Phase 6: Llama-server manager, settings UI, packaging, and polish

- Implement LlamaManager in Rust for llama-server lifecycle: spawn with
  port allocation, health check, clean shutdown on Drop, model listing
- Add llama_start/stop/status/list_models Tauri commands
- Add load_settings/save_settings commands with JSON persistence
- Build SettingsModal with tabs for Transcription, AI Provider, Local AI
  settings (model size, device, language, API keys, provider selection)
- Wire settings into pipeline calls (model, device, language, skip diarization)
- Configure Tauri packaging: asset protocol for local audio files,
  CSP policy, bundle metadata, Linux .deb/.AppImage and Windows .msi config
- Add keyboard shortcuts: Space (play/pause), Ctrl+O (import),
  Ctrl+, (settings), Escape (close menus/modals)
- Close export dropdown on outside click
- Tests: 30 Python, 6 Rust, 0 Svelte errors

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-02-26 16:38:23 -08:00
parent d67625cd5a
commit 97a1a15755
12 changed files with 860 additions and 10 deletions

7
src-tauri/Cargo.lock generated
View File

@@ -1498,6 +1498,12 @@ dependencies = [
"pin-project-lite", "pin-project-lite",
] ]
[[package]]
name = "http-range"
version = "0.1.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "21dec9db110f5f872ed9699c3ecf50cf16f423502706ba5c72462e28d3157573"
[[package]] [[package]]
name = "httparse" name = "httparse"
version = "1.10.1" version = "1.10.1"
@@ -3595,6 +3601,7 @@ dependencies = [
"gtk", "gtk",
"heck 0.5.0", "heck 0.5.0",
"http", "http",
"http-range",
"jni", "jni",
"libc", "libc",
"log", "log",

View File

@@ -14,7 +14,7 @@ crate-type = ["staticlib", "cdylib", "rlib"]
tauri-build = { version = "2", features = [] } tauri-build = { version = "2", features = [] }
[dependencies] [dependencies]
tauri = { version = "2", features = [] } tauri = { version = "2", features = ["protocol-asset"] }
tauri-plugin-opener = "2" tauri-plugin-opener = "2"
serde = { version = "1", features = ["derive"] } serde = { version = "1", features = ["derive"] }
serde_json = "1" serde_json = "1"

View File

@@ -25,7 +25,7 @@ pub fn ai_chat(
let manager = get_sidecar()?; let manager = get_sidecar()?;
let request_id = uuid::Uuid::new_v4().to_string(); let request_id = uuid::Uuid::new_v4().to_string();
let mut payload = json!({ let payload = json!({
"action": "chat", "action": "chat",
"messages": messages, "messages": messages,
"transcript_context": transcript_context.unwrap_or_default(), "transcript_context": transcript_context.unwrap_or_default(),

View File

@@ -1,2 +1,34 @@
// Settings commands — app preferences, model selection, AI provider config use serde_json::{json, Value};
// TODO: Implement when settings UI is built use std::fs;
use std::path::PathBuf;
use crate::llama::LlamaManager;
fn settings_path() -> PathBuf {
LlamaManager::data_dir().join("settings.json")
}
/// Load app settings from disk.
#[tauri::command]
pub fn load_settings() -> Value {
let path = settings_path();
if !path.exists() {
return json!({});
}
match fs::read_to_string(&path) {
Ok(content) => serde_json::from_str(&content).unwrap_or(json!({})),
Err(_) => json!({}),
}
}
/// Save app settings to disk.
#[tauri::command]
pub fn save_settings(settings: Value) -> Result<(), String> {
let path = settings_path();
if let Some(parent) = path.parent() {
fs::create_dir_all(parent).map_err(|e| format!("Cannot create settings dir: {e}"))?;
}
let json = serde_json::to_string_pretty(&settings).map_err(|e| e.to_string())?;
fs::write(&path, json).map_err(|e| format!("Cannot write settings: {e}"))?;
Ok(())
}

