NVIDIA NeMo Agent Toolkit + MemorySync
A pip-installable MemoryEditor plugin: one YAML block gives any toolkit workflow long-term memory — explicit memory tools or fully automatic via auto_memory_agent.
Overview
Install nat-memorysync and `_type: memorysync_memory` becomes available in every NeMo Agent Toolkit workflow YAML — a real entry-point plugin, not example code to vendor (the toolkit’s Mem0 and Zep editors live in its repo as examples). It works with both wiring modes: NVIDIA’s built-in add_memory/get_memory tools, and the automatic auto_memory_agent wrapper that stores every turn and enriches every prompt with no tools and no prompt changes. The editor is engineered against the in-repo editors’ sharp edges: search without user_id raises a ValueError naming the kwarg (the Mem0 editor throws a bare KeyError), your metadata dict is never mutated (the Mem0 editor pops keys out of it), search returns one MemoryItem per fact with similarity_score populated (the Zep editor returns a single joined blob; the Mem0 editor discards scores), and remove_items with no kwargs raises instead of silently doing nothing. Deletes are session-scoped by default — wiping a user’s entire memory requires the explicit scope="user" opt-in. Rows are always keyed by each item’s user_id, so an unset conversation id can never mix users (the in-repo Zep editor routes everyone to one shared "default_zep_thread"). Recall runs under a hard 1.2s budget and fails open, so automatic memory can never stall a turn; deterministic idempotency seeds make RetryMixin retries converge on one stored row.
Setup status and requirements
- Supported version
- nat-memorysync 1.0.0 (PyPI)
- Last setup review
- 2026-08-24
- Permissions
- A MemorySync API key with read and write scopes.
- Limits
- Requires nvidia-nat-core 1.5+ (Python 3.11+, the toolkit’s own floor).
Capabilities
- Real pip-installable plugin via the nat.components entry point — not vendored example code
- Both wiring modes: add_memory/get_memory tools and the automatic auto_memory_agent
- One MemoryItem per fact with similarity_score — no joined blobs, no discarded scores
- Loud typed contracts — ValueError naming the missing kwarg, never a bare KeyError
- Caller items and metadata never mutated (copy-first, tested)
- Session-scoped deletes by default; whole-user wipe is an explicit scope="user" opt-in
- Bleed-safe by construction — rows always keyed by item user_id
- Hard 1.2s recall budget, fail-open both directions; RetryMixin-safe idempotent writes
Quick Start
memory:saas_memory:_type: memorysync_memory # key from MEMORYSYNC_API_KEYfunctions:add_memory:_type: add_memorymemory: saas_memorydescription: Save any user preference or fact.get_memory:_type: get_memorymemory: saas_memorydescription: Recall saved user preferences and facts.workflow:_type: react_agenttool_names: [add_memory, get_memory]llm_name: my_llm
Use Cases
NVIDIA-stack agents (NIM, Nemotron) that remember users across sessions
Zero-code memory for existing workflows via auto_memory_agent
Replacing the in-repo Mem0/Zep example editors with a maintained plugin
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