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PyPI version Python versions License: MIT Research: SLoD arXiv

Mnemoverse Python SDK

Persistent memory for AI agents. Not vector search — statistical learning backed by Hebbian associations.

Installation

pip install mnemoverse

Quick Start

from mnemoverse import MnemoClient

client = MnemoClient(api_key="mk_live_YOUR_KEY")

# Store a memory
result = client.write(
    "Retry with exponential backoff fixed the timeout issue",
    concepts=["retry", "backoff", "timeout"]
)

# Query — Hebbian associations expand "timeout" → "retry", "backoff"
memories = client.read("how to handle timeouts?")

# Report outcome — the system learns what works
client.feedback(
    atom_ids=[item.atom_id for item in memories.items],
    outcome=1.0,
    query_concepts=memories.query_concepts
)

Async Client

from mnemoverse import AsyncMnemoClient

async with AsyncMnemoClient(api_key="mk_live_YOUR_KEY") as client:
    result = await client.write("async memory", concepts=["async"])
    memories = await client.read("what about async?")

Features

  • Circuit breaker — 5 failures → open → 30s half-open → probe
  • Retry with backoff — 3 attempts, rate-limit-aware
  • Sync + async — MnemoClient for scripts, AsyncMnemoClient for FastAPI
  • Type-safe — Pydantic models, full type hints

Methods

Method Description
write(content, concepts, domain, metadata) Store a memory
write_batch(items) Store up to 500 memories
read(query, top_k, domain, since, until, order_by, exclude_author) Semantic search — "what do I know about X"
recent(domain, since, until, exclude_author, limit, cursor) Newest-first feed — "what happened lately"
feedback(atom_ids, outcome) Report success/failure
stats() Memory statistics
health() API health check

Every method exists on both MnemoClient (sync) and AsyncMnemoClient (async).

Search or feed?

read() answers what do I know about X and ranks by relevance. recent() answers what happened lately and is complete within one scope by construction — nothing is skipped, which a semantic search cannot promise. Reach for recent() to resume after a break or to catch up on a shared room.

from mnemoverse import MnemoClient

client = MnemoClient(api_key="mk_live_...")

# Catch up on a shared room. Rooms are SEPARATE stores: pass the address as
# `domain`, or an unscoped feed will not cover them.
page = client.recent(domain="xroom:room_01ABC", since="2026-08-01T00:00:00Z", limit=20)
for item in page.items:
    print(item.created_at, item.content)

if page.next_cursor:
    page = client.recent(domain="xroom:room_01ABC", cursor=page.next_cursor)

Read items carry created_at and provenance (who wrote it, where from).

Documentation

License

MIT

Metadata

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