qmd

You can search personal notes locally by using an AI-powered search engine that indexes documents directly on your machine, combining keyword matching and semantic understanding to find information privately without cloud reliance.

Hybrid search for knowledge bases combines traditional keyword matching with semantic understanding. LLM reranking then reorders these search results using a language model to prioritize the most contextually relevant documents for your query.

Yes, you need Node.js and SQLite to run this local AI search engine. Node.js executes the search scripts while SQLite stores the indexed document data and knowledge base metadata locally on your system.

Yes, you can integrate local document search with an AI agent using MCP. This integration allows an agent like Hermes to query your local knowledge base directly and retrieve relevant information through the search interface.

To search for specific text within markdown files, execute a query against your local knowledge base using the command-line interface. The search engine will scan your indexed markdown documents and return the matching notes.

Limitations of local AI knowledge base search include requiring local environment setup with specific dependencies like Node.js and SQLite. Search performance and semantic understanding accuracy are also constrained by your local hardware capabilities.