zeno-memory 1.0.2

Zeno memory protocols, context-bound handles, and SQLite defaults.

zeno-memory

Memory protocols, per-turn view handles, and SQLite-backed defaults for the Zeno framework.

Install

uv add 'zeno-framework[memory]'

What's in here

• Protocols: SessionStore, UserMemoryStore, KnowledgeStore, ConversationStore, VectorStore.
• Per-turn handles: MemoryView, UserMemoryView, KnowledgeView, ConversationHandle, SessionHandle.
• SQLite defaults: SqliteSessionStore, SqliteUserMemoryStore, SqliteConversationStore.
• Composer: ThreeLayer (session + user memory + knowledge + conversation).
• Adapter: VectorBackedUserMemoryStore — wraps any KnowledgeStore to make user memory semantically searchable.

Wiring

from pathlib import Path

from zeno.app import ZenoApp
from zeno.memory import ThreeLayer
from zeno.memory.sqlite.conversation_store import SqliteConversationStore
from zeno.memory.sqlite.session_store import SqliteSessionStore
from zeno.memory.sqlite.user_memory_store import SqliteUserMemoryStore

data = Path.home() / ".zeno"
data.mkdir(parents=True, exist_ok=True)

# `knowledge=` is a `KnowledgeStore` from a vector backend — see
# `zeno-chroma` or `zeno-qdrant` for concrete adapters. The example below
# uses `SqliteUserMemoryStore` for user memory; swap in
# `VectorBackedUserMemoryStore(knowledge_store=...)` to make user memory
# semantically searchable.
memory = ThreeLayer(
    session=SqliteSessionStore(data / "sessions.db"),
    user_memory=SqliteUserMemoryStore(data / "user_memory.db"),
    knowledge=...,  # ChromaKnowledgeStore | QdrantKnowledgeStore | …
    conversation=SqliteConversationStore(data / "conversations.db"),
)

app = ZenoApp(agent=..., memory=memory, channels=..., provider=...)

ZenoApp calls memory.view_for(user_id=, channel=, thread_key=) once per turn and binds the resulting MemoryView into Ctx. Tools use ctx.memory.user, ctx.memory.knowledge, ctx.memory.session, and ctx.memory.conversation without ever seeing the underlying store.

Choosing a UserMemoryStore

Store	Use when
SqliteUserMemoryStore	You want exact-match recall on stored facts. Cheap, no embedding model required.
VectorBackedUserMemoryStore(knowledge_store=…)	You want semantic recall (e.g. "what did the user say about their job?"). Reuses the same vector backend you wired for knowledge.

Both implement the same UserMemoryStore protocol — swap freely without changing tool code.

ConversationStore (provider portability)

Non-Claude providers (e.g. OpenAIProvider) write each turn's assistant, tool, and user messages through ConversationStore so the next turn has prior context. ClaudeSDKProvider does not use it — the SDK owns its own session history.

Vector backends

Concrete KnowledgeStore adapters live in sibling packages:

• zeno-chroma — ChromaDB-backed.
• zeno-qdrant — Qdrant-backed.

See also: zeno-core for Ctx, @tool, and the MemoryBinderProtocol.

Part of the Zeno framework.