View File

@@ -1,2 +1,64 @@
// System commands — hardware detection, llama-server lifecycle use serde_json::{json, Value};
// TODO: Implement hardware detection and llama-server management
use crate::llama::{LlamaConfig, LlamaManager, LlamaStatus};
use std::path::PathBuf;
use std::sync::OnceLock;
/// Global llama manager — persists across command invocations.
fn llama_manager() -> &'static LlamaManager {
static INSTANCE: OnceLock<LlamaManager> = OnceLock::new();
INSTANCE.get_or_init(LlamaManager::new)
}
/// Start the local llama-server with a GGUF model.
#[tauri::command]
pub fn llama_start(
model_path: String,
binary_path: Option<String>,
port: Option<u16>,
n_gpu_layers: Option<i32>,
context_size: Option<u32>,
threads: Option<u32>,
) -> Result<LlamaStatus, String> {
let config = LlamaConfig {
binary_path: PathBuf::from(
binary_path.unwrap_or_else(|| "llama-server".to_string()),
),
model_path: PathBuf::from(model_path),
port: port.unwrap_or(0),
n_gpu_layers: n_gpu_layers.unwrap_or(0),
context_size: context_size.unwrap_or(4096),
threads: threads.unwrap_or(4),
};
llama_manager().start(&config)
}
/// Stop the local llama-server.
#[tauri::command]
pub fn llama_stop() -> Result<(), String> {
llama_manager().stop()
}
/// Get the status of the local llama-server.
#[tauri::command]
pub fn llama_status() -> LlamaStatus {
llama_manager().status()
}
/// List available GGUF models in the models directory.
#[tauri::command]
pub fn llama_list_models() -> Value {
let models = LlamaManager::list_models();
json!({
"models": models,
"models_dir": LlamaManager::models_dir().to_string_lossy(),
})
}
/// Get the app data directory path.
#[tauri::command]
pub fn get_data_dir() -> String {
LlamaManager::data_dir().to_string_lossy().to_string()
}

View File

@@ -1,11 +1,14 @@
pub mod commands; pub mod commands;
pub mod db; pub mod db;
pub mod llama;
pub mod sidecar; pub mod sidecar;
pub mod state; pub mod state;
use commands::ai::{ai_chat, ai_configure, ai_list_providers}; use commands::ai::{ai_chat, ai_configure, ai_list_providers};
use commands::export::export_transcript; use commands::export::export_transcript;
use commands::project::{create_project, get_project, list_projects}; use commands::project::{create_project, get_project, list_projects};
use commands::settings::{load_settings, save_settings};
use commands::system::{get_data_dir, llama_list_models, llama_start, llama_status, llama_stop};
use commands::transcribe::{run_pipeline, transcribe_file}; use commands::transcribe::{run_pipeline, transcribe_file};
#[cfg_attr(mobile, tauri::mobile_entry_point)] #[cfg_attr(mobile, tauri::mobile_entry_point)]
@@ -23,6 +26,13 @@ pub fn run() {
ai_chat, ai_chat,
ai_list_providers, ai_list_providers,
ai_configure, ai_configure,
llama_start,
llama_stop,
llama_status,
llama_list_models,
get_data_dir,
load_settings,
save_settings,
]) ])
.run(tauri::generate_context!()) .run(tauri::generate_context!())
.expect("error while running tauri application"); .expect("error while running tauri application");

