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Voice-powered research assistant for physical books and papers

Project description

Klaus

Klaus is a desktop voice assistant built for reading physical papers and books. You place a page under a document camera (or phone on a tripod), ask a question out loud, and Klaus answers in natural speech while keeping the page context and conversation visible in the UI.

The experience is tuned for fast study loops: read, ask, clarify, and continue without switching between typing and separate search tools.

Klaus also searches the web when necessary to answer your query, and has the ability to write notes directly to your obsidian vault when asked.

Under the hood, WebRTC voice activation detection or push to talk feeds Moonshine Medium (local speech to text model), then a hybrid router (local heuristics with claude-haiku-4-5 fallback) decides whether to include camera image, history, memory, and notes context.

Main reasoning loop runs on claude-sonnet-4-6. Tools include Tavily for search and optional Obsidian note actions. Output is streamed sentence by sentence to OpenAI gpt-4o-mini-tts. End to end latency is around 2-4 seconds.

Platforms: Windows and macOS

Quick Setup

Windows:

pip install pipx && pipx ensurepath

Restart your terminal, then:

pipx install klaus-assistant
klaus

macOS:

brew tap bgigurtsis/klaus
brew install klaus
klaus

macOS input monitoring: When launching Klaus from a terminal, macOS may prompt you to grant that terminal app Accessibility (input monitoring) permission. This is required for global hotkeys — specifically, the push-to-talk and voice-activation toggle keys — to work while Klaus is not in focus. If you'd prefer not to grant this permission, simply deny the prompt; you can still switch input modes using the buttons in the Klaus UI.

macOS + Python 3.14: pynput global hotkeys can crash on macOS 26. Klaus now disables global hotkeys on this combo and keeps in-app hotkeys active; use Python 3.13 for stable global hotkeys.

On first launch, a setup wizard walks you through API keys, camera, mic, and voice model setup.

Updating

Windows: pipx upgrade klaus-assistant

macOS: brew upgrade klaus

Camera Setup

Required: A camera is required for Klaus to ingest what you're currently reading and to use it as context.

A USB document camera (AKA visualiser) is reccomended. Alternatively, a phone on a gooseneck mount (~$10-15) pointed straight down at your reading surface works. Either should gives Klaus a clear, stable view of the full page.

Some reccomended apps to connect your phone to your computer are listed below:

Setup App
macOS + iPhone Built-in -- Continuity Camera (iOS 16+, macOS Ventura+, no install needed)
macOS + Android Camo (free, 1080p) -- install on phone + Mac, pair via QR or USB
Windows + Android DroidCam (free) -- install on phone + PC, connect over Wi-Fi or USB
Windows + iPhone Camo (free, 1080p) -- install on phone + PC, pair via QR or USB

Klaus auto-detects portrait orientation and rotates the image. Override with camera_rotation in ~/.klaus/config.toml if needed.

Other install options

Prerequisites: Python 3.11-3.13, camera, mic, speakers. On Windows, install Visual C++ Build Tools (Desktop development with C++) so webrtcvad can compile. On macOS without Homebrew: brew install python@3.13 portaudio.

From source (development):

git clone https://github.com/bgigurtsis/Klaus.git
cd Klaus
pip install -e .
klaus

API keys: The setup wizard asks for them on first launch, or add to ~/.klaus/config.toml under [api_keys]: Anthropic, OpenAI, Tavily (free tier: 1,000 searches/mo). Optional: OBSIDIAN_VAULT_PATH in .env for Obsidian notes.

Latency & Cost

End-to-end latency from question to first spoken word is 2-3 seconds (STT + Claude + first TTS chunk). TTS streams sentence-by-sentence so playback starts before the full response is generated.

Usage Approx. cost
10 questions ~$0.05
50 questions ~$0.25
100 questions/day ~$2.50-3.50/day

Largest cost driver is Claude (vision + context window). STT is free (local). TTS is $0.015/min of generated audio.

Usage

Klaus captures the page image when your question ends and sends it with your transcript to Claude. If Claude is uncertain about a claim, it searches the web via Tavily before answering.

Configuration

Settings live in ~/.klaus/config.toml (created on first run). Edit any line to override defaults:

Setting Default Notes
hotkey F2 Push-to-talk key, works without app focus
toggle_key § (macOS) / F3 (Windows) Toggle between voice_activation and push_to_talk
input_mode voice_activation Or push_to_talk
voice cedar Options: coral, nova, alloy, ash, ballad, echo, fable, onyx, sage, shimmer, verse, cedar, marin
tts_speed 1.0 0.25 to 4.0
camera_index 0 Change if you have multiple cameras
mic_index -1 -1 uses system default microphone
camera_rotation auto auto, none, 90, 180, 270
camera_width / camera_height 1920 / 1080 Camera resolution
vad_sensitivity 3 0-3, higher = more aggressive noise filtering
vad_silence_timeout 1.5 Seconds of silence before voice activation finalizes
stt_moonshine_model medium Options: tiny, small, medium
stt_moonshine_language en Moonshine language code
log_level INFO DEBUG, INFO, WARNING, ERROR

Architecture

Mic --> WebRTC VAD --> Moonshine Medium (local STT) --\
                                                       --> Claude (vision + tools) --> TTS --> Speakers
Camera (live feed) -----------------------------------/        |
                                                               +--> Tavily (web search)
                                                               +--> Obsidian (notes)
                                                               +--> SQLite (memory)
                                                               +--> Chat UI

Speech-to-text runs entirely locally via Moonshine Medium (245M params, ~300ms latency, no API cost). Voice activation uses WebRTC VAD with multi-stage filtering (voiced ratio, RMS loudness, contiguous voiced runs) to reject background noise before audio reaches STT.

Module Layout

Module Role
config.py Config, API keys, system prompt, voice settings
camera.py OpenCV background thread, frame capture, auto-rotation
audio.py Push-to-talk recorder (sounddevice), VAD recorder, WAV buffer
stt.py Moonshine Voice local speech-to-text
tts.py OpenAI gpt-4o-mini-tts with sentence-level streaming
brain.py Claude vision + tool use, conversation history, tool-use loop
search.py Tavily web search, exposed as a Claude tool
notes.py Obsidian vault note-taking, exposed as Claude tools
memory.py SQLite persistence (sessions, exchanges, knowledge profile)
ui/ PyQt6 GUI (main window, camera, chat, sessions, status, theme, setup wizard, settings)
main.py Wires everything together, hotkey listener, Qt signal bridge

Data

  • Config: ~/.klaus/config.toml
  • Database: ~/.klaus/klaus.db (sessions, exchanges, knowledge profile)
  • No images stored, only a short hash of each page capture
  • Delete the database to start fresh

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