Release v1.0.4: The Compatibility Update

- Added robust CPU Fallback for AMD/Non-CUDA GPUs.
- Implemented Lazy Load for AI Engine to prevent startup crashes.
- Added explicit DLL injection for Cublas/Cudnn on Windows.
- Added Corrupt Model Auto-Repair logic.
- Includes pre-compiled v1.0.4 executable.

README.md

@@ -1,71 +1,190 @@
-# Whisper Voice
+<div align="center">
 
-**Reclaim Your Voice from the Cloud.**
+# 🎙️ W H I S P E R &nbsp; V O I C E
+### SOVEREIGN SPEECH RECOGNITION
 
-Whisper Voice is a high-performance, strictly local speech-to-text tool designed for the desktop. It provides instant, high-accuracy dictation anywhere on your system—no internet connection required, no corporate servers, and absolutely no data harvesting.
+<br>
 
-We believe that the tools of production—and communication—should belong to the individual, not rented from centralized tech giants.
+![Status](https://img.shields.io/badge/STATUS-OPERATIONAL-success?style=for-the-badge&logo=server&color=2ecc71)
+[![Download](https://img.shields.io/gitea/v/release/lashman/whisper_voice?gitea_url=https%3A%2F%2Fgit.lashman.live&label=Install&style=for-the-badge&logo=windows&logoColor=white&color=3b82f6)](https://git.lashman.live/lashman/whisper_voice/releases/latest)
+[![License](https://img.shields.io/badge/LICENSE-PUBLIC_DOMAIN-lightgrey?style=for-the-badge&logo=creative-commons&logoColor=black)](https://creativecommons.org/publicdomain/zero/1.0/)
+
+<br>
+
+> *"The master's tools will never dismantle the master's house."*
+> <br>
+> **Build your own tools. Run them locally. Free your mind.**
+
+[View Source](https://git.lashman.live/lashman/whisper_voice) • [Report Issue](https://git.lashman.live/lashman/whisper_voice/issues)
+
+</div>
+
+<br>
+<br>
+
+## 📡 The Transmission
+
+We are witnessing the **enshittification** of the digital world. What were once vibrant social commons are being walled off, strip-mined for data, and degraded into rent-seeking silos. Your voice is no longer your own; it is a training set for a corporate oracle that charges you for the privilege of listening.
+
+**Whisper Voice** is a small act of sabotage against this trend.
+
+It is built on the axiom of **Technological Sovereignty**. By moving state-of-the-art inference from the server farms to your own silicon, you reclaim the means of digital production. No telemetry. No subscriptions. No "cloud processing" that eavesdrops on your intent. 
 
 ---
 
-## ✊ Core Principles
+## ⚡ The Engine
 
-### 1. Total Autonomy (Local-First)
-Your voice data is yours alone. Unlike commercial alternatives that siphon your words to remote data centers for processing and profiling, Whisper Voice runs entirely on your hardware. **No masters, no servers.** You retain full sovereignty over your digital footprint.
+Whisper Voice operates directly on the metal. It is not an API wrapper; it is an autonomous machine.
 
-### 2. Decentralized Power
-By leveraging optimized local processing, we strip away the need for reliance on massive, energy-hungry corporate infrastructure. This is technology scaled to the human level—powerful, efficient, and completely under your control.
+| Component | Technology | Benefit |
+| :--- | :--- | :--- |
+| **Inference Core** | **Faster-Whisper** | Hyper-optimized C++ implementation via **CTranslate2**. Delivers **4x velocity** over standard PyTorch. |
+| **Compression** | **INT8 quantization** | Enables Pro-grade models (`Large-v3`) to run on consumer-grade GPUs, democratizing elite AI. |
+| **Sensory Gate** | **Silero VAD** | Enterprise-grade Voice Activity Detection filters out the noise, ensuring only pure intent is processed. |
+| **Interface** | **Qt 6 / QML** | Hardware-accelerated, glassmorphic UI that is fluid, responsive, and sovereign. |
 
-### 3. Accessible to All
-High-quality speech recognition shouldn't be gated behind subscriptions or paywalls. This tool is free, open, and built to empower users to interact with their machines on their own terms.
+### 🛑 Compatibility Matrix (Windows)
+The core engine (`CTranslate2`) is heavily optimized for Nvidia tensor cores.
+
+| Manufacturer | Hardware | Status | Notes |
+| :--- | :--- | :--- | :--- |
+| **Nvidia** | GTX 900+ / RTX | ✅ **Supported** | Full heavy-metal acceleration. |
+| **AMD** | Radeon RX | ⚠️ **CPU Fallback** | Runs on CPU. Valid for `Small/Medium`, slow for `Large`. |
+| **Intel** | Arc / Iris | ⚠️ **CPU Fallback** | Runs on CPU. Valid for `Small/Medium`, slow for `Large`. |
+| **Apple** | M1 / M2 / M3 | ❌ **Unsupported** | Release is strictly Windows x64. |
+
+> **AMD Users**: v1.0.3 auto-detects GPU failures and silently falls back to CPU.
+
+<br>
+
+## 🖋️ Universal Transcription
+
+At its core, Whisper Voice is the ultimate bridge between thought and text. It listens with superhuman precision, converting spoken word into written form across **99 languages**.
+
+*   **Punctuation Mastery**: Automatically handles capitalization and complex punctuation formatting.
+*   **Contextual Intelligence**: Smarter than standard dictation; it understands the flow of sentences to resolve homophones and technical jargon ($1.5k vs "fifteen hundred dollars").
+*   **Total Privacy**: Your private dictation, legal notes, or creative writing never leave your RAM.
+
+### Workflow: `F9 (Default)`
+The primary channel for native-language transcription. It transcribes precisely what it hears in the language you speak (or the one you've locked in Settings).
+
+### ✨ Style Prompting (New in v1.0.2)
+Whisper Voice replaces traditional "grammar correction models" with a native **Style Prompting** engine. By injecting a specific "pre-prompt" into the model's context window, we can guide its internal style without external post-processing.
+
+*   **Standard (Default)**: Forces the model to use full sentences, proper capitalization, and periods. Ideal for dictation.
+*   **Casual**: Encourages a relaxed, lowercase style (e.g., "no way that's crazy lol").
+*   **Custom**: Allows you to seed the model with your own context (e.g., "Here is a list of medical terms:").
+
+This approach incurs **zero latency penalty** and **zero extra VRAM** usage.
+
+<br>
+
+## 🌎 Universal Translation
+
+Whisper Voice v1.0.1 includes a **Neural Translation Engine** that allows you to bridge any linguistic gap instantly.
+
+*   **Input**: Speak in French, Japanese, Russian, or **96 other languages**.
+*   **Output**: The engine instantly reconstructs the semantic meaning into fluent **English**.
+*   **Task Protocol**: Handled via the dedicated `F10` channel.
+
+### 🔍 Why only English translation?
+A common question arises: *Why can't I translate from French to Japanese?*
+
+The architecture of the underlying Whisper model is a **Many-to-English** design. During its massive training phase (680,000 hours of audio), the translation task was specifically optimized to map the global linguistic commons onto a single bridge language: **English**. This allowed the model to reach incredible levels of semantic understanding without the exponential complexity of a "Many-to-Many" mapping. 
+
+By focusing its translation decoder solely on English, Whisper achieves "Zero-Shot" quality that rivals specialized translation engines while remaining lightweight enough to run on your local GPU.
 
 ---
 
-## ✨ Features
+## 🕹️ Command & Control
 
-*   **100% Offline Processing**: Once the recognition engine is downloaded, the cable can be cut. Nothing leaves your machine.
-*   **Universal Compatibility**: Works in any text field—editors, chat apps, terminals, or browsers. If you can type there, you can speak there.
-*   **Adaptive Input**:
-    *   *Clipboard Mode*: Standard paste injection.
-    *   *High-Speed Simulation*: Simulates keystrokes at supersonic speeds (up to 6000 CPM) for apps that block pasting.
-*   **System Integration**: Minimalist overlay and system tray presence. It exists when you need it and vanishes when you don't.
-*   **Resource Efficiency**: Optimized to run smoothly on consumer hardware without monopolizing your system resources.
+### Global Hotkeys
+The agent runs silently in the background, waiting for your signal.
+
+*   **Transcribe (F9)**: Opens the channel for standard speech-to-text.
+*   **Translate (F10)**: Opens the channel for neural translation.
+*   **Customization**: Remap these keys in Settings. The recorder supports complex chords (e.g. `Ctrl + Alt + Space`) to fit your workflow.
+
+### Injection Protocols
+*   **Clipboard Paste**: Standard text injection. Instant, reliable.
+*   **Simulate Typing**: Mimics physical keystrokes at superhuman speed (6000 CPM). Bypasses anti-paste restrictions and "protected" windows.
+
+<br>
+
+## 📊 Intelligence Matrix
+
+Select the model that aligns with your available resources.
+
+| Model | VRAM (GPU) | RAM (CPU) | Designation | Capability |
+| :--- | :--- | :--- | :--- | :--- |
+| `Tiny` | **~500 MB** | ~1 GB | ⚡ **Supersonic** | Command & Control, older hardware. |
+| `Base` | **~600 MB** | ~1 GB | 🚀 **Very Fast** | Daily driver for low-power laptops. |
+| `Small` | **~1 GB** | ~2 GB | ⏩ **Fast** | High accuracy English dictation. |
+| `Medium` | **~2 GB** | ~4 GB | ⚖️ **Balanced** | Complex vocabulary, foreign accents. |
+| `Large-v3 Turbo` | **~4 GB** | ~6 GB | ✨ **Optimal** | **The Sweet Spot.** Near-Large intelligence, Medium speed. |
+| `Large-v3` | **~5 GB** | ~8 GB | 🧠 **Maximum** | Professional grade. Uncompromised. |
+
+> *Note: Acceleration requires you to manually select your Compute Device (CUDA GPU or CPU) in Settings.*
+
+### 📉 Low VRAM Mode
+For users with limited GPU memory (e.g., 4GB cards) or those running heavy games simultaneously, Whisper Voice offers a specialized **Low VRAM Mode**.
+
+*   **Behavior**: The AI model is aggressively unloaded from the GPU immediately after every transcription.
+*   **Benefit**: When idle, the app consumes near-zero VRAM (~0MB), leaving your GPU completely free for gaming or rendering.
+*   **Trade-off**: There is a "cold start" latency of 1-2 seconds for every voice command as the model reloads from the disk cache.
 
