Persistent cognitive memory for AI agents, powered by YantrikDB (docs).
Install
bash
pip install yantrik-memory
yantrik-memory init
What it does
Gives your AI agent persistent memory that survives across conversations:
Remember & Recall — Store and retrieve memories with hybrid search (semantic + graph + temporal + keyword)
Personality Traits — 9 evolving traits that adapt to each user
Bond Evolution — Relationships grow from stranger to bonded over time
Knowledge Graph — Entity relationships for context-aware retrieval
Context Assembly — One call to get everything an LLM needs
Quick Start
python
from yantrik_memory import YantrikMemory
mem = YantrikMemory()
# Single entry point for agents
context = mem.process_turn(
agent_id="assistant",
user_id="user123",
message="I prefer dark mode and concise answers",
)
# Returns: memories, traits, bond state, personality guidance, mood, intent
print(context["traits"]) # {'conciseness': 0.55, 'humor': 0.5, ...}
print(context["bond"]["level"]) # 'acquaintance'
Real Conversation Demo
Here's Yantrik Memory running inside OpenClaw — an open-source AI agent platform. The agent remembers context across turns, learns preferences, and builds a profile over time.
Turn 1 — Alex introduces himself:
Alex: Hey! I'm Alex. I'm a backend engineer at a startup. We're building a task management app and I need help setting up the API.
Agent: Hi Alex. What stack are you using? What API help do you need?
Turn 2 — Alex shares preferences, agent adapts:
Alex: We're using Python with FastAPI. I prefer keeping things simple — no over-engineering. Can you suggest a basic project structure?
Alex: That's perfect, thanks! Oh and remember — I always use PostgreSQL for production and SQLite for local dev. What about the database layer?
Agent:
python
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.core.config import settings
# Use SQLite for dev, PostgreSQL for prod
engine = create_engine(settings.DATABASE_URL)
SessionLocal = sessionmaker(bind=engine)
Turn 4 — Alex asks what the agent remembers:
Alex: Great work! You're really helpful. One more thing — what do you remember about me and my project so far?
Agent:
Backend engineer at a startup
Building a task management app
Using Python with FastAPI
Prefer simple solutions, no over-engineering
Always use PostgreSQL for production, SQLite for local dev
