Initial commit: Javis project

config.example.yaml

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+# Javis configuration. Copy to config.yaml and edit.
+
+gui:
+  theme: "dark"             # dark | light  (Tools → "Toggle light/dark theme")
+  show_startup_dialog: true # show the configuration dialog before the main window
+  minimize_to_tray: true    # closing the window hides to the tray; quit via File → Quit
+  global_ptt_hotkey: "ctrl+alt+space"  # system-wide push-to-talk (Windows); "" = off
+
+llm:
+  base_url: "http://localhost:11434"
+  model: "gemma3:4b"
+  temperature: 0.7
+  request_timeout_seconds: 120
+  # Keep the model loaded in Ollama for 1 h after each request (default is
+  # only 5 min, so gaps > 5 min force a full model reload next turn).
+  # "infinity" keeps it loaded forever.
+  keep_alive: 3600
+
+stt:
+  model_size: "large-v3"     # tiny, base, small, medium, large-v3, distil-large-v3
+  device: "auto"             # auto, cuda, cpu
+  compute_type: "float16"    # float16, int8_float16, int8, float32
+  language: null             # null = auto-detect
+
+tts:
+  backend: "piper"           # piper (Piper VITS — CPU ONNX, default) | f5 (F5-TTS voice cloning)
+  device: "auto"
+  default_voice: "default"   # Piper voice name (see the Voices tab / voice-ref-curator)
+
+# Overnight voice training — the default voice is retrained once per night
+# inside the start_hour → end_hour window, resuming from the latest checkpoint.
+# Toggle/disable here (or in Settings → Voice Training); changes apply live.
+training:
+  enabled: true
+  start_hour: 3              # window opens at 03:00 (0-23)
+  end_hour: 6                # window closes at 06:00 (0-23)
+  min_remaining_minutes: 60  # don't start a run if less window time remains
+  max_epochs: 6000
+  batch_size: 32
+  num_workers: 2
+  accelerator: "gpu"         # gpu | cpu
+  precision: "16-mixed"      # 32 | 16-mixed | bf16-mixed
+  language: "de"             # Piper language code
+
+audio:
+  sample_rate: 16000
+  input_device: null         # null = system default; or int device index
+  output_device: null
+  thinking_cue_delay_s: 2.5  # soft tick while Javis is still working; 0 = off
+
+wake_word:
+  enabled: true
+  model: "hey_jarvis"        # built-in openWakeWord name, or a custom model: "rufus" -> ~/.javis/models/wakeword/rufus.onnx (see docs/WAKE_WORD.md)
+  threshold: 0.5
+  vad_threshold: 0.5         # silero-vad probability threshold
+  silence_ms: 800            # end-of-utterance silence
+
+mcp:
+  servers_config: "mcp_servers.json"
+  approval_default: "ask"    # ask | allow | deny  (headless: "ask" is denied — no UI)
+  call_timeout_seconds: 30
+  approval_timeout_seconds: 45  # auto-deny if the approval dialog isn't answered; 0 = wait
+  voice_approval: true       # answer the approval prompt with "ja"/"nein" (needs STT + mic)
+
+api:
+  # HTTP API for javis-slave companion devices (plain HTTP — trusted LAN only).
+  enabled: false
+  host: "0.0.0.0"            # bind address; 0.0.0.0 = all interfaces
+  port: 8765
+  pairing_code_ttl_seconds: 300   # lifetime of a single-use pairing code
+
+agent:
+  # Persona preset. Choose one: default | smart_home | concise | verbose
+  preset: "default"
+  # Optional verbatim system prompt (overrides the preset above).
+  system_prompt_inline: null
+  # Optional path to a .txt file (highest priority — overrides everything else).
+  system_prompt_file: null
+  history_max_turns: 20
+  # Maximum LLM <-> tool-call iterations per turn before giving up.
+  max_llm_iterations: 5
+  # Spoken feedback for voice users (empty string = silent).
+  error_phrase: "Entschuldigung, da ist etwas schiefgelaufen. Bitte versuch es noch einmal."
+  approval_phrase: "Soll ich das ausführen? Sag ja oder nein."
+
+memory:
+  # "ollama" uses llm.base_url; "hermes" uses the remote Hermes API server.
+  provider: "ollama"
+  # Hermes API root (not the dashboard URL). Required when provider is hermes.
+  base_url: null
+  # Store API_SERVER_KEY in this environment variable; never put it in YAML.
+  api_key_env: "JAVIS_HERMES_API_KEY"
+  # Dedicated model for background fact extraction.
+  # null = use the same model as llm.model.
+  # Set to a smarter or reasoning model for higher-quality extraction without
+  # slowing down the main conversation (extraction runs in the background).
+  # Examples: "qwen2.5:14b", "qwen3:8b", "deepseek-r1:8b", "llama3.1:8b"
+  model: null
+  # Temperature for extraction calls. Low values (0.0–0.2) give more consistent
+  # JSON output. Reasoning models work well at 0.1.
+  temperature: 0.1
+  # Context window for extraction. Much smaller than the main LLM is fine —
+  # extraction prompts are short. Reduce if memory calls are slow.
+  num_ctx: 4096
+  # Timeout (seconds) for extraction calls. 120 is a safe default.
+  # Increase for reasoning models on slow hardware (deepseek-r1 can take 3–5 min on CPU).
+  # Set to null only to inherit llm.request_timeout_seconds (not recommended).
+  timeout_seconds: 120
+  # Maximum number of new facts to extract per turn.
+  max_facts: 2
+  # Maximum number of existing memories included in the extraction prompt
+  # (most-recently-updated first). Raise for larger memories, lower to keep
+  # extraction prompts short.
+  max_existing_for_prompt: 25
+
+paths:
+  base_dir: null             # null = ~/.javis