Markdown RAG
Indexes and semantically searches Markdown documents using vector embeddings and a self-contained vector database.
About
Empower your local Markdown document collection with advanced search capabilities. This command-line tool efficiently indexes your notes and documents, leveraging vector embeddings and an integrated vector database for semantic search, allowing you to find relevant information not just by keywords, but by meaning, all in a local-first environment.
Key Features
- Semantic search powered by vector embeddings
- 0 GitHub stars
- Indexing of diverse Markdown documents
- Integrated, self-contained vector database
- Local-first operation for data privacy and control
- Command-line interface for efficient interaction
Use Cases
- Facilitating research by semantically linking and recalling relevant notes and articles
- Enhancing personal knowledge management and note organization
- Efficiently searching and retrieving information from large technical documentation sets