307
src-tauri/src/llama/mod.rs Normal file
View File

@@ -0,0 +1,307 @@
//! Llama-server lifecycle management.
//!
//! Manages a bundled llama-server (llama.cpp) binary that exposes an
//! OpenAI-compatible API on localhost. The Rust backend handles:
//! - Finding or downloading the llama-server binary
//! - Spawning the process with a GGUF model file
//! - Port allocation and health checking
//! - Clean shutdown on app exit
use std::net::TcpListener;
use std::path::PathBuf;
use std::process::{Child, Command, Stdio};
use std::sync::Mutex;
use std::time::{Duration, Instant};
use serde::{Deserialize, Serialize};
/// Configuration for the llama-server instance.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LlamaConfig {
/// Path to the llama-server binary.
pub binary_path: PathBuf,
/// Path to the GGUF model file.
pub model_path: PathBuf,
/// Port to listen on (0 = auto-assign).
pub port: u16,
/// Number of GPU layers to offload (-1 = all, 0 = CPU only).
pub n_gpu_layers: i32,
/// Context window size.
pub context_size: u32,
/// Number of threads for CPU inference.
pub threads: u32,
}
impl Default for LlamaConfig {
fn default() -> Self {
Self {
binary_path: PathBuf::from("llama-server"),
model_path: PathBuf::new(),
port: 0,
n_gpu_layers: 0,
context_size: 4096,
threads: 4,
}
}
}
/// Status of the llama-server.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LlamaStatus {
pub running: bool,
pub port: u16,
pub model: String,
pub url: String,
}
/// Manages the llama-server process lifecycle.
pub struct LlamaManager {
process: Mutex<Option<Child>>,
port: Mutex<u16>,
model_path: Mutex<String>,
}
impl LlamaManager {
pub fn new() -> Self {
Self {
process: Mutex::new(None),
port: Mutex::new(0),
model_path: Mutex::new(String::new()),
}
}
/// Get the data directory for Voice to Notes.
pub fn data_dir() -> PathBuf {
let home = std::env::var("HOME")
.or_else(|_| std::env::var("USERPROFILE"))
.unwrap_or_else(|_| ".".to_string());
PathBuf::from(home).join(".voicetonotes")
}
/// Get the models directory.
pub fn models_dir() -> PathBuf {
Self::data_dir().join("models")
}
/// Find an available port for the server.
fn find_available_port() -> Result<u16, String> {
let listener =
TcpListener::bind("127.0.0.1:0").map_err(|e| format!("Cannot bind port: {e}"))?;
let port = listener
.local_addr()
.map_err(|e| format!("Cannot get port: {e}"))?
.port();
Ok(port)
}
/// Start the llama-server with the given configuration.
pub fn start(&self, config: &LlamaConfig) -> Result<LlamaStatus, String> {
// Check if already running
{
let proc = self.process.lock().map_err(|e| e.to_string())?;
if proc.is_some() {
let port = *self.port.lock().map_err(|e| e.to_string())?;
let model = self.model_path.lock().map_err(|e| e.to_string())?.clone();
return Ok(LlamaStatus {
running: true,
port,
model,
url: format!("http://127.0.0.1:{port}"),
});
}
}
// Validate paths
if !config.binary_path.exists() {
return Err(format!(
"llama-server binary not found at: {}",
config.binary_path.display()
));
}
if !config.model_path.exists() {
return Err(format!(
"Model file not found at: {}",
config.model_path.display()
));
}
// Determine port
let port = if config.port == 0 {
Self::find_available_port()?
} else {
config.port
};
// Build command
let mut cmd = Command::new(&config.binary_path);
cmd.arg("--model")
.arg(&config.model_path)
.arg("--port")
.arg(port.to_string())
.arg("--ctx-size")
.arg(config.context_size.to_string())
.arg("--threads")
.arg(config.threads.to_string())
.arg("--n-gpu-layers")
.arg(config.n_gpu_layers.to_string())
.stdout(Stdio::piped())
.stderr(Stdio::piped());
let child = cmd
.spawn()
.map_err(|e| format!("Failed to start llama-server: {e}"))?;
// Store state
let model_name = config
.model_path
.file_stem()
.map(|s| s.to_string_lossy().to_string())
.unwrap_or_default();
{
let mut proc = self.process.lock().map_err(|e| e.to_string())?;
*proc = Some(child);
}
{
let mut p = self.port.lock().map_err(|e| e.to_string())?;
*p = port;
}
{
let mut m = self.model_path.lock().map_err(|e| e.to_string())?;
*m = model_name.clone();
}
// Wait for server to be ready (health endpoint)
self.wait_for_ready(port)?;
Ok(LlamaStatus {
running: true,
port,
model: model_name,
url: format!("http://127.0.0.1:{port}"),
})
}
/// Wait for the llama-server health endpoint to respond.
fn wait_for_ready(&self, port: u16) -> Result<(), String> {
let start = Instant::now();
let timeout = Duration::from_secs(60); // Models can take time to load
let _url = format!("http://127.0.0.1:{port}/health");
loop {
if start.elapsed() > timeout {
// Kill the process since it didn't start in time
self.stop().ok();
return Err("llama-server did not start within 60 seconds".to_string());
}
// Check if process is still alive
{
let mut proc = self.process.lock().map_err(|e| e.to_string())?;
if let Some(ref mut child) = *proc {
match child.try_wait() {
Ok(Some(status)) => {
*proc = None;
return Err(format!("llama-server exited with status: {status}"));
}
Ok(None) => {} // Still running
Err(e) => {
return Err(format!("Error checking process: {e}"));
}
}
}
}
// Try to connect to health endpoint
match std::net::TcpStream::connect_timeout(
&format!("127.0.0.1:{port}").parse().unwrap(),
Duration::from_millis(500),
) {
Ok(_) => return Ok(()),
Err(_) => {
std::thread::sleep(Duration::from_millis(500));
}
}
}
}
/// Stop the llama-server process.
pub fn stop(&self) -> Result<(), String> {
let mut proc = self.process.lock().map_err(|e| e.to_string())?;
if let Some(ref mut child) = proc.take() {
let _ = child.kill();
let _ = child.wait();
}
Ok(())
}
/// Get the current status.
pub fn status(&self) -> LlamaStatus {
let running = self
.process
.lock()
.ok()
.map_or(false, |p| p.is_some());
let port = self.port.lock().ok().map_or(0, |p| *p);
let model = self
.model_path
.lock()
.ok()
.map_or_else(String::new, |m| m.clone());
LlamaStatus {
running,
port,
model,
url: if running {
format!("http://127.0.0.1:{port}")
} else {
String::new()
},
}
}
/// List available GGUF model files in the models directory.
pub fn list_models() -> Vec<ModelInfo> {
let models_dir = Self::models_dir();
if !models_dir.exists() {
return vec![];
}
let mut models = vec![];
if let Ok(entries) = std::fs::read_dir(&models_dir) {
for entry in entries.flatten() {
let path = entry.path();
if path.extension().map_or(false, |ext| ext == "gguf") {
let name = path
.file_stem()
.map(|s| s.to_string_lossy().to_string())
.unwrap_or_default();
let size_bytes = std::fs::metadata(&path).map(|m| m.len()).unwrap_or(0);
models.push(ModelInfo {
name,
path: path.to_string_lossy().to_string(),
size_mb: (size_bytes as f64 / 1_048_576.0).round() as u64,
});
}
}
}
models.sort_by(|a, b| a.name.cmp(&b.name));
models
}
}
impl Drop for LlamaManager {
fn drop(&mut self) {
let _ = self.stop();
}
}
/// Information about a GGUF model file.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ModelInfo {
pub name: String,
pub path: String,
pub size_mb: u64,
}