 ---
 
-## 🚀 Getting Started
+## 🛠️ Deployment
 
-### Installation
-1.  Download the latest release.
-2.  Run `WhisperVoice.exe`.
-3.  On the first run, the bootstrapper will autonomously provision the necessary runtime environment. This ensures your system remains clean and dependencies are self-contained.
+### 📥 Installation
+1.  **Acquire**: Download `WhisperVoice.exe` from [Releases](https://git.lashman.live/lashman/whisper_voice/releases).
+2.  **Deploy**: Place it anywhere. It is portable.
+3.  **Bootstrap**: Run it. The agent will self-provision an isolated Python runtime (~2GB) on first launch.
+4.  **Sync**: Future updates are handled by the **Smart Bootstrapper**, which surgically updates only changed files, respecting your bandwidth and your settings.
 
-### Usage
-1.  **Set Your Trigger**: Configure a global hotkey (default: `F9`) in the settings.
-2.  **Speak Freely**: Hold the hotkey (or toggle it) and speak.
-3.  **Direct Action**: Your words are instantly transcribed and injected into your active window.
+### 🔧 Troubleshooting
+*   **App crashes on start**: Ensure you have [Microsoft Visual C++ Redistributable 2015-2022](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist) installed.
+*   **"Simulate Typing" is slow**: Some applications (remote desktops, legacy games) cannot handle the data stream. Lower the typing speed in Settings to ~1200 CPM.
+*   **No Audio**: The agent listens to the **Default Communication Device**. Verify your Windows Sound Control Panel.
+
+<br>
 
 ---
 
-## ⚙️ Configuration
+## 🌐 Supported Languages
 
-The **Settings** panel puts the means of configuration in your hands:
+The engine understands the following 99 languages. You can lock the focus to a specific language in Settings to improve accuracy, or rely on **Auto-Detect** for fluid multilingual usage.
 
-*   **Recognition Engine**: Choose the size of the model that fits your hardware capabilities (Tiny to Large). Larger models offer greater precision but require more computing power.
-*   **Input Method**: Switch between "Clipboard Paste" and "Simulate Typing" depending on target application restrictions.
-*   **Typing Speed**: Adjust the keystroke injection rate. Crank it up to 6000 CPM for instant text delivery.
-*   **Run on Startup**: Configure the agent to be ready the moment your session begins.
+| | | | | | |
+| :--- | :--- | :--- | :--- | :--- | :--- |
+| Afrikaans 🇿🇦 | Albanian 🇦🇱 | Amharic 🇪🇹 | Arabic 🇸🇦 | Armenian 🇦🇲 | Assamese 🇮🇳 |
+| Azerbaijani 🇦🇿 | Bashkir 🇷🇺 | Basque 🇪🇸 | Belarusian 🇧🇾 | Bengali 🇧🇩 | Bosnian 🇧🇦 |
+| Breton 🇫🇷 | Bulgarian 🇧🇬 | Burmese 🇲🇲 | Castilian 🇪🇸 | Catalan 🇪🇸 | Chinese 🇨🇳 |
+| Croatian 🇭🇷 | Czech 🇨🇿 | Danish 🇩🇰 | Dutch 🇳🇱 | English 🇺🇸 | Estonian 🇪🇪 |
+| Faroese 🇫🇴 | Finnish 🇫🇮 | Flemish 🇧🇪 | French 🇫🇷 | Galician 🇪🇸 | Georgian 🇬🇪 |
+| German 🇩🇪 | Greek 🇬🇷 | Gujarati 🇮🇳 | Haitian 🇭🇹 | Hausa 🇳🇬 | Hawaiian 🇺🇸 |
+| Hebrew 🇮🇱 | Hindi 🇮🇳 | Hungarian 🇭🇺 | Icelandic 🇮🇸 | Indonesian 🇮🇩 | Italian 🇮🇹 |
+| Japanese 🇯🇵 | Javanese 🇮 Indonesa | Kannada 🇮🇳 | Kazakh 🇰🇿 | Khmer 🇰🇭 | Korean 🇰🇷 |
+| Lao 🇱🇦 | Latin 🇻🇦 | Latvian 🇱🇻 | Lingala 🇨🇩 | Lithuanian 🇱🇹 | Luxembourgish 🇱🇺 |
+| Macedonian 🇲🇰 | Malagasy 🇲🇬 | Malay 🇲🇾 | Malayalam 🇮🇳 | Maltese 🇲🇹 | Maori 🇳🇿 |
+| Marathi 🇮🇳 | Moldavian 🇲🇩 | Mongolian 🇲🇳 | Myanmar 🇲🇲 | Nepali 🇳🇵 | Norwegian 🇳🇴 |
+| Occitan 🇫🇷 | Panjabi 🇮🇳 | Pashto 🇦🇫 | Persian 🇮🇷 | Polish 🇵🇱 | Portuguese 🇵🇹 |
+| Punjabi 🇮🇳 | Romanian 🇷🇴 | Russian 🇷🇺 | Sanskrit 🇮🇳 | Serbian 🇷🇸 | Shona 🇿🇼 |
+| Sindhi 🇵🇰 | Sinhala 🇱🇰 | Slovak 🇸🇰 | Slovenian 🇸🇮 | Somali 🇸🇴 | Spanish 🇪🇸 |
+| Sundanese 🇮🇩 | Swahili 🇰🇪 | Swedish 🇸🇪 | Tagalog 🇵🇭 | Tajik 🇹🇯 | Tamil 🇮🇳 |
+| Tatar 🇷🇺 | Telugu 🇮🇳 | Thai 🇹🇭 | Tibetan 🇨🇳 | Turkish 🇹🇷 | Turkmen 🇹🇲 |
+| Ukrainian 🇺🇦 | Urdu 🇵🇰 | Uzbek 🇺🇿 | Vietnamese 🇻e | Welsh 🏴󠁧󠁢󠁷󠁬󠁳󠁿 | Yiddish 🇮🇱 |
+| Yoruba 🇳🇬 | | | | | |
 
----
+<br>
+<br>
 
-## 🤝 Mutual Aid
+<div align="center">
 
-This project thrives on community collaboration. If you have improvements, fixes, or ideas, you are encouraged to contribute. We build better systems when we build them together, horizontally and transparently.
+### ⚖️ PUBLIC DOMAIN (CC0 1.0)
+*No Rights Reserved. No Gods. No Masters. No Managers.*
 
-*   **Report Issues**: If something breaks, let us know.
-*   **Contribute Code**: The source is open. Fork it, improve it, share it.
+Credit to **OpenAI** (Whisper), **Systran** (Faster-Whisper), and **Silero** (VAD).
 
