[audio]
backend = "parec"                     # "parec" (PulseAudio by name) | "sounddevice"
device  = "VirtualMicSink.monitor"    # PulseAudio source name (parec) or device index/name (sounddevice)
sample_rate = 16000
channels    = 1
frame_ms    = 30                      # webrtcvad requires 10/20/30 ms
gain        = 1.0

[vad]
aggressiveness   = 2                  # webrtcvad 0-3
pre_roll_ms      = 400                # ring buffer kept BEFORE speech is confirmed
speech_start_ms  = 90                 # consecutive speech frames needed to confirm start
silence_ms       = 700                # trailing silence that ends a turn
min_utterance_ms = 300                # discard utterances with less actual speech than this
max_utterance_s  = 30.0               # hard cap: force-finalize a very long utterance
chunk_pause_ms   = 350                # once soft_max_s is reached, end a chunk at a pause this long
soft_max_s       = 10.0               # after this much speech, chunk-ends become eligible at pauses
rms_floor        = 0.008              # drop segments quieter than this RMS (kills noise-triggered blips)
trailing_trim_ms = 200                # keep only this much trailing silence (less hallucination-prone padding)

[whisper]
model        = "small"                # multilingual (DO NOT use .en suffix)
device       = "cpu"                  # "cpu" | "cuda"
compute_type = "int8"                 # "int8" cpu, "float16" cuda
language     = "auto"                 # "auto" | "en" | "es"
beam_size    = 1
vad_filter   = false
no_speech_prob_max = 0.6              # drop segments Whisper thinks are non-speech above this
avg_logprob_min    = -1.0             # drop segments with confidence below this

[output]
stdout    = true
jsonl_dir = "transcripts"             # one JSONL file per day: YYYY-MM-DD.jsonl
save_audio = false                    # write each transcribed utterance as a 16 kHz mono WAV
audio_dir  = "audio"                  # WAV destination (YYYY-MM-DD subfolders); used only if save_audio

[sink]
sink_name             = "VirtualMicSink"    # Name of the null sink to create
remap_source_name     = "VirtualMic"        # Name of the exposed microphone
loopback_latency_msec = 1                   # Loopback latency in ms
monitor_output        = false               # Loop sink.monitor to default sink (AVOID: causes acoustic feedback)

[daemon]
queue_size      = 50                  # max utterances waiting for transcription (oldest dropped when full)
backlog_warn_at = 5                   # warn when the queue backs up this far (worker falling behind)

[events]
socket       = ""                     # publish-only event socket (default $XDG_RUNTIME_DIR/stt-daemon.sock)
heartbeat_ms = 1000                   # heartbeat interval (progress-driven, from the capture loop)
ring_size    = 200                    # recent events replayed to a newly attached subscriber

[assistant]
control_socket        = ""            # control socket (default $XDG_RUNTIME_DIR/stt-assistant.sock)
stall_timeout_ms      = 3000          # no heartbeat for this long -> STT considered offline
worker_stall_ms       = 15000         # heartbeats arriving but a transcription runs this long -> degraded
command_arm_timeout_s = 10            # disarm a command if no turn is captured in this time
chat_idle_timeout_s   = 300           # leave chat mode after this much silence
turn_gap_s            = 1.5           # quiet gap that ends a turn
require_viewer        = true          # refuse to execute commands with no TUI attached
chat_exit_phrases     = ["end conversation", "that's all", "stop listening"]

[audit]
enabled = true                        # write executed actions to a daily JSONL file
dir     = "audit"                     # audit/YYYY-MM-DD.jsonl

[llm]
enabled              = true
endpoint             = "http://localhost:9931/v1/chat/completions"  # llama.cpp, OpenAI-compatible
temperature          = 0.7
max_tokens           = 1024           # reasoning models spend tokens before the answer; keep this generous
timeout_s            = 120
cache_prompt         = true           # reuse the KV prefix (append-only history keeps it warm)
max_prompt_tokens    = 64000          # ~half of the 131072 context
trim_block_turns     = 4              # drop history in blocks (not per-turn) to limit re-prefill
max_tool_iterations  = 3
system_prompt_chat   = "You are a concise voice assistant. Reply in 1-3 sentences."
system_prompt_command = "You translate a spoken request into a single tool call when one applies."