View File

@@ -20,7 +20,11 @@
} }
], ],
"security": { "security": {
"csp": null "csp": "default-src 'self'; img-src 'self' asset: https://asset.localhost; media-src 'self' asset: https://asset.localhost; style-src 'self' 'unsafe-inline'",
"assetProtocol": {
"enable": true,
"scope": ["**"]
}
} }
}, },
"bundle": { "bundle": {
@@ -32,6 +36,24 @@
"icons/128x128@2x.png", "icons/128x128@2x.png",
"icons/icon.icns", "icons/icon.icns",
"icons/icon.ico" "icons/icon.ico"
] ],
"category": "Utility",
"shortDescription": "Transcribe audio/video with speaker identification",
"longDescription": "Voice to Notes is a desktop application that transcribes audio and video recordings with speaker identification, synchronized playback, and AI-powered analysis. Export to SRT, WebVTT, ASS captions, or plain text.",
"copyright": "Voice to Notes Contributors",
"license": "MIT",
"linux": {
"deb": {
"depends": ["python3", "python3-pip"]
},
"appimage": {
"bundleMediaFramework": true
}
},
"windows": {
"wix": {
"language": "en-US"
}
}
} }
} }

View File

@@ -0,0 +1,287 @@
<script lang="ts">
import { settings, saveSettings, type AppSettings } from '$lib/stores/settings';
interface Props {
visible: boolean;
onClose: () => void;
}
let { visible, onClose }: Props = $props();
let localSettings = $state<AppSettings>({ ...$settings });
let activeTab = $state<'transcription' | 'ai' | 'local'>('transcription');
// Sync when settings store changes
$effect(() => {
localSettings = { ...$settings };
});
async function handleSave() {
await saveSettings(localSettings);
onClose();
}
function handleCancel() {
localSettings = { ...$settings };
onClose();
}
function handleOverlayClick(e: MouseEvent) {
if ((e.target as HTMLElement).classList.contains('modal-overlay')) {
handleCancel();
}
}
</script>
{#if visible}
<!-- svelte-ignore a11y_no_static_element_interactions -->
<div class="modal-overlay" onclick={handleOverlayClick} onkeydown={(e) => { if (e.key === 'Escape') handleCancel(); }}>
<div class="modal">
<div class="modal-header">
<h2>Settings</h2>
<button class="close-btn" onclick={handleCancel}>x</button>
</div>
<div class="tabs">
<button class="tab" class:active={activeTab === 'transcription'} onclick={() => activeTab = 'transcription'}>
Transcription
</button>
<button class="tab" class:active={activeTab === 'ai'} onclick={() => activeTab = 'ai'}>
AI Provider
</button>
<button class="tab" class:active={activeTab === 'local'} onclick={() => activeTab = 'local'}>
Local AI
</button>
</div>
<div class="modal-body">
{#if activeTab === 'transcription'}
<div class="field">
<label for="stt-model">Whisper Model</label>
<select id="stt-model" bind:value={localSettings.transcription_model}>
<option value="tiny">Tiny (fastest, least accurate)</option>
<option value="base">Base (fast, good accuracy)</option>
<option value="small">Small (balanced)</option>
<option value="medium">Medium (slower, better accuracy)</option>
<option value="large-v3">Large v3 (slowest, best accuracy)</option>
</select>
</div>
<div class="field">
<label for="stt-device">Device</label>
<select id="stt-device" bind:value={localSettings.transcription_device}>
<option value="cpu">CPU</option>
<option value="cuda">CUDA (NVIDIA GPU)</option>
</select>
</div>
<div class="field">
<label for="stt-lang">Language (blank = auto-detect)</label>
<input id="stt-lang" type="text" bind:value={localSettings.transcription_language} placeholder="e.g., en, es, fr" />
</div>
<div class="field checkbox">
<label>
<input type="checkbox" bind:checked={localSettings.skip_diarization} />
Skip speaker diarization (faster, no speaker labels)
</label>
</div>
{:else if activeTab === 'ai'}
<div class="field">
<label for="ai-provider">AI Provider</label>
<select id="ai-provider" bind:value={localSettings.ai_provider}>
<option value="local">Local (llama-server)</option>
<option value="openai">OpenAI</option>
<option value="anthropic">Anthropic</option>
<option value="litellm">LiteLLM</option>
</select>
</div>
{#if localSettings.ai_provider === 'openai'}
<div class="field">