----
-
-*Built with local processing libraries and Qt.*
-*No gods, no cloud managers.*
+</div>

RELEASE_NOTES.md

@@ -0,0 +1,28 @@
+# Release v1.0.4
+
+**"The Compatibility Update"**
+
+This release focuses on maximum stability across different hardware configurations (AMD, Intel, Nvidia) and fixing startup crashes related to corrupted models or missing drivers.
+
+## 🛠️ Critical Fixes
+
+### 1. Robust CPU Fallback (AMD / Intel Support)
+*   **Problem**: Previously, if an AMD user tried to run the app, it would crash instantly because it tried to load Nvidia CUDA libraries by default.
+*   **Fix**: The app now **silently detects** if CUDA initialization fails (due to missing DLLs or incompatible hardware) and **automatically falls back to CPU mode**.
+*   **Result**: The app "just works" on any Windows machine, regardless of GPU.
+
+### 2. Startup Crash Protection
+*   **Problem**: If `faster_whisper` was imported before checking for valid drivers, the app would crash on launch for some users.
+*   **Fix**: Implemented **Lazy Loading** for the AI engine. The app now starts the UI first, and only loads the heavy AI libraries inside a safety block that catches errors.
+
+### 3. Corrupt Model Auto-Repair
+*   **Problem**: Interrupted downloads could leave a corrupted model folder, preventing the app from ever starting again.
+*   **Fix**: If the app detects a "vocabulary missing" or invalid config error, it will now **automatically delete the corrupt folder** and allow you to re-download it cleanly.
+
+### 4. Windows DLL Injection
+*   **Fix**: Added explicit DLL path injection for `nvidia-cublas` and `nvidia-cudnn` to ensure Python 3.8+ can find the required CUDA libraries on Windows systems that don't have them in PATH.
+
+## 📦 Installation
+1.  Download `WhisperVoice.exe` below.
+2.  Replace your existing `.exe`.
+3.  Run it.

bootstrapper.py

@@ -259,48 +259,72 @@ class Bootstrapper:
         process.wait()
         
     def refresh_app_source(self):
-        """Refresh app source files. Skips if already exists to save time."""
-        # Optimization: If app/main.py exists, skip update to improve startup speed.
-        # The user can delete the 'runtime' folder to force an update.
-        if (self.app_path / "main.py").exists():
-            log("App already exists. Skipping update.")
-            return True
-
-        if self.ui: self.ui.set_status("Updating app files...")
+        """
+        Smartly updates app source files by only copying changed files.
+        Preserves user settings and reduces disk I/O.
+        """
+        if self.ui: self.ui.set_status("Checking for updates...")
         
         try:
-            # Preserve settings.json if it exists
-            settings_path = self.app_path / "settings.json"
-            temp_settings = None
-            if settings_path.exists():
-                try:
-                    temp_settings = settings_path.read_bytes()
-                except:
-                    log("Failed to backup settings.json, it involves risk of data loss.")
+            # 1. Ensure destination exists
+            if not self.app_path.exists():
+                self.app_path.mkdir(parents=True, exist_ok=True)
                 
-            if self.app_path.exists():
-                shutil.rmtree(self.app_path, ignore_errors=True)
+            # 2. Walk source and sync
+            # source_path is the temporary bundled folder
+            # app_path is the persistent runtime folder
             
-            shutil.copytree(
-                self.source_path,
-                self.app_path,
-                ignore=shutil.ignore_patterns(
-                    '__pycache__', '*.pyc', '.git', 'venv', 
-                    'build', 'dist', '*.egg-info', 'runtime'
-                )
-            )
+            changes_made = 0
             
-            # Restore settings.json
-            if temp_settings:
-                try:
-                    settings_path.write_bytes(temp_settings)
-                    log("Restored settings.json")
-                except:
-                    log("Failed to restore settings.json")
+            for src_dir, dirs, files in os.walk(self.source_path):
+                # Determine relative path from source root
+                rel_path = Path(src_dir).relative_to(self.source_path)
+                dst_dir = self.app_path / rel_path
+                
+                # Ensure directory exists
+                if not dst_dir.exists():
+                    dst_dir.mkdir(parents=True, exist_ok=True)
+                
+                for file in files:
+                    # Skip ignored files
+                    if file in ['__pycache__', '.git', 'settings.json'] or file.endswith('.pyc'):
+                        continue
+                        
+                    src_file = Path(src_dir) / file
+                    dst_file = dst_dir / file
+                    
+                    # Check if update needed
+                    should_copy = False
+                    if not dst_file.exists():
+                        should_copy = True
+                    else:
+                        # Compare size first (fast)
+                        if src_file.stat().st_size != dst_file.stat().st_size:
+                            should_copy = True
+                        else:
+                            # Compare content (slower but accurate)
+                            # Only read if size matches to verify diff
+                            if src_file.read_bytes() != dst_file.read_bytes():
+                                should_copy = True
+                    
+                    if should_copy:
+                        shutil.copy2(src_file, dst_file)
+                        changes_made += 1
+                        if self.ui: self.ui.set_detail(f"Updated: {file}")
+
+            # 3. Cleanup logic (Optional: remove files in dest that are not in source)
+            # For now, we only add/update to prevent deleting generated user files (logs, etc)
+            
+            if changes_made > 0:
+                log(f"Update complete. {changes_made} files changed.")
+            else:
+                log("App is up to date.")
                 
             return True
         except Exception as e:
             log(f"Error refreshing app source: {e}")
+            # Fallback to nuclear option if sync fails completely? 
+            # No, 'smart_sync' failing might mean permissions, nuclear wouldn't help.
             return False
         
     def run_app(self):
@@ -323,11 +347,17 @@ class Bootstrapper:
             messagebox.showerror("WhisperVoice Error", f"Failed to launch app: {e}")
             return False
 
+    def check_dependencies(self):
+        """Quick check if critical dependencies are installed."""
+        return True # Deprecated logic placeholder
+
     def setup_and_run(self):
         """Full setup/update and run flow."""
         try:
+            # 1. Ensure basics
             if not self.is_python_ready():
                 self.download_python()
+                self._fix_pth_file() # Ensure pth is fixed immediately after download
                 self.install_pip()
                 self.install_packages()
             
@@ -338,7 +368,10 @@ class Bootstrapper:
             if self.run_app():
                 if self.ui: self.ui.root.quit()
         except Exception as e:
-            messagebox.showerror("Setup Error", f"Installation failed: {e}")
+            if self.ui:
+                import tkinter.messagebox as mb
+                mb.showerror("Setup Error", f"Installation failed: {e}") # Improved error visibility
+            log(f"Fatal error: {e}")
             import traceback
             traceback.print_exc()
 

main.py

@@ -9,6 +9,31 @@ app_dir = os.path.dirname(os.path.abspath(__file__))
 if app_dir not in sys.path:
     sys.path.insert(0, app_dir)
 
+# -----------------------------------------------------------------------------
+# WINDOWS DLL FIX (CRITICAL for Portable CUDA)
+# Python 3.8+ on Windows requires explicit DLL directory addition.
+# -----------------------------------------------------------------------------
+if os.name == 'nt' and hasattr(os, 'add_dll_directory'):
+    try:
+        from pathlib import Path
+        # Scan sys.path for site-packages
+        for p in sys.path:
+            path_obj = Path(p)
+            if path_obj.name == 'site-packages' and path_obj.exists():
+                nvidia_path = path_obj / "nvidia"
+                if nvidia_path.exists():
+                    for subdir in nvidia_path.iterdir():
+                        # Add 'bin' folder from each nvidia stub (cublas, cudnn, etc.)
+                        bin_path = subdir / "bin"
+                        if bin_path.exists():
+                            os.add_dll_directory(str(bin_path))
+                # Also try adding site-packages itself just in case
+                # os.add_dll_directory(str(path_obj))
+                break
+    except Exception:
+        pass
+# -----------------------------------------------------------------------------
+
 from PySide6.QtWidgets import QApplication, QFileDialog, QMessageBox
 from PySide6.QtCore import QObject, Slot, Signal, QThread, Qt, QUrl
 from PySide6.QtQml import QQmlApplicationEngine
@@ -87,7 +112,7 @@ def _silent_shutdown_hook(exc_type, exc_value, exc_tb):
 sys.excepthook = _silent_shutdown_hook
 
 class DownloadWorker(QThread):
-    """Background worker for model downloads."""
+    """Background worker for model downloads with REAL progress."""
     progress = Signal(int)
     finished = Signal()
     error = Signal(str)
@@ -98,33 +123,81 @@ class DownloadWorker(QThread):
 
     def run(self):
         try:
-            from faster_whisper import download_model
+            import requests
+            from tqdm import tqdm
             model_path = get_models_path()
-            # Download to a specific subdirectory to keep things clean and predictable
-            # This matches the logic in transcriber.py which looks for this specific path
+            # Determine what to download
             dest_dir = model_path / f"faster-whisper-{self.model_name}"
-            logging.info(f"Downloading Model '{self.model_name}' to {dest_dir}...")
+            repo_id = f"Systran/faster-whisper-{self.model_name}"
+            files = ["config.json", "model.bin", "tokenizer.json", "vocabulary.json"]
+            base_url = f"https://huggingface.co/{repo_id}/resolve/main"
 
-            # Ensure parent exists
-            model_path.mkdir(parents=True, exist_ok=True)
+            dest_dir.mkdir(parents=True, exist_ok=True)
+            logging.info(f"Downloading {self.model_name} to {dest_dir}...")
             
