Expand description
§Converge Knowledge
A self-learning knowledgebase built on ruvector that gets smarter the more you use it.
§Features
- Vector Storage: High-performance HNSW-based vector indexing
- Self-Learning: Adaptive query understanding using GNN-inspired learning
- Knowledge Graph: Semantic relationships between knowledge entries
- Hybrid Search: Combine vector similarity with metadata filtering
- gRPC Interface: High-performance RPC for service integration
- MCP Server: Model Context Protocol for Claude Desktop
§Quick Start
use converge_knowledge::{KnowledgeBase, KnowledgeEntry};
#[tokio::main]
async fn main() -> anyhow::Result<()> {
let kb = KnowledgeBase::open("./knowledge.db").await?;
// Add knowledge
kb.add_entry(KnowledgeEntry::new(
"Rust Memory Safety",
"Rust ensures memory safety through ownership and borrowing rules...",
)).await?;
// Search with learning
let results = kb.search_simple("memory management in rust", 5).await?;
Ok(())
}§Architecture
┌─────────────────────────────────────────────────────────────┐
│ Converge Knowledge │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────────────┐ │
│ │ CLI │ │ gRPC │ │ MCP │ │ Library API │ │
│ │ │ │ Server │ │ Server │ │ │ │
│ └────┬────┘ └────┬────┘ └────┬────┘ └────────┬────────┘ │
│ │ │ │ │ │
│ └────────────┴────────────┴────────────────┘ │
│ │ │
│ ┌────────────────────────┴───────────────────────────────┐ │
│ │ KnowledgeBase │ │
│ │ ┌─────────────┐ ┌───────────────┐ ┌──────────────┐ │ │
│ │ │ Embedding │ │ Learning │ │ Storage │ │ │
│ │ │ Engine │ │ Engine │ │ Backend │ │ │
│ │ │ (Hash/ML) │ │ (GNN-style) │ │ (Bincode) │ │ │
│ │ └─────────────┘ └───────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘Re-exports§
pub use crate::agentic::AgenticDB;pub use crate::agentic::AgenticStats;pub use crate::agentic::CausalEdge;pub use crate::agentic::CausalMemory;pub use crate::agentic::CausalNode;pub use crate::agentic::Critique;pub use crate::agentic::CritiqueType;pub use crate::agentic::DriftDetector;pub use crate::agentic::Experience;pub use crate::agentic::ExperienceWindow;pub use crate::agentic::FewShotLearner;pub use crate::agentic::Hyperedge;pub use crate::agentic::LearningSession;pub use crate::agentic::LearningStrategy;pub use crate::agentic::MetaLearner;pub use crate::agentic::OnlineLearner;pub use crate::agentic::ParameterSnapshot;pub use crate::agentic::ReflexionEpisode;pub use crate::agentic::ReflexionMemory;pub use crate::agentic::Reward;pub use crate::agentic::SessionTurn;pub use crate::agentic::Skill;pub use crate::agentic::SkillLibrary;pub use crate::agentic::SkillPattern;pub use crate::agentic::TaskFeatures;pub use crate::agentic::TemporalMemory;pub use crate::agentic::TemporalOccurrence;pub use crate::agentic::TemporalPeriod;pub use crate::agentic::TimeCrystal;pub use crate::core::KnowledgeBase;pub use crate::core::KnowledgeBaseConfig;pub use crate::core::KnowledgeEntry;pub use crate::core::SearchOptions;pub use crate::core::SearchResult;pub use crate::embedding::EmbeddingEngine;pub use crate::error::Error;pub use crate::error::Result;pub use crate::learning::LearningEngine;pub use crate::storage::StorageBackend;
Modules§
- agentic
- AgenticDB: Agent Memory System
- core
- Core types and knowledge base implementation.
- embedding
- Embedding generation for text vectorization.
- error
- Error types for the knowledge base.
- grpc
- gRPC service implementation.
- ingest
- Document ingestion module for extracting content from various file formats.
- learning
- Self-learning engine using GNN-inspired approaches.
- mcp
- Model Context Protocol (MCP) server for Claude Desktop integration.
- storage
- Storage backend for persistence.