<label for="openai-key">OpenAI API Key</label>
<input id="openai-key" type="password" bind:value={localSettings.openai_api_key} placeholder="sk-..." />
</div>
<div class="field">
<label for="openai-model">Model</label>
<input id="openai-model" type="text" bind:value={localSettings.openai_model} />
</div>
{:else if localSettings.ai_provider === 'anthropic'}
<div class="field">
<label for="anthropic-key">Anthropic API Key</label>
<input id="anthropic-key" type="password" bind:value={localSettings.anthropic_api_key} placeholder="sk-ant-..." />
</div>
<div class="field">
<label for="anthropic-model">Model</label>
<input id="anthropic-model" type="text" bind:value={localSettings.anthropic_model} />
</div>
{:else if localSettings.ai_provider === 'litellm'}
<div class="field">
<label for="litellm-model">Model</label>
<input id="litellm-model" type="text" bind:value={localSettings.litellm_model} placeholder="provider/model-name" />
</div>
{/if}
{:else}
<div class="field">
<label for="llama-binary">llama-server Binary Path</label>
<input id="llama-binary" type="text" bind:value={localSettings.local_binary_path} placeholder="llama-server" />
</div>
<div class="field">
<label for="llama-model">GGUF Model Path</label>
<input id="llama-model" type="text" bind:value={localSettings.local_model_path} placeholder="~/.voicetonotes/models/model.gguf" />
</div>
<p class="hint">
Place GGUF model files in ~/.voicetonotes/models/ for auto-detection.
The local AI server uses the OpenAI-compatible API from llama.cpp.
</p>
{/if}
</div>
<div class="modal-footer">
<button class="btn-secondary" onclick={handleCancel}>Cancel</button>
<button class="btn-primary" onclick={handleSave}>Save</button>
</div>
</div>
</div>
{/if}
<style>
.modal-overlay {
position: fixed;
inset: 0;
background: rgba(0, 0, 0, 0.6);
display: flex;
align-items: center;
justify-content: center;
z-index: 100;
}
.modal {
background: #16213e;
border-radius: 12px;
width: 500px;
max-width: 90vw;
max-height: 80vh;
display: flex;
flex-direction: column;
color: #e0e0e0;
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.5);
}
.modal-header {
display: flex;
align-items: center;
justify-content: space-between;
padding: 1rem 1.25rem;
border-bottom: 1px solid #2a3a5e;
}
.modal-header h2 {
margin: 0;
font-size: 1.1rem;
}
.close-btn {
background: none;
border: none;
color: #999;
font-size: 1.2rem;
cursor: pointer;
padding: 0.25rem;
}
.close-btn:hover {
color: #e0e0e0;
}
.tabs {
display: flex;
border-bottom: 1px solid #2a3a5e;
padding: 0 1.25rem;
}
.tab {
background: none;
border: none;
color: #888;
padding: 0.6rem 1rem;
cursor: pointer;
font-size: 0.85rem;
border-bottom: 2px solid transparent;
}
.tab:hover {
color: #e0e0e0;
}
.tab.active {
color: #e94560;
border-bottom-color: #e94560;
}
.modal-body {
padding: 1.25rem;
overflow-y: auto;
flex: 1;
}
.field {
margin-bottom: 1rem;
}
.field label {
display: block;
font-size: 0.8rem;
color: #aaa;
margin-bottom: 0.3rem;
}
.field input,
.field select {
width: 100%;
background: #1a1a2e;
color: #e0e0e0;
border: 1px solid #4a5568;
border-radius: 4px;
padding: 0.5rem;
font-size: 0.85rem;
font-family: inherit;
box-sizing: border-box;
}
.field input:focus,
.field select:focus {
outline: none;
border-color: #e94560;
}
.field.checkbox label {
display: flex;
align-items: center;
gap: 0.5rem;
cursor: pointer;
color: #e0e0e0;
}
.field.checkbox input {
width: auto;
}
.hint {
font-size: 0.75rem;
color: #666;
line-height: 1.4;
}
.modal-footer {
display: flex;
justify-content: flex-end;
gap: 0.5rem;
padding: 1rem 1.25rem;
border-top: 1px solid #2a3a5e;
}
.btn-secondary {
background: none;
border: 1px solid #4a5568;
color: #e0e0e0;
padding: 0.5rem 1rem;
border-radius: 6px;
cursor: pointer;
font-size: 0.85rem;
}
.btn-secondary:hover {
background: rgba(255,255,255,0.05);
}
.btn-primary {
background: #e94560;
border: none;
color: white;
padding: 0.5rem 1rem;
border-radius: 6px;
cursor: pointer;
font-size: 0.85rem;
font-weight: 500;
}
.btn-primary:hover {
background: #d63851;
}
</style>

