# qi configuration — annotated example
# Copy to ~/.config/qi/config.yaml and customize.

# Path to the SQLite database (supports ~ expansion)
database_path: ~/.local/share/qi/qi.db

# Collections: directories of documents to index.
# Names are generated from paths; keep name aligned with path.
collections:
  - name: notes
    path: ~/notes
    description: Personal notes and documents
    extensions: [.md, .txt]     # Omit to use defaults (.md, .markdown, .txt, .text)
    ignore: [.git, node_modules, .DS_Store]

  - name: wiki
    path: ~/wiki
    description: Team wiki and documentation
    extensions: [.md, .txt]
    ignore: [.git, .DS_Store]

providers:
  # Embedding provider for vector search (OpenAI-compatible /v1/embeddings)
  # Uncomment to enable hybrid search with local Ollama or llama.cpp
  # embedding:
  #   name: ollama
  #   base_url: http://localhost:11434      # ${VAR} env references are expanded
  #   model: nomic-embed-text
  #   dimension: 768
  #   batch_size: 32
  #   max_input_chars: 24000   # optional safety net: truncate texts over ~6k tokens (omit/0 = no limit)
  #   api_key: ${OPENAI_API_KEY}   # optional; ${VAR} is read from the environment


search:
  default_mode: hybrid   # lexical | hybrid | deep
  bm25_top_k: 50         # Candidates from BM25 for fusion
  vector_top_k: 50       # Candidates from vector search for fusion
  rrf_k: 60              # Reciprocal Rank Fusion constant (default 60)
  chunk_size: 512        # Target chunk size in characters
  # prefer_extensions: [.md, .txt]   # Boost scores for these file types
  # extension_boost: 2.0             # Multiplier applied to preferred extensions (default 2.0)