QMD - Query Markup DocumentsBLOCK

An on-device search engine for everything you need to remember. Index your markdown notes, meeting transcripts, documentation, and knowledge bases. Search with keywords or natural language. Ideal for your agentic flows.

QMD combines BM25 full-text search, vector semantic search, and LLM re-ranking—all running locally via node-llama-cpp with GGUF models.

flowchart LR
Q[User Query] --> X[Query Expansion]
Q --> FTS[BM25 Search]
Q --> VS[Vector Search]
X --> HYDE[HyDE]
X --> VEC[Vec dense sentences]
X --> LEX[Lex BM25 keywords]
HYDE --> VS
VEC --> VS
LEX --> FTS
VS --> RRF[Reciprocal Rank Fusion]
FTS --> RRF
RRF --> RR[LLM Reranker]
RR --> OUT[Final ranked results]

Typed expansions are routed exclusively: lex → BM25/FTS, vec and hyde → vector search. The original query is sent to both backends, then fused with RRF and reranked.

You can read more about QMD's progress in the CHANGELOG.

Quick Start

# Install globally (Node or Bun)
npm install -g @tobilu/qmd
# or
bun install -g @tobilu/qmd

# Or run directly
npx @tobilu/qmd ...
bunx @tobilu/qmd ...

# Create collections for your notes, docs, and meeting transcripts
qmd collection add ~/notes --name notes
qmd collection add ~/Documents/meetings --name meetings
qmd collection add ~/work/docs --name docs

# Add context to help with search results, each piece of context will be returned when matching sub documents are returned. This works as a tree. This is the key feature of QMD as it allows LLMs to make much better contextual choices when selecting documents. Don't sleep on it!
qmd context add qmd://notes "Personal notes and ideas"
qmd context add qmd://meetings "Meeting transcripts and notes"
qmd context add qmd://docs "Work documentation"

# Generate embeddings for semantic search
qmd embed

# Search across everything
qmd search "project timeline"           # Fast keyword search
qmd vsearch "how to deploy"