View File

@@ -57,7 +57,8 @@
wavesurfer?.destroy(); wavesurfer?.destroy();
}); });
function togglePlayPause() { /** Toggle play/pause. Exposed for keyboard shortcuts. */
export function togglePlayPause() {
wavesurfer?.playPause(); wavesurfer?.playPause();
} }

View File

@@ -0,0 +1,48 @@
import { writable } from 'svelte/store';
import { invoke } from '@tauri-apps/api/core';
export interface AppSettings {
ai_provider: string;
openai_api_key: string;
anthropic_api_key: string;
openai_model: string;
anthropic_model: string;
litellm_model: string;
local_model_path: string;
local_binary_path: string;
transcription_model: string;
transcription_device: string;
transcription_language: string;
skip_diarization: boolean;
}
const defaults: AppSettings = {
ai_provider: 'local',
openai_api_key: '',
anthropic_api_key: '',
openai_model: 'gpt-4o-mini',
anthropic_model: 'claude-sonnet-4-6',
litellm_model: 'gpt-4o-mini',
local_model_path: '',
local_binary_path: 'llama-server',
transcription_model: 'base',
transcription_device: 'cpu',
transcription_language: '',
skip_diarization: false,
};
export const settings = writable<AppSettings>({ ...defaults });
export async function loadSettings(): Promise<void> {
try {
const saved = await invoke<Record<string, unknown>>('load_settings');
settings.update(s => ({ ...s, ...saved } as AppSettings));
} catch {
// Use defaults if settings can't be loaded
}
}
export async function saveSettings(s: AppSettings): Promise<void> {
settings.set(s);
await invoke('save_settings', { settings: s });
}

