feat: Make Whisper tiny the default engine and download during install (#45)

* feat: Make Whisper tiny the default engine and download during install

- Changed default engine from 'vosk' to 'whisper' in config_manager.py
- Changed default model_size from 'small' to 'tiny' in config_manager.py
- Added install_whisper_model() function to install.sh that downloads
  the Whisper tiny model (~75MB) during installation
- Whisper model is downloaded when Whisper package is installed
  (in non-interactive mode or with --with-whisper flag)
- Updated installation summary to show Whisper model status
- Updated documentation (README.md, INSTALL.md, SECURITY.md, USER_GUIDE.md)
  to reflect Whisper tiny as the default engine

This provides a better out-of-box experience: users can install and
immediately use Vocalinux without any additional downloads or prompts.

* test: Update test to reflect whisper as default engine

README.md

@@ -42,7 +42,7 @@ This will:
 - Set up a virtual environment in `~/.local/share/vocalinux/venv`
 - Install **both VOSK and Whisper AI** speech engines
 - Create a symlink at `~/.local/bin/vocalinux`
-- Download the default VOSK speech model
+- Download the default **Whisper tiny** speech model (~75MB)
 
 > ⏱️ **Note**: Installation takes ~5-10 minutes due to Whisper AI dependencies (PyTorch).
 

SECURITY.md

@@ -42,14 +42,14 @@ We take security seriously. If you discover a security vulnerability within Voca
 
 Vocalinux is designed with privacy in mind:
 
-- **Offline by default**: The VOSK engine works completely offline
+- **Offline by default**: Both Whisper (default) and VOSK engines work completely offline
 - **Local processing**: All speech recognition happens on your device
 - **No data collection**: We don't collect or transmit your voice data
 - **No telemetry**: We don't track usage or behavior
 
-### Whisper AI
+### Whisper AI (Default Engine)
 
-When using Whisper, be aware:
+Whisper is the default speech recognition engine:
 - Whisper processes locally on your machine
 - Models are downloaded once and cached locally
 - No audio data is sent to external servers

docs/INSTALL.md

@@ -83,7 +83,7 @@ Options:
 1. **Detects your Linux distribution** and installs appropriate system packages
 2. **Creates a Python virtual environment** with system site-packages access
 3. **Installs the Vocalinux package** and all dependencies
-4. **Downloads speech recognition models** (VOSK small model by default)
+4. **Downloads speech recognition models** (Whisper tiny model by default, VOSK as fallback)
 5. **Installs desktop integration** (icons, .desktop file)
 6. **Creates activation script** for easy environment activation
 