-            # output_dir in download_model specifies where the model files are saved
-            download_model(self.model_name, output_dir=str(dest_dir))
+            # 1. Calculate Total Size
+            total_size = 0
+            file_sizes = {}
+            
+            with requests.Session() as s:
+                for fname in files:
+                    url = f"{base_url}/{fname}"
+                    head = s.head(url, allow_redirects=True)
+                    if head.status_code == 200:
+                        size = int(head.headers.get('content-length', 0))
+                        file_sizes[fname] = size
+                        total_size += size
+                    else:
+                        # Fallback for vocabulary.json vs vocabulary.txt
+                        if fname == "vocabulary.json":
+                             # Try .txt? Or just skip if not found? 
+                             # Faster-whisper usually has vocabulary.json
+                             pass
+            
+            # 2. Download loop
+            downloaded_bytes = 0
+            
+            with requests.Session() as s:
+                for fname in files:
+                    if fname not in file_sizes: continue
+                    
+                    url = f"{base_url}/{fname}"
+                    dest_file = dest_dir / fname
+                    
+                    # Resume check? 
+                    # Simpler to just overwrite for reliability unless we want complex resume logic.
+                    # We'll overwrite.
+                    
+                    resp = s.get(url, stream=True)
+                    resp.raise_for_status()
+                    
+                    with open(dest_file, 'wb') as f:
+                        for chunk in resp.iter_content(chunk_size=8192):
+                            if chunk:
+                                f.write(chunk)
+                                downloaded_bytes += len(chunk)
+                                
+                                # Emit Progress
+                                if total_size > 0:
+                                    pct = int((downloaded_bytes / total_size) * 100)
+                                    self.progress.emit(pct)
 
             self.finished.emit()
+            
         except Exception as e:
             logging.error(f"Download failed: {e}")
             self.error.emit(str(e))
 
 class TranscriptionWorker(QThread):
     finished = Signal(str)
-    def __init__(self, transcriber, audio_data, is_file=False, parent=None):
+    def __init__(self, transcriber, audio_data, is_file=False, parent=None, task_override=None):
         super().__init__(parent)
         self.transcriber = transcriber
         self.audio_data = audio_data
         self.is_file = is_file
+        self.task_override = task_override
     def run(self):
-        text = self.transcriber.transcribe(self.audio_data, is_file=self.is_file)
+        text = self.transcriber.transcribe(self.audio_data, is_file=self.is_file, task=self.task_override)
         self.finished.emit(text)
 
 class WhisperApp(QObject):
@@ -166,13 +239,18 @@ class WhisperApp(QObject):
         self.tray.transcribe_file_requested.connect(self.transcribe_file)
         
         # Init Tooltip
-        hotkey = self.config.get("hotkey")
-        self.tray.setToolTip(f"Whisper Voice - Press {hotkey} to Record")
+        from src.utils.formatters import format_hotkey
+        self.format_hotkey = format_hotkey # Store ref
+        
+        hk1 = self.format_hotkey(self.config.get("hotkey"))
+        hk2 = self.format_hotkey(self.config.get("hotkey_translate"))
+        self.tray.setToolTip(f"Whisper Voice\nTranscribe: {hk1}\nTranslate: {hk2}")
         
         # 3. Logic Components Placeholders
         self.audio_engine = None
         self.transcriber = None
-        self.hotkey_manager = None
+        self.hk_transcribe = None
+        self.hk_translate = None
         self.overlay_root = None
         
         # 4. Start Loader
@@ -222,12 +300,23 @@ class WhisperApp(QObject):
             self.settings_root.setVisible(False)
         
         # Install Low-Level Window Hook for Transparent Hit Test
-        # We must keep a reference to 'self.hook' so it isn't GC'd
-        # scale = self.overlay_root.devicePixelRatio()
-        # self.hook = WindowHook(int(self.overlay_root.winId()), 500, 300, scale)
-        # self.hook.install()
+        try:
+            from src.utils.window_hook import WindowHook
+            hwnd = self.overlay_root.winId()
+            # Initial scale from config
+            scale = float(self.config.get("ui_scale"))
             
-        # NOTE: HitTest hook will be installed here later
+            # Current Overlay Dimensions
+            win_w = int(460 * scale)
+            win_h = int(180 * scale)
+            
+            self.window_hook = WindowHook(hwnd, win_w, win_h, initial_scale=scale)
+            self.window_hook.install()
+            
+            # Initial state: Disabled because we start inactive
+            self.window_hook.set_enabled(False)
+        except Exception as e:
+            logging.error(f"Failed to install WindowHook: {e}")
 
     def center_overlay(self):
         """Calculates and sets the Overlay position above the taskbar."""
@@ -255,9 +344,16 @@ class WhisperApp(QObject):
         self.audio_engine.set_visualizer_callback(self.bridge.update_amplitude)
         self.audio_engine.set_silence_callback(self.on_silence_detected)
         self.transcriber = WhisperTranscriber()
-        self.hotkey_manager = HotkeyManager()
-        self.hotkey_manager.triggered.connect(self.toggle_recording)
-        self.hotkey_manager.start()
+        
+        # Dual Hotkey Managers
+        self.hk_transcribe = HotkeyManager(config_key="hotkey")
+        self.hk_transcribe.triggered.connect(lambda: self.toggle_recording(task_override="transcribe"))
+        self.hk_transcribe.start()
+        
+        self.hk_translate = HotkeyManager(config_key="hotkey_translate")
+        self.hk_translate.triggered.connect(lambda: self.toggle_recording(task_override="translate"))
+        self.hk_translate.start()
+        
         self.bridge.update_status("Ready")
 
     def run(self):
@@ -275,7 +371,8 @@ class WhisperApp(QObject):
             except: pass
             self.bridge.stats_worker.stop()
         
-        if self.hotkey_manager: self.hotkey_manager.stop()
+        if self.hk_transcribe: self.hk_transcribe.stop()
+        if self.hk_translate: self.hk_translate.stop()
         
         # Close all QML windows to ensure bindings stop before Python objects die
         if self.overlay_root: 
@@ -350,10 +447,14 @@ class WhisperApp(QObject):
         print(f"Setting Changed: {key} = {value}")
         
         # 1. Hotkey Reload
-        if key == "hotkey":
-            if self.hotkey_manager: self.hotkey_manager.reload_hotkey()
+        if key in ["hotkey", "hotkey_translate"]:
+            if self.hk_transcribe: self.hk_transcribe.reload_hotkey()
+            if self.hk_translate: self.hk_translate.reload_hotkey()
+            
             if self.tray:
-                self.tray.setToolTip(f"Whisper Voice - Press {value} to Record")
+                hk1 = self.format_hotkey(self.config.get("hotkey"))
+                hk2 = self.format_hotkey(self.config.get("hotkey_translate"))
+                self.tray.setToolTip(f"Whisper Voice\nTranscribe: {hk1}\nTranslate: {hk2}")
 
         # 2. AI Model Reload (Heavy)
         if key in ["model_size", "compute_device", "compute_type"]:
@@ -456,6 +557,8 @@ class WhisperApp(QObject):
         file_path, _ = QFileDialog.getOpenFileName(None, "Select Audio", "", "Audio (*.mp3 *.wav *.flac *.m4a *.ogg)")
         if file_path:
             self.bridge.update_status("Thinking...")
+            # Files use the default configured task usually, or we could ask? 
+            # Default to config setting for files.
             self.worker = TranscriptionWorker(self.transcriber, file_path, is_file=True, parent=self)
             self.worker.finished.connect(self.on_transcription_done)
             self.worker.start()
@@ -463,10 +566,13 @@ class WhisperApp(QObject):
     @Slot()
     def on_silence_detected(self):
         from PySide6.QtCore import QMetaObject, Qt
+        # Silence detection always triggers the task that was active? 
+        # Since silence stops recording, it just calls toggle_recording with no arg, using the stored current_task?
+        # Let's ensure toggle_recording handles no arg calls by stopping the CURRENT task.
         QMetaObject.invokeMethod(self, "toggle_recording", Qt.QueuedConnection)
 
-    @Slot()
-    def toggle_recording(self):
+    @Slot() # Modified to allow lambda override
+    def toggle_recording(self, task_override=None):
         if not self.audio_engine: return
         
         # Prevent starting a new recording while we are still transcribing the last one
@@ -474,23 +580,36 @@ class WhisperApp(QObject):
             logging.warning("Ignored toggle request: Transcription in progress.")
             return
 
+        # Determine which task we are entering
+        if task_override:
+            intended_task = task_override
+        else:
+            intended_task = self.config.get("task")
+
         if self.audio_engine.recording:
+            # STOP RECORDING
             self.bridge.update_status("Thinking...")
             self.bridge.isRecording = False
             self.bridge.isProcessing = True # Start Processing
             audio_data = self.audio_engine.stop_recording()
-            self.worker = TranscriptionWorker(self.transcriber, audio_data, parent=self)
+            
+            # Use the task that started this session, or the override if provided (though usually override is for starting)
+            final_task = getattr(self, "current_recording_task", self.config.get("task"))
+            
+            self.worker = TranscriptionWorker(self.transcriber, audio_data, parent=self, task_override=final_task)
             self.worker.finished.connect(self.on_transcription_done)
             self.worker.start()
         else:
-            self.bridge.update_status("Recording")
+            # START RECORDING
+            self.current_recording_task = intended_task
+            self.bridge.update_status(f"Recording ({intended_task})...") 
             self.bridge.isRecording = True
             self.audio_engine.start_recording()
 
     @Slot(bool)
     def on_ui_toggle_request(self, state):
         if state != self.audio_engine.recording:
-            self.toggle_recording()
+            self.toggle_recording() # Default behavior for UI clicks
 