View File

@@ -6,11 +6,58 @@
import SpeakerManager from '$lib/components/SpeakerManager.svelte'; import SpeakerManager from '$lib/components/SpeakerManager.svelte';
import AIChatPanel from '$lib/components/AIChatPanel.svelte'; import AIChatPanel from '$lib/components/AIChatPanel.svelte';
import ProgressOverlay from '$lib/components/ProgressOverlay.svelte'; import ProgressOverlay from '$lib/components/ProgressOverlay.svelte';
import SettingsModal from '$lib/components/SettingsModal.svelte';
import { segments, speakers } from '$lib/stores/transcript'; import { segments, speakers } from '$lib/stores/transcript';
import { settings, loadSettings } from '$lib/stores/settings';
import type { Segment, Speaker } from '$lib/types/transcript'; import type { Segment, Speaker } from '$lib/types/transcript';
import { onMount } from 'svelte';
let waveformPlayer: WaveformPlayer; let waveformPlayer: WaveformPlayer;
let audioUrl = $state(''); let audioUrl = $state('');
let showSettings = $state(false);
onMount(() => {
loadSettings();
// Global keyboard shortcuts
function handleKeyDown(e: KeyboardEvent) {
// Don't trigger shortcuts when typing in inputs
const tag = (e.target as HTMLElement)?.tagName;
if (tag === 'INPUT' || tag === 'TEXTAREA' || tag === 'SELECT') return;
if (e.key === ' ' && !e.ctrlKey && !e.metaKey) {
e.preventDefault();
waveformPlayer?.togglePlayPause?.();
} else if (e.key === 'o' && (e.ctrlKey || e.metaKey)) {
e.preventDefault();
handleFileImport();
} else if (e.key === ',' && (e.ctrlKey || e.metaKey)) {
e.preventDefault();
showSettings = true;
} else if (e.key === 'Escape') {
showExportMenu = false;
showSettings = false;
}
}
// Close export dropdown on outside click
function handleClickOutside(e: MouseEvent) {
if (showExportMenu) {
const target = e.target as HTMLElement;
if (!target.closest('.export-dropdown')) {
showExportMenu = false;
}
}
}
document.addEventListener('keydown', handleKeyDown);
document.addEventListener('click', handleClickOutside);
return () => {
document.removeEventListener('keydown', handleKeyDown);
document.removeEventListener('click', handleClickOutside);
};
});
let isTranscribing = $state(false); let isTranscribing = $state(false);
let transcriptionProgress = $state(0); let transcriptionProgress = $state(0);
let transcriptionStage = $state(''); let transcriptionStage = $state('');
@@ -61,7 +108,13 @@
duration_ms: number; duration_ms: number;
speakers: string[]; speakers: string[];
num_speakers: number; num_speakers: number;
}>('run_pipeline', { filePath }); }>('run_pipeline', {
filePath,
model: $settings.transcription_model || undefined,
device: $settings.transcription_device || undefined,
language: $settings.transcription_language || undefined,
skipDiarization: $settings.skip_diarization || undefined,
});
// Create speaker entries from pipeline result // Create speaker entries from pipeline result
const newSpeakers: Speaker[] = (result.speakers || []).map((label, idx) => ({ const newSpeakers: Speaker[] = (result.speakers || []).map((label, idx) => ({
@@ -167,6 +220,9 @@
<button class="import-btn" onclick={handleFileImport}> <button class="import-btn" onclick={handleFileImport}>
Import Audio/Video Import Audio/Video
</button> </button>
<button class="settings-btn" onclick={() => showSettings = true} title="Settings">
Settings
</button>
{#if $segments.length > 0} {#if $segments.length > 0}
<div class="export-dropdown"> <div class="export-dropdown">
<button class="export-btn" onclick={() => showExportMenu = !showExportMenu}> <button class="export-btn" onclick={() => showExportMenu = !showExportMenu}>
@@ -204,6 +260,11 @@
message={transcriptionMessage} message={transcriptionMessage}
/> />
<SettingsModal
visible={showSettings}
onClose={() => showSettings = false}
/>
<style> <style>
.app-header { .app-header {
display: flex; display: flex;
@@ -235,6 +296,19 @@
gap: 0.5rem; gap: 0.5rem;
align-items: center; align-items: center;
} }
.settings-btn {
background: none;
border: 1px solid #4a5568;
color: #e0e0e0;
padding: 0.5rem 0.75rem;
border-radius: 6px;
cursor: pointer;
font-size: 0.875rem;
}
.settings-btn:hover {
background: rgba(255,255,255,0.05);
border-color: #e94560;
}
.export-dropdown { .export-dropdown {
position: relative; position: relative;
} }