Architecture Overview

Memori is built with a modular, enterprise-grade architecture focused on simplicity, reliability, and flexible database integration.

System Architecture

┌─────────────────────────────────────────┐
│ APPLICATION LAYER                       │
|                                         |
│  • Your code + LLM client               │
└──────────────┬──────────────────────────┘
               │
┌──────────────▼──────────────────────────┐
│ MEMORI CORE                             │
|                                         |
│  • LLM provider wrappers                │
│  • Attribution (entity/process/session) │
│  • Recall API                           │
└──────────────┬──────────────────────────┘
               │
┌──────────────▼──────────────────────────┐
│ STORAGE LAYER                           │
|                                         |
│  • Connection Registry                  │
|  • Schema Builder                       |
│  • Database Adapters                    │
|  • Database Drivers                     |
└──────────────┬──────────────────────────┘
               │
┌──────────────▼──────────────────────────┐
│ DATABASE AGNOSTIC STORAGE               │
└─────────────────────────────────────────┘

Core Components

1. Memori Core

Key Responsibilities:

• Manage attribution (entity, process, session)
• Coordinate storage and Advanced Augmentation
• Provide LLM provider wrappers
• Expose recall API for semantic search

2. LLM Provider Wrappers

How it works:

• Intercepts LLM client method calls
• Captures user messages and AI responses
• Persists to database via storage manager
• Supports sync, async, streamed, and unstreamed modes
• Works with OpenAI, Anthropic, Google, xAI, LangChain, Pydantic AI

3. Attribution System

Tracking Model:

• Entity: Person, place, or thing (typically a user)
• Process: Agent, program, or workflow
• Session: Groups related LLM interactions

4. Storage System

Supported Connections:

• SQLAlchemy sessionmaker
• DB API 2.0 connections
• Django ORM connections
• MongoDB databases
• OceanBase/SeekDB via SQLAlchemy (pyobvector)

5. Advanced Augmentation

What it does:

• Extracts facts from conversations
• Generates embeddings for semantic search
• Identifies preferences, skills, attributes
• Runs asynchronously with no latency impact
• Upgrade via MEMORI_API_KEY (free tier available)

Data Flow

1. Conversation Capture

2. Attribution Tracking

3. Recall API Flow

4. Advanced Augmentation

Configuration

Environment Variables

# Memori API key for Advanced Augmentation
export MEMORI_API_KEY="your-api-key"