     @Slot(str)
     def on_transcription_done(self, text: str):
@@ -503,8 +622,8 @@ class WhisperApp(QObject):
 
     @Slot(bool)
     def on_hotkeys_enabled_toggle(self, state):
-        if self.hotkey_manager:
-            self.hotkey_manager.set_enabled(state)
+        if self.hk_transcribe: self.hk_transcribe.set_enabled(state)
+        if self.hk_translate: self.hk_translate.set_enabled(state)
 
     @Slot(str)
     def on_download_requested(self, size):
@@ -531,6 +650,25 @@ class WhisperApp(QObject):
         self.bridge.update_status("Error")
         logging.error(f"Download Error: {err}")
 
+    @Slot(bool)
+    def on_ui_toggle_request(self, is_recording):
+        """Called when recording state changes."""
+        # Update Window Hook to allow clicking if active
+        is_active = is_recording or self.bridge.isProcessing
+        if hasattr(self, 'window_hook'):
+            self.window_hook.set_enabled(is_active)
+            
+    @Slot(bool)
+    def on_processing_changed(self, is_processing):
+        is_active = self.bridge.isRecording or is_processing
+        if hasattr(self, 'window_hook'):
+            self.window_hook.set_enabled(is_active)
+
 if __name__ == "__main__":
+    import sys
     app = WhisperApp()
-    app.run()
+    
+    # Connect extra signal for processing state
+    app.bridge.isProcessingChanged.connect(app.on_processing_changed)
+    
+    sys.exit(app.run())

portable_build.py

@@ -39,39 +39,36 @@ def build_portable():
     print("⏳ This may take 5-10 minutes...")
     
     PyInstaller.__main__.run([
-        "main.py",                       # Entry point
+        "bootstrapper.py",               # Entry point (Tiny Installer)
         "--name=WhisperVoice",           # EXE name
-        "--onefile",                     # Single EXE (slower startup but portable)
+        "--onefile",                     # Single EXE
         "--noconsole",                   # No terminal window
         "--clean",                       # Clean cache
-        *add_data_args,                  # Bundled assets
         
-        # Heavy libraries that need special collection
-        "--collect-all", "faster_whisper",
-        "--collect-all", "ctranslate2",
-        "--collect-all", "PySide6",
-        "--collect-all", "torch",
-        "--collect-all", "numpy",
+        # Bundle the app source to be extracted by bootstrapper
+        # The bootstrapper expects 'app_source' folder in bundled resources
+        "--add-data", f"src{os.pathsep}app_source/src",
+        "--add-data", f"main.py{os.pathsep}app_source",
+        "--add-data", f"requirements.txt{os.pathsep}app_source",
         
-        # Hidden imports (modules imported dynamically)
-        "--hidden-import", "keyboard",
-        "--hidden-import", "pyperclip",
-        "--hidden-import", "psutil",
-        "--hidden-import", "pynvml",
-        "--hidden-import", "sounddevice",
-        "--hidden-import", "scipy",
-        "--hidden-import", "scipy.signal",
-        "--hidden-import", "huggingface_hub",
-        "--hidden-import", "tokenizers",
+        # Add assets
+        "--add-data", f"src/ui/qml{os.pathsep}app_source/src/ui/qml",
+        "--add-data", f"assets{os.pathsep}app_source/assets",
         
-        # Qt plugins
-        "--hidden-import", "PySide6.QtQuickControls2",
-        "--hidden-import", "PySide6.QtQuick.Controls",
+        # No heavy collections! 
+        # The bootstrapper uses internal pip to install everything.
         
-        # Icon (convert to .ico for Windows)
-        # "--icon=icon.ico",  # Uncomment if you have a .ico file
+        # Exclude heavy modules to ensure this exe stays tiny
+        "--exclude-module", "faster_whisper",
+        "--exclude-module", "torch",
+        "--exclude-module", "PySide6",
+
+        
+        # Icon
+        # "--icon=icon.ico",
     ])
 
+
     print("\n" + "="*60)
     print("✅ BUILD COMPLETE!")
     print("="*60)

publish_release.py

@@ -0,0 +1,73 @@
+import os
+import requests
+import mimetypes
+
+# Configuration
+API_URL = "https://git.lashman.live/api/v1"
+OWNER = "lashman"
+REPO = "whisper_voice"
+TAG = "v1.0.4"
+TOKEN = "6153890332afff2d725aaf4729bc54b5030d5700" # Extracted from git config
+EXE_PATH = r"dist\WhisperVoice.exe"
+
+headers = {
+    "Authorization": f"token {TOKEN}",
+    "Accept": "application/json"
+}
+
+def create_release():
+    print(f"Creating release {TAG}...")
+    
+    # Read Release Notes
+    with open("RELEASE_NOTES.md", "r", encoding="utf-8") as f:
+        notes = f.read()
+    
+    # Create Release
+    payload = {
+        "tag_name": TAG,
+        "name": TAG,
+        "body": notes,
+        "draft": False,
+        "prerelease": False
+    }
+    
+    url = f"{API_URL}/repos/{OWNER}/{REPO}/releases"
+    resp = requests.post(url, json=payload, headers=headers)
+    
+    if resp.status_code == 201:
+        print("Release created successfully!")
+        return resp.json()
+    elif resp.status_code == 409:
+        print("Release already exists. Fetching it...")
+        # Get by tag
+        resp = requests.get(f"{API_URL}/repos/{OWNER}/{REPO}/releases/tags/{TAG}", headers=headers)
+        if resp.status_code == 200:
+            return resp.json()
+            
+    print(f"Failed to create release: {resp.status_code} - {resp.text}")
+    return None
+
+def upload_asset(release_id, file_path):
+    print(f"Uploading asset: {file_path}...")
+    filename = os.path.basename(file_path)
+    
+    with open(file_path, "rb") as f:
+        data = f.read()
+        
+    url = f"{API_URL}/repos/{OWNER}/{REPO}/releases/{release_id}/assets?name={filename}"
+    
+    # Gitea API expects raw body
+    resp = requests.post(url, data=data, headers=headers)
+    
+    if resp.status_code == 201:
+        print(f"Uploaded {filename} successfully!")
+    else:
+        print(f"Failed to upload asset: {resp.status_code} - {resp.text}")
+
+def main():
+    release = create_release()
+    if release:
+        upload_asset(release["id"], EXE_PATH)
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -5,6 +5,7 @@
 faster-whisper>=1.0.0
 torch>=2.0.0
 
+
 # UI Framework
 PySide6>=6.6.0
 

src/core/config.py

@@ -16,6 +16,7 @@ from src.core.paths import get_base_path
 # Default Configuration
 DEFAULT_SETTINGS = {
     "hotkey": "f8",
+    "hotkey_translate": "f10",
     "model_size": "small",
     "input_device": None,       # Device ID (int) or Name (str), None = Default
     "save_recordings": False,   # Save .wav files for debugging
@@ -38,13 +39,20 @@ DEFAULT_SETTINGS = {
     
     # AI - Advanced
     "language": "auto",         # "auto" or ISO code
+    "task": "transcribe",       # "transcribe" or "translate" (to English)
     "compute_device": "auto",   # "auto", "cuda", "cpu"
     "compute_type": "int8",     # "int8", "float16", "float32"
     "beam_size": 5,
     "best_of": 5,
     "vad_filter": True,
     "no_repeat_ngram_size": 0,
-    "condition_on_previous_text": True
+    "condition_on_previous_text": True,
+    "initial_prompt": "Mm-hmm. Okay, let's go. I speak in full sentences.", # Default: Forces punctuation
+    
+
+    
+    # Low VRAM Mode
+    "unload_models_after_use": False # If True, models are unloaded immediately to free VRAM
 }
 
 class ConfigManager:

src/core/hotkey_manager.py

@@ -30,15 +30,16 @@ class HotkeyManager(QObject):
     
     triggered = Signal()
 
-    def __init__(self, hotkey: str = "f8"):
+    def __init__(self, config_key: str = "hotkey"):
         """
         Initialize the HotkeyManager.
 
