What problem does it solve?
Building distributed AI systems with efficient data synchronization, complex search capabilities, and multi-database management is incredibly challenging. This Skill provides advanced AgentDB features like QUIC synchronization for sub-millisecond cross-node communication, hybrid search, and custom distance metrics, enabling you to build highly performant and sophisticated AI architectures.
Core Features & Use Cases
- QUIC Synchronization: Achieve <1ms latency synchronization between AgentDB instances across networks with built-in encryption and automatic retry.
- Multi-Database Management: Coordinate multiple AgentDB instances for different domains or abstraction levels, ensuring data isolation and efficient scaling.
- Hybrid Search & Custom Metrics: Combine vector search with metadata filtering and define custom distance metrics for highly relevant and precise retrieval.
- Use Case: Deploy a distributed multi-agent system where agents across different servers need to share and retrieve knowledge instantly. Enable QUIC Sync on AgentDB instances, allowing agents to store and access patterns with sub-millisecond latency, ensuring real-time collective intelligence and coordinated decision-making.
Quick Start
import { createAgentDBAdapter } from 'agentic-flow/reasoningbank';
// Initialize with QUIC synchronization
const adapter = await createAgentDBAdapter({
dbPath: '.agentdb/distributed.db',
enableQUICSync: true,
syncPort: 4433,
syncPeers: [
'192.168.1.10:4433',
'192.168.1.11:4433',
'192.168.1.12:4433',
],
});
// Patterns automatically sync across all peers
await adapter.insertPattern({
// ... pattern data
});