@@ -108,8 +108,9 @@ vocalinux
 ```bash
 vocalinux --help              # Show all options
 vocalinux --debug             # Enable debug logging
-vocalinux --engine whisper    # Use Whisper AI engine
-vocalinux --engine vosk       # Use VOSK engine (default)
+vocalinux --engine whisper    # Use Whisper AI engine (default)
+vocalinux --engine vosk       # Use VOSK engine
+vocalinux --model tiny        # Use tiny model (default, fastest)
 vocalinux --model small       # Use small model
 vocalinux --model medium      # Use medium model
 vocalinux --model large       # Use large model

docs/USER_GUIDE.md

@@ -63,8 +63,8 @@ You can change the speech recognition model for better accuracy or faster perfor
 
 1. Open settings from the tray icon menu
 2. Go to the "Recognition" tab
-3. Select your preferred model size
-4. Choose between VOSK (offline, faster) and Whisper (offline, more accurate)
+3. Select your preferred model size (tiny is the default, use larger models for better accuracy)
+4. Choose between Whisper (default, more accurate) and VOSK (lighter weight, faster)
 
 ## Troubleshooting
 

install.sh

@@ -699,6 +699,83 @@ if ! install_python_package; then
     exit 1
 fi
 
+# Function to download and install Whisper tiny model
+install_whisper_model() {
+    print_info "Installing Whisper tiny model (~75MB)..."
+    
+    # Create whisper models directory
+    local WHISPER_DIR="$DATA_DIR/models/whisper"
+    mkdir -p "$WHISPER_DIR"
+    
+    # Whisper tiny model URL and path
+    local TINY_MODEL_URL="https://openaipublic.azureedge.net/main/whisper/models/65147644a518d12f04e32d6f3b26facc3f8dd46e5390956a9424a650c0ce22b9/tiny.pt"
+    local TINY_MODEL_PATH="$WHISPER_DIR/tiny.pt"
+    
+    # Check if model already exists
+    if [ -f "$TINY_MODEL_PATH" ]; then
+        print_info "Whisper tiny model already exists at $TINY_MODEL_PATH"
+        return 0
+    fi
+    
+    # Check internet connectivity
+    if ! command -v wget >/dev/null 2>&1 && ! command -v curl >/dev/null 2>&1; then
+        print_warning "Neither wget nor curl found. Cannot download Whisper model."
+        print_warning "Model will be downloaded on first application run."
+        return 1
+    fi
+    
+    # Test internet connectivity
+    if ! ping -c 1 google.com >/dev/null 2>&1; then
+        print_warning "No internet connection detected."
+        print_warning "Whisper model will be downloaded on first application run."
+        return 1
+    fi
+    
+    print_info "Downloading Whisper tiny model..."
+    print_info "This may take a few minutes depending on your internet connection."
+    
+    local TEMP_FILE="$TINY_MODEL_PATH.tmp"
+    
+    # Download the model
+    if command -v wget >/dev/null 2>&1; then
+        if ! wget --progress=bar:force:noscroll -O "$TEMP_FILE" "$TINY_MODEL_URL" 2>&1; then
+            print_error "Failed to download Whisper model with wget"
+            rm -f "$TEMP_FILE"
+            return 1
+        fi
+    elif command -v curl >/dev/null 2>&1; then
+        if ! curl -L --progress-bar -o "$TEMP_FILE" "$TINY_MODEL_URL"; then
+            print_error "Failed to download Whisper model with curl"
+            rm -f "$TEMP_FILE"
+            return 1
+        fi
+    fi
+    
+    # Verify download
+    if [ ! -f "$TEMP_FILE" ] || [ ! -s "$TEMP_FILE" ]; then
+        print_error "Downloaded model file is empty or missing"
+        rm -f "$TEMP_FILE"
+        return 1
+    fi
+    
+    # Move to final location
+    mv "$TEMP_FILE" "$TINY_MODEL_PATH"
+    
+    # Verify the model file
+    if [ -f "$TINY_MODEL_PATH" ]; then
+        local MODEL_SIZE=$(du -h "$TINY_MODEL_PATH" | cut -f1)
+        print_success "Whisper tiny model installed successfully ($MODEL_SIZE)"
+        
+        # Create a marker file to indicate this model was pre-installed
+        echo "$(date)" > "$WHISPER_DIR/.vocalinux_preinstalled"
+        
+        return 0
+    else
+        print_error "Whisper model installation failed"
+        return 1
+    fi
+}
+
 # Function to download and install VOSK models
 install_vosk_models() {
     print_info "Installing VOSK speech recognition models..."
@@ -906,7 +983,21 @@ install_desktop_entry || print_warning "Desktop entry installation failed"
 # Install icons
 install_icons || print_warning "Icon installation failed"
 
-# Install VOSK models
+# Install Whisper tiny model (if Whisper was installed)
+if [ "$WITH_WHISPER" = "yes" ] || [ "$NON_INTERACTIVE" = "yes" ]; then
+    # Check if Whisper is actually installed before downloading model
+    if python -c "import whisper" 2>/dev/null; then
+        if [ "$SKIP_MODELS" = "no" ]; then
+            install_whisper_model || print_warning "Whisper model download failed - model will be downloaded on first run"
+        else
+            print_info "Skipping Whisper model download (--skip-models specified)"
+        fi
+    else
+        print_info "Whisper not available, skipping model download"
+    fi
+fi
+
+# Install VOSK models (as fallback)
 if [ "$SKIP_MODELS" = "no" ]; then
     install_vosk_models || print_warning "VOSK model installation failed - models will be downloaded on first run"
 else
@@ -1036,9 +1127,16 @@ print_installation_summary() {
     print_info "- Configuration: $CONFIG_DIR"
     print_info "- Data directory: $DATA_DIR"
     
+    # Check if Whisper model was installed
+    if [ -f "$DATA_DIR/models/whisper/tiny.pt" ]; then
+        print_info "- Whisper tiny model: $DATA_DIR/models/whisper/tiny.pt (default engine)"
+    elif python -c "import whisper" 2>/dev/null; then
+        print_info "- Whisper tiny model: Will be downloaded on first run"
+    fi
+    
     # Check if VOSK model was installed
     if [ "$SKIP_MODELS" = "no" ] && [ -d "$DATA_DIR/models/vosk-model-small-en-us-0.15" ]; then
-        print_info "- VOSK small model: $DATA_DIR/models/vosk-model-small-en-us-0.15"
+        print_info "- VOSK small model: $DATA_DIR/models/vosk-model-small-en-us-0.15 (fallback)"
     elif [ "$SKIP_MODELS" = "yes" ]; then
         print_info "- VOSK models: Will be downloaded on first run (--skip-models used)"
     else

src/vocalinux/ui/config_manager.py

@@ -19,8 +19,8 @@ CONFIG_FILE = os.path.join(CONFIG_DIR, "config.json")
 # Default configuration
 DEFAULT_CONFIG = {
     "speech_recognition": {  # Changed section name
-        "engine": "vosk",  # "vosk" or "whisper"
-        "model_size": "small",  # "small", "medium", or "large"
+        "engine": "whisper",  # "vosk" or "whisper"
+        "model_size": "tiny",  # "tiny", "small", "medium", or "large"
         "vad_sensitivity": 3,  # Voice Activity Detection sensitivity (1-5) - Moved here
         "silence_timeout": 2.0,  # Seconds of silence before stopping recognition - Moved here
     },

tests/test_config_manager.py

@@ -142,7 +142,7 @@ class TestConfigManager(unittest.TestCase):
         """Test getting an existing configuration value."""
         config_manager = ConfigManager()
         value = config_manager.get("speech_recognition", "engine")
-        self.assertEqual(value, "vosk")
+        self.assertEqual(value, "whisper")  # Default is now whisper
 
     def test_get_nonexistent_value(self):
         """Test getting a nonexistent configuration value."""
@@ -153,9 +153,9 @@ class TestConfigManager(unittest.TestCase):
     def test_set_existing_section(self):
         """Test setting a value in an existing section."""
         config_manager = ConfigManager()
-        result = config_manager.set("speech_recognition", "engine", "whisper")
+        result = config_manager.set("speech_recognition", "engine", "vosk")
         self.assertTrue(result)
-        self.assertEqual(config_manager.config["speech_recognition"]["engine"], "whisper")
+        self.assertEqual(config_manager.config["speech_recognition"]["engine"], "vosk")
 
     def test_set_new_section(self):
         """Test setting a value in a new section."""