         Args:
-            hotkey (str): The global hotkey string description. Default: "f8".
+            config_key (str): The configuration key to look up (e.g. "hotkey").
         """
         super().__init__()
-        self.hotkey = hotkey
+        self.config_key = config_key
+        self.hotkey = "f8" # Placeholder
         self.is_listening = False
         self._enabled = True
 
@@ -58,9 +59,9 @@ class HotkeyManager(QObject):
             
         from src.core.config import ConfigManager
         config = ConfigManager()
-        self.hotkey = config.get("hotkey")
+        self.hotkey = config.get(self.config_key)
         
-        logging.info(f"Registering global hotkey: {self.hotkey}")
+        logging.info(f"Registering global hotkey ({self.config_key}): {self.hotkey}")
         try:
             # We don't suppress=True here because we want the app to see keys during recording 
             # (Wait, actually if we are recording we WANT keyboard to see it, 

src/core/languages.py

@@ -0,0 +1,120 @@
+"""
+Supported Languages Module
+==========================
+Full list of languages supported by OpenAI Whisper.
+Maps ISO codes to display names.
+"""
+
+LANGUAGES = {
+    "auto": "Auto Detect",
+    "af": "Afrikaans",
+    "sq": "Albanian",
+    "am": "Amharic",
+    "ar": "Arabic",
+    "hy": "Armenian",
+    "as": "Assamese",
+    "az": "Azerbaijani",
+    "ba": "Bashkir",
+    "eu": "Basque",
+    "be": "Belarusian",
+    "bn": "Bengali",
+    "bs": "Bosnian",
+    "br": "Breton",
+    "bg": "Bulgarian",
+    "my": "Burmese",
+    "ca": "Catalan",
+    "zh": "Chinese",
+    "hr": "Croatian",
+    "cs": "Czech",
+    "da": "Danish",
+    "nl": "Dutch",
+    "en": "English",
+    "et": "Estonian",
+    "fo": "Faroese",
+    "fi": "Finnish",
+    "fr": "French",
+    "gl": "Galician",
+    "ka": "Georgian",
+    "de": "German",
+    "el": "Greek",
+    "gu": "Gujarati",
+    "ht": "Haitian",
+    "ha": "Hausa",
+    "haw": "Hawaiian",
+    "he": "Hebrew",
+    "hi": "Hindi",
+    "hu": "Hungarian",
+    "is": "Icelandic",
+    "id": "Indonesian",
+    "it": "Italian",
+    "ja": "Japanese",
+    "jw": "Javanese",
+    "kn": "Kannada",
+    "kk": "Kazakh",
+    "km": "Khmer",
+    "ko": "Korean",
+    "lo": "Lao",
+    "la": "Latin",
+    "lv": "Latvian",
+    "ln": "Lingala",
+    "lt": "Lithuanian",
+    "lb": "Luxembourgish",
+    "mk": "Macedonian",
+    "mg": "Malagasy",
+    "ms": "Malay",
+    "ml": "Malayalam",
+    "mt": "Maltese",
+    "mi": "Maori",
+    "mr": "Marathi",
+    "mn": "Mongolian",
+    "ne": "Nepali",
+    "no": "Norwegian",
+    "oc": "Occitan",
+    "pa": "Punjabi",
+    "ps": "Pashto",
+    "fa": "Persian",
+    "pl": "Polish",
+    "pt": "Portuguese",
+    "ro": "Romanian",
+    "ru": "Russian",
+    "sa": "Sanskrit",
+    "sr": "Serbian",
+    "sn": "Shona",
+    "sd": "Sindhi",
+    "si": "Sinhala",
+    "sk": "Slovak",
+    "sl": "Slovenian",
+    "so": "Somali",
+    "es": "Spanish",
+    "su": "Sundanese",
+    "sw": "Swahili",
+    "sv": "Swedish",
+    "tl": "Tagalog",
+    "tg": "Tajik",
+    "ta": "Tamil",
+    "tt": "Tatar",
+    "te": "Telugu",
+    "th": "Thai",
+    "bo": "Tibetan",
+    "tr": "Turkish",
+    "tk": "Turkmen",
+    "uk": "Ukrainian",
+    "ur": "Urdu",
+    "uz": "Uzbek",
+    "vi": "Vietnamese",
+    "cy": "Welsh",
+    "yi": "Yiddish",
+    "yo": "Yoruba",
+}
+
+def get_language_names():
+    return list(LANGUAGES.values())
+
+def get_code_by_name(name):
+    for code, lang in LANGUAGES.items():
+        if lang == name:
+            return code
+    return "auto"
+
+def get_name_by_code(code):
+    return LANGUAGES.get(code, "Auto Detect")

src/core/transcriber.py

@@ -15,8 +15,13 @@ import numpy as np
 from src.core.config import ConfigManager
 from src.core.paths import get_models_path
 
+try:
+    import torch
+except ImportError:
+    torch = None
+
 # Import directly - valid since we are now running in the full environment
-from faster_whisper import WhisperModel
+
 
 class WhisperTranscriber:
     """
@@ -57,6 +62,8 @@ class WhisperTranscriber:
             # Force offline if path exists to avoid HF errors
             local_only = new_path.exists()
 
+            try:
+                from faster_whisper import WhisperModel
                 self.model = WhisperModel(
                     model_input, 
                     device=device, 
@@ -64,6 +71,23 @@ class WhisperTranscriber:
                     download_root=str(get_models_path()),
                     local_files_only=local_only
                 )
+            except Exception as load_err:
+                # CRITICAL FALLBACK: If CUDA/cublas fails (AMD/Intel users), fallback to CPU
+                err_str = str(load_err).lower()
+                if "cublas" in err_str or "cudnn" in err_str or "library" in err_str or "device" in err_str:
+                    logging.warning(f"CUDA Init Failed ({load_err}). Falling back to CPU...")
+                    self.config.set("compute_device", "cpu") # Update config for persistence/UI
+                    self.current_compute_device = "cpu"
+                    
+                    self.model = WhisperModel(
+                        model_input, 
+                        device="cpu", 
+                        compute_type="int8", # CPU usually handles int8 well with newer extensions, or standard
+                        download_root=str(get_models_path()),
+                        local_files_only=local_only
+                    )
+                else:
+                    raise load_err
             
             self.current_model_size = size
             self.current_compute_device = device
@@ -74,41 +98,119 @@ class WhisperTranscriber:
             logging.error(f"Failed to load model: {e}")
             self.model = None
             
-    def transcribe(self, audio_data, is_file: bool = False) -> str:
+            # Auto-Repair: Detect vocabulary/corrupt errors
+            err_str = str(e).lower()
+            if "vocabulary" in err_str or "tokenizer" in err_str or "config.json" in err_str:
+                # ... existing auto-repair logic ...
+                logging.warning("Corrupt model detected on load. Attempting to delete and reset...")
+                try:
+                    import shutil
+                    # Differentiate between simple path and HF path
+                    new_path = get_models_path() / f"faster-whisper-{size}"
+                    if new_path.exists():
+                        shutil.rmtree(new_path)
+                        logging.info(f"Deleted corrupt model at {new_path}")
+                    else:
+                        # Try legacy HF path
+                        hf_path = get_models_path() / f"models--Systran--faster-whisper-{size}"
+                        if hf_path.exists():
+                            shutil.rmtree(hf_path)
+                            logging.info(f"Deleted corrupt HF model at {hf_path}")
+                            
+                    # Notify UI to refresh state (will show 'Download' button now)
+                    # We can't reach bridge easily here without passing it in, 
+                    # but the UI polls or listens to logs. 
+                    # The user will simply see "Model Missing" in settings after this.
+                except Exception as del_err:
+                    logging.error(f"Failed to delete corrupt model: {del_err}")
+
+    def transcribe(self, audio_data, is_file: bool = False, task: Optional[str] = None) -> str:
         """
         Transcribe audio data.
         """
-        logging.info(f"Starting transcription... (is_file={is_file})")
+        logging.info(f"Starting transcription... (is_file={is_file}, task={task})")
         
         # Ensure model is loaded
         if not self.model:
             self.load_model()
             if not self.model:
-                return "Error: Model failed to load."
+                return "Error: Model failed to load. Please check Settings -> Model Info."
 
         try:
             # Config
             beam_size = int(self.config.get("beam_size"))
             best_of = int(self.config.get("best_of"))
             vad = False if is_file else self.config.get("vad_filter")
+            language = self.config.get("language")
+            
+            # Use task override if provided, otherwise config
+            # Ensure safe string and lowercase ("transcribe" vs "Transcribe")
+            raw_task = task if task else self.config.get("task")
+            final_task = str(raw_task).strip().lower() if raw_task else "transcribe"
+            
+            # Sanity check for valid Whisper tasks
+            if final_task not in ["transcribe", "translate"]:
+                logging.warning(f"Invalid task '{final_task}' detected. Defaulting to 'transcribe'.")
+                final_task = "transcribe"
+            
+            # Language handling
+            final_language = language if language != "auto" else None
+            
+            # Anti-Hallucination: Force condition_on_previous_text=False for translation
+            condition_prev = self.config.get("condition_on_previous_text")
+            
+            # Helper options for Translation Stability
+            initial_prompt = self.config.get("initial_prompt")
+            
+            if final_task == "translate":
+                condition_prev = False
+                # Force beam search if user has set it to greedy (1)
+                # Translation requires more search breadth to find the English mapping
+                if beam_size < 5:
+                    logging.info("Forcing beam_size=5 for Translation task.")
+                    beam_size = 5
+                    
+                # Inject guidance prompt if none exists
+                if not initial_prompt:
+                    initial_prompt = "Translate this to English."
+
+            logging.info(f"Model Dispatch: Task='{final_task}', Language='{final_language}', ConditionPrev={condition_prev}, Beam={beam_size}")
+            
+            # Build arguments dynamically to avoid passing None if that's the issue
+            transcribe_opts = {
+                "beam_size": beam_size,
+                "best_of": best_of,
+                "vad_filter": vad,
+                "task": final_task,
+                "vad_parameters": dict(min_silence_duration_ms=500),
+                "condition_on_previous_text": condition_prev,
+                "without_timestamps": True
+            }
+            
+            if initial_prompt:
+                 transcribe_opts["initial_prompt"] = initial_prompt
+            
+            # Only add language if it's explicitly set (not None/Auto)
+            # This avoids potentially confusing the model with explicit None
+            if final_language:
+                transcribe_opts["language"] = final_language
             
