory, delete_memory). The tools are thin REST calls to the Unity Catalog memory-store APIs.

Beta. The Databricks memory-store APIs are in beta — APIs and behavior may change.

This is Databricks managed memory — NOT the self-hosted Lakebase memory

A memory store is a governed Unity Catalog securable you read/write purely over REST: no database to provision, no tables to create, no embedding endpoint, and no extra Python dependency (it uses the databricks-sdk already in the template). This is different from the agent-openai-memory / agent-langgraph-memory skills, which persist to a Lakebase instance you run yourself. It's additive to short-term/session memory (the OpenAI AsyncDatabricksSession or the LangGraph checkpointer) — keep that. But it is the agent's long-term memory, and there should be only one: if the template already has a long-term memory system, remove it before adding these tools.

This skill is framework-agnostic and flexible with both the OpenAI Agents SDK and LangGraph; each step notes the small per-SDK difference.