# Meeting Assistant configuration — copy to config.yaml and edit.
# (config.yaml is gitignored; it may hold machine-specific/private settings.)

audio:
  sample_rate: 16000
  chunk_duration: 2.0
  vad_threshold: 0.5
  # Transcription model (local dirs load fully offline — no Hugging Face access
  # at runtime). base.en is ~9x faster than medium.en on CPU (~0.3s vs ~2.9s per
  # clip) and is the main latency fix. Switch to models/whisper-medium.en for
  # more robustness to noise/accents (slower).
  whisper_model: models/whisper-base.en
  language: en
  # "push_to_talk" (hold the key, release to answer) or "continuous" (auto-listen).
  # Toggle at runtime with ctrl+shift+m.
  capture_mode: push_to_talk
  ptt_key: alt_r            # push-to-talk key (Right Option). e.g. cmd_r, f8, ctrl_r
  source: both              # "microphone", "system", or "both"
  mic_device: null          # null = auto. Or a device index / name substring.
  system_device: null       # null = auto-detect loopback. Or index / name.
  # Devices to try (in priority order) as the "system" source that hears OTHER
  # participants. A true loopback (BlackHole/Soundflower/VB-Cable) carries ALL
  # system audio — works for Google Meet, Zoom, Teams, anything. "teams audio"
  # is Microsoft Teams' own virtual device: zero-install but Teams-only, and it
  # may be silent outside screen-share; treat it as an experiment.
  loopback_keywords: ["blackhole", "soundflower", "vb-cable", "loopback", "teams audio"]
  # Which speakers trigger an answer (others still add transcript context).
  answer_sources: ["system", "microphone"]
  # Incremental transcription while the push-to-talk key is held. Off by default:
  # faster-whisper pads every call to a fixed 30s window, so on small/fast models
  # this barely helps and can drop words at chunk seams. Enable only with a
  # large/slow model where the per-call cost is worth amortizing during the hold.
  streaming_transcription: false
  # Bias Whisper toward your meeting's vocabulary (optional):
  # transcription_prompt: "A software engineering interview about Python and Flask."

screen:
  capture_key: ctrl+shift+space   # press, then drag a box over an on-screen question

hotkeys:
  toggle_overlay: ctrl+shift+h
  meeting_summary: ctrl+shift+s
  toggle_listening: ctrl+shift+m

ai:
  context_window: 2048
  max_history: 10
  model: Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf
  mmproj: mmproj-Qwen2.5-VL-7B-Instruct-f16.gguf   # required for screen reading
  answer_mode: auto_obvious   # auto_obvious | auto_all | suggest_only
  user_name: you
  # Pin the active context window by file name (contexts/<name>.yaml). If unset,
  # the first contexts/*.yaml with `active: true` is used.
  # active_context: python_flask_backend
  # Optional web search to ground factual answers in current information.
  # PRIVACY: when enabled, the question text is sent to DuckDuckGo — this
  # breaks the otherwise fully on-device guarantee. Off by default.
  web_search:
    enabled: false
    max_results: 3
    timeout: 6.0

overlay:
  position: top-right
  font_size: 14