agentmemo-py 1.0.0

Persistent memory for AI agents — store, retrieve, and recall context across sessions.

agentmemo

Persistent memory for AI agents. Store, semantically retrieve, and recall context across sessions. Pure standard library (no required dependencies).

pip install agentmemo

Quick start

from agentmemo import MemoryClient

# Get a free key (or pass an existing one)
key = MemoryClient.signup("my-agent")["api_key"]
mem = MemoryClient(key)

# Store
mem.store(
    user_id="user_123",
    agent_id="assistant",
    content="User prefers dark mode and works in TypeScript.",
    tags=["preference"],
    importance=8,
)

# Retrieve semantically
hits = mem.search(user_id="user_123", query="what are the user's preferences?")

# Context for an LLM system prompt
ctx = mem.context(user_id="user_123", format="anthropic")["context"]

API

• store(user_id, agent_id, content, metadata=None, ttl_seconds=None, tags=None, namespace="default", importance=5, outcome="unknown", detect_conflicts=False)
• search(user_id, query, agent_id=None, limit=10, namespace=None, tags=None, min_importance=None)
• delete(id=None, user_id=None, agent_id=None)
• context(user_id, agent_id=None, max_tokens=2000, format="raw")
• feedback(memory_id, outcome, confidence=1.0)
• batch(memories)
• stats(user_id=None), usage()
• MemoryClient.signup(name) — static, returns a free API key
• Async: await mem.async_store(...), await mem.async_search(...) (requires pip install agentmemo[async])

Errors raise AgentMemoError with .status, .code, .body.

Docs: https://agentmemo.dev/docs · Apache-2.0 · Built by Dr. Nadeem Shaikh