Local personal knowledge base with hybrid search and GraphRAG

Local Personal Knowledge Base with Hybrid Search and GraphRAG

This tool provides a robust, local personal knowledge base designed for developers. It leverages advanced search capabilities and integrates with Large Language Models (LLMs) to enrich your stored information. Built for efficiency and privacy, it keeps your data entirely on your machine, accessible via a command-line interface (CLI). This makes it an ideal solution for managing complex projects, research, or any scenario requiring deep information retrieval and contextual understanding.

What it Does

The core functionality is to create and manage a personal knowledge base locally. It ingests your documents and makes them searchable. The system supports hybrid search, combining full-text search (FTS) with vector similarity search using pgvector . This allows for both keyword-based and semantic retrieval of information. Furthermore, it implements GraphRAG (Retrieval Augmented Generation) to build a knowledge graph from your data, enabling more sophisticated querying and reasoning. LLM enrichment is achieved by integrating with Ollama, allowing you to process and enhance your knowledge base with AI capabilities.

Key Features

• Local-First Architecture: All data is stored and processed on your local machine, ensuring privacy and control.
• Hybrid Search: Combines traditional full-text search with vector embeddings for precise and semantic retrieval.
• pgvector Integration: Utilizes PostgreSQL with the pgvector extension for efficient vector storage and querying.
• GraphRAG Implementation: Builds a knowledge graph from your documents for advanced contextual understanding and querying.
• LLM Enrichment: Integrates with Ollama for seamless LLM-powered data processing and enhancement.
• CLI Interface: Designed for developers, offering a command-line interface for easy integration into workflows.

Who it's For

This tool is specifically targeted at AI builders, researchers, and developers who need a powerful and private way to manage their personal knowledge. If you work with large datasets, conduct extensive research, or build AI applications that require deep contextual understanding of your own data, this local knowledge base will be invaluable. Developers looking to integrate LLM capabilities with their private information stores will find the GraphRAG and Ollama integrations particularly useful. It's for those who prioritize data ownership and require sophisticated search and reasoning capabilities without relying on cloud services.