Skip to main content
Anona gives a LangChain chain or LangGraph agent memory that survives the process. You bring no LLM key and run no vector database. Anona is managed, and every call is scoped so one space can serve many end users without their memories mixing.

​
LangGraph agents

The context block is fetched once per turn and injected as a system message before every model call in that turn, reused across each step of a tool-calling loop rather than re-fetched. If you also pass system_prompt to create_agent, both survive: your instructions first, the memory block after. The completed turn as a whole, not each intermediate step, is stored once the agent run finishes. Nothing else changes.
That per-turn reuse is implemented as a declared field on LangGraph’s own graph state, which is exactly what a checkpointer persists. If you compile create_agent(..., checkpointer=...) with a durable checkpointer (SQLite, Postgres, …), the retrieved memory text is written into your checkpoint store verbatim (once per checkpoint saved during that run), not just held in process memory. That copy lives outside Anona’s storage and retention: deleting or expiring a memory on Anona’s side does not remove it from checkpoints already written. Expected given what the cache is for, not a bug, just worth knowing if your own checkpoint store needs to honor a retention or deletion policy.

​
Retrieval chains

AnonaRetriever is async-only: call ainvoke() (shown above), not invoke(). The sync form raises NotImplementedError rather than silently blocking an event loop. It is the one place across any of these six adapters that raises into the caller instead of failing open. Every other failure mode on this page (Anona unreachable, no matches, …) still returns normally with an empty result.

​
Scoping

user_id, agent_id and session_id on the bridge isolate memory inside one space. A memory written under user_id="customer-42" is only ever returned to a query carrying the same user_id.

​
Turning off writes

Keeps recall, skips storing new turns.

​
Why not a LangGraph Store?

A BaseStore is namespaced key-value: get(namespace, key) returns one exact record. Anona is search: you ask a question and get ranked, deduplicated, token-budgeted context. A partial Store implementation would break LangGraph’s built-in memory tools at runtime, so we ship the two shapes that fit instead.

​
Failure behaviour

If Anona is unreachable, your agent keeps running without memory. Memory failures are logged, never raised.