             # Transcribe
-            segments, info = self.model.transcribe(
-                audio_data,
-                beam_size=beam_size,
-                best_of=best_of,
-                vad_filter=vad,
-                vad_parameters=dict(min_silence_duration_ms=500),
-                condition_on_previous_text=self.config.get("condition_on_previous_text"),
-                without_timestamps=True
-            )
+            segments, info = self.model.transcribe(audio_data, **transcribe_opts)
             
             # Aggregate text
             text_result = ""
             for segment in segments:
                 text_result += segment.text + " "
                 
-            return text_result.strip()
+            text_result = text_result.strip()
+            
+            # Low VRAM Mode: Unload Whisper Model immediately
+            if self.config.get("unload_models_after_use"):
+                self.unload_model()
+
+            logging.info(f"Final Transcription Output: '{text_result}'")
+            return text_result
             
         except Exception as e:
             logging.error(f"Transcription failed: {e}")
@@ -117,7 +219,10 @@ class WhisperTranscriber:
     def model_exists(self, size: str) -> bool:
         """Checks if a model size is already downloaded."""
         new_path = get_models_path() / f"faster-whisper-{size}"
-        if (new_path / "config.json").exists():
+        if new_path.exists():
+            # Strict check
+            required = ["config.json", "model.bin", "vocabulary.json"]
+            if all((new_path / f).exists() for f in required):
                 return True
             
         # Legacy HF cache check
@@ -127,3 +232,21 @@ class WhisperTranscriber:
             return True
             
         return False
+
+    def unload_model(self):
+        """
+        Unloads model to free memory.
+        """
+        if self.model:
+            del self.model
+        
+        self.model = None
+        self.current_model_size = None
+        
+        # Force garbage collection
+        import gc
+        gc.collect()
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+            
+        logging.info("Whisper Model unloaded (Low VRAM Mode).")

src/ui/bridge.py

@@ -245,6 +245,26 @@ class UIBridge(QObject):
 
     # --- Methods called from QML ---
     
+    @Slot(result=list)
+    def get_supported_languages(self):
+        from src.core.languages import get_language_names
+        return get_language_names()
+
+    @Slot(str)
+    def set_language_by_name(self, name):
+        from src.core.languages import get_code_by_name
+        from src.core.config import ConfigManager
+        code = get_code_by_name(name)
+        ConfigManager().set("language", code)
+        self.settingChanged.emit("language", code)
+        
+    @Slot(result=str)
+    def get_current_language_name(self):
+        from src.core.languages import get_name_by_code
+        from src.core.config import ConfigManager
+        code = ConfigManager().get("language")
+        return get_name_by_code(code)
+
     @Slot(str, result='QVariant')
     def getSetting(self, key):
         from src.core.config import ConfigManager
@@ -356,9 +376,15 @@ class UIBridge(QObject):
         
         try:
             from src.core.paths import get_models_path
+            
+
+
             # Check new simple format used by DownloadWorker
             path_simple = get_models_path() / f"faster-whisper-{size}"
-            if path_simple.exists() and any(path_simple.iterdir()):
+            if path_simple.exists():
+                # Strict check: Ensure all critical files exist
+                required = ["config.json", "model.bin", "vocabulary.json"]
+                if all((path_simple / f).exists() for f in required):
                     return True
             
             # Check HF Cache format (legacy/default)
@@ -366,16 +392,12 @@ class UIBridge(QObject):
             path_hf = get_models_path() / folder_name
             snapshots = path_hf / "snapshots"
             if snapshots.exists() and any(snapshots.iterdir()):
-                return True
+                return True # Legacy cache structure is complex, assume valid if present
                 
-            # Check direct folder (simple)
-            path_direct = get_models_path() / size
-            if (path_direct / "config.json").exists():
-                return True
+            return False
             
         except Exception as e:
             logging.error(f"Error checking model status: {e}")
-            
             return False
 
     @Slot(str)

src/ui/qml/ModernComboBox.qml

@@ -100,7 +100,7 @@ ComboBox {
     popup: Popup {
         y: control.height - 1
         width: control.width
-        implicitHeight: contentItem.implicitHeight
+        implicitHeight: Math.min(contentItem.implicitHeight, 300)
         padding: 5
 
         contentItem: ListView {

src/ui/qml/ModernKeySequenceRecorder.qml

@@ -25,7 +25,7 @@ Rectangle {
     
     Text {
         anchors.centerIn: parent
-        text: control.recording ? "Listening..." : (control.currentSequence || "None")
+        text: control.recording ? "Listening..." : (formatSequence(control.currentSequence) || "None")
         color: control.recording ? SettingsStyle.accent : (control.currentSequence ? "#ffffff" : "#808080")
         font.family: "JetBrains Mono"
         font.pixelSize: 13
@@ -72,6 +72,23 @@ Rectangle {
         if (!activeFocus) control.recording = false
     }
 
+    function formatSequence(seq) {
+        if (!seq) return ""
+        var parts = seq.split("+")
+        for (var i = 0; i < parts.length; i++) {
+            var p = parts[i]
+            // Standardize modifiers
+            if (p === "ctrl") parts[i] = "Ctrl"
+            else if (p === "alt") parts[i] = "Alt"
+            else if (p === "shift") parts[i] = "Shift"
+            else if (p === "win") parts[i] = "Win"
+            else if (p === "esc") parts[i] = "Esc"
+            // Capitalize F-keys and others (e.g. f8 -> F8, space -> Space)
+            else parts[i] = p.charAt(0).toUpperCase() + p.slice(1)
+        }
+        return parts.join(" + ")
+    }
+
     function getKeyName(key, text) {
         // F-Keys
         if (key >= Qt.Key_F1 && key <= Qt.Key_F35) return "f" + (key - Qt.Key_F1 + 1)

src/ui/qml/Settings.qml

@@ -314,15 +314,25 @@ Window {
                                     spacing: 0
                                     
                                     ModernSettingsItem {
-                                        label: "Global Hotkey"
-                                        description: "Press to record a new shortcut (e.g. Ctrl+Space)"
+                                        label: "Global Hotkey (Transcribe)"
+                                        description: "Press to record a new shortcut (e.g. F9)"
                                         control: ModernKeySequenceRecorder {
-                                            Layout.preferredWidth: 200
+                                            implicitWidth: 240
                                             currentSequence: ui.getSetting("hotkey")
                                             onSequenceChanged: (seq) => ui.setSetting("hotkey", seq)
                                         }
                                     }
 
+                                    ModernSettingsItem {
+                                        label: "Global Hotkey (Translate)"
+                                        description: "Press to record a new shortcut (e.g. F10)"
+                                        control: ModernKeySequenceRecorder {
+                                            implicitWidth: 240
+                                            currentSequence: ui.getSetting("hotkey_translate")
+                                            onSequenceChanged: (seq) => ui.setSetting("hotkey_translate", seq)
+                                        }
+                                    }
+                                    
                                     ModernSettingsItem {
                                         label: "Run on Startup"
                                         description: "Automatically launch when you log in"
@@ -577,6 +587,53 @@ Window {
                                 Text { text: "Model configuration and performance"; color: SettingsStyle.textSecondary; font.family: mainFont; font.pixelSize: 14 }
                             }
 
+                                    ModernSettingsSection {
+                                title: "Style & Prompting"
+                                Layout.margins: 32
+                                Layout.topMargin: 0
+                                
+                                content: ColumnLayout {
+                                    width: parent.width
+                                    spacing: 0
+                                    
+                                    ModernSettingsItem {
+                                        label: "Punctuation Style"
+                                        description: "Hint for how to format text"
+                                        control: ModernComboBox {
+                                            id: styleCombo
+                                            width: 180
+                                            model: ["Standard (Proper)", "Casual (Lowercase)", "Custom"]
+                                            
+                                            // Logic to determine initial index based on config string
+                                            Component.onCompleted: {
+                                                let current = ui.getSetting("initial_prompt")
+                                                if (current === "Mm-hmm. Okay, let's go. I speak in full sentences.") currentIndex = 0
+                                                else if (current === "um, okay... i guess so.") currentIndex = 1
+                                                else currentIndex = 2
+                                            }
+
+                                            onActivated: {
+                                                if (index === 0) ui.setSetting("initial_prompt", "Mm-hmm. Okay, let's go. I speak in full sentences.")
+                                                else if (index === 1) ui.setSetting("initial_prompt", "um, okay... i guess so.")
+                                                // Custom: Don't change string immediately, let user type
+                                            }
+                                        }
+                                    }
+
+                                    ModernSettingsItem {
+                                        label: "Custom Prompt"
+                                        description: "Advanced: Define your own style hint"
+                                        visible: styleCombo.currentIndex === 2
+                                        control: ModernTextField {
+                                            Layout.preferredWidth: 280
+                                            placeholderText: "e.g. 'Hello, World.'"
+                                            text: ui.getSetting("initial_prompt") || ""
+                                            onEditingFinished: ui.setSetting("initial_prompt", text === "" ? null : text)
+                                        }
+                                    }
+                                }
+                            }
+
                             ModernSettingsSection {
                                 title: "Model Config"
                                 Layout.margins: 32
@@ -742,15 +799,17 @@ Window {
                                     
                                     ModernSettingsItem {
                                         label: "Language"
-                                        description: "Force language or Auto-detect"
+                                        description: "Spoken language to transcribe"
                                         control: ModernComboBox {
-                                            width: 140
-                                            model: ["auto", "en", "fr", "de", "es", "it", "ja", "zh", "ru"]
-                                            currentIndex: model.indexOf(ui.getSetting("language"))
-                                            onActivated: ui.setSetting("language", currentText)
+                                            Layout.preferredWidth: 200
+                                            model: ui.get_supported_languages()
+                                            currentIndex: model.indexOf(ui.get_current_language_name())
+                                            onActivated: (index) => ui.set_language_by_name(currentText)
                                         }
                                     }
                             
+                                    // Task selector removed as per user request (Hotkeys handle this now)
+                            
                                     ModernSettingsItem {
                                         label: "Compute Device"
                                         description: "Hardware acceleration (CUDA requires NVidia GPU)"
@@ -773,6 +832,16 @@ Window {
                                             onActivated: ui.setSetting("compute_type", currentText)
                                         }
                                     }
+                                    
+                                    ModernSettingsItem {
+                                        label: "Low VRAM Mode"
+                                        description: "Unload models immediately after use (Saves VRAM, Adds Delay)"
+                                        showSeparator: false
+                                        control: ModernSwitch {
+                                            checked: ui.getSetting("unload_models_after_use")
+                                            onToggled: ui.setSetting("unload_models_after_use", checked)
+                                        }
+                                    }
                                 }
                             }
 

src/utils/formatters.py

@@ -0,0 +1,32 @@
+"""
+Formatter Utilities
+===================
+Helper functions for text formatting.
+"""
+
+def format_hotkey(sequence: str) -> str:
+    """
+    Formats a hotkey sequence string (e.g. 'ctrl+alt+f9') 
+    into a pretty readable string (e.g. 'Ctrl + Alt + F9').
+    """
+    if not sequence:
+        return "None"
+    
+    parts = sequence.split('+')
+    formatted_parts = []
+    
+    for p in parts:
+        p = p.strip().lower()
+        if p == 'ctrl': formatted_parts.append('Ctrl')
+        elif p == 'alt': formatted_parts.append('Alt')
+        elif p == 'shift': formatted_parts.append('Shift')
+        elif p == 'win': formatted_parts.append('Win')
+        elif p == 'esc': formatted_parts.append('Esc')
+        else:
+            # Capitalize first letter
+            if len(p) > 0:
+                formatted_parts.append(p[0].upper() + p[1:])
+            else:
+                formatted_parts.append(p)
+                
+    return " + ".join(formatted_parts)

src/utils/window_hook.py

@@ -55,6 +55,10 @@ except AttributeError:
 def LOWORD(l): return l & 0xffff
 def HIWORD(l): return (l >> 16) & 0xffff
 
+GWL_EXSTYLE = -20
+WS_EX_TRANSPARENT = 0x00000020
+WS_EX_LAYERED = 0x00080000
+
 class WindowHook:
     def __init__(self, hwnd, width, height, initial_scale=1.0):
         self.hwnd = hwnd
@@ -65,6 +69,34 @@ class WindowHook:
         # (Window 420x140, Pill 380x100)
         self.logical_rect = [20, 20, 20+380, 20+100]
         self.current_scale = initial_scale
+        self.enabled = True # New flag
+
+    def set_enabled(self, enabled):
+        """
+        Enables or disables interaction.
+        When disabled, we set WS_EX_TRANSPARENT so clicks pass through physically.
+        """
+        if self.enabled == enabled:
+            return
+            
+        self.enabled = enabled
+        
+        # Get current styles
+        style = user32.GetWindowLongW(self.hwnd, GWL_EXSTYLE)
+        
+        if not enabled:
+            # Enable Click-Through (Add Transparent)
+            # We also ensure Layered is set (Qt usually sets it, but good to be sure)
+            new_style = style | WS_EX_TRANSPARENT | WS_EX_LAYERED
+        else:
+            # Disable Click-Through (Remove Transparent)
+            new_style = style & ~WS_EX_TRANSPARENT
+            
+        if new_style != style:
+            SetWindowLongPtr(self.hwnd, GWL_EXSTYLE, new_style)
+            
+        # Force a redraw/frame update just in case
+        user32.SetWindowPos(self.hwnd, 0, 0, 0, 0, 0, 0x0027) # SWP_NOMOVE | SWP_NOSIZE | SWP_NOZORDER | SWP_FRAMECHANGED
 
     def install(self):
         proc_address = ctypes.cast(self.new_wnd_proc, ctypes.c_void_p)
@@ -73,6 +105,10 @@ class WindowHook:
     def wnd_proc_callback(self, hwnd, msg, wParam, lParam):
         try:
             if msg == WM_NCHITTEST:
+                # If disabled (invisible/inactive), let clicks pass through (HTTRANSPARENT)
+                if not self.enabled:
+                    return HTTRANSPARENT
+                    
                 res = self.on_nchittest(lParam)
                 if res != 0: 
                     return res

test_m2m.py

@@ -0,0 +1,38 @@
+
+import sys
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+def test_m2m():
+    model_name = "facebook/m2m100_418M"
+    print(f"Loading {model_name}...")
+    
+    tokenizer = M2M100Tokenizer.from_pretrained(model_name)
+    model = M2M100ForConditionalGeneration.from_pretrained(model_name)
+    
+    # Test cases: (Language Code, Input)
+    test_cases = [
+        ("en", "he go to school yesterday"),
+        ("pl", "on iść do szkoła wczoraj"), # Intentional broken grammar in Polish
+    ]
+    
+    print("\nStarting M2M Tests (Self-Translation):\n")
+    
+    for lang, input_text in test_cases:
+        tokenizer.src_lang = lang
+        encoded = tokenizer(input_text, return_tensors="pt")
+        
+        # Translate to SAME language
+        generated_tokens = model.generate(
+            **encoded, 
+            forced_bos_token_id=tokenizer.get_lang_id(lang)
+        )
+        
+        corrected = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+        
+        print(f"[{lang}]")
+        print(f"Input:    {input_text}")
+        print(f"Output:   {corrected}")
+        print("-" * 20)
+
+if __name__ == "__main__":
+    test_m2m()

test_mt0.py

@@ -0,0 +1,40 @@
+
+import sys
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+def test_mt0():
+    model_name = "bigscience/mt0-base"
+    print(f"Loading {model_name}...")
+    
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+    
+    # Test cases: (Language, Prompt, Input)
+    # MT0 is instruction tuned, so we should prompt it in the target language or English.
+    # Cross-lingual prompting (English prompt -> Target tasks) is usually supported.
+    
+    test_cases = [
+        ("English", "Correct grammar:", "he go to school yesterday"),
+        ("Polish", "Popraw gramatykę:", "to jest testowe zdanie bez kropki"),
+        ("Finnish", "Korjaa kielioppi:", "tämä on testilause ilman pistettä"),
+        ("Russian", "Исправь грамматику:", "это тестовое предложение без точки"),
+        ("Japanese", "文法を直してください:", "これは点のないテスト文です"),
+        ("Spanish", "Corrige la gramática:", "esta es una oración de prueba sin punto"),
+    ]
+    
+    print("\nStarting MT0 Tests:\n")
+    
+    for lang, prompt_text, input_text in test_cases:
+        full_input = f"{prompt_text} {input_text}"
+        inputs = tokenizer(full_input, return_tensors="pt")
+        
+        outputs = model.generate(inputs.input_ids, max_length=128)
+        corrected = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        
+        print(f"[{lang}]")
+        print(f"Input:    {full_input}")
+        print(f"Output:   {corrected}")
+        print("-" * 20)
+
+if __name__ == "__main__":
+    test_mt0()

test_punctuation.py

@@ -0,0 +1,34 @@
+
+import sys
+import os
+
+# Add src to path
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from src.core.grammar_assistant import GrammarAssistant
+
+def test_punctuation():
+    assistant = GrammarAssistant()
+    assistant.load_model()
+    
+    samples = [
+        # User's example (verbatim)
+        "If the voice recognition doesn't recognize that I like stopped Or something would that would it also correct that",
+        
+        # Generic run-on
+        "hello how are you doing today i am doing fine thanks for asking",
+        
+        # Missing commas/periods
+        "well i think its valid however we should probably check the logs first"
+    ]
+    
+    print("\nStarting Punctuation Tests:\n")
+    
+    for sample in samples:
+        print(f"Original: {sample}")
+        corrected = assistant.correct(sample)
+        print(f"Corrected: {corrected}")
+        print("-" * 20)
+
+if __name__ == "__main__":
+